Science.gov

Sample records for leili saarse anneli

  1. Ann Stewart.

    PubMed

    1991-04-24

    Ann Stewart, English National Board Professional Adviser in Midwifery F.ducation and Supervision, who had been a practising midwife since 1954 and served as vice-president of the Royal College of Midwives, died last week.

  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. Beyond Anne Frank.

    ERIC Educational Resources Information Center

    Kunczt, Kim

    1993-01-01

    According to a former junior high school teacher, eighth graders--inquisitive and opinionated--are not too young to grasp the impact of the Holocaust. This teacher went beyond "The Diary of Anne Frank" to push deeply into topics of genocide, racism, prejudice, and persecution. Students approached this discussion by considering examples…

  4. Anne Frank's headache.

    PubMed

    de Almeida, R F; Kowacs, P A

    2007-11-01

    There are a significant number of famous people who suffered from frequent headaches during their lifetime while also exerting an influence of some kind on politics or the course of history. One such person was Anneliese Marie Frank, the German-born Jewish teenager better known as Anne Frank, who was forced into hiding during World War II. When she turned 13, she received a diary as a present, named it 'Kitty' and started to record her experiences and feelings. She kept the diary during her period in hiding, describing her daily life, including the feeling of isolation, her fear of being discovered, her admiration for her father and her opinion about women's role in society, as well as the discovery of her own sexuality. She sometimes reported a headache that disturbed her tremendously. The 'bad' to 'terrifying' and 'pounding' headache attacks, which were accompanied by vomiting and during which she felt like screaming to be left alone, matched the International Headache Society criteria for probable migraine, whereas the 'more frequent headaches' described by Anne's father are more likely to have been tension-type headaches than headaches secondary to ocular or other disorders.

  5. 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.

  6. ANN - based distribution system reconfiguration

    SciTech Connect

    Momoh, J.A.; Wang, Yanchun; Rizy, D.T.

    1997-08-01

    This paper describes an Artificial Neural Network (ANN) - based distribution system reconfiguration scheme to reduce system loss. The ANN is trained for different load levels and different network topologies. The proposed scheme has been tested using a 38 - bus distribution system. The results are very promising.

  7. Hybrid ANN-ES architecture for automatic target recognition

    NASA Astrophysics Data System (ADS)

    Teng, Chungte; Ligomenides, Panos A.

    1992-03-01

    Automatic target recognition can benefit from cooperation of artificial neural networks (ANNs) and expert systems (ESs). Bottom-up training and generalization properties of artificial neural networks, and top-down utilization of accumulated knowledge by expert system processors, can be combined to offer robust performance of the automatic target recognition models. In this paper, we propose a modular, flexible and expandable, hybrid architecture which provides cooperative, functional and operational interfaces between expert system and artificial neural networks facilities. In order to make the problem more specific, we apply this architecture to the Multline Optical Character Reader (MLOCR) system, which is being developed to sort the postal mail pieces automatically.

  8. DOLLY ANN ROADLESS AREA, VIRGINIA.

    USGS Publications Warehouse

    Lesure, Frank G.; Jones, Jay G.

    1984-01-01

    Mineral-resource surveys indicate that much of the Dolly Ann Roadless Area, in the George Washington National Forest, Alleghany County, Virginia, has substantiated iron resource potential. Inferred low-grade iron resources occur in folded sedimentary rocks of Paleozoic age. The area has an estimated 540 million long tons of contained iron in hematitic sandstone and 700,000 long tons contained iron in deposits of sandy Limonite. Other mineral resources include various rocks suitable for crushed rock, quartzite suitable for high-silica uses, limestone suitable for agricultural uses, and clay and shale suitable for structural clay products, all of which can be readily obtained outside the wilderness. A potential for natural gas and geothermal energy may exist but cannot be quantified from present knowledge.

  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. 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.

  11. 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

  12. 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,…

  13. Wind Power Forecasting techniques in complex terrain: ANN vs. ANN-CFD hybrid approach

    NASA Astrophysics Data System (ADS)

    Castellani, Francesco; Astolfi, Davide; Mana, Matteo; Burlando, Massimiliano; Meißner, Cathérine; Piccioni, Emanuele

    2016-09-01

    Due to technology developments, renewable energies are becoming competitive against fossil sources and the number of wind farms is growing, which have to be integrated into power grids. Therefore, accurate power forecast is needed and often operators are charged with penalties in case of imbalance. Yet, wind is a stochastic and very local phenomenon, and therefore hard to predict. It has a high variability in space and time and wind power forecast is challenging. Statistical methods, as Artificial Neural Networks (ANN), are often employed for power forecasting, but they have some shortcomings: they require data sets over several years and are not able to capture tails of wind power distributions. In this work a pure ANN power forecast is compared against a hybrid method, based on the combination of ANN and a physical method using computational fluid dynamics (CFD). The validation case is a wind farm sited in southern Italy in a very complex terrain, with a wide spread turbine layout.

  14. ANN-implemented robust vision model

    NASA Astrophysics Data System (ADS)

    Teng, Chungte; Ligomenides, Panos A.

    1991-02-01

    A robust vision model has been developed and implemented with a self-organizing/unsupervised artificial neural network (ANN) classifier-KART which is a novel hybrid model of a modified Kohonen''s feature map and the Carpenter/Grossberg''s ART architecture. The six moment invariants have been mapped onto a 7-dimensional unit hypersphere and have been applied to the KART classifier. In this paper the KART model will be presented. The non-adaptive neural implementations on the image processing and the moment invariant feature extraction will be discussed. In addition the simulation results that illustrate the capabilities of this model will also be provided. 1.

  15. 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…

  16. 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…

  17. Anne Frank: A Content-Based Research Class.

    ERIC Educational Resources Information Center

    Rosser, Carl

    1995-01-01

    Examines a content-based English-as-a-Second-Language (ESL) research class focusing on Anne Frank because of the dramatic story of her life and the literary quality of her diary's contents. The students were required to write about the character of Anne Frank and to use the same sources for their research journals. The course was a vehicle for…

  18. Notes from Girl X: Anne Frank at the Millennium.

    ERIC Educational Resources Information Center

    Levitsky, Holli

    2002-01-01

    Considers if Anne Frank's diary is still viable or if it has been too far removed from its original author or its original context. Concludes that the book "Anne Frank and Me" offers historical accuracies about the Holocaust while placing its readers squarely at the millennium. (SG)

  19. 77 FR 75629 - Pramaggiore, Anne R.; Notice of Filing

    Federal Register 2010, 2011, 2012, 2013, 2014

    2012-12-21

    ... From the Federal Register Online via the Government Publishing Office DEPARTMENT OF ENERGY Federal 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...

  20. Anne Frank: One of Hundreds of Thousands. [Lesson Plan].

    ERIC Educational Resources Information Center

    2002

    Anne Frank was one of the hundreds of thousands of Jewish children who died in the Holocaust. In that sense, she is not unique; however, through the very ordinary act of writing a diary, through her youthful wisdom and budding literary talent, Anne remains today an extraordinary "symbol of the lost promise of the children who died in the…

  1. 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.

  2. Spectrophotometric determination of synthetic colorants using PSO-GA-ANN.

    PubMed

    Benvidi, Ali; Abbasi, Saleheh; Gharaghani, Sajjad; Dehghan Tezerjani, Marzieh; Masoum, Saeed

    2017-04-01

    Four common food colorants, containing tartrazine, sunset yellow, ponceau 4R and methyl orange, are simultaneously quantified without prior chemical separation. In this study, an effective artificial neural network (ANN) method is designed for modeling multicomponent absorbance data with the presence of shifts or changes of peak shapes in spectroscopic analysis. Gradient descent methods such as Levenberg-Marquardt function are usually used to determine the parameters of ANN. However, these methods may provide inappropriate parameters. In this paper, we propose combination of genetic algorithms (GA) and partial swarm optimization (PSO) to optimize parameters of ANN, and then the algorithm is used to process the relationship between the absorbance data and the concentration of analytes. The hybrid algorithm has the benefits of both PSO and GA techniques. The performance of this algorithm is compared to the performance of PSO-ANN, PC-ANN and ANN based Levenberg-Marquardt function. The obtained results revealed that the designed model can accurately determine colorant concentrations in real and synthetic samples. According to the observations, it is clear that the proposed hybrid method is a powerful tool to estimate the concentration of food colorants with a high degree of overlap using nonlinear artificial neural network.

  3. Can Anne Be Like Margot and Still Be Anne? Adolescent Girls' Development and "Anne Frank: The Diary of a Young Girl."

    ERIC Educational Resources Information Center

    Irwin-DeVitis, Linda; Benjamin, Beth

    1995-01-01

    Explores the thoughts and feelings of a group of young adolescent girls on dilemmas of identity, self, and society through reading and discussing "The Diary of Anne Frank." Discusses adolescent females in literature and life, the double standard revisited, the dilemma of being right or being nice, and the challenge of including girls'…

  4. 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.

  5. 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…

  6. 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,…

  7. 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.

  8. 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)

  9. 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.

  10. 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

    ... environmental impacts in the study area. Upon publication of the Draft EA and a Final EA, MDOT will be... Considering Environmental Impacts; FAA Order 5050.4B, National Environmental Policy Act (NEPA) Implementing... Federal Aviation Administration Notice of Availability of Draft Environmental Assessment; Ann...

  11. An ANN model for treatment prediction in HBV patients

    PubMed Central

    Iqbal, Sajid; Masood, Khalid; Jafer, Osman

    2011-01-01

    Two types of antiviral treatments, namely, interferon and nucleoside/nucleotide analogues are available for hepatitis infections. The selection of drug and dose determined using known pharmacokinetics and pharmacodynamics data is important. The lack of sufficient information for pharmacokinetics of a drug may not produce the desired results. Artificial neural network (ANN) provides a novel model-independent approach to pharmacokinetics and pharmacodynamics data. ANN model is created by supervised learning of 90 patients sample to predict the treatment strategy (lamivudine only and Lamivudine + Interferon) on the basis of viral load, liver function test, visit number, treatment duration, ethnic area, sex, and age. The model was trained with 68 (77.3%) samples and tested with 20 (22.7%) samples. The model produced 92% accuracy with 92.8% sensitivity and 83.3% specificity. PMID:21738322

  12. 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.

  13. 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. |

  14. 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.

    2016-09-01

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

  15. 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.

  16. Gasification characteristics of MSW and an ANN prediction model.

    PubMed

    Xiao, Gang; Ni, Ming-jiang; Chi, Yong; Jin, Bao-sheng; Xiao, Rui; Zhong, Zhao-ping; Huang, Ya-ji

    2009-01-01

    Gasification characteristics make up the important parts of municipal solid waste (MSW) gasification and melting technology. These characteristics are closely related to the composition of MSW, which alters with climates and seasons. It is important to find a practical way to predict gasification characteristics. In this paper, five typical kinds of organic components (wood, paper, kitchen garbage, plastic, and textile) and three representative types of simulated MSW are gasified in a fluidized-bed at 400-800 degrees C with the equivalence ratio (ER) in the range of 0.2-0.6. The lower heating value (LHV) of gas, gasification products, and gas yield are reported. The results indicate that gasification characteristics are different from sample to sample. Based on the experimental data, an artificial neural networks (ANN) model is developed to predict gasification characteristics. The training and validating relative errors are within +/-15% and +/-20%, respectively, and predicting relative errors of an industrial sample are below +/-25%. This indicates that it is acceptable to predict gasification characteristics via ANN model.

  17. Hybridization of GA and ANN to Solve Graph Coloring

    NASA Astrophysics Data System (ADS)

    Maitra, Timir; Pal, Anindya J.; Choi, Minkyu; Kim, Taihoon

    A recent and very promising approach for combinatorial optimization is to embed local search into the framework of evolutionary algorithms. In this paper, we present one efficient hybrid algorithms for the graph coloring problem. Here we have considered the hybridization of Boltzmann Machine (BM) of Artificial Neural Network with Genetic Algorithms. Genetic algorithm we have used to generate different coloration of a graph quickly on which we have applied boltzmann machine approach. Unlike traditional approaches of GA and ANN the proposed hybrid algorithm is guranteed to have 100% convergence rate to valid solution with no parameter tuning. Experiments of such a hybrid algorithm are carried out on large DIMACS Challenge benchmark graphs. Results prove very competitive. Analysis of the behavior of the algorithm sheds light on ways to further improvement.

  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. 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...

  20. 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... of exemption should be issued, and does so here. Notice Ann Arbor Railroad, Inc. (AARR), a Class III... Southern Railway Company (NSR) two rail lines totaling 3.69 miles: (1) A line of railroad between...

  1. Anne Frank in Historical Perspective: A Teaching Guide for Secondary Schools.

    ERIC Educational Resources Information Center

    Grobman, Alex; Fishman, Joel

    This guide helps secondary students to understand "The Diary of Anne Frank" through a series of short essays, maps, and photographs. In view of new scholarship, the historical context in which Anne Frank wrote may be studied to improve the student's perspective of recent history and of the present. A drawing shows the hiding place in the…

  2. 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...

  3. 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... INTERNATIONAL NAVIGATION RULES COLREGS DEMARCATION LINES Atlantic Coast § 80.115 Portland Head, ME to Cape Ann... harbors, bays, and inlets on the east coast of Maine, New Hampshire, and Massachusetts from Portland...

  4. 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... INTERNATIONAL NAVIGATION RULES COLREGS DEMARCATION LINES Atlantic Coast § 80.115 Portland Head, ME to Cape Ann... harbors, bays, and inlets on the east coast of Maine, New Hampshire, and Massachusetts from Portland...

  5. 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... INTERNATIONAL NAVIGATION RULES COLREGS DEMARCATION LINES Atlantic Coast § 80.115 Portland Head, ME to Cape Ann... harbors, bays, and inlets on the east coast of Maine, New Hampshire, and Massachusetts from Portland...

  6. 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

  7. 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

  8. Predicting stream water quality using artificial neural networks (ANN)

    SciTech Connect

    Bowers, J.A.

    2000-05-17

    Predicting point and nonpoint source runoff of dissolved and suspended materials into their receiving streams is important to protecting water quality and traditionally has been modeled using deterministic or statistical methods. The purpose of this study was to predict water quality in small streams using an Artificial Neural Network (ANN). The selected input variables were local precipitation, stream flow rates and turbidity for the initial prediction of suspended solids in the stream. A single hidden-layer feedforward neural network using backpropagation learning algorithms was developed with a detailed analysis of model design of those factors affecting successful implementation of the model. All features of a feedforward neural model were investigated including training set creation, number and layers of neurons, neural activation functions, and backpropagation algorithms. Least-squares regression was used to compare model predictions with test data sets. Most of the model configurations offered excellent predictive capabilities. Using either the logistic or the hyperbolic tangent neural activation function did not significantly affect predicted results. This was also true for the two learning algorithms tested, the Levenberg-Marquardt and Polak-Ribiere conjugate-gradient descent methods. The most important step during model development and training was the representative selection of data records for training of the model.

  9. 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.

  10. Review of Artificial Neural Networks (ANN) applied to corrosion monitoring

    NASA Astrophysics Data System (ADS)

    Mabbutt, S.; Picton, P.; Shaw, P.; Black, S.

    2012-05-01

    The assessment of corrosion within an engineering system often forms an important aspect of condition monitoring but it is a parameter that is inherently difficult to measure and predict. The electrochemical nature of the corrosion process allows precise measurements to be made. Advances in instruments, techniques and software have resulted in devices that can gather data and perform various analysis routines that provide parameters to identify corrosion type and corrosion rate. Although corrosion rates are important they are only useful where general or uniform corrosion dominates. However, pitting, inter-granular corrosion and environmentally assisted cracking (stress corrosion) are examples of corrosion mechanisms that can be dangerous and virtually invisible to the naked eye. Electrochemical noise (EN) monitoring is a very useful technique for detecting these types of corrosion and it is the only non-invasive electrochemical corrosion monitoring technique commonly available. Modern instrumentation is extremely sensitive to changes in the system and new experimental configurations for gathering EN data have been proven. In this paper the identification of localised corrosion by different data analysis routines has been reviewed. In particular the application of Artificial Neural Network (ANN) analysis to corrosion data is of key interest. In most instances data needs to be used with conventional theory to obtain meaningful information and relies on expert interpretation. Recently work has been carried out using artificial neural networks to investigate various types of corrosion data in attempts to predict corrosion behaviour with some success. This work aims to extend this earlier work to identify reliable electrochemical indicators of localised corrosion onset and propagation stages.

  11. 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.

  12. 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.

  13. Objectivity and Commitment in Linguistic Science: The Case of the Black English Trial in Ann Arbor.

    ERIC Educational Resources Information Center

    Labov, William

    1982-01-01

    Discusses the factors that led to linguists being able to present effective testimony in the form of an unified view on the origins and structural characteristics of the Black English vernacular at the Ann Arbor trial. (EKN)

  14. 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

    ... From the Federal Register Online via the Government Publishing Office DEPARTMENT OF THE INTERIOR National Park Service Notice of Inventory Completion: Museum of Anthropology, University of Michigan, Ann Arbor, MI; Correction AGENCY: National Park Service, Interior. ACTION: Notice; correction. Notice...

  15. 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

  16. Water-quality data collected at Lake Anne, Reston, Virginia, 1997-1999

    USGS Publications Warehouse

    Conko, Kathryn M.; Kennedy, Margaret M.; Rice, Karen C.

    2000-01-01

    Samples from the Lake Anne watershed were collected and analyzed to assess the water quality from December 1997 through January 1999. Lake Anne is a stream impoundment in suburban Northern Virginia and its outflow is a sub-tributary of the Potomac River. Samples of wet deposition (precipitation), lake water, and streamwater that drain into and from Lake Anne were collected and analyzed. Trace-element clean sampling and analysis protocols were followed throughout the project. This report is a compilation of the precipitation, lake-water, and streamwater data collected in the Lake Anne watershed and the associated quality assurance/quality control data. Concentrations of the trace elements arsenic, barium, cadmium, chromium, copper, lead, manganese, nickel, strontium, vanadium, and zinc, and of the major inorganic ions, aluminum, bicarbonate, calcium, chloride, hydrogen ion, iron, magnesium, potassium, nitrate, sodium, and sulfate are reported.

  17. Flowering a Feminist Garden: The Writings and Poetry of Anne Spencer.

    ERIC Educational Resources Information Center

    Ford, Charita M.

    1988-01-01

    Reviews the life and poetry of Anne Spencer, one of the "lost" poets of the Harlem Renaissance. Discusses her varied and effective use of imagery and examines the Black and feminist perspectives of her work. (FMW)

  18. 76 FR 81991 - Tecumseh Products Corporation, Ann Arbor, MI; Notice of Termination of Investigation

    Federal Register 2010, 2011, 2012, 2013, 2014

    2011-12-29

    ... From the Federal Register Online via the Government Publishing Office DEPARTMENT OF LABOR Employment and Training Administration Tecumseh Products Corporation, Ann Arbor, MI; Notice of Termination of Investigation On September 15, 2011, the Department issued a Notice of Affirmative Determination...

  19. ANN Prediction of Metabolic Syndrome: a Complex Puzzle that will be Completed.

    PubMed

    Ivanović, Darko; Kupusinac, Aleksandar; Stokić, Edita; Doroslovački, Rade; Ivetić, Dragan

    2016-12-01

    The diagnosis of metabolic syndrome (MetS) has a leading role in the early prevention of chronic disease, such as cardiovascular disease, type 2 diabetes, cancers and chronic kidney disease. It would be very greatful that MetS diagnosis can be predicted in everyday clinical practice. This paper presents artificial neural network (ANN) prediction of the diagnosis of MetS that includes solely non-invasive, low-cost and easily-obtained diagnostic methods. This solution can extract the risky persons and suggests complete tests only on them by saving money and time. ANN input vectors are very simple and contain solely non-invasive, low-cost and easily-obtained parameters: gender, age, body mass index, waist-to-height ratio, systolic and diastolic blood pressures. ANN output is M e t S-coefficient in true/false form, obtained from MetS definition of International Diabetes Federation (IDF). ANN training, validation and testing are conducted on the large dataset that includes 2928 persons. Feed-forward ANNs with 1-100 hidden neurons were considered and an optimal architecture were determinated. Comparison with other authors leads to the conclusion that our solution achieves the highest positive predictive value P P V = 0.8579. Further, obtained negative predictive value N P V = 0.8319 is also high and close to PPV, which means that our ANN solution is suitable both for positive and negative MetS prediction.

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

    PubMed

    Kamesh, Reddi; Rani, Kalipatnapu Yamuna

    2016-10-13

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

  1. 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.

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

    SciTech Connect

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

    2010-10-26

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

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

    NASA Astrophysics Data System (ADS)

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

    2017-03-01

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

  4. 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.

  5. 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.

  6. 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.

  7. 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.

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

    NASA Astrophysics Data System (ADS)

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

    2010-10-01

    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.

  9. 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.

  10. 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.

  11. Cotton AnnGh3 encoding an annexin protein is preferentially expressed in fibers and promotes initiation and elongation of leaf trichomes in transgenic Arabidopsis.

    PubMed

    Li, Bing; Li, Deng-Di; Zhang, Jie; Xia, Hui; Wang, Xiu-Lan; Li, Ying; Li, Xue-Bao

    2013-10-01

    The annexins are a multifamily of calcium-regulated phospholipid-binding proteins. To investigate the roles of annexins in fiber development, four genes encoding putative annexin proteins were isolated from cotton (Gossypium hirsutum) and designated AnnGh3, AnnGh4, AnnGh5, and AnnGh6. Quantitative reverse transcription-polymerase chain reaction (qRT-PCR) results indicated that AnnGh3, AnnGh4, and AnnGh5 were preferentially expressed in fibers, while the transcripts of AnnGh6 were predominantly accumulated in roots. During fiber development, the transcripts of AnnGh3/4/5 genes were mainly accumulated in rapidly elongating fibers. With fiber cells further developed, their expression activity was dramatically declined to a relatively low level. In situ hybridization results indicated that AnnGh3 and AnnGh5 were expressed in initiating fiber cells (0-2 DPA). Additionally, their expression in fibers was also regulated by phytohormones and [Ca(2+)]. Subcellular localization analysis discovered that AnnGh3 protein was localized in the cytoplasm. Overexpression of AnnGh3 in Arabidopsis resulted in a significant increase in trichome density and length on leaves of the transgenic plants, suggesting that AnnGh3 may be involved in fiber cell initiation and elongation of cotton.

  12. 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…

  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. 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…

  15. 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)

  16. 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…

  17. 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…

  18. Alternate Sources of Funding: Scholarship Fund Raising. and Anne Arundel Community College Scholarship Fund Raising Campaign.

    ERIC Educational Resources Information Center

    Weinberg, Barry M.

    This two-part paper provides guidance on alternative sources of funding for college scholarships and describes Anne Arundel Community College's (AACC's) Scholarship Fund Raising Campaign. First, an outline is presented, covering: (1) prerequisites to fundraising (i.e., leadership, sense of direction, commitment, and a plan for identifying,…

  19. 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: National Park Service, Interior. ACTION: Notice. SUMMARY: The University of Michigan has completed an... remains should submit a written request to the University of Michigan. If no additional requestors...

  20. 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: National Park Service, Interior. ACTION: Notice. SUMMARY: The University of Michigan has completed an... submit a written request to the University of Michigan. If no additional requestors come...

  1. 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: National Park Service, Interior. ACTION: Notice. SUMMARY: The University of Michigan has completed an... submit a written request to the University of Michigan. If no additional requestors come...

  2. 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: National Park Service, Interior. ACTION: Notice. SUMMARY: The University of Michigan has completed an... remains should submit a written request to the University of Michigan. If no additional requestors...

  3. 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: National Park Service, Interior. ACTION: Notice. SUMMARY: The University of Michigan has completed an... remains should submit a written request to the University of Michigan. If no additional requestors...

  4. 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…

  5. 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 INTERNATIONAL NAVIGATION RULES COLREGS DEMARCATION LINES Atlantic Coast § 80.115 Portland Head, ME to Cape...

  6. 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.

  7. 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…

  8. 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)

  9. 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.…

  10. 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.

  11. 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

    ... Nonattainment Area; Fine Particulate Matter 2005 Base Year Emissions Inventory AGENCY: Environmental Protection... base year emissions inventory, a portion of the State Implementation Plan (SIP) revision submitted by... rulemaking to approve Michigan's PM 2.5 2005 base year emissions inventory for the Detroit-Ann Arbor...

  12. 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

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

  13. 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

    ... National Park Service Notice of Inventory Completion: Museum of Anthropology, University of Michigan, Ann Arbor, MI AGENCY: National Park Service, Interior. ACTION: Notice. SUMMARY: The Museum of Anthropology... affiliated with the human remains may contact the Museum of Anthropology, University of...

  14. 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…

  15. 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…

  16. 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.…

  17. 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…

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

    PubMed

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

    2016-11-01

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

  19. Damaging Confusions in England's KS2 Reading Tests: A Response to Anne Kispal

    ERIC Educational Resources Information Center

    Hilton, Mary

    2006-01-01

    This article is written in response to the article published in issue 39.3 of this journal, in November 2005, on the nature of the Key Stage 2 National Curriculum reading tests: "Examining England's National Curriculum assessments: an analysis of the KS2 reading test questions" by Anne Kispal of the National Foundation for Educational…

  20. ANN reconstruction of geoelectrical parameters of the Minou fault zone by scalar CSAMT data

    NASA Astrophysics Data System (ADS)

    Spichak, V.; Fukuoka, K.; Kobayashi, T.; Mogi, T.; Popova, I.; Shima, H.

    2002-01-01

    Scalar controlled source AMT data collected in a northern part of the Minou fault area (Kyushu Island, Japan) are interpreted by means of the ANN Expert System MT-NET in terms of 3-D earth macro-parameters. A number of synthetic responses created in advance by means of forward modeling in typical 3-D geoelectrical models (conductive and resistive local bodies, fault, dyke, etc.) formed sequences for teaching an artificial neural network (ANN). MT-NET, once taught to the correspondence between the data images and the model parameters, is able to recognize unknown parameters given even incomplete and noisy data. The results of ANN reconstruction are compared with the resistivity distribution obtained for the same area using fast 3-D imaging based on synthesis of 1-D Bostick transforms of the apparent resistivities beneath each site as well as on 2-D TM mode inversion along four profiles. The best-fitting model reconstructed by ANN belongs to the guessed model class formed by "dykes buried in the two-layered earth", on the one hand, and to the equivalence class formed by all models giving rms misfit less than the noise level in the data, on the other hand.

  1. 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…

  2. Assessment of Impact Detection Techniques for Aeronautical Application: ANN vs. LSSVM

    NASA Astrophysics Data System (ADS)

    Yue, N.; Sharif Khodaei, Z.

    2016-10-01

    The impact localization in composite panels is assessed using two machine learning techniques: least square support vector machines (LSSVM) and artificial neural networks (ANN) with local strain signals from piezoelectric sensors. Sensor signals from impact experiments on a composite plate as well as signals simulated by a finite element model are used to train and test models. A comparative study shows that LSSVM achieves better accuracy than ANN on identifying location of impacts for a combination of large mass impact and small mass impact, in particular when less data is available for training which is more appropriate for real aeronautical application. Additionally, LSSVM is more capable of identifying new impact events which have not been considered in the training process.

  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. 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.

  5. 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.

  6. 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.

  7. 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.

  8. Muscle force estimation with surface EMG during dynamic muscle contractions: a wavelet and ANN based approach.

    PubMed

    Bai, Fengjun; Chew, Chee-Meng

    2013-01-01

    Human muscle force estimation is important in biomechanics studies, sports and assistive devices fields. Therefore, it is essential to develop an efficient algorithm to estimate force exerted by muscles. The purpose of this study is to predict force/torque exerted by muscles under dynamic muscle contractions based on continuous wavelet transform (CWT) and artificial neural networks (ANN) approaches. Mean frequency (MF) of the surface electromyography (EMG) signals power spectrum was calculated from CWT. ANN models were trained to derive the MF-force relationships from the subset of EMG signals and the measured forces. Then we use the networks to predict the individual muscle forces for different muscle groups. Fourteen healthy subjects (10 males and 4 females) were voluntarily recruited in this study. EMG signals were collected from the biceps brachii, triceps, hamstring and quadriceps femoris muscles to evaluate the proposed method. Root mean square errors (RMSE) and correlation coefficients between the predicted forces and measured actual forces were calculated.

  9. [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.

  10. The Anne Boleyn Illusion is a Six-Fingered Salute to Sensory Remapping

    PubMed Central

    Wong, Dominic Y.; Howard, Ellen M.; Silver, Eden

    2016-01-01

    The Anne Boleyn Illusion exploits the somatotopic representation of touch to create the illusion of an extra digit and demonstrates the instantaneous remapping of relative touch location into body-based coordinates through visuo-tactile integration. Performed successfully on thousands, it is also a simple demonstration of the flexibility of body representations for use at public events, in schools or in the home and can be implemented anywhere by anyone with a mirror and some degree of bimanual coordination. PMID:27708755

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

    ScienceCinema

    Mary Ann Piette

    2016-07-12

    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. Prediction of frequency for simulation of asphalt mix fatigue tests using MARS and ANN.

    PubMed

    Ghanizadeh, Ali Reza; 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.

  14. 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

  15. 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.

  16. Use of ANN modelling in structure--retention relationships of diuretics in RP-HPLC.

    PubMed

    Agatonovic-Kustrin, S; Zecevic, M; Zivanovic, L

    1999-10-01

    Structure retention relationship study, conducted by RP HPLC, was used to investigate physical chemical parameters related to the RP retention times of amiloride, hydrochlorothiazide and methyldopa in order to predict the separation of amiloride and methylclothiazide from Lometazid tablets. Retention data were obtained with an ODS column using a mobile phase methanol water (pH adjusted with phosphoric acid). Physical chemical properties were calculated directly from the molecular structure. Artificial neural networks (ANNs) were used to correlate chromatograms retention times with mobile phase composition and pH, and with physical chemical properties of amiloride, hydrochlorothiazide and methyldopa and to predict separation of amiloride and methylclothiazide from Lometazid tablets. Sensitivity analysis was performed to interpret the meaning of the descriptors included in the models. Results confirmed the dominant role of the polar modifier in such chromatographic systems. Within a series of solutes chromatographed under identical conditions, the retention parameters could be approximated by a non-linear combination of logP, logD, pKa, surface tension, parachor, molar volume and to minor extend by polarisability, reetractivity index and density. This study has demonstrated that the use ANNs techniques can result in much more efficient use of experimental information. As HPLC is the most popular analytical technique, improvements in HPLC methods development can yield significant gains in the overall analytical effort. The ANNs extension presented could be the method of choice in some advanced research settings and serves as an indication of the broad potential of neural networks in chromatography analysis.

  17. 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.

  18. Multiple Regression (MR) and Artificial Neural Network (ANN) models for prediction of soil suction

    NASA Astrophysics Data System (ADS)

    Erzin, Yusuf; Yilmaz, Isik

    2010-05-01

    This article presents a comparison of multiple regression (MR) and artificial neural network (ANN) model for prediction of soil suction of clayey soils. The results of the soil suction tests utilizing thermocouple psychrometers on statically compacted specimens of Bentonite-Kaolinite clay mixtures with varying soil properties were used to develope the models. The results obtained from both models were then compared with the experimental results. The performance indices such as coefficient of determination (R2), root mean square error (RMSE), mean absolute error (MAE), and variance account for (VAF) were used to control the performance of the prediction capacity of the models developed in this study. ANN model has shown higher prediction performance than regression model according to the performance indices. It is shown that ANN models provide significant improvements in prediction accuracy over statistical models. The potential benefits of soft computing models extend beyond the high computation rates. Higher performances of the soft computing models were sourced from greater degree of robustness and fault tolerance than traditional statistical models because there are many more processing neurons, each with primarily local connections. It appears that there is a possibility of estimating soil suction by using the proposed empirical relationships and soft computing models. The population of the analyzed data is relatively limited in this study. Therefore, the practical outcome of the proposed equations and models could be used, with acceptable accuracy.

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

    PubMed

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

    2015-09-01

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

  20. [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.

  1. 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 Carnival Corporation hereinafter ``Respondents.'' Complainant alleges that: Respondent Princess...

  2. 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

  3. High-Resolution Geologic Mapping of the Inner Continental Shelf: Cape Ann to Salisbury Beach, Massachusetts

    USGS Publications Warehouse

    Barnhardt, Walter A.; Andrews, Brian D.; Ackerman, Seth D.; Baldwin, Wayne E.; Hein, Christopher J.

    2009-01-01

    The geologic framework of the Massachusetts inner continental shelf between Cape Ann and Salisbury Beach has been shaped by a complicated history of glaciation, deglaciation, and changes in relative sea level. New geophysical data (swath bathymetry, sidescan sonar and seismic-reflection profiling), sediment samples, and seafloor photography provide insight into the geomorphic and stratigraphic record generated by these processes. High-resolution spatial data and geologic maps in this report support coastal research and efforts to understand the type, distribution, and quality of subtidal marine habitats in the Massachusetts coastal ocean.

  4. 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

  5. Rough Set-Based Analysis of Characteristic Features for ANN Classifier

    NASA Astrophysics Data System (ADS)

    Stańczyk, Urszula

    Selection of characteristic features for a classification task is always crucial to high recognition ratio, regardlessly of the particular processing technique applied. Most methodologies offer some inherent mechanisms of dimension reduction that lead to expression of available data in more succinct way, however, combining elements of distinctively different approaches to data analysis brings interesting conclusions as to the role of particular features and their influence on the power of the resulting classifier. The paper presents research on such fusion of processing techniques, namely employing rough set based analysis of features for ANN classifier within stylometric studies on writing styles.

  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. 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.

  8. Dynamic Flow Modeling Using Double POD and ANN-ARX System Identification

    NASA Astrophysics Data System (ADS)

    Siegel, Stefan; Seidel, Jürgen; Cohen, Kelly; Aradag, Selin; McLaughlin, Thomas

    2007-11-01

    Double Proper Orthogonal Decomposition (DPOD), a modification of conventional POD, is a powerful tool for modeling of transient flow field spatial features, in particular, a 2D cylinder wake at a Reynolds number of 100. To develop a model for control design, the interaction of DPOD mode amplitudes with open-loop control inputs needs to be captured. Traditionally, Galerkin projection onto the Navier Stokes equations has been used for that purpose. Given the stability problems as well as issues in correctly modeling actuation input, we propose a different approach. We demonstrate that the ARX (Auto Regressive eXternal input) system identification method in connection with an Artificial Neural Network (ANN) nonlinear structure leads to a model that captures the dynamic behavior of the unforced and transient forced open loop data used for model development. Moreover, we also show that the model is valid at different Reynolds numbers, for different open loop forcing parameters, as well as for closed loop flow states with excellent accuracy. Thus, we present with this DPOD-ANN-ARX model a paradigm shift for laminar circular cylinder wake modeling that is proven valid for feedback flow controller development.

  9. Mineral resource potential map of the Dolly Ann Roadless Area, Alleghany County, Virginia

    USGS Publications Warehouse

    Lesure, Frank G.; Jones, Jay G.

    1983-01-01

    The Dolly Ann Roadless Area comprises 7,900 acres (3,200 ha) in the George Washington National Forest in the Valley and Ridge physiographic province of west-central Virginia. The area is at the southern ·end of Warm Springs Mountain in Alleghany County just northeast of Covington, the county seat (index map). U.S. Highway 220 forms part of the western boundary, and U.S. Forest Service Road 125, which parallels Pounding Mill Creek, forms the eastern boundary. The principal streams draining the area are Pounding Mill Creek, Dry Run, and Roaring Run, all tributaries of the Jackson River. The highest point in the area is Big Knob at the north end, 4,072 ft (1241 m) above sea level; the lowest points, about 1,400 ft (427 m) above sea level, are at the south side, along Dry Run and Pounding Mill Creek. In general, the hill slopes are steep and heavily wooded with second- or third-growth hardwoods and scattered pine and hemlock. Dolly Ann Hollow near the east end of the area is a steep, boulder-strewn gorge, quite picturesque, but containing no good trails. A good trail up Dry Run connects a trail crossing the ridge between Bald Knob and Big Knob. No other trails cross the area.

  10. 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%.

  11. Comparison of predictive ability of water solubility QSPR models generated by MLR, PLS and ANN methods.

    PubMed

    Erös, Dániel; Kéri, György; Kövesdi, István; Szántai-Kis, Csaba; Mészáros, György; Orfi, László

    2004-02-01

    ADME/Tox computational screening is one of the most hot topics of modern drug research. About one half of the potential drug candidates fail because of poor ADME/Tox properties. Since the experimental determination of water solubility is time-consuming also, reliable computational predictions are needed for the pre-selection of acceptable "drug-like" compounds from diverse combinatorial libraries. Recently many successful attempts were made for predicting water solubility of compounds. A comprehensive review of previously developed water solubility calculation methods is presented here, followed by the description of the solubility prediction method designed and used in our laboratory. We have selected carefully 1381 compounds from scientific publications in a unified database and used this dataset in the calculations. The externally validated models were based on calculated descriptors only. The aim of model optimization was to improve repeated evaluations statistics of the predictions and effective descriptor scoring functions were used to facilitate quick generation of multiple linear regression analysis (MLR), partial least squares method (PLS) and artificial neural network (ANN) models with optimal predicting ability. Standard error of prediction of the best model generated with ANN (with 39-7-1 network structure) was 0.72 in logS units while the cross validated squared correlation coefficient (Q(2)) was better than 0.85. These values give a good chance for successful pre-selection of screening compounds from virtual libraries, based on the predicted water solubility.

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

    PubMed

    Albaradeyia, Issa; Hani, Azzedine; Shahrour, Isam

    2011-09-01

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

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

    PubMed

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

    2014-10-01

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

  14. 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.

  15. [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.

  16. Improving offline handwritten text recognition with hybrid HMM/ANN models.

    PubMed

    España-Boquera, Salvador; Castro-Bleda, Maria Jose; Gorbe-Moya, Jorge; Zamora-Martinez, Francisco

    2011-04-01

    This paper proposes the use of hybrid Hidden Markov Model (HMM)/Artificial Neural Network (ANN) models for recognizing unconstrained offline handwritten texts. The structural part of the optical models has been modeled with Markov chains, and a Multilayer Perceptron is used to estimate the emission probabilities. This paper also presents new techniques to remove slope and slant from handwritten text and to normalize the size of text images with supervised learning methods. Slope correction and size normalization are achieved by classifying local extrema of text contours with Multilayer Perceptrons. Slant is also removed in a nonuniform way by using Artificial Neural Networks. Experiments have been conducted on offline handwritten text lines from the IAM database, and the recognition rates achieved, in comparison to the ones reported in the literature, are among the best for the same task.

  17. 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.

  18. The heart of Blessed Anne-Madeleine Remuzat: a biomedical approach of "miraculous" heart conservation.

    PubMed

    Charlier, Philippe; Huynh-Charlier, Isabelle; Poupon, Joël; Fox, Carles Lalueza; Keyser, Christine; Mougniot, Christian; Popescu, Spéranta-Maria; Brun, Luc; Pietri, Sylvia; Thévenard, Frédéric; Laquay, Laëtitia; Hurel, Agathe; Ellul, Jean-Pierre; Hervé, Christian

    2014-01-01

    We present here the results of our inter-disciplinary examination of the mummified heart of Blessed Anne-Madeleine Remuzat (1696-1730). This organ has been examined in the context of a canonization process. This analysis is related to important aspects of the early history of anatomy in Europe, that of "Holy autopsies", and to the relationship between anatomical investigations, Catholic theology, and religious/medical customs. According to anatomical, genetic, toxicological, and palynological analyses, it has been shown that this organ has not been naturally ("miraculously") conserved but embalmed using myrtle, honey, and lime. Moreover, a right ventricle dilatation has been diagnosed, that may represent a post-tuberculosis condition and may have played a role in the cause of death of this religious figure.

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

    NASA Astrophysics Data System (ADS)

    Ekinci, Şerafettin; Akdemir, Ahmet; Kahramanli, Humar

    2013-05-01

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

  20. 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.

  1. 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.

  2. 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

    ... the International Traffic in Arms Regulations (ITAR) (22 CFR parts 120 to 130) on LeAnne Lesmeister... Regulations (``ITAR''), the implementing regulations of Section 38 of the Arms Export Control Act, as amended... services. Section 127.7(a) of the ITAR authorizes the Assistant Secretary of State for...

  3. 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

    ... To Repatriate Cultural Items: University of Michigan Museum of Anthropology, Ann Arbor, MI AGENCY: National Park Service, Interior. ACTION: Notice. SUMMARY: The University of Michigan Museum of Anthropology... with the sacred objects may contact the University of Michigan Museum of Anthropology....

  4. 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...

  5. 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."…

  6. 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.

  7. 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…

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

    PubMed Central

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

    2016-01-01

    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

  9. 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

  10. RSM and ANN modeling-based optimization approach for the development of ultrasound-assisted liposome encapsulation of piceid.

    PubMed

    Huang, Shang-Ming; Kuo, Chia-Hung; Chen, Chun-An; Liu, Yung-Chuan; Shieh, Chwen-Jen

    2017-05-01

    Piceid, a naturally occurring derivative of resveratrol found in many plants, has recently been considered as a potential nutraceutical. However, its poorly water-soluble property could cause a coupled problem of biological activities concerning drug dispersion and absorption in human body, which is still unsolved now. Liposome, a well-known aqueous carrier for water-insoluble ingredients, is commonly applied in drug delivery systems. In this study, a feasible approach for solving the problem is that the targeted piceid was encapsulated into a liposomal formula as aqueous substrate to overcome its poor water-solubility. The encapsulation process was assisted by ultrasound, with investigation of lipid content, ultrasound power and ultrasound time, for controlling encapsulation efficiency (E.E%), absolute loading (A.L%) and particle size (PS). Moreover, both RSM and ANN methodologies were further applied to optimize the ultrasound-assisted encapsulation process. The data indicated that the most important effects on the encapsulation performance were found to be of lipid content followed by ultrasound time and ultrasound power. The maximum E.E% (75.82%) and A.L% (2.37%) were exhibited by ultrasound assistance with the parameters of 160mg lipid content, ultrasound time for 24min and ultrasound power of 90W. By methodological aspects of processing, the predicted E.E% and A.L% were respectively in good agreement with the experimental results for both RSM and ANN. Moreover, RMSE, R(2) and AAD statistics were further used to compare the prediction abilities of RSM and ANN based on the validation data set. The results indicated that the prediction accuracy of ANN was better than that of RSM. In conclusion, ultrasound-assisted liposome encapsulation can be an efficient strategy for producing well-soluble/dispersed piceid, which could be further applied to promote human health by increased efficiency of biological absorption, and the process of ultrasound-mediated liposome

  11. Comparison of Different Artificial Neural Network (ANN) Architectures in Modeling of Chlorella sp. Flocculation.

    PubMed

    Zenooz, Alireza Moosavi; Ashtiani, Farzin Zokaee; Ranjbar, Reza; Nikbakht, Fatemeh; Bolouri, Oberon

    2017-01-03

    Biodiesel production from microalgae feedstock should be performed after growth and harvesting of the cells and the most feasible method for harvesting and dewatering of microalgae is flocculation. Flocculation modeling can be used for evaluation and prediction of its performance under different affective parameters. However, the modeling of flocculation in microalgae is not simple and has not performed yet, under all experimental conditions, mostly due to different behaviors of microalgae cells during the process under different flocculation conditions. In the current study, the modeling of microalgae flocculation is studied with different neural network architectures. Microalgae specie, Chlorella sp., was flocculated with ferric chloride under different conditions and then the experimental data modeled using artificial neural network (ANN). Neural network architectures of Multilayer Perceptron (MLP) and Radial Basis Function (RBF) architectures, failed to predict the targets successfully, though, modeling was effective with ensemble architecture of MLP networks. Comparison between the performances of the ensemble and each individual network explains the ability of the ensemble architecture in microalgae flocculation modeling.

  12. Amygdalostriatal projections in the neurocircuitry for motivation: A neuroanatomical thread through the career of Ann Kelley

    PubMed Central

    Zorrilla, Eric P.; Koob, George F.

    2013-01-01

    In MacLean’s triune brain, the amygdala putatively subserves motivated behavior by modulating the “reptilian” basal ganglia. Accordingly, Ann Kelley, with Domesick and Nauta, influentially showed that amygdalostriatal projections are much more extensive than were appreciated. Caudal of the anterior commissure, the entire striatum receives afferents from deep basal nuclei of the amygdala. They highlighted that amygdalar projections to the rostral ventromedial striatum converged with projections from the ventral tegmental area and cingulate cortex, forming a “limbic striatum”. Orthologous topographic projections subsequently were observed in fish, amphibians, and reptiles. Subsequent functional studies linked acquired value to action via this neuroanatomical substrate. From Dr. Kelley’s work evolved insights into components of the distributed, interconnected network that subserves motivated behavior, including the nucleus accumbens shell and core and the striatal-like extended amygdala macrostructure. These heuristic frameworks provide a neuroanatomical basis for adaptively translating motivation into behavior. The ancient amygdala-to-striatum pathways remain a current functional thread not only for stimulus–response valuation, but also for the psychopathological plasticity that underlies addictionrelated memory, craving and relapse. PMID:23220696

  13. 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.

  14. 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.

  15. 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.

  16. An Emotional ANN (EANN) approach to modeling rainfall-runoff process

    NASA Astrophysics Data System (ADS)

    Nourani, Vahid

    2017-01-01

    This paper presents the first hydrological implementation of Emotional Artificial Neural Network (EANN), as a new generation of Artificial Intelligence-based models for daily rainfall-runoff (r-r) modeling of the watersheds. Inspired by neurophysiological form of brain, in addition to conventional weights and bias, an EANN includes simulated emotional parameters aimed at improving the network learning process. EANN trained by a modified version of back-propagation (BP) algorithm was applied to single and multi-step-ahead runoff forecasting of two watersheds with two distinct climatic conditions. Also to evaluate the ability of EANN trained by smaller training data set, three data division strategies with different number of training samples were considered for the training purpose. The overall comparison of the obtained results of the r-r modeling indicates that the EANN could outperform the conventional feed forward neural network (FFNN) model up to 13% and 34% in terms of training and verification efficiency criteria, respectively. The superiority of EANN over classic ANN is due to its ability to recognize and distinguish dry (rainless days) and wet (rainy days) situations using hormonal parameters of the artificial emotional system.

  17. Developing an ANN electron density profile model over Cyprus based on ionosonde measurements

    NASA Astrophysics Data System (ADS)

    Haralambous, H.; Papadopoulos, Harris; Mostafa, Md. Golam

    2015-06-01

    The impact of the upper atmosphere on navigation, communication as well as surveillance systems is defined by the state of the ionosphere and in particular by variations in its electron density profile along the signal propagation path. The requirement for the accurate specification of the electron density profile stems from the fact that the electron density at each altitude determines the refractive index for radiowaves that are refracted by or penetrate the ionosphere and therefore affects significantly navigation and communication signals. Consequently satellite systems that are based on trans-ionospheric propagation may be affected by complex variations in the ionospheric structure in space and time leading to degradation of the availability, accuracy and reliability of their services. Therefore the specification of the electron density profile over a geographical region is very important within the context of operation of such systems. Although regional models have been developed for such a purpose by interpolating data coming from different instruments using various techniques, for a limited geographical scope, the single station model approach is the preferable option as it best encapsulates the behaviour of the ionosphere over the station. This paper presents the development of an Artificial Neural Network (ANN) model for the electron density profile of the ionosphere over Cyprus based on manually scaled ionograms collected at the Nicosia ionosonde station during the period 2009-2013.

  18. Watershed optimization of best management practices using AnnAGNPS and a genetic algorithm

    NASA Astrophysics Data System (ADS)

    Srivastava, P.; Hamlett, J. M.; Robillard, P. D.; Day, R. L.

    2002-03-01

    An optimization algorithm linked with a nonpoint source (NPS) pollution model can be used to optimize NPS pollution control strategies on a field-by-field basis in a watershed by maximizing NPS pollution reduction and net monetary return. In this paper a methodology is described which integrated a genetic algorithm (GA) (an optimization algorithm) with a continuous simulation, watershed-scale, NPS pollution model, Annualized Agricultural Non-Point Source Pollution model (AnnAGNPS) to optimize the selection of best management practices (BMP) on a field-by-field basis for an entire watershed. To test the methodology, optimization analysis was performed for a U.S. Department of Agriculture experimental watershed in Pennsylvania to identify BMPs that minimized long-term (over a 4-year period) water quality degradation and maximized net farm return on an annual basis. Results indicate that the GA was able to identify BMP schemes that reduced pollutant load by as much as 56% and increased net annual return by 109%.

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

    PubMed

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

    2015-05-20

    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.

  20. Detection and molecular characterization of an aster yellows phytoplasma in poker statice and Queen Anne's lace in Alberta, Canada.

    PubMed

    Chang, Kan-Fa; Hwang, Sheau-Fang; Khadhair, Abdul-Hameed; Kawchuk, Lawrence; Howard, Ronald

    2004-01-01

    Queen Anne's lace and poker statice plants were found with a yellows-type disease with typical phytoplasma symptoms in an experimental farm near Brooks, Alberta in 1996. Phytoplasma bodies were detected by transmission electron microscopy in phloem cells of symptomatic plants, but not in healthy plants. The presence of a phytoplasma was confirmed by analysis with the polymerase chain reaction. Using a pair of universal primer sequences derived from phytoplasma 16S rRNA, an amplified product of the expected size (1.2 kb) was observed in samples from infected plants, but not in asymptomatic plants. Sequence analysis of the PCR products from the 16S/23S rDNA intergenic spacer region indicated that the two phytoplasma isolates in Queen Anne's lace and poker statice are genetically closely related to the western aster yellows phytoplasma.

  1. Geology-based method of assessing sensitivity of streams to acidic deposition in Charles and Anne Arundel Counties, Maryland

    USGS Publications Warehouse

    Rice, Karen C.; Bricker, Owen P.

    1991-01-01

    The report describes the results of a study to assess the sensitivity of streams to acidic deposition in Charles and Anne Arundel Counties, Maryland using a geology-based method. Water samples were collected from streams in July and August 1988 when streams were at base-flow conditions. Eighteen water samples collected from streams in Charles County, and 17 water samples from streams in Anne Arundel County were analyzed in the field for pH, specific conductance, and acid-neutralizing capacity (ANC); 8 water samples from streams in Charles County were analyzed in the laboratory for chloride and sulfate concentrations. The assessment revealed that streams in these counties are sensitive to acidification by acidic deposition.

  2. 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.

  3. Comparison of geology of Jurassic Norphlet Mary Ann field, Mobile Bay, Alabama, to onshore regional Norphlet trends

    SciTech Connect

    Marzono, M.; Pense, G.; Andronaco, P.

    1988-09-01

    The geology of the Mary Ann field is better understood in light of regional studies, which help to establish a depositional model in terms of both facies and thickness variations. These studies also illustrate major differences between onshore and offshore Norphlet deposits concerning topics such as diagenesis, hydrocarbon trapping, and migration. The Jurassic Norphlet sandstone was deposited in an arid basin extending from east Texas to Florida by a fluvial-eolian depositional system, prior to the transgression of the Smackover Formation. Until discovery of the Mary Ann field in 1979, Norphlet production was restricted to onshore areas, mostly along the Pickens-Pollard fault system in Mississippi, Alabama, and Florida. The Mary Ann field is a Norphlet dry-gas accumulation, and was the first offshore field in the Gulf of Mexico to establish economic reserves in the Jurassic. The field is located in Mobile Bay, approximately 25 mi (40 km) south of Mobile, Alabama. Formed by a deep-seated (more than 20,000 ft or 6096 m) faulted salt pillow, Mary Ann field produces from a series of stacked eolian dune sands situated near the Norphlet paleocoastline. Five lithofacies have been recognized in cores from the Mobil 76 No. 2 well. Each lithofacies has a distinct reservoir quality. Optimum reservoir faces are the dune and sheet sands. Nonreservoir facies are interdune (wet and dry), marine reworked, and evaporitic sands. Following deposition, these sediments have undergone varying amounts of diagenesis. Early cementation of well-sorted sands supported the pore system during compaction. However, late cementation by chlorite, silica, and alteration of liquid hydrocarbons to an asphaltic residue have completely occluded the pore system in parts of the reservoir.

  4. [Determination of brix and POL in sugar cane juice by using near infrared spectroscopy coupled with BP-ANN].

    PubMed

    Wang, Xin; Ye, Hua-jun; Li, Qing-tao; Xie, Jin-chun; Lu, Jia-jiong; Xia, A-lin; Wang, Jian

    2010-07-01

    The models of quantitative analysis of brix and pol in sugar cane juice were established by using near infrared spectroscopy (NIR) coupled with the back propagation-artificial neural network method (BP-ANN). The spectra of cane juice samples were obtained by the way of 2 mm optical length transmission and using the NIR spectrometer of 1,000-1,800 nm wavelength. Firstly, the data of original spectra were pretreated by Savitzky-Golay derivative and mean-centering. Secondly, the wavelength range of model was optimized by using correlation coefficient method coupled with the characteristic absorbance of the spectrum. Finally, the principal components, obtained by PLS dimension-reducing, were inputed into BP-ANN. The calibration models were established by calibration set and validated by prediction set. The results showed that the related coefficients (R2) of prediction for brix and pol were 0.982 and 0.979, respectively; and the standard errors of prediction (SEP) for brix and pol were 0.159 and 0.137, respectively. BP-ANN was more accurate in the prediction of brix and pol compared with the partial least square method (PLS). The method can be applied to fast and accurate determination of brix and pol in sugar cane juice.

  5. 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

  6. Seafloor monitoring west of Helgoland (German Bight, North Sea) using the acoustic ground discrimination system RoxAnn

    NASA Astrophysics Data System (ADS)

    Hass, H. Christian; Mielck, Finn; Fiorentino, Dario; Papenmeier, Svenja; Holler, Peter; Bartholomä, Alexander

    2016-11-01

    Marine habitats of shelf seas are in constant dynamic change and therefore need regular assessment particularly in areas of special interest. In this study, the single-beam acoustic ground discrimination system RoxAnn served to assess seafloor hardness and roughness, and combine these parameters into one variable expressed as RGB (red green blue) color code followed by k-means fuzzy cluster analysis (FCA). The data were collected at a monitoring site west of the island of Helgoland (German Bight, SE North Sea) in the course of four surveys between September 2011 and November 2014. The study area has complex characteristics varying from outcropping bedrock to sandy and muddy sectors with mostly gradual transitions. RoxAnn data enabled to discriminate all seafloor types that were suggested by ground-truth information (seafloor samples, video). The area appears to be quite stable overall; sediment import (including fluid mud) was detected only from the NW. Although hard substrates (boulders, bedrock) are clearly identified, the signal can be modified by inclination and biocover. Manually, six RoxAnn zones were identified; for the FCA, only three classes are suggested. The latter classification based on `hard' boundaries would suffice for stakeholder issues, but the former classification based on `soft' boundaries is preferred to meet state-of-the-art scientific objectives.

  7. The use of artificial neural network (ANN) for modeling of COD removal from antibiotic aqueous solution by the Fenton process.

    PubMed

    Elmolla, Emad S; Chaudhuri, Malay; Eltoukhy, Mohamed Meselhy

    2010-07-15

    The study examined the implementation of artificial neural network (ANN) for the prediction and simulation of antibiotic degradation in aqueous solution by the Fenton process. A three-layer backpropagation neural network was optimized to predict and simulate the degradation of amoxicillin, ampicillin and cloxacillin in aqueous solution in terms of COD removal. The configuration of the backpropagation neural network giving the smallest mean square error (MSE) was three-layer ANN with tangent sigmoid transfer function (tansig) at hidden layer with 14 neurons, linear transfer function (purelin) at output layer and Levenberg-Marquardt backpropagation training algorithm (LMA). ANN predicted results are very close to the experimental results with correlation coefficient (R(2)) of 0.997 and MSE 0.000376. The sensitivity analysis showed that all studied variables (reaction time, H(2)O(2)/COD molar ratio, H(2)O(2)/Fe(2+) molar ratio, pH and antibiotics concentration) have strong effect on antibiotic degradation in terms of COD removal. In addition, H(2)O(2)/Fe(2+) molar ratio is the most influential parameter with relative importance of 25.8%. The results showed that neural network modeling could effectively predict and simulate the behavior of the Fenton process.

  8. Seafloor monitoring west of Helgoland (German Bight, North Sea) using the acoustic ground discrimination system RoxAnn

    NASA Astrophysics Data System (ADS)

    Hass, H. Christian; Mielck, Finn; Fiorentino, Dario; Papenmeier, Svenja; Holler, Peter; Bartholomä, Alexander

    2017-04-01

    Marine habitats of shelf seas are in constant dynamic change and therefore need regular assessment particularly in areas of special interest. In this study, the single-beam acoustic ground discrimination system RoxAnn served to assess seafloor hardness and roughness, and combine these parameters into one variable expressed as RGB (red green blue) color code followed by k-means fuzzy cluster analysis (FCA). The data were collected at a monitoring site west of the island of Helgoland (German Bight, SE North Sea) in the course of four surveys between September 2011 and November 2014. The study area has complex characteristics varying from outcropping bedrock to sandy and muddy sectors with mostly gradual transitions. RoxAnn data enabled to discriminate all seafloor types that were suggested by ground-truth information (seafloor samples, video). The area appears to be quite stable overall; sediment import (including fluid mud) was detected only from the NW. Although hard substrates (boulders, bedrock) are clearly identified, the signal can be modified by inclination and biocover. Manually, six RoxAnn zones were identified; for the FCA, only three classes are suggested. The latter classification based on `hard' boundaries would suffice for stakeholder issues, but the former classification based on `soft' boundaries is preferred to meet state-of-the-art scientific objectives.

  9. 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

  10. A new thermographic NDT for condition monitoring of electrical components using ANN with confidence level analysis.

    PubMed

    Huda, A S N; Taib, S; Ghazali, K H; Jadin, M S

    2014-05-01

    Infrared thermography technology is one of the most effective non-destructive testing techniques for predictive faults diagnosis of electrical components. Faults in electrical system show overheating of components which is a common indicator of poor connection, overloading, load imbalance or any defect. Thermographic inspection is employed for finding such heat related problems before eventual failure of the system. However, an automatic diagnostic system based on artificial neural network reduces operating time, human efforts and also increases the reliability of system. In the present study, statistical features and artificial neural network (ANN) with confidence level analysis are utilized for inspection of electrical components and their thermal conditions are classified into two classes namely normal and overheated. All the features extracted from images do not produce good performance. Features having low performance reduce the diagnostic performance. The study reveals the performance of each feature individually for selecting the suitable feature set. In order to find the individual feature performance, each feature of thermal image was used as input for neural network and the classification of condition types were used as output target. The multilayered perceptron network using Levenberg-Marquardt training algorithm was used as classifier. The performances were determined in terms of percentage of accuracy, specificity, sensitivity, false positive and false negative. After selecting the suitable features, the study introduces the intelligent diagnosis system using suitable features as inputs of neural network. Finally, confidence percentage and confidence level were used to find out the strength of the network outputs for condition monitoring. The experimental result shows that multilayered perceptron network produced 79.4% of testing accuracy with 43.60%, 12.60%, 21.40, 9.20% and 13.40% highest, high, moderate, low and lowest confidence level respectively.

  11. Thiamine Deficiency Complex Workshop final report: November 6-7, 2008, Ann Arbor, MI

    USGS Publications Warehouse

    Honeyfield, Dale C.; Tillitt, Donald E.; Riley, Stephen C.

    2008-01-01

    Fry mortality which was first observed in the late 1960s in Great Lakes salmonines and in Baltic Sea salmon in 1974 has now been linked to thiamine deficiency (historically referred to as Early Mortality Syndrome, or EMS and M74, respectively). Over the past 14 years significant strides have been made in our understanding of this perplexing problem. It is now known that thiamine deficiency causes embryonic mortality in these salmonids. Both overt mortality and secondary effects of thiamine deficiency are observed in juvenile and adult animals. Collectively the morbidity and mortality (fry and adult mortality, secondary metabolic and behavior affects in juveniles and adult fish) are referred to as Thiamine Deficiency Complex (TDC). A workshop was held in Ann Arbor, MI on 6-7 November 2008 that brought together 38 federal, state, provincial, tribal and university scientists to share information, present data and discuss the latest observations on thiamine status of aquatic animals with thiamine deficiency and the causative agent, thiaminase. Twenty presentations (13 oral and 7 posters) detailed current knowledge. In Lake Huron, low alewife Alosa pseudoharengus abundance has persisted and egg thiamine concentrations in salmonines continue to increase, along with evidence of natural reproduction in lake trout Salvelinus namaycush. Lake Michigan Chinook salmon Oncorhynchus tshawytscha appear to have a lower thiamine requirement than other salmonids in the lake. Lake Ontario American eel Anguilla rostrata foraging on alewife have approximately one third the muscle thiamine compared to eels not feeding on alewife, suggesting that eels may be suffering from thiamine deficiency. Secondary effects of low thiamine exist in Great Lakes salmonines and should not be ignored. Thiaminase activity in dreissenid mussels is extremely high but a connection to TDC has not been made. Thiaminase in net plankton was found more consistently in lakes Michigan and Ontario than other lakes

  12. 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

  13. 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)

  14. 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

  15. WE-A-201-00: Anne and Donald Herbert Distinguished Lectureship On Modern Statistical Modeling.

    PubMed

    Deasy, Joseph

    2016-06-01

    Commission and may be remembered for his critique of the National Academy of Sciences BEIR III report (stating that their methodology "imposes a Delphic quality to the .. risk estimates".) This led to his appointment as a member of the BEIR V committee. Don presented refresher courses at the AAPM, ASTRO and RSNA meetings and was active in the AAPM as a member or chair of several committees. He was the principal author of AAPM Report 43, which is essentially a critique of established clinical studies prior to 1992. He was co-editor of the Proceedings of many symposia on Time, Dose and Fractionation held in Madison, Wisconsin. He received the AAPM lifetime Achievement award in 2004. Don's second wife of 46 years, Ann, predeceased him and he is survived by daughters Hillary and Emily, son John and two grandsons. Don was a true gentleman with a unique and erudite writing style illuminated by pithy quotations. If he had a fault it was, perhaps, that he did not realize how much smarter he was than the rest of us. This presentation draws heavily on a biography and video interview in the History and Heritage section of the AAPM website. The quote is his own. Andrzej Niemierko: Statistical modeling plays an essential role in modern medicine for quantitative evaluation of the effect of treatment. This session will feature an overview of statistical modeling techniques used for analyzing the many types of research data and an exploration of recent advances in new statistical modeling methodologies.

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

    NASA Astrophysics Data System (ADS)

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

    2005-01-01

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

  17. 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.

  18. 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.

  19. 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

    2016-11-01

    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.

  20. 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

  1. 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.

  2. Quantitative and qualitative models for carcinogenicity prediction for non-congeneric chemicals using CP ANN method for regulatory uses.

    PubMed

    Fjodorova, Natalja; Vračko, Marjan; Tušar, Marjan; Jezierska, Aneta; Novič, Marjana; Kühne, Ralph; Schüürmann, Gerrit

    2010-08-01

    The new European chemicals regulation Registration, Evaluation, Authorization and Restriction of Chemicals entered into force in June 2007 and accelerated the development of quantitative structure-activity relationship (QSAR) models for a variety of endpoints, including carcinogenicity. Here, we would like to present quantitative (continuous) and qualitative (categorical) models for non-congeneric chemicals for prediction of carcinogenic potency. A dataset of 805 substances was obtained after a preliminary screening of findings of rodent carcinogenicity for 1,481 chemicals accessible via Distributed Structure-Searchable Toxicity (DSSTox) Public Database Network originated from the Lois Gold Carcinogenic Potency Database (CPDB). Twenty seven two-dimensional MDL descriptors were selected using Kohonen mapping and principal component analysis. The counter propagation artificial neural network (CP ANN) technique was applied. Quantitative models were developed exploring the relationship between the experimental and predicted carcinogenic potency expressed as a tumorgenic dose TD(50) for rats. The obtained models showed low prediction power with correlation coefficient less than 0.5 for the test set. In the next step, qualitative models were developed. We found that the qualitative models exhibit good accuracy for the training set (92%). The model demonstrated good predicted performance for the test set. It was obtained accuracy (68%), sensitivity (73%), and specificity (63%). We believe that CP ANN method is a good in silico approach for modeling and predicting rodent carcinogenicity for non-congeneric chemicals and may find application for other toxicological endpoints.

  3. 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.

  4. 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.

  5. 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

  6. 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

  7. 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.

  8. 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%.

  9. 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.

  10. [Sensitivity analysis of AnnAGNPS model's hydrology and water quality parameters based on the perturbation analysis method].

    PubMed

    Xi, Qing; Li, Zhao-Fu; Luo, Chuan

    2014-05-01

    Sensitivity analysis of hydrology and water quality parameters has a great significance for integrated model's construction and application. Based on AnnAGNPS model's mechanism, terrain, hydrology and meteorology, field management, soil and other four major categories of 31 parameters were selected for the sensitivity analysis in Zhongtian river watershed which is a typical small watershed of hilly region in the Taihu Lake, and then used the perturbation method to evaluate the sensitivity of the parameters to the model's simulation results. The results showed that: in the 11 terrain parameters, LS was sensitive to all the model results, RMN, RS and RVC were generally sensitive and less sensitive to the output of sediment but insensitive to the remaining results. For hydrometeorological parameters, CN was more sensitive to runoff and sediment and relatively sensitive for the rest results. In field management, fertilizer and vegetation parameters, CCC, CRM and RR were less sensitive to sediment and particulate pollutants, the six fertilizer parameters (FR, FD, FID, FOD, FIP, FOP) were particularly sensitive for nitrogen and phosphorus nutrients. For soil parameters, K is quite sensitive to all the results except the runoff, the four parameters of the soil's nitrogen and phosphorus ratio (SONR, SINR, SOPR, SIPR) were less sensitive to the corresponding results. The simulation and verification results of runoff in Zhongtian watershed show a good accuracy with the deviation less than 10% during 2005- 2010. Research results have a direct reference value on AnnAGNPS model's parameter selection and calibration adjustment. The runoff simulation results of the study area also proved that the sensitivity analysis was practicable to the parameter's adjustment and showed the adaptability to the hydrology simulation in the Taihu Lake basin's hilly region and provide reference for the model's promotion in China.

  11. 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

  12. 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.

  13. 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...

  14. The 1979-80 Evaluation of the Title VII Bilingual Program, Project Cumbre, at the Ann Street Bilingual School of Hartford, Connecticut.

    ERIC Educational Resources Information Center

    Roby, Wallace R.

    An evaluation report of second year accomplishments at the Ann Street Bilingual School is presented. Objectives are established for students, instructional personnel, and parents at the school, the testing programs, standards set, and results for each are explained. Kindergarten students were expected to meet established standards in Spanish and…

  15. Summary Findings from a Preliminary Study of Black Student Adjustment, Achievement and Aspirations at the University of Michigan (Ann Arbor), Winter, 1980. Pretest of a National Study.

    ERIC Educational Resources Information Center

    Allen, Walter R.

    Adjustments, achievements, and aspirations of black undergraduates attending the University of Michigan were studied with a focus on characteristics correlating highly with black student continuance and successful matriculation. Questionnaire responses from 229 black undergraduates at the Ann Arbor campus provided information on: family…

  16. 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

  17. 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

  18. Investigation of an HMM/ANN hybrid structure in pattern recognition application using cepstral analysis of dysarthric (distorted) speech signals.

    PubMed

    Polur, Prasad D; Miller, Gerald E

    2006-10-01

    Computer speech recognition of individuals with dysarthria, such as cerebral palsy patients requires a robust technique that can handle conditions of very high variability and limited training data. In this study, application of a 10 state ergodic hidden Markov model (HMM)/artificial neural network (ANN) hybrid structure for a dysarthric speech (isolated word) recognition system, intended to act as an assistive tool, was investigated. A small size vocabulary spoken by three cerebral palsy subjects was chosen. The effect of such a structure on the recognition rate of the system was investigated by comparing it with an ergodic hidden Markov model as a control tool. This was done in order to determine if this modified technique contributed to enhanced recognition of dysarthric speech. The speech was sampled at 11 kHz. Mel frequency cepstral coefficients were extracted from them using 15 ms frames and served as training input to the hybrid model setup. The subsequent results demonstrated that the hybrid model structure was quite robust in its ability to handle the large variability and non-conformity of dysarthric speech. The level of variability in input dysarthric speech patterns sometimes limits the reliability of the system. However, its application as a rehabilitation/control tool to assist dysarthric motor impaired individuals holds sufficient promise.

  19. Experimental and numerical study of nanofluid in heat exchanger fitted by modified twisted tape: exergy analysis and ANN prediction model

    NASA Astrophysics Data System (ADS)

    Maddah, Heydar; Ghasemi, Nahid; Keyvani, Bahram; Cheraghali, Ramin

    2016-09-01

    Present study provides an experimental investigation of the exergetic efficiency due to the flow and heat transfer of nanofluids in different geometries and flow regimes of the double pipe heat exchangers. The experiments with different Geometrical Progression Ratio (GPR) of twists as the new modified twisted tapes and different nanofluid concentration were performed under similar operation condition. Pitch length of the proposed twisted tapes and consequently the twist ratios changed along the twists with respect to the Geometrical Progression Ratio (GPR) whether reducer (RGPR < 1) or increaser (IGPR > 1). Regarding the experimental data, utilization of RGPR twists together with nanofluids tends to increase exergetic efficiency. Since the Prediction of exergetic efficiency from experimental process is complex and time consuming, artificial neural networks for identification of the relationship, which may exist between the thermal and flow parameters and exergetic efficiency, have been utilized. The network input consists of five parameters (Re,Pr ,φ, Tr, GPR) that crucially dominate the heat transfer process. The results proved that the introduced ANN model is reliable and capable in proposing a proper development plan for a heat exchanger and/or to determine the optimal plan of operation for heat transfer process.

  20. Biotreatment of zinc-containing wastewater in a sulfidogenic CSTR: Performance and artificial neural network (ANN) modelling studies.

    PubMed

    Sahinkaya, Erkan

    2009-05-15

    Sulfidogenic treatment of sulfate (2-10g/L) and zinc (65-677mg/L) containing simulated wastewater was studied in a mesophilic (35 degrees C) CSTR. Ethanol was supplemented (COD/sulfate=0.67) as carbon and energy source for sulfate-reducing bacteria (SRB). The robustness of the system was studied by increasing Zn, COD and sulfate loadings. Sulfate removal efficiency, which was 70% at 2g/L feed sulfate concentration, steadily decreased with increasing feed sulfate concentration and reached 40% at 10g/L. Over 99% Zn removal was attained due to the formation of zinc-sulfide precipitate. COD removal efficiency at 2g/L feed sulfate concentration was over 94%, whereas, it steadily decreased due to the accumulation of acetate at higher loadings. Alkalinity produced from acetate oxidation increased wastewater pH remarkably when feed sulfate concentration was 5g/L or lower. Electron flow from carbon oxidation to sulfate reduction averaged 83+/-13%. The rest of the electrons were most likely coupled with fermentative reactions as the amount of methane production was insignificant. The developed ANN model was very successful as an excellent to reasonable match was obtained between the measured and the predicted concentrations of sulfate (R=0.998), COD (R=0.993), acetate (R=0.976) and zinc (R=0.827) in the CSTR effluent.

  1. Maps and seismic profiles showing geology of the inner continental shelf, Cape Ann, Massachusetts to New Hampshire

    USGS Publications Warehouse

    Oldale, R.N.; Wommack, L.E.

    1987-01-01

    Early studies in the western Gulf of Maine have outlined the general geology and geologic history of the region. Seismic-reflection data have defined the major stratigraphic units and unconformities (Oldale and Uchupi, 1970; Ballard and Uchupi, 1972; Oldale and others, 1973). Two long cores provided information on the glacial and postglacial sediments in the deep offshore basins (Tucholke and Hollister, 1973). Generalized bottom-sediment type and distribution were determined by Schlee and others (1973) and by Folger and others (1975). Investigations on land, which have provided information on the late Quaternary history of the offshore area, include descriptions of ice retreat and marine submergence (Bloom, 1963; Smith, 1982; Stone and Peper, 1982; Thompson, 1982). Radiocarbon dates from coastal marsh peats have established the middle to late Holocene sea-level-rise history (McIntire and Morgan, 1964; Keene, 1971). Submarine moraincs that recently were recognized off Cape Ann provide additional information on the nature and chronology of ice retreat (Oldale, 1985a). A submerged delta of the Merrimack River and a submerged barrier spit have been used to establish an early IIolocene lowstand of 588 level of about 50 meters (m) below present sea level (Oldale and others, 1983; Oldale, 1985b).

  2. 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.

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

    PubMed

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

    2016-01-01

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

  4. 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.

  5. Estimation of daily global solar radiation using wavelet regression, ANN, GEP and empirical models: A comparative study of selected temperature-based approaches

    NASA Astrophysics Data System (ADS)

    Sharifi, Sayed Saber; Rezaverdinejad, Vahid; Nourani, Vahid

    2016-11-01

    Although the sunshine-based models generally have a better performance than temperature-based models for estimating solar radiation, the limited availability of sunshine duration records makes the development of temperature-based methods inevitable. This paper presents a comparative study between Artificial Neural Networks (ANNs), Gene Expression Programming (GEP), Wavelet Regression (WR) and 5 selected temperature-based empirical models for estimating the daily global solar radiation. A new combination of inputs including four readily accessible parameters have been employed: daily mean clearness index (KT), temperature range (ΔT), theoretical sunshine duration (N) and extraterrestrial radiation (Ra). Ten statistical indicators in a form of GPI (Global Performance Indicator) is used to ascertain the suitability of the models. The performance of selected models across the range of solar radiation values, was depicted by the quantile-quantile (Q-Q) plots. Comparing these plots makes it evident that ANNs can cover a broader range of solar radiation values. The results shown indicate that the performance of ANN model was clearly superior to the other models. The findings also demonstrated that WR model performed well and presented high accuracy in estimations of daily global solar radiation.

  6. A comparison of two adaptive multivariate analysis methods (PLSR and ANN) for winter wheat yield forecasting using Landsat-8 OLI images

    NASA Astrophysics Data System (ADS)

    Chen, Pengfei; Jing, Qi

    2017-02-01

    An assumption that the non-linear method is more reasonable than the linear method when canopy reflectance is used to establish the yield prediction model was proposed and tested in this study. For this purpose, partial least squares regression (PLSR) and artificial neural networks (ANN), represented linear and non-linear analysis method, were applied and compared for wheat yield prediction. Multi-period Landsat-8 OLI images were collected at two different wheat growth stages, and a field campaign was conducted to obtain grain yields at selected sampling sites in 2014. The field data were divided into a calibration database and a testing database. Using calibration data, a cross-validation concept was introduced for the PLSR and ANN model construction to prevent over-fitting. All models were tested using the test data. The ANN yield-prediction model produced R2, RMSE and RMSE% values of 0.61, 979 kg ha-1, and 10.38%, respectively, in the testing phase, performing better than the PLSR yield-prediction model, which produced R2, RMSE, and RMSE% values of 0.39, 1211 kg ha-1, and 12.84%, respectively. Non-linear method was suggested as a better method for yield prediction.

  7. [Evaluation of AnnAGNPS model for simulation water and sediment yield in the Lianshui River watershed].

    PubMed

    Li, Shuo; Liu, Lei

    2010-01-01

    Soil erosion has caused a series of environmental and ecological issues, such as land resource degradation and water pollution. It is an effective approach for quantitative evaluation and control of soil erosion by using processes based mathematic models. In this study, the Cell discretization units was extracted and a large number of basic geographical data including Digital Elevation Model (DEM), land use, soil as well as crop management practices, were collected and parameterized. The distributed computer modeling for water yield, sediment yield for the years 1991 to 2005 were carried out in the study area of Lianshui Basin, Xingguo County, Jiangxi province by using the basin scale AnnAGNPS model developed by USDA. The average simulation error and deterministic coefficient (R2) were 11.8% and 0.94 for annual surface flow and 19.71% and 0.77 for annual sediment yield,respectively. The simulation result indicates that the model has an acceptable performance in prediction of surface flow and sediment loading in Lianshui basin. However, the predicted subsurface flow is much less than observed value, and the reason and the applicability for subsurface flow module in Lianshui basin will be further checked up in the future study. The spatial distribution of the sediment yield in the study area was analyzed using the simulation results. The average soil erosion amount is 1150.29 t x (km2 x a)(-1), which imply that Lianshui basin belongs to slight erosion. The areas nearby residential area and along the roads were the main sources of soil erosion and the soil loss is closely related to human activities.

  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. [Nonpoint source pollution model, AnnAGNPS, assessment for a mixed forested watershed in Three Gorges Reservoir area].

    PubMed

    Huang, Zhi-lin; Tian, Yao-wu; Xiao, Wen-fa; Zeng, Li-xiong; Ma, De-ju

    2009-10-15

    Watershed models provide a cost-effective and efficient means of estimating the pollutant loadings entering surface waters, especially when combined with traditional water quality sampling and analyses. But there have often been questions about the accuracy or certainty of models and their predictions. The main goal of this study was to evaluate the performance of AnnAGNPS (Annualized AGricultural NonPoint Source)Pollution Model, in simulating runoff, sediment loading and nutrient loadings under Three Gorges Reservoir area. Most of model input parameters were sourced from Zigui Forest Ecology Station in Three Gorges Reservoir area, State Forestry Administration. Data year 2003 was used for calibration while data year 2004 was used for validation of the model. The whole evaluation consisted of determining the coefficient of determination (R2), Nash-Sutcliffe coefficient of efficiency (E), and the percentage volume error (VE). Results showed that the model predicted the daily runoff volume within the range of acceptable accuracy. The runoff on a daily basis was underpredicted by 5.0% with R2 of 0.93 (p < 0.05) during calibration and underpredicted by 6.7% with R2 of 0.90 (p < 0.05) during validation. But sediment loading was able to produce a moderate result. The model underpredicted the event-based sediment loading by 15.1% with R2 of 0.63 (p < 0.05) during calibration and 26.7% with R2 of 0.59 (p < 0.05) during validation. For the events of small magnitude, the model generally overpredicted sediment loading, while the opposite was true for larger events. Nitrogen loading prediction was slightly better with R2 = 0.68 (p < 0.05), and phosphorus loading performance was slightly poor with R2 = 0.65 (p < 0.05). In general, the model performs well in simulating runoff compare to sediment loading and nutrient loadings, and as a watershed management tools it can be used for Three Gorges Reservoir area conditions that with mixed types of land uses and steep slopes.

  10. 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

  11. Le groupe de recherches transfusionnelles d’Afrique francophone: bilan des cinq premières années

    PubMed Central

    Tagny, Claude Tayou; Murphy, Edward L.; Lefrère, Jean-Jacques

    2016-01-01

    Les travaux de recherches sur la sécurité transfusionnelle en Afrique sub-saharienne sont peu nombreux, souvent limités à des initiatives locales avec des conclusions difficilement représentatives de cette région. Le Groupe de recherches transfusionnelles en Afrique sub-saharienne francophone a été créé en mai 2007 avec pour objectif de développer des stratégies globales d’amélioration de la sécurité transfusionnelle mais adaptables à la situation de chaque pays. Les activités du Groupe à ce jour ont porté essentiellement sur l’obtention de données épidémiologiques et de laboratoire sur la transfusion sanguine et à proposer des stratégies de sécurité transfusionnelle dans le domaine des infections transmissibles par la transfusion. Pour mener à bien ces activités de recherche, le Groupe travaille en étroite collaboration avec les Centres nationaux de transfusion sanguine (CNTS), les Centres régionaux de transfusion sanguine (CRTS), les banques de sang hospitalières (BSH) et les postes de collecte de sang. Pour les 5 premières années, quatre priorités de recherche ont été identifiées: (i) des études descriptives sur les caractéristiques des donneurs de sang et des centres de transfusion; (ii) une estimation du risque résiduel post-transfusionnel des principales infections virales transmissibles par la transfusion; (iii) une analyse des stratégies de sélection médicale des donneurs de sang; et (iv) une description des stratégies de dépistage des ITT et une description du système d’assurance qualité externe existant. Durant cette période, sept projets ont été mis en œuvre au niveau national et publiés et cinq études multicentriques ont été réalisées et publiées. La présente étude rapporte les principales observations et recommandations de ces études. PMID:24360798

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

    PubMed

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

    2017-01-01

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

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

    PubMed Central

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

    2017-01-01

    Artificial neural networks (ANNs) have been employed to solve a broad variety of tasks. The selection of an ANN model with appropriate weights is important in achieving accurate results. This paper presents an optimization strategy for ANN model selection based on the cuckoo search (CS) algorithm, which is rooted in the obligate brood parasitic actions of some cuckoo species. In order to enhance the convergence ability of basic CS, some modifications are proposed. The fraction Pa of the n nests replaced by new nests is a fixed parameter in basic CS. As the selection of Pa is a challenging issue and has a direct effect on exploration and therefore on convergence ability, in this work the Pa is set to a maximum value at initialization to achieve more exploration in early iterations and it is decreased during the search to achieve more exploitation in later iterations until it reaches the minimum value in the final iteration. In addition, a novel master-leader-slave multi-population strategy is used where the slaves employ the best fitness function among all slaves, which is selected by the leader under a certain condition. This fitness function is used for subsequent Lévy flights. In each iteration a copy of the best solution of each slave is migrated to the master and then the best solution is found by the master. The method is tested on benchmark classification and time series prediction problems and the statistical analysis proves the ability of the method. This method is also applied to a real-world water quality prediction problem with promising results. PMID:28125609

  14. Development of CAD based on ANN analysis of power spectra for pneumoconiosis in chest radiographs: effect of three new enhancement methods.

    PubMed

    Okumura, Eiichiro; Kawashita, Ikuo; Ishida, Takayuki

    2014-07-01

    We have been developing a computer-aided detection (CAD) scheme for pneumoconiosis based on a rule-based plus artificial neural network (ANN) analysis of power spectra. In this study, we have developed three enhancement methods for the abnormal patterns to reduce false-positive and false-negative values. The image database consisted of 2 normal and 15 abnormal chest radiographs. The International Labour Organization standard chest radiographs with pneumoconiosis were categorized as subcategory, size, and shape of pneumoconiosis. Regions of interest (ROIs) with a matrix size of 32 × 32 were selected from normal and abnormal lungs. Three new enhanced methods were obtained by window function, top-hat transformation, and gray-level co-occurrence matrix analysis. We calculated the power spectrum (PS) of all ROIs by Fourier transform. For the classification between normal and abnormal ROIs, we applied a combined analysis using the ruled-based plus the ANN method. To evaluate the overall performance of this CAD scheme, we employed ROC analysis for distinguishing between normal and abnormal ROIs. On the chest radiographs of the highest categories (severe pneumoconiosis) and the lowest categories (early pneumoconiosis), this CAD scheme achieved area under the curve (AUC) values of 0.93 ± 0.02 and 0.72 ± 0.03. The combined rule-based plus ANN method with the three new enhanced methods obtained the highest classification performance for distinguishing between abnormal and normal ROIs. Our CAD system based on the three new enhanced methods would be useful in assisting radiologists in the classification of pneumoconiosis.

  15. Constitutive Equations and ANN Approach to Predict the Flow Stress of Ti-6Al-4V Alloy Based on ABI Tests

    NASA Astrophysics Data System (ADS)

    Wang, Fuzeng; Zhao, Jun; Zhu, Ningbo

    2016-11-01

    The flow behavior of Ti-6Al-4V alloy was studied by automated ball indentation (ABI) tests in a wide range of temperatures (293, 493, 693, and 873 K) and strain rates (10-6, 10-5, and 10-4 s-1). Based on the experimental true stress-plastic strain data derived from the ABI tests, the Johnson-Cook (JC), Khan-Huang-Liang (KHL) and modified Zerilli-Armstrong (ZA) constitutive models, as well as artificial neural network (ANN) methods, were employed to predict the flow behavior of Ti-6Al-4V. A comparative study was made on the reliability of the four models, and their predictability was evaluated in terms of correlation coefficient ( R) and mean absolute percentage error. It is found that the flow stresses of Ti-6Al-4V alloy are more sensitive to temperature than strain rate under current experimental conditions. The predicted flow stresses obtained from JC model and KHL model show much better agreement with the experimental results than modified ZA model. Moreover, the ANN model is much more efficient and shows a higher accuracy in predicting the flow behavior of Ti-6Al-4V alloy than the constitutive equations.

  16. Modeling multiple land use changes using ANN, CART and MARS: Comparing tradeoffs in goodness of fit and explanatory power of data mining tools

    NASA Astrophysics Data System (ADS)

    Tayyebi, Amin; Pijanowski, Bryan C.

    2014-05-01

    Over half of the earth's terrestrial surface has been modified by humans. This modification is called land use change and its pattern is known to occur in a non-linear way. The land use change modeling community can advance its models using data mining tools. Here, we present three data mining land use change models, one based on Artificial Neural Network (ANN), another on Classification And Regression Trees (CART) and another Multivariate Adaptive Regression Splines (MARS). We reconfigured the three data mining models to concurrently simulate multiple land use classes (e.g. agriculture, forest and urban) in South-Eastern Wisconsin (SEWI), USA (time interval 1990-2000) and in Muskegon River Watershed (MRW), Michigan, USA (time interval 1978-1998). We compared the results of the three data mining tools using relative operating characteristic (ROC) and percent correct match (PCM). We found that ANN provided the best accuracy in both areas for three land use classes (e.g. urban, agriculture and forest). In addition, in both regions, CART and MARS both showed that forest gain occurred in areas close to current forests, agriculture patches and away from roads. Urban increased in areas of high urban density, close to roads and in areas with few forests and wetlands. We also found that agriculture gain is more likely for the areas closer to the agriculture and forest patches. Elevation strongly influenced urbanization and forest gain in MRW while it has no effect in SEWI.

  17. 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.

  18. Type-IV pili spectroscopic markers: applications in the quantification of piliation levels in Moraxella bovis cells by a FT-IR ANN-based model.

    PubMed

    Bosch, Alejandra; Prieto, Claudia; Serra, Diego Omar; Martina, Pablo; Stämmbler, Maren; Naumann, Dieter; Schmitt, Jürgen; Yantorno, Osvaldo

    2010-08-01

    Type-IV pili are cell surface organelles found in a wide variety of Gram-negative bacteria. They have traditionally been detected by electron microscopy and ELISA techniques. However, these methodologies are not appropriate for the rapid discrimination and quantification of piliated and nonpiliated cells in industrial or field conditions. Here, the analysis of FT-IR spectra of piliated, nonpiliated and sheared Moraxella bovis cells, together with purified pili suspensions spectra, allowed the identification of 3 IR regions associated to spectroscopic markers of Type-IV pili: 1750-1600, 1450-1350 and 1280-950 cm(-1). Such IR-specific markers were found for piliated cells grown in different culture systems (liquid or solid media), independently of the strain or pili serotype. They were also sensitive to pili expression levels. Therefore, on the bases of these specific spectral features, an FT-IR ANN-based model was developed to classify piliation levels in 5 distinct groups. An overall classification rate of almost 90% demonstrates the strong potential of the ANN system developed to monitor M. bovis cultures in vaccine production.

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

    PubMed

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

    2015-09-02

    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.

  20. 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

  1. 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

  2. Contribution des réseaux de neurones artificiels (RNA) à la caractérisation des pollutions de sol. Exemples des pollutions en hydrocarbures aromatiques polycycliques (HAP)Artificial Neural Networks (ANNs) characterisation of soil pollution: the Polycyclic Aromatic Hydrocarbons (PAHs) case study

    NASA Astrophysics Data System (ADS)

    Dan, Adrian; Oosterbaan, Jasha; Jamet, Philippe

    2002-10-01

    We develop the ANNs (Artificial Neural Networks) method to explore contaminant concentration profiles observed in soils of polluted sites. ANNs are particularly efficient in simultaneous analysis of numerous parameters and in identification of complex relations involving field data. Applying the ANN models on a PAH (Polycyclic Aromatic Hydrocarbon) database, we extracted the most characteristic components of known contaminations and applied it to identify the source type of similar polluted sites. The performed tests prove the generalisation capability of the selected ANN model. To cite this article: A. Dan et al., C. R. Geoscience 334 (2002) 957-965.

  3. ANFIS, SVM and ANN soft-computing techniques to estimate daily global solar radiation in a warm sub-humid environment

    NASA Astrophysics Data System (ADS)

    Quej, Victor H.; Almorox, Javier; Arnaldo, Javier A.; Saito, Laurel

    2017-03-01

    Daily solar radiation is an important variable in many models. In this paper, the accuracy and performance of three soft computing techniques (i.e., adaptive neuro-fuzzy inference system (ANFIS), artificial neural network (ANN) and support vector machine (SVM) were assessed for predicting daily horizontal global solar radiation from measured meteorological variables in the Yucatán Peninsula, México. Model performance was assessed with statistical indicators such as root mean squared error (RMSE), mean absolute error (MAE) and coefficient of determination (R2). The performance assessment indicates that the SVM technique with requirements of daily maximum and minimum air temperature, extraterrestrial solar radiation and rainfall has better performance than the other techniques and may be a promising alternative to the usual approaches for predicting solar radiation.

  4. The National Association of Social Workers Code of Ethics and Cultural Competence: What Does Anne Fadiman's The Spirit Catches You and You Fall Down Teach Us Today?

    PubMed

    Hebenstreit, Haylee

    2017-03-04

    This article discusses limitations in the National Association of Social Workers (NASW) Code of Ethics conceptualization of "cultural competence." It uses the case example presented in Anne Fadiman's classic (2012) work, The Spirit Catches You and You Fall Down: A Hmong Child, Her American Doctors, and the Collision of Two Cultures, to explore the conventional markers of cultural competence, as taught in contemporary graduate-level social work education curricula, and their implications for socially just practice. Furthermore, it proposes that an expanded commitment to antiracist practice is necessary to deliver care and craft policies that, in the spirit of the NASW Code of Ethics, truly respect the "dignity and worth" of the individual.

  5. Analysis of Multiple Impacts of Global Change on Water Utilization Using ANN Model - A case study in North-West China

    NASA Astrophysics Data System (ADS)

    Ma, L.; Xuan, Y.; Su, X.; Solomatine, D. P.; Kang, S.

    2010-05-01

    Availability of water resources is one of the most fundamental factors that affect socio-economic development as well as environment. This is especially true in arid areas of China where this effect has always been highlighted by composition of vegetation and limited biosphere cycle. On the other hand, uncontrolled water utilization often causes desertification and disappearance of oases. Many oases in arid areas nowadays face threats from both changing climate and impacts from human activities such as the increase in stressful water demand. A sound adaptation strategy towards global change necessitates a better understanding of changes due to these two sources of impacts. In this study, a typical inland river basin, Shiyang river basin, located in the arid Northwest of China, is studied aiming to reveal the key driving factor (using factor analysis) that threats the local oasis ecology in view of water utilization change under climate, the land use change and human activity impact during the last 50 years and in the coming decades. Various climate change scenarios as well as socio-economic scenarios (including policy orientated) are combined and analyzed. An ANN model is developed to reveal the complicated relationship between regional water utilization and multiple driving factors, i.e. climatic variables, land use and vegetation, socio-economic development etc. The model also makes use of remote sensing data to take into account the land use change coincident with local socio-economic development. In the meantime, risk due to uncertainty in climate model downscaling is also analyzed and incorporated in order to make the analysis more robust. The study shows that the ANN model is able to quantify the contribution of these driving factors to the regional water utilization, which is of great utility in support of making effective adaptive measures for water-scarce area in view of global changes.

  6. Artificial neural network (ANN) method for modeling of sunset yellow dye adsorption using zinc oxide nanorods loaded on activated carbon: Kinetic and isotherm study

    NASA Astrophysics Data System (ADS)

    Maghsoudi, M.; Ghaedi, M.; Zinali, A.; Ghaedi, A. M.; Habibi, M. H.

    2015-01-01

    In this research, ZnO nanoparticle loaded on activated carbon (ZnO-NPs-AC) was synthesized simply by a low cost and nontoxic procedure. The characterization and identification have been completed by different techniques such as SEM and XRD analysis. A three layer artificial neural network (ANN) model is applicable for accurate prediction of dye removal percentage from aqueous solution by ZnO-NRs-AC following conduction of 270 experimental data. The network was trained using the obtained experimental data at optimum pH with different ZnO-NRs-AC amount (0.005-0.015 g) and 5-40 mg/L of sunset yellow dye over contact time of 0.5-30 min. The ANN model was applied for prediction of the removal percentage of present systems with Levenberg-Marquardt algorithm (LMA), a linear transfer function (purelin) at output layer and a tangent sigmoid transfer function (tansig) in the hidden layer with 6 neurons. The minimum mean squared error (MSE) of 0.0008 and coefficient of determination (R2) of 0.998 were found for prediction and modeling of SY removal. The influence of parameters including adsorbent amount, initial dye concentration, pH and contact time on sunset yellow (SY) removal percentage were investigated and optimal experimental conditions were ascertained. Optimal conditions were set as follows: pH, 2.0; 10 min contact time; an adsorbent dose of 0.015 g. Equilibrium data fitted truly with the Langmuir model with maximum adsorption capacity of 142.85 mg/g for 0.005 g adsorbent. The adsorption of sunset yellow followed the pseudo-second-order rate equation.

  7. Artificial neural network (ANN) method for modeling of sunset yellow dye adsorption using zinc oxide nanorods loaded on activated carbon: Kinetic and isotherm study.

    PubMed

    Maghsoudi, M; Ghaedi, M; Zinali, A; Ghaedi, A M; Habibi, M H

    2015-01-05

    In this research, ZnO nanoparticle loaded on activated carbon (ZnO-NPs-AC) was synthesized simply by a low cost and nontoxic procedure. The characterization and identification have been completed by different techniques such as SEM and XRD analysis. A three layer artificial neural network (ANN) model is applicable for accurate prediction of dye removal percentage from aqueous solution by ZnO-NRs-AC following conduction of 270 experimental data. The network was trained using the obtained experimental data at optimum pH with different ZnO-NRs-AC amount (0.005-0.015 g) and 5-40 mg/L of sunset yellow dye over contact time of 0.5-30 min. The ANN model was applied for prediction of the removal percentage of present systems with Levenberg-Marquardt algorithm (LMA), a linear transfer function (purelin) at output layer and a tangent sigmoid transfer function (tansig) in the hidden layer with 6 neurons. The minimum mean squared error (MSE) of 0.0008 and coefficient of determination (R(2)) of 0.998 were found for prediction and modeling of SY removal. The influence of parameters including adsorbent amount, initial dye concentration, pH and contact time on sunset yellow (SY) removal percentage were investigated and optimal experimental conditions were ascertained. Optimal conditions were set as follows: pH, 2.0; 10 min contact time; an adsorbent dose of 0.015 g. Equilibrium data fitted truly with the Langmuir model with maximum adsorption capacity of 142.85 mg/g for 0.005 g adsorbent. The adsorption of sunset yellow followed the pseudo-second-order rate equation.

  8. 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

  9. 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

  10. 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

  11. 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.

  12. 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.

  13. 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

    2015-01-01

    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.

  14. 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.

  15. Spectral feature extraction of EEG signals and pattern recognition during mental tasks of 2-D cursor movements for BCI using SVM and ANN.

    PubMed

    Bascil, M Serdar; Tesneli, Ahmet Y; Temurtas, Feyzullah

    2016-09-01

    Brain computer interface (BCI) is a new communication way between man and machine. It identifies mental task patterns stored in electroencephalogram (EEG). So, it extracts brain electrical activities recorded by EEG and transforms them machine control commands. The main goal of BCI is to make available assistive environmental devices for paralyzed people such as computers and makes their life easier. This study deals with feature extraction and mental task pattern recognition on 2-D cursor control from EEG as offline analysis approach. The hemispherical power density changes are computed and compared on alpha-beta frequency bands with only mental imagination of cursor movements. First of all, power spectral density (PSD) features of EEG signals are extracted and high dimensional data reduced by principle component analysis (PCA) and independent component analysis (ICA) which are statistical algorithms. In the last stage, all features are classified with two types of support vector machine (SVM) which are linear and least squares (LS-SVM) and three different artificial neural network (ANN) structures which are learning vector quantization (LVQ), multilayer neural network (MLNN) and probabilistic neural network (PNN) and mental task patterns are successfully identified via k-fold cross validation technique.

  16. 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.

  17. Investigation of the panel painting of St Anne with the Virgin Mary and the Child Jesus using analytical and imaging methods.

    PubMed

    Sefců, R; Chlumská, S; Třeštíková, A; Trojek, T; Dragounová, L

    2014-10-08

    This paper presents an investigation of a panel painting depicting St Anne with the Virgin Mary and the Child Jesus that dates back to the beginning of the 16th century. This work is attributed to the Master of the Litoměřice Altarpiece, who was the most important painter in the time period of the Jagiellonian dynasty in Bohemia (the historical name of a part of the Czech Republic). At present, the painting is deposited in the collections of the National Gallery in Prague. The aims of this study were to carry out a systematic collection of sufficient data to make correct interpretations of the materials that were used, to compare the results with the technique of the Master of the Litoměřice Altarpiece, and in this way to prove his authorship. In the analyses of the material compositions, emphasis was placed on non-destructive and non-invasive methods, e.g. X-ray fluorescence microanalysis, which was performed using a device with lateral resolution of 20μm. Further applied methods were X-ray radiography, Infrared Reflectography, photographic documentation in visible and ultraviolet light, Scanning Electron Microscopy-Energy Dispersive Spectroscopy, Infrared microspectroscopy with Fourier transformation, and microscopic analysis.

  18. Erratum to “Axial and transverse acoustic radiation forces on a fluid sphere placed arbitrarily in Bessel beam standing wave tweezers” [Ann. Phys. 342 (3) (2014) 158-170

    NASA Astrophysics Data System (ADS)

    Mitri, F. G.

    2014-09-01

    A typographical error is corrected in three equations in the article [Ann. Phys. 342 (3) (2014) 158-170, http://dx.doi.org/10.1016/j.aop.2013.12.009]. They are Eqs. (12)-(14), where the factor (1+Sp,q) should have been printed as (1+sp(ka)). The numerical computations and plots used the correct factor (1+sp(ka)) in the related equations.

  19. 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.

  20. 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.

  1. 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

  2. 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

    Hernández Suárez, Marcos; Astray Dopazo, Gonzalo; Larios López, Dina; Espinosa, Francisco

    2015-01-01

    There are a large number of tomato cultivars with a wide range of morphological, chemical, nutritional and sensorial characteristics. Many factors are known to affect the nutrient content of tomato cultivars. A complete understanding of the effect of these factors would require an exhaustive experimental design, multidisciplinary scientific approach and a suitable statistical method. Some multivariate analytical techniques such as Principal Component Analysis (PCA) or Factor Analysis (FA) have been widely applied in order to search for patterns in the behaviour and reduce the dimensionality of a data set by a new set of uncorrelated latent variables. However, in some cases it is not useful to replace the original variables with these latent variables. In this study, Automatic Interaction Detection (AID) algorithm and Artificial Neural Network (ANN) models were applied as alternative to the PCA, AF and other multivariate analytical techniques in order to identify the relevant phytochemical constituents for characterization and authentication of tomatoes. To prove the feasibility of AID algorithm and ANN models to achieve the purpose of this study, both methods were applied on a data set with twenty five chemical parameters analysed on 167 tomato samples from Tenerife (Spain). Each tomato sample was defined by three factors: cultivar, agricultural practice and harvest date. General Linear Model linked to AID (GLM-AID) tree-structured was organized into 3 levels according to the number of factors. p-Coumaric acid was the compound the allowed to distinguish the tomato samples according to the day of harvest. More than one chemical parameter was necessary to distinguish among different agricultural practices and among the tomato cultivars. Several ANN models, with 25 and 10 input variables, for the prediction of cultivar, agricultural practice and harvest date, were developed. Finally, the models with 10 input variables were chosen with fit's goodness between 44 and 100

  3. 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.

  4. 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.

  5. 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.

  6. [The training of public school cafeteria staff: an analysis of the instructional material developed by Instituto de Nutrição Annes Dias - Rio de Janeiro (1956-1994)].

    PubMed

    Costa, Ester de Queirós; Lima, Eronides da Silva; Ribeiro, Vitória Maria Brant

    2002-01-01

    The present study aims at analyzing educational approaches in the training of public school cafeteria staff members from 1956 to 1994 through the study 17 instructions brochures developed by Instituto de Nutrição Annes Dias in the municipality of Rio de Janeiro. The analysis of the documents has considered two periods: the first one, from 1956 to 1971, is characterized by the foundation of the institute and its first training activities; the second period goes from 1972 to 1994, which is characterized by the consolidation of the institute's organizational structure and the presence of educational concepts in its training activities. Training focused on technical aspects and recurrently alluded to hygiene and organization. Discussions on the training of school cafeteria staff members should define what kind of workers is expected before defining what skills and abilities they are expected to develop.

  7. [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.

  8. 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.

  9. Ireland's hidden diaspora - the 'abortion trail'and the making of a london-irish underground,1980-2000 Ann Rossiter Ireland's hidden diaspora - the 'abortion trail'and the making of a london-irish underground,1980-2000 Iasc (email: arossit@yahoo.com ) 237 £8+p&p 9780956178503 0956178502 [Formula: see text].

    PubMed

    2009-12-09

    This is a passionate book about patients, politics and women supporting women. It does not make for light reading. Every year more than 5,000 women cross the Irish Sea to have an abortion in a British clinic. The emigrant journey is deeply embedded in Irish consciousness, but, as Ann Rossiter points out, the abortion-seeker rarely features in migration lore.

  10. 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

  11. Application of artificial neural network (ANN) and partial least-squares regression (PLSR) to predict the changes of anthocyanins, ascorbic acid, Total phenols, flavonoids, and antioxidant activity during storage of red bayberry juice based on fractal analysis and red, green, and blue (RGB) intensity values.

    PubMed

    Zheng, Hong; Jiang, Lingling; Lou, Heqiang; Hu, Ya; Kong, Xuecheng; Lu, Hongfei

    2011-01-26

    Artificial neural network (ANN) and partial least-squares regression (PLSR) models were developed to predict the changes of anthocyanin (AC), ascorbic acid (AA), total phenols (TP), total flavonoid (TF), and DPPH radical scavenging activity (SA) in bayberry juice during storage based on fractal analysis (FA) and red, green, and blue (RGB) intensity values. The results show the root mean squared error (RMSE) of ANN-FA decreased 2.44 and 12.45% for AC (RMSE = 18.673 mg/100 mL, R(2) = 0.939) and AA (RMSE = 8.694 mg/100 mL, R(2) = 0.935) compared with PLSR-RGB, respectively. In addition, PLSR-FA (RMSE = 5.966%, R(2) = 0.958) showed a 12.01% decrease in the RMSE compared with PLSR-RGB for predicting SA. For the prediction of TP and TF, however, both models showed poor performances based on FA and RGB. Therefore, ANN and PLSR combined with FA may be a potential method for quality evaluation of bayberry juice during processing, storage, and distribution, but the selection of the most adequate model is of great importance to predict different nutritional components.

  12. 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…

  13. ANN-Models for Jaw-Research

    DTIC Science & Technology

    2007-11-02

    Recently [5], the Peck-Langenbach-Hannam ( PLH ) dynamic model has been developed at U.B.C for the human jaw. It is based on published musculoskele- tal...of Abstract UU Number of Pages 4 Table 1: 3 sets from a 59–set of steady–state measurements of T(m;i) from the PLH simulator. m Set i=1 Set i=2 Set...Training sets can be obtained from the PLH model. The training sets will have special interest be- cause we want the network to generalize by predicting near

  14. 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…

  15. 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:

  16. 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

  17. 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.

  18. The Indecisive Feminist: Study of Anne Sexton's Revisionist Fairy Tales

    ERIC Educational Resources Information Center

    Mohammed, Nadia Fayidh

    2015-01-01

    Fairy tales to female writers are major resource for their abundant writings, but for the feminist poets since 1960s, they become essential subject matter to often deal with in their literary production. With the motivation to address the conventional tradition of patriarchal society, and re-address the stereotype females inhabiting these tales,…

  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. Jessica Ann Ellis Gold Star Fathers Act of 2010

    THOMAS, 111th Congress

    Sen. Wyden, Ron [D-OR

    2010-07-26

    12/17/2010 By Senator Lieberman from Committee on Homeland Security and Governmental Affairs filed written report. Report No. 111-374. (All Actions) Tracker: This bill has the status Passed SenateHere are the steps for Status of Legislation:

  1. 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.

  2. Archaeological Data Recovery at the Mary Ann Cole Site

    DTIC Science & Technology

    1981-06-01

    within the Paleolithic Stage of eastern Europe and Asia. Many of the fluted points reported in the midwestern United States have been made from Wyandotte...and the leading exponent of the French approach to the Paleolithic technology of Europe. Also, his American equivalant, Donald Crabtree of Idaho

  3. JoAnn - Working Together to Help Her See.

    ERIC Educational Resources Information Center

    Gottlieb, Daniel; Shorkey, Carolyn A.

    Presented is the case history and interdisciplinary approach used with a partially sighted 8-year-old girl including vision training, large print instruction, and regular class placement. The viewpoints of the optometrist, the child's parents, the educational consultant, the principal, the regular classroom teacher, and a resource room teacher are…

  4. 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…

  5. 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.

  6. 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.

  7. 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…

  8. 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

    ... the final CCP for Patuxent RR in accordance with National Environmental Policy Act ] (NEPA) (42 U.S.C... System Administration Act of 1966 (16 U.S.C. 668dd-668ee) (Refuge Administration Act), as amended by the.... There are also several actions that are common to both alternatives B and C. These include using...

  9. 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’

  10. 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.

  11. 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…

  12. 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

    2017-02-01

    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.

  13. 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

    ... could pass safely around the safety zone. Before the activation of the zone, we would issue maritime... power and responsibilities between the Federal Government and Indian tribes. 12. Energy Effects This proposed rule is not a ``significant energy action'' under Executive Order 13211, Actions...

  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

    ... [Federal Register Volume 75, Number 2 (Tuesday, January 5, 2010)] [Notices] [Page 418] [FR Doc No: E9-31226] DEPARTMENT OF HOMELAND SECURITY Coast Guard [Docket No. USCG-2009-1050] Certificate of... find this docket on the Internet by going to http://www.regulations.gov , inserting USCG-2009-1050...

  15. 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.

  16. Nineteenth-Century African American Women's Autobiography as Social Discourse: The Example of Harriet Ann Jacobs

    ERIC Educational Resources Information Center

    Stover, Johnnie M.

    2003-01-01

    The power of black women's personal narratives emerging out of nineteenth-century America rested in their sociopolitical as well as in their literary contributions. These slave narratives and autobiographical texts, however, were either ignored, sentimentalized, or reduced in scope as addenda to the abolitionist-inspired texts produced by black…

  17. 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 ...

  18. 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

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

    Federal Register 2010, 2011, 2012, 2013, 2014

    2013-10-31

    .... +/-112 years) based on radiocarbon 14 dating. No known individuals were identified. No associated... Period (500-1200 A.D.) based on diagnostic artifacts and chronometric dating. No known individuals...

  1. 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…

  2. 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...

  3. 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...

  4. MRF-ANN: a machine learning approach for automated ER scoring of breast cancer immunohistochemical images.

    PubMed

    Mungle, T; Tewary, S; DAS, D K; Arun, I; Basak, B; Agarwal, S; Ahmed, R; Chatterjee, S; Chakraborty, C

    2017-03-20

    Molecular pathology, especially immunohistochemistry, plays an important role in evaluating hormone receptor status along with diagnosis of breast cancer. Time-consumption and inter-/intraobserver variability are major hindrances for evaluating the receptor score. In view of this, the paper proposes an automated Allred Scoring methodology for estrogen receptor (ER). White balancing is used to normalize the colour image taking into consideration colour variation during staining in different labs. Markov random field model with expectation-maximization optimization is employed to segment the ER cells. The proposed segmentation methodology is found to have F-measure 0.95. Artificial neural network is subsequently used to obtain intensity-based score for ER cells, from pixel colour intensity features. Simultaneously, proportion score - percentage of ER positive cells is computed via cell counting. The final ER score is computed by adding intensity and proportion scores - a standard Allred scoring system followed by pathologists. The classification accuracy for classification of cells by classifier in terms of F-measure is 0.9626. The problem of subjective interobserver ability is addressed by quantifying ER score from two expert pathologist and proposed methodology. The intraclass correlation achieved is greater than 0.90. The study has potential advantage of assisting pathologist in decision making over manual procedure and could evolve as a part of automated decision support system with other receptor scoring/analysis procedure.

  5. 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.

  6. "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.

  7. 78 FR 65376 - Notice of Inventory Completion: University of Michigan, Ann Arbor, MI

    Federal Register 2010, 2011, 2012, 2013, 2014

    2013-10-31

    ...); Quechan Tribe of the Fort Yuma Indian Reservation, California & Arizona; Red Cliff Band of Lake Superior Chippewa Indians of Wisconsin; Red Lake Band of Chippewa Indians, Minnesota; Sokaogon Chippewa Community... objects present are 1 unworked deer scapula, 3 worked animal bones, 1 unworked turkey bone, 5 slate...

  8. 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.

  9. 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.

  10. 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…

  11. Always in the Mood for Moody: Teaching History through Anne Moody's "Coming of Age in Mississippi"

    ERIC Educational Resources Information Center

    Boisseau, T. J.

    2014-01-01

    In searching for a way of teaching American history as something that truly belongs to women, and men, to the powerful as well as to those who lack power in a formal sense, as something that is not the story of white people with an interesting person of color charitably thrown in for good measure, Boisseau writes that while many influential…

  12. 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...

  13. 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...

  14. User Activity Recognition in Smart Homes Using Pattern Clustering Applied to Temporal ANN Algorithm.

    PubMed

    Bourobou, Serge Thomas Mickala; Yoo, Younghwan

    2015-05-21

    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.

  15. 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

    ... be free of any defects or viruses. For additional instructions on submitting comments, go to Section... generating unit (EGU) point sources, non-EGU point sources, area sources, non-road mobile sources, marine...., Vehicle Miles Traveled, fuel programs, the NONROAD 2002 model data for commercial marine...

  16. 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

    .... We will announce upcoming public meetings in local news media, via our project mailing list, and on.... The refuge also offers unique opportunities for environmental education and interpretation in an urban..., and environmental education and interpretation. We will review and update the CCP at least every...

  17. 75 FR 12563 - Patuxent Research Refuge, Anne Arundel and Prince George's Counties, MD

    Federal Register 2010, 2011, 2012, 2013, 2014

    2010-03-16

    ... input in local news media throughout the CCP process. ADDRESSES: Send your comments or requests for more..., wildlife observation, photography, and environmental education and interpretation. We will review and... environmental education, interpretation, and scientific information exchange. There are over 24 miles of...

  18. 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.

  19. 78 FR 65364 - Notice of Inventory Completion: University of Michigan, Ann Arbor, MI

    Federal Register 2010, 2011, 2012, 2013, 2014

    2013-10-31

    ... shell disk beads, 1 copper awl, 3 round shell gorgets perforated at the center, 6 large sandal-sole..., but museum records indicate that the mandible was placed in the teaching collection in 1967. Green... as part of the death rite or ceremony. Pursuant to 25 U.S.C. 3001(2), a relationship of shared...

  20. 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.

  1. 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...

  2. 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.

  3. 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...

  4. The Cape Ann Conference on Junior High School Mathematics, September 9-12, 1973.

    ERIC Educational Resources Information Center

    Newton Coll. of the Sacred Heart, MA. Physical Sciences Group.

    This NSF-sponsored conference on the teaching of mathematics at the junior high level involved mathematics teachers and teachers of the natural and social sciences. Papers written for the conference form the bulk of this report. Summaries of the papers and general discussions are organized into shorter reports to give some guidelines which could…

  5. 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

  6. 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 Rocky Boy's Reservation, Montana; Citizen Potawatomi Nation, Oklahoma; Delaware Nation, Oklahoma... Chippewa Tribe, Minnesota; Chippewa-Cree Indians of the Rocky Boy's Reservation, Montana; Fond du Lac Band... Rocky Boy's Reservation, Montana; Citizen Potawatomi Nation, Oklahoma; Delaware Nation,...

  7. 78 FR 65357 - Notice of Inventory Completion: University of Michigan, Ann Arbor, MI

    Federal Register 2010, 2011, 2012, 2013, 2014

    2013-10-31

    ... Community, Michigan; Chippewa-Cree Indians of the Rocky Boy's Reservation, Montana; Grand Traverse Band of... Band (Nett Lake) of the Minnesota Chippewa Tribe, Minnesota; Chippewa-Cree Indians of the Rocky...

  8. 78 FR 65369 - Notice of Inventory Completion: University of Michigan, Ann Arbor, MI

    Federal Register 2010, 2011, 2012, 2013, 2014

    2013-10-31

    ..., Michigan; Chippewa-Cree Indians of the Rocky Boy's Reservation, Montana; Grand Traverse Band of Ottawa and...; Chippewa-Cree Indians of the Rocky Boy's Reservation, Montana; Citizen Potawatomi Nation, Oklahoma; Fond...

  9. 78 FR 65360 - Notice of Inventory Completion: University of Michigan, Ann Arbor, MI

    Federal Register 2010, 2011, 2012, 2013, 2014

    2013-10-31

    ... Boy's Reservation, Montana; Grand Traverse Band of Ottawa and Chippewa Indians, Michigan; Hannahville...; Chippewa-Cree Indians of the Rocky Boy's Reservation, Montana; Fond du Lac Band of the Minnesota...

  10. 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.

  11. Response to the Publican Using the Perspective Provided by Anne Roe.

    ERIC Educational Resources Information Center

    Moss, Colleen; Bradley, Richard W.

    1988-01-01

    Analyzes the interview with the Publican in the previous article, based on Roe's theory on the factors that influence personality and, therefore, career choice. Analyzes the interview data in terms of Roe's propositions regarding genetic inheritance, environmental factors, early childhood interactions with parents, patterns of psychic energies,…

  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. 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′...

  14. 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′...

  15. 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...

  16. Comparison of the Nature of Chaos in Experimental [EEG] Data and Theoretical [ANN] Data

    NASA Astrophysics Data System (ADS)

    Das, Atin; Das, Pritha

    2003-08-01

    In this paper, nonlinear dynamical tools like largest Lyapunov exponents (LE), fractal dimension, correlation dimension, pointwise correlation dimension will be employed to analyze electroencephalogram [EEG] data and determine the nature of chaos. Results of similar calculations from some earlier works will be produced for comparison with present results. Also, a brief report on difference of opinion among coworkers regarding tools to characterize chaos will be reported; particularly applicability of LE will be reviewed. The issue of nonlinearity present in experimental time series will be addressed by using surrogate data technique. We have extracted another data set which represented chaotic state of the system considered in our earlier work of mathematical modeling of artificial neural network. By comparing the values of measures employed to the two datasets, it can be concluded that EEG represents high dimensional chaos, whereas the experimental data due to its deterministic nature, is of low dimension. Also results give the evidence that LE exponent is applicable for low dimensional chaotic system while for experimental data, due to their stochasticity and presence of noise- LE is not a reliable tool to characterize chaos.

  17. 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...

  18. 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...

  19. "[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…

  20. 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.

  1. 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.

  2. Comment on: "Ground state energies from converging and diverging power series expansions", Ann. Phys. 373 (2016) 456-469

    NASA Astrophysics Data System (ADS)

    Amore, Paolo; Fernández, Francisco M.

    2017-01-01

    We compare two alternative expansions for finite attractive wells. One of them is known from long ago and is given in terms of powers of the strength parameter. The other one is based on the solution of the equations of the Rayleigh-Schrödinger perturbation theory in a basis set of functions of period L. The analysis of exactly solvable models shows that although the exact solution of the problem with periodic boundary conditions yields the correct result when L → ∞ the coefficients of the series for this same problem blow up and fail to produce the correct asymptotic expansion.

  3. Symposium of Naval Hydrodynamics (14th) held at Ann Arbor, Michigan on August 23-27, 1982,

    DTIC Science & Technology

    1982-01-01

    Chahine -Viscous Effects on the Stability of Cavitating Line Vortices -. 195 Jaakko V. Pylkknen Nuclei and Cavitation 215 Jean -Pierre Le G9fu and Yves...the sectional area of the sheet cavity at • ,this position. . .~ . . * , ILv ’. - ,’ 4 4- ,*-. . ... . 4.4 K"% Nuclei and Cavitation Jean -Pierre Le Goff...the experiments, with analysing .- the results and with running computer programs. Thanks are also due to U H Pinto who developed a substantial part of

  4. 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…

  5. 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,…

  6. 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.

  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. Withdrawal notice to: Local causality in a Friedmann-Robertson-Walker spacetime [Ann. Phys. 373 (2016) 67-79

    NASA Astrophysics Data System (ADS)

    Christian, Joy

    2016-10-01

    This article has been withdrawn at the request of the Editors. Soon after the publication of this paper was announced, several experts in the field contacted the Editors to report errors. After extensive review, the Editors unanimously concluded that the results are in obvious conflict with a proven scientific fact, i.e., violation of local realism that has been demonstrated not only theoretically but experimentally in recent experiments. On this basis, the Editors decided to withdraw the paper. As a consequence, pages 67-79 originally occupied by the withdrawn article are missing from the printed issue. The publisher apologizes for any inconvenience this may cause. The full Elsevier Policy on Article Withdrawal can be found at http://www.elsevier.com/locate/withdrawalpolicy.

  9. Withdrawal notice to: Local causality in a Friedmann-Robertson-Walker spacetime [Ann. Phys. 373 (2016) 67-79

    NASA Astrophysics Data System (ADS)

    Christian, Joy

    2016-10-01

    This article has been withdrawn at the request of the Editors. Soon after the publication of this paper was announced, several experts in the field contacted the Editors to report errors. After extensive review, the Editors unanimously concluded that the results are in obvious conflict with a proven scientific fact, i.e., violation of local realism that has been demonstrated not only theoretically but experimentally in recent experiments. On this basis, the Editors decided to withdraw the paper. As a consequence, pages 67-79 originally occupied by the withdrawn article are missing from the printed issue. The publisher apologizes for any inconvenience this may cause. The full Elsevier Policy on Article Withdrawal can be found at http://www.elsevier.com/locate/withdrawalpolicy.

  10. 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…

  11. 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...

  12. OPPORTUNITIES FOR WOMEN THROUGH EDUCATION, CONFERENCE-WORKSHOP PROCEEDINGS (UNIVERSITY OF MICHIGAN, ANN ARBOR, MARCH 16, 1965).

    ERIC Educational Resources Information Center

    Michigan Univ., Ann Arbor. Center for Continuing Education for Women.

    A CONFERENCE ON OPPORTUNITIES FOR WOMEN EMPHASIZED THE EDUCATIONAL AND TRAINING REQUIREMENTS FOR EMPLOYMENT IN THE FIELDS OF TEACHING, SOCIAL WORK, HEALTH SCIENCES, MATHEMATICS, PHYSICAL SCIENCES, ENGINEERING, AND LIBRARY SCIENCE, AND OPPORTUNITIES FOR CONTINUING EDUCATION IN UNDERGRADUATE LIBERAL ARTS. THE MORNING ADDRESS DESCRIBED THE SARAH…

  13. 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...

  14. Improvement of adaptive GAs and back propagation ANNs performance in condition diagnosis of multiple bearing system using grey relational analysis.

    PubMed

    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.

  15. Workshop on Developing Potentials for Atomistic Simulations Held in Ann Arbor, Michigan on 25-27 September 1991

    DTIC Science & Technology

    1991-12-20

    ELECTE MAR0 6 1992 12a. DISTRIBUTION AVAiLABIL1T- STA"E’," FN7 •. DISTRIBUTON CODE Approved for public release;Distribution is unlimited i 3. A8S TR...Research. In the last 20 years or so it has become possible to compute total energies and electronic structures of extended defects, such as crystalline...latter. He then proposed a tight-binding approach for bcc metals, which relies on a moments method up to the fourth moment for the electronic density of

  16. 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...

  17. 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

  18. 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…

  19. 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.

  20. Workshop on Surface Science and Technology Held in Ann Arbor, Michigan on 7-9 November 1990

    DTIC Science & Technology

    1992-03-01

    for all brittle materials, toughness should be the main determinant of wear resistance. This was verified in the case of zirconia which can be...materials increases with the fourth power of toughness (by a factor of 1200 when toughness increases by a factor of 6). In transformation- toughened zirconia ...this transition, the wear rate increases with the fifth power of the load. In sliding wear of zirconia , the wear rate of a spherical slider decreases

  1. 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.

  2. 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…

  3. International Conference: Paraoxonases - Basic and Clinical Directions of Current Research (1st) Held in Ann Arbor, Michigan on April 22-24, 2004

    DTIC Science & Technology

    2005-04-01

    HDL cholesterol levels but prevented impairment of LCAT activity when plasma was exposed to oxidative stress. Excess PON 1 inhibited...variation at the PON- 1 gene locus in terms of their effect on HDL - cholesterol levels and on the carotid intima media thickness (IMT), a surrogate...positive correlation between PON- 1 levels and activity and HDL - cholesterol (PON- 1 levels : r=0.37, pɘ.001; paraoxonase activity: r=0.23, p=0.01;

  4. 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...

  5. The Freshman Year in Science and Engineering: Old Problems, New Perspectives for Research Universities. Report of a Conference (Ann Arbor, Michigan, April 6-7, 1990).

    ERIC Educational Resources Information Center

    Wineke, William R.; Certain, Phillip

    The goal of the conference reported in this document was to initiate major revitalization of freshman science by bringing together individuals who have been working to improve introductory courses with research faculty who may or may not have been actively involved in the teaching of these courses. This report tries to capture the spirit and the…

  6. 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…

  7. National Dam Safety Program. Oldham Pond Dam (NJ00238), Passaic River Basin, Molly Ann Brook, Passaic County, New Jersey. Phase 1 Inspection Report

    DTIC Science & Technology

    1980-01-01

    Environm~ental Protection Jan Division of Water Resources ______________ Trenton, NJ 08625 122 14. ONIORIG AENCYNAM & DDRSS(f difernt romConrollng ffie...of the structure. (6) Investigate the reasons for the uneven surface of the crest, including the area where a hole has been filled with concrete and...design remedial measures as needed. (7) Design and implement necessary remedial measures to prevent erosion of the toe of the dam by water flowing in

  8. AFOSR/ONR Contractors’ Meeting on Combustion Rocket Propulsion Diagnostics of Reacting Flow Held in Ann Arbor, Michigan on 19-23 June 1989

    DTIC Science & Technology

    1989-06-19

    measurement of the hot band peak heights. In the near future , we will incorporate chemical kinetics of the BAMO/NMMO decomposition and combustion processes...Tennessee 37388 SUMMARY/OVERVIEW: Combustion process in scramjets, and to some extent in raznjets, is limited by mixing. Various concepts of mixing which are...Chemical Mechanism Relationships in Decomposition, Combustion , and Explosion: Current Status and Future Studies. (b) S.A. Shackelford, P.C. Trlove

  9. 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.

  10. Oxford Handbook of Adult Nursing Castledine George Close Ann Oxford Handbook of Adult Nursing 1252 Oxford University Press 9780199231355 0199231354 [Formula: see text].

    PubMed

    2010-06-02

    This sturdy book with its plastic cover gives the impression it is expecting a great deal of use. It is a book to dip in and out of, and would be helpful in the clinical setting for quick reference, as well as for revision.

  11. ONR Workshop on Nonlinear Sea Loads and Ship Response: A Basis for Ship Structural Design Held in Ann Arbor, Michigan on July 7-8, 1994

    DTIC Science & Technology

    1994-07-08

    Avail arý,dlIor8:00 - 8:30 Coffee and doughnuts, registration Dist Special Workshop Introduction 8:30 - 8:45 Welcome Prof. Michael G. Parsons, Naval...Bureau of Shipping Friday, July 8 8:00 - 8:30 Coffee and doughnuts Simulation-Based Design Environment 8:30 - 8:50 Use of Reliability in Structural Design...virtual environment with user, data glove and I physical elements I 73 VW Super Beetle -H 10364 Vertices 10514 Polygons 73 VW Super Beetle -L 1520 Vertices

  12. Languages and Communication for World Business and the Professions. Proceedings of the Annual Conference (6th, Ann Arbor, Michigan, May 8-9, 1987).

    ERIC Educational Resources Information Center

    Des Harnais, Gaston R., Ed.

    Topics covered in papers presented at a conference on languages and communication for world business and the professions include: (1) trends and aspects of internationalizing the business curriculum; (2) internationalized programs in business, foreign language, and cultures; (3) internationalized courses in business, foreign languages, and…

  13. 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…

  14. 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.

  15. Suivi thérapeutique pharmacologique de trois médicaments antiépileptiques: retour sur vingt années d’expérience

    PubMed Central

    Serragui, Samira; Zalagh, Fatima; Tanani, Driss Soussi; Ouammi, Lahcen; Moussa, Latifa Ait; Badrane, Narjis; Bencheikh, Rachida Soulaymani

    2016-01-01

    Introduction Le suivi thérapeutique pharmacologique (STP) des médicaments antiépileptiques (MAE) est un outil très utilisé dans la gestion de l'épilepsie. Au Maroc, ce dosage est réalisé au Centre Anti Poison et de Pharmacovigilance du Maroc (CAPM) depuis Avril 1995. Méthodes Il s'agit d'une étude rétrospective s'étalant sur 20 ans. Elle concerne le STP du Phénobarbital (PB), de la Carbamazépine (CBZ) et de l'Acide Valproique (AVP). Résultats Le STP des 3 MAE représentaient 58,85% de l'ensemble des demandes de STP reçue par le CAPM. Le dosage du PB était classé en première position suivi par celui de la CBZ et enfin par l'AVP. La faible demande de STP au Maroc pouvait être expliquée par le faible nombre de neurologues auquel s'ajoutaient des facteurs sociaux. Grâce à son prix très accessible par les patients, le PB est le MAE le plus prescrit dans notre pays expliquant ainsi la demande élevée de son dosage. Quant aux motifs de STP des 3 MAE, ils étaient essentiellement liés à l'âge, à l'apparition d'effets indésirables, à l'association de MAE ou dans le cas de vérification de l'observance des malades. Conclusion Des efforts sont à fournir pour promouvoir l'intérêt du STP des MAE dans la prise en charge de l'épilepsie au Maroc. PMID:28154702

  16. 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…

  17. 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:

  18. 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…

  19. 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.

  20. 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...

  1. 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...

  2. Comparison of Artificial Neural Network (ANN) Model Development Methods for Prediction of Macroinvertebrate Communities in the Zwalm River Basin in Flanders, Belgium.

    PubMed

    Dedecker, Andy P; Goethals, Peter L M; De Pauw, Niels

    2002-01-12

    Modelling has become an interesting tool to support decision making in water management. River ecosystem modelling methods have improved substantially during recent years. New concepts, such as artificial neural networks, fuzzy logic, evolutionary algorithms, chaos and fractals, cellular automata, etc., are being more commonly used to analyse ecosystem databases and to make predictions for river management purposes. In this context, artificial neural networks were applied to predict macroinvertebrate communities in the Zwalm River basin (Flanders, Belgium). Structural characteristics (meandering, substrate type, flow velocity) and physical and chemical variables (dissolved oxygen, pH) were used as predictive variables to predict the presence or absence of macroinvertebrate taxa in the headwaters and brooks of the Zwalm River basin. Special interest was paid to the frequency of occurrence of the taxa as well as the selection of the predictors and variables to be predicted on the prediction reliability of the developed models. Sensitivity analyses allowed us to study the impact of the predictive variables on the prediction of presence or absence of macroinvertebrate taxa and to define which variables are the most influential in determining the neural network outputs.

  3. 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...

  4. 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).

  5. 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.

  6. 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...

  7. 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.

  8. 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…

  9. Erratum to "Dynamics of the normal-superconductor phase transition and the puzzle of the Meissner effect" [Ann. Physics 362 (2015) 1-23

    NASA Astrophysics Data System (ADS)

    Hirsch, J. E.

    2017-01-01

    The paper contains several incorrect statements related to the fact that the key issues of reversibility of the normal-superconductor transition [1] and the hole-like nature of the normal charge carriers [2] were not properly recognized. Even though these issues were clarified in subsequent publications [3,4], we believe it should be useful for the reader that we clarify here which of the statements in this paper are incorrect.

  10. IEEE International Symposium on Information Theory (ISIT): Abstracts of Papers, Held in Ann Arbor, Michigan on 6-9 October 1986.

    DTIC Science & Technology

    1986-10-01

    19 DECODING RATE 1/n CONVOLUTIONAL CODES IN VLSI, Glenn Gulak, V.P. Roy - chowdhury, and T. Kailath...ESTIMATION IN CORRELATED NOISE, Summit Roy and Ronald A . lltis... ROY and RONALD A. ILTIS, Department of Electrical and Computer Engineer- ing, University of California, Santa Barbara, CA 93106, USA. It has been

  11. National Dam Inspection Program. Wye Mills Dam, (NDI-Number-MD-00029) Upper Chesapeake Bay Basin. Queen Annes County, Maryland. Phase I Inspection Report.

    DTIC Science & Technology

    1979-05-01

    AD-AOG8 799 cORPS OF ENGINEERS BALTIMORE MD BALTIMORE DISTRICT F/6 13/13 NATIONAL DAM INSPECTION PROGRAM? WYE MILLS DAM, (NOI-NJMBFR-MD---ETC(U...ARMY Baltimore District, Corps of Engineers Baltimore, Maryland 21203 Prepared by: WATER RESOURCES ADMINISTRATION Department of Natural Resources Tawes...Copies of these guidelines may be obtained from the Office of Chief of Engineers , Washington, D.C. 20314. The purpose of a Phase I Investigation is to

  12. "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.…

  13. The Development of Mauna Kea as an Astronomical Site Panelists: John Jefferies, Ann Boesgaard, Alan Stockton, Eric Becklin, and Alan Tokunaga

    NASA Astrophysics Data System (ADS)

    Harmony, Teasel Muir; Devorkin, David

    2016-10-01

    On August 11 we held a panel discussion at the 2015 IAU General Assembly, within the three-day Focus Meeting FM2, ``Astronomical Heritage: Progressing the UNESCO-IAU Initiative''. Our purpose was to both honor and explore the contributions of John Jefferies to the creation and development of Mauna Kea as an astronomical site.

  14. 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.

  15. International Conference on Atomic Physics (12TH) Held at Ann Arbor, Michigan on July 29-August 2, 1990. Abstracts of Contributed Papers.

    DTIC Science & Technology

    1990-09-26

    the flux vanishes. The diffusion equation is justified when the thermalization by Wall collisions drives the atomic velocity distribution to...cavity collisions in which particles can either lose energy or annihilate for a distribution of initial o-Ps energies. We expect such a combination to...shell electrons and a target nucleus due to outer electrons. However, this FP assumption is almost justified in the case of collision system dealt

  16. International Conference on Atomic Physics: Abstracts of Contributed Papers (12th) Held in Ann Arbor, Michigan on 29 July-3 August 1990

    DTIC Science & Technology

    1990-09-26

    the local physics of the 2 1Ne nucleus . Systematic variations of the quadrupole component at multiples of the earth’s solar frequency do arise, mostly...equation is justified when the thermalization by wal Collisions drives the atomic velocity distribution to equilibrium on a time scale that is slow...inelastic cavity collisions in which particles can either lose energy or annihilate for a distribution of initial o-Ps energies. We expect such a

  17. 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...

  18. 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…

  19. Oversight Hearing on the Reauthorization of the Higher Education Act of 1965: Ann Arbor, Michigan. Hearing before the Subcommittee on Postsecondary Education of the Committee on Education and Labor. House of Representatives, One Hundred Second Congress, First Session (Ann Arbor, Michigan).

    ERIC Educational Resources Information Center

    Congress of the U.S., Washington, DC. House Committee on Education and Labor.

    This document presents testimony and statements from one of a series of Congressional field hearings intended to critically review all the programs associated with the Higher Education Act of 1965. Issues addressed in the testimony and prepared statements include: how the United States can maximize the number of students, including non-traditional…

  20. 30 CFR 941.780 - Surface mining permit applications-minimum requirements for reclamation and operation plan.

    Code of Federal Regulations, 2011 CFR

    2011-07-01

    ... 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....

  1. 30 CFR 941.780 - Surface mining permit applications-minimum requirements for reclamation and operation plan.

    Code of Federal Regulations, 2010 CFR

    2010-07-01

    ... 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....

  2. 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....

  3. 78 FR 77664 - Defense Policy Board (DPB); Notice of Federal Advisory Committee Meeting

    Federal Register 2010, 2011, 2012, 2013, 2014

    2013-12-24

    ..., Washington, DC 20301- 2000. FOR FURTHER INFORMATION CONTACT: Ms. Ann Hansen, 2000 Defense Pentagon... classified material. Committee's Designated Federal Officer or Point of Contact: Ann Hansen,...

  4. 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…

  5. A Nurse's Survival Guide to the Ward - Third edition Richards Ann Edwards Sharon A Nurse's Survival Guide to the Ward - Third edition 500pp £19.99 Elsevier 978 0 7020 4603 2 0702046035 [Formula: see text].

    PubMed

    2013-05-08

    This guide is a useful 'friend and companion' to keep close at hand. It is an essential reference for nurses, not only on the ward but in every field of practice where patient care is given. In fact, it makes an accessible guide for all healthcare practitioners.

  6. Book Review: The Einstein tower: an intertexture of dynamic construction, relativity theory, and astronomy. Klaus Hentschel and Ann M. Hentschel (Trans.); Stanford University Press, 270pp., US 51, ISBN 0804728240

    NASA Astrophysics Data System (ADS)

    Smith, Robert W.

    Standing atop the Telegraphenberg in Potsdam stands a large and visually striking historic observatory known as the Einstein Tower. Erected with the aim of testing the general theory of relativity, by examining the postulated effect of gravitational redshift on the solar spectrum, the tower was completed in 1924. What forces led to its construction at a time when general relativity was only a few years old and still viewed skeptically by many a working astronomer? And why was a tower telescope housed in such an exotic building, perhaps the most architecturally remarkable observatory ever built?

  7. A resolution to authorize testimony and legal representation in City of St. Paul v. Irene Victoria Andrews, Bruce Jerome Berry, John Joseph Braun, David Eugene Luce, and Elizabeth Ann McKenzie.

    THOMAS, 111th Congress

    Sen. Reid, Harry [D-NV

    2010-12-09

    12/09/2010 Submitted in the Senate, considered, and agreed to without amendment and with a preamble by Unanimous Consent. (consideration: CR S8692; text as passed Senate: CR S8692; text of measure as introduced: CR S8715) (All Actions) Tracker: This bill has the status Passed SenateHere are the steps for Status of Legislation:

  8. A resolution commemorating and celebrating the lives of Officer Kristine Marie Fairbanks, Deputy Anne Marie Jackson, and Sergeant Nelson Kai Ng who gave their lives in the service of the people of Washington State in 2008.

    THOMAS, 111th Congress

    Sen. Murray, Patty [D-WA

    2009-05-14

    05/14/2009 Submitted in the Senate, considered, and agreed to without amendment and with a preamble by Unanimous Consent. (consideration: CR S5538-5539; text as passed Senate: CR S5538-5539; text of measure as introduced: CR S5530) (All Actions) Tracker: This bill has the status Passed SenateHere are the steps for Status of Legislation:

  9. 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…

  10. 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…

  11. AFOSR/ONR (Air Force Office of Scientific Research/Office of Naval Research) Contractors’ Meeting - Combustion Rocket Propulsion Diagnostics of Reacting Flow Held in Ann Arbor, Michigan on June 19-23, 1989

    DTIC Science & Technology

    1989-06-19

    Diffusion An experimental and numerical investigation has been conducted to investigate the influence of the mobility of inert additives on soot formation...krypton, being the least mobile inert, yields the greatest soot loading while helium, being the most mobile , yields the least (Fig. 4). By relating...that this influence on soot loading is likely caused by concentration modifications of the fuel and the soot precursors due to the different mobilities

  12. 78 FR 5176 - Proposed Settlement Agreement Pursuant to the Comprehensive Environmental Response, Compensation...

    Federal Register 2010, 2011, 2012, 2013, 2014

    2013-01-24

    ... may be obtained from Ann Gardner, U.S. Environmental Protection Agency, Region I, 5 Post Office Square... gardner.ann@epa.gov . Comments should be addressed to Ann Gardner at the above address and reference Bay... INFORMATION CONTACT: Ann Gardner, U.S. Environmental Protection Agency, Region I, 5 Post Office Square,...

  13. 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.

  14. 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.

  15. Prediction of the competitive adsorption isotherms of 2-phenylethanol and 3-phenylpropanol by artificial neural networks.

    PubMed

    Wu, Xiuhong; Wang, Shaoyan; Zhang, Renzhuang; Gao, Zhiming

    2014-03-07

    Artificial neural networks (ANNs) were regarded as data-mapping networks with strong nonlinear fitting abilities. A 2-6-2 network was used to determine the competitive adsorption isotherm of 2-phenylethanol (PE) and 3-phenylpropanol (PP). The ANN results were forms of data mapping rather than theoretical mathematical model. The ANN architecture was established after training with a set of experimental data. The established ANN was applied to predict the adsorption isotherms of PE and PP. The selection of parameters for the ANN was discussed. The results indicate that ANN has excellent potential for use in non-linear chromatography for the prediction of adsorption isotherms.

  16. Dating Kaali Crater (Estonia) based on charcoal emplaced within proximal ejecta blanket

    NASA Astrophysics Data System (ADS)

    Losiak, Anna; Wild, Eva Maria; Huber, Matthew S.; Wisniowski, Tomasz; Paavel, Kristiina; Jõeleht, Argo; Välja, Rudolf; Plado, Jüri; Kriiska, Aivar; Wilk, Jakob; Zanetti, Michael; Geppert, Wolf D.; Kulkov, Alexander; Steier, Peter; Pirkovic, Irena

    2015-04-01

    The Kaali impact field consists of nine identified craters located on the Saaremaa Island in Estonia. The largest crater is 110 m in diameter (centered around 58°22'21.94"N, 22°40'09.91" E). It was formed by impact of an IAB iron meteoroid into Silurian dolomite target rocks covered by up to a few meters of glacial till (Veski et al. 2007). The age of the Kaali impact structure is still a matter of debate, and the estimates provided by different authors vary considerably between ~6400 BC (Raukas et al. 1995, Moora et al. 2012) and ~400 BC (Rasmussen et al. 2000, Veski et al. 2001). These ages were derived by 14C dating of marker horizons, characterized by a slightly elevated iridium content within the nearby Piila bog yielding a calibrated age of 800-400 BC (Rasmussen et al. 2000, Veski et al. 2001) and occurrences of glassy siliceous material in the Piila bog (~6400 BC: Raukas et al. 1995) or iron microspherules in an organic-rich layer of the Reo gravel pit (6400 BC: Moora et al. 2012). However, the source of the foreign material within those layers was never unequivocally connected with the Kaali crater. 14C dating of material from post-impact organic sediments within Kaali impact craters yielded ages between 1800-1500 BC (Saarse et al. 1991, Veski et al. 2004) and 1450-400 BC (Aaloe et al. 1963). These dates underestimate the age of impact as organic sediments within the crater started to form at unknown period after the impact. On the other hand, Veski et al. (2004) suggested a reservoir effect that might have caused artificially "aging" of the organic matter because the crater was emplaced within Silurian dolomite which is rich in old carbon. The aim of this study is to determine the age of the Kaali crater by 14C dating of organic material covered by the continuous layer of proximal ejecta. This research was conducted in conjunction with a new structural investigation of Kaali Main (Zanetti et al. 2015). Ten samples collected from different locations

  17. 75 FR 56857 - Pilot, Flight Instructor, and Pilot School Certification

    Federal Register 2010, 2011, 2012, 2013, 2014

    2010-09-17

    ..., contact: Anne Moore, AGC-240, Office of Chief Counsel, Regulations Division, Federal Aviation Administration, (202) 267-3123; e-mail to anne.moore@faa.gov . SUPPLEMENTARY INFORMATION: Background On August...

  18. 77 FR 73031 - Change in Bank Control Notices; Acquisitions of Shares of a Bank or Bank Holding Company

    Federal Register 2010, 2011, 2012, 2013, 2014

    2012-12-07

    ..., Illinois 60690-1414: 1. The Guttau Family consisting of Michael K. Guttau, Judith Ann Guttau, and the Heidi Guttau-Fox and Joshua Guttau Irrevocable Living Trust, Treynor, Iowa, Heidi Ann Guttau-Fox, Minden,...

  19. Islamic Revival in the Balkans

    DTIC Science & Technology

    2006-03-01

    Thesis Co-Advisors: Glenn Robinson Anne Marie Baylouny Approved for public release; distribution is unlimited...Robinson Thesis Co-Advisor Anne Marie Baylouny Thesis Co-Advisor Gordon McCormick Chairman, Department of Defense Analysis Douglas...

  20. 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,...

  1. 75 FR 68000 - Notice of Inventory Completion: U.S. Department of Agriculture, Forest Service, Hiawatha National...

    Federal Register 2010, 2011, 2012, 2013, 2014

    2010-11-04

    ... of Michigan, Museum of Anthropology, Ann Arbor, MI AGENCY: National Park Service, Interior. ACTION... physical custody of the University of Michigan, Museum of Anthropology, Ann Arbor, MI. The human...

  2. 77 FR 20123 - Fee Change for Paying Agents Redeeming Definitive Savings Bonds and Savings Notes

    Federal Register 2010, 2011, 2012, 2013, 2014

    2012-04-03

    ... >. Ann Fowler, Attorney-Adviser, Brian Metz, Attorney-Adviser, Dean Adams, Assistant Chief Counsel, or...) 480- 8692 or ann.fowler@bpd.treas.gov >. SUPPLEMENTARY INFORMATION: Beginning October 1,...

  3. Electricity price short-term forecasting using artificial neural networks

    SciTech Connect

    Szkuta, B.R.; Sanabria, L.A.; Dillon, T.S.

    1999-08-01

    This paper presents the System Marginal Price (SMP) short-term forecasting implementation using the Artificial Neural Networks (ANN) computing technique. The described approach uses the three-layered ANN paradigm with back-propagation. The retrospective SMP real-world data, acquired from the deregulated Victorian power system, was used for training and testing the ANN. The results presented in this paper confirm considerable value of the ANN based approach in forecasting the SMP.

  4. 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.

  5. Implementation of artificial neural networks with optics

    NASA Astrophysics Data System (ADS)

    Yu, Francis T. S.

    1999-04-01

    Optical implementation of artificial neural nets (ANNs) with electronically addressable liquid crystal televisions (LCTVs) are presented. The major advantages of the proposed ANNs must be the low cost and the flexibility to operate. To test the performance, several artificial neural net models have been implemented in the LCTV ANNs. These models include the Hopfield, Interpattern Association, Hetero-association, and Unsupervised ANNs. System design considerations and experimental demonstrates are provided.

  6. Towards Unbiased Evaluation of Uncertainty Reasoning: The URREF Ontology

    DTIC Science & Technology

    2013-01-01

    NUMBER 19a. NAME OF RESPONSIBLE PERSON 19b. TELEPHONE NUMBER Paulo Costa Paulo Costa, Kathryn Laskey, Erik Blasch, Anne- Laure Jousselme 611102 c...Force Research Lab Rome, NY, 13441 erik.blasch@rl.af.mil Anne- Laure Jousselme Defence R&D Canada-Valcartier Québec City, QC, G3J 1X5 Anne

  7. Congress’s Contempt Power: Law, History, Practice, and Procedure

    DTIC Science & Technology

    2007-07-24

    that prosecution of Anne Gorsuch Burford, Administrator of the Environmental Protection Agency, was not required following implementation of an...House of Representatives against the Then-Administrator of the Environmental Protection Agency, Anne Gorsuch Burford, Hearing before the House Committee...not to present to the grand jury the contempt citation of Environmental Protection Agency Administration Anne Gorsuch Burford.157 CRS-27 157

  8. 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);…

  9. Wide Area Recovery and Resiliency Program (WARRP) Knowledge Enhancement Events: CBR Workshop After Action Report

    DTIC Science & Technology

    2012-01-01

    Laboratories Walker Ray Walker Engineering Solutions, LLC Williams Patricia Denver Office of Emergency Management Wood- Zika Annmarie Lawrence Livermore...llnl.gov AnnMarie Wood- Zika woodzika1@llnl.gov Pacific Northwest National Laboratory Ann Lesperance ann.lesperance@pnnl.gov Jessica Sandusky

  10. 40 CFR 147.2300 - State-administered program.

    Code of Federal Regulations, 2010 CFR

    2010-07-01

    ... was approved by the Director of the Federal Register July 6, 1984. (1) Vt. Stat. Ann. tit. 10... are part of the approved State-administered program: (1) Vt. Stat. Ann. tit. 10, sections 1251 through 1283 (1973 and Supp. 1981). (2) Vt. Stat. Ann. tit. 10, sections 901 through 911 (1973 and Supp....

  11. 75 FR 30457 - Self-Regulatory Organizations; Financial Industry Regulatory Authority, Inc.; Notice of Filing of...

    Federal Register 2010, 2011, 2012, 2013, 2014

    2010-06-01

    ... meeting of such members.\\4\\ \\3\\ Del. Code Ann. tit. 8 Sec. 215(c) (2010). \\4\\ Del. Code Ann. tit. 8 Sec... a meeting of such members.\\5\\ \\5\\ Del. Code Ann. tit. 8 Sec. 215(c)(1) (2010). On August 1,...

  12. 75 FR 51150 - Notice of Solicitation of Public Comment on Consideration of Incorporating IFRS Into the...

    Federal Register 2010, 2011, 2012, 2013, 2014

    2010-08-18

    ... securities, or to repurchase such securities? \\12\\ \\12\\ E.g., Del. Code Ann., tit. 8, Sec. 154 (defining... change ] as a result of a change in accounting standards? \\15\\ E.g., Del. Code Ann., tit. 8, Sec. 271(a...? \\17\\ To what extent and in what ways, and why? \\17\\ E.g., Del. Code Ann., tit. 8, Sec. 503...

  13. 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…

  14. 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.

  15. 75 FR 82033 - National Institute of Environmental Health Sciences; Notice of Closed Meetings

    Federal Register 2010, 2011, 2012, 2013, 2014

    2010-12-29

    ..., Research Triangle Park, NC 27709. (Telephone Conference Call). Contact Person: RoseAnne M McGee, Associate... Park, NC 27709. (Telephone Conference Call). Contact Person: RoseAnne M McGee, Associate Scientific...). Contact Person: RoseAnne M McGee, Associate Scientific Review Administrator, Scientific Review...

  16. 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…

  17. 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…

  18. 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.

  19. Ann Sevi Ak Tout Entelijans Elev Ayisyen Yo: Yon Seri leson matematik ak syans pou elev edikasyon jeneral ak elev edikasyon espesyal (4em-8em ane) = Tapping into Haitian Students' Multiple Intelligences: A Collection of Mathematics and Science Lessons for General and Special Education Students (Grades 4-8).

    ERIC Educational Resources Information Center

    New York City Board of Education, Brooklyn, NY. Office of Bilingual Education.

    The materials consist of five mathematics and five science lessons for Haitian bilingual students in general and special education in grades 4-8. A thematic/interdisciplinary approach was used in designing the lesson, incorporating theory of multiple intelligences, Bloom's taxonomy of educational objectives, and other learning theories. The…

  20. Evapotranspiration and Dual Crop Coefficients Sonisa Sharma1, Ayse Irmak12, Anne Parkhurst3, Elizabeth walter-Shea1 and Kenneth G. Hubbard1 1School of Natural Resources, 2Civil Engineering, 3Departments of Statistics, University of Nebraska-Lincoln

    NASA Astrophysics Data System (ADS)

    Sharma, S.

    2012-12-01

    Accurate estimation of water content in the crop root zone is most important for water conservation and management practices like irrigation. The objective of this study is to use the FA0-56 dual crop cefficients: basal crop coefficient Kcb and the soil evaporation coefficient Ke for a large corn/soybean field in the year 2005 at the Mead Turf Farm in the state of Nebraska, USA..Dual crop coefficients can be used to estimate both transpiration from crops and evaporation from soil. The Kcb has a low value of 0.15(K cb, in) during the initial period, increases rapidly to a maximum of 1.14 (K cb, mid) for the entire midseason and decreases rapidly to 0.5 at the end of the corn growing season (K cb,end). When examined together with precipitation, the dual crop coefficient was higher following rainfall or irrigation, as expected. The data suggests that the dual crop coefficient approach is a good estimation of water loss from well-watered crops. Irrigation can be scheduled to replace the loss of water from the crop/soil system. Similarly, when we compared the measured daily ET and the ET calculated from dual crop coefficients, it gives 98 % R2.; Comparision of calculated ET from dual crop coefficient appraoch with Weather Station ET

  1. FIRST Quantum-(1980)-Computing DISCOVERY in Siegel-Rosen-Feynman-...A.-I. Neural-Networks: Artificial(ANN)/Biological(BNN) and Siegel FIRST Semantic-Web and Siegel FIRST ``Page''-``Brin'' ``PageRank'' PRE-Google Search-Engines!!!

    NASA Astrophysics Data System (ADS)

    Rosen, Charles; Siegel, Edward Carl-Ludwig; Feynman, Richard; Wunderman, Irwin; Smith, Adolph; Marinov, Vesco; Goldman, Jacob; Brine, Sergey; Poge, Larry; Schmidt, Erich; Young, Frederic; Goates-Bulmer, William-Steven; Lewis-Tsurakov-Altshuler, Thomas-Valerie-Genot; Ibm/Exxon Collaboration; Google/Uw Collaboration; Microsoft/Amazon Collaboration; Oracle/Sun Collaboration; Ostp/Dod/Dia/Nsa/W.-F./Boa/Ubs/Ub Collaboration

    2013-03-01

    Belew[Finding Out About, Cambridge(2000)] and separately full-decade pre-Page/Brin/Google FIRST Siegel-Rosen(Machine-Intelligence/Atherton)-Feynman-Smith-Marinov(Guzik Enterprises/Exxon-Enterprises/A.-I./Santa Clara)-Wunderman(H.-P.) [IBM Conf. on Computers and Mathematics, Stanford(1986); APS Mtgs.(1980s): Palo Alto/Santa Clara/San Francisco/...(1980s) MRS Spring-Mtgs.(1980s): Palo Alto/San Jose/San Francisco/...(1980-1992) FIRST quantum-computing via Bose-Einstein quantum-statistics(BEQS) Bose-Einstein CONDENSATION (BEC) in artificial-intelligence(A-I) artificial neural-networks(A-N-N) and biological neural-networks(B-N-N) and Siegel[J. Noncrystalline-Solids 40, 453(1980); Symp. on Fractals..., MRS Fall-Mtg., Boston(1989)-5-papers; Symp. on Scaling..., (1990); Symp. on Transport in Geometric-Constraint (1990)

  2. Modeling a scientific career: an essential component of the mentorship process. An interview with John A. Williams, Professor of Molecular and Integrative Physiology, University Of Michigan, Ann Arbor, Mich., USA by Martín E. Fernández-Zapico.

    PubMed

    Williams, John A

    2010-01-01

    In the current interview article, Dr. John A. Williams shares his experiences, and provides career advice to junior investigators. Dr. Williams is one of the world's leading physiologists working on signal transduction mechanisms in pancreatic acinar cells. He is worldwide recognized for his contribution to many areas of pancreatology, especially the understanding of GI hormone regulation of pancreatic exocrine function. and IAP.

  3. The great ormond street hospital manual of children's nursing practices Susan Macqueen The great ormond street hospital manual of children's nursing practices Elizabeth Anne Bruce Faith Gibbon (Eds) Wiley-Blackwell 790pp £29.99 978 1 4051 0932 1 1405109327 [Formula: see text].

    PubMed

    2012-10-10

    This long-awaited book has been written by expert specialist nurse contributors, mainly from Great Ormond Street Hospital, who offer clear and easy-to-follow practical information on a wide range of paediatric procedures.

  4. Anatomy and Physiology in Health and Illness - Text, Colouring Book and Workbook Package:Tenth edition Anne Waugh and Allison Grant Anatomy and Physiology in Health and Illness - Text, Colouring Book and Workbook Package:Tenth edition Elsevier 490pp plus 285pp £39.99 for the two 044310416 044310416 [Formula: see text].

    PubMed

    2006-10-11

    There are many useful anatomy and physiology texts on the market but few address adequately the needs of the undergraduate student of nursing science. However, this new edition by Ross and Wilson proves a valuable exception, appealing to those with little or no scientific background and more experienced students wishing to enhance their knowledge of biomedical principles.

  5. Simulation of structural response using a recurrent radial basis function network

    SciTech Connect

    Paez, T.L.

    1994-08-01

    System behaviors can be accurately simulated using artificial neural networks (ANNs), and one that performs well in simulation of structural response is the radial basis function network. A specific implementation of this is the connectionist normalized linear spline (CNLS) network, investigated in this study. A useful framework for ANN simulation of structural response is the recurrent network. This framework simulates the response of a structure one step at a time. It requires as inputs some measures of the excitation, and the response at previous times. On output, the recurrent ANN yields the response at some time in the future. This framework is practical to implement because every ANN requires training, and this is executed by showing the ANN examples of correct input/output behavior (exemplars), and requiring the ANN to simulate this behavior. In practical applications, hundreds or, perhaps, thousands, of exemplars are required for ANN training. The usual laboratory and non-neural numerical applications to be simulated by ANNs produce these amounts of information. Once the recurrent ANN is trained, it can be provided with excitation information, and used to propagate structural response, simulating the response it was trained to approximate. The structural characteristics, parameters in the CNLS network, and degree of training influence the accuracy of approximation. This investigation studies the accuracy of structural response simulation for a single-degree-of-freedom (SDF), nonlinear system excited by random vibration loading. The ANN used to simulate structural response is a recurrent CNLS network. We investigate the error in structural system simulation.

  6. Proteomic study of microsomal proteins reveals a key role for Arabidopsis annexin 1 in mediating heat stress-induced increase in intracellular calcium levels.

    PubMed

    Wang, Xu; Ma, Xiaolong; Wang, Hui; Li, Bingjie; Clark, Greg; Guo, Yi; Roux, Stan; Sun, Daye; Tang, Wenqiang

    2015-03-01

    To understand the early signaling steps in the response of plant cells to increased environmental temperature, 2-D difference gel electrophoresis was used to study the proteins in microsomes of Arabidopsis seedlings that are regulated early during heat stress. Using mass spectrometry, 19 microsomal proteins that showed an altered expression level within 5 min after heat treatment were identified. Among these proteins, annexin 1 (AtANN1) was one of those up-regulated rapidly after heat-shock treatment. Functional studies show loss-of-function mutants for AtANN1 and its close homolog AtANN2 were more sensitive to heat-shock treatment, whereas plants overexpressing AtANN1 showed more resistance to this treatment. Correspondingly, the heat-induced expression of heat-shock proteins and heat-shock factors is inhibited in ann1/ann2 double mutant, and the heat-activated increase in cytoplasmic calcium concentration ([Ca(2+)]cyt) is greatly impaired in the ann1 mutant and almost undetectable in ann1/ann2 double mutant. Taken together these results suggest that AtANN1 is important in regulating the heat-induced increase in [Ca(2+)]cyt and in the response of Arabidopsis seedlings to heat stress.

  7. On the inter-relations between artificial and physiological neural networks.

    PubMed

    Graupe, D; Vern, B

    2001-07-01

    This paper discusses the inter-relations between findings on the physiological neural network (PNN) and artificial neural networks (ANN). It discusses the interaction of progress in both PNN and ANN for the purpose of borrowing from ANN's mathematical understandings to establish pointers for further explorations to better understand the PNN, and also for the reciprocal transferring of knowledge from PNN findings to improve ANN schemes. Such improvements in ANN are essential for better handling the needs of the information technology (IT) explosion in dealing with huge data bases and where data often defy analysis and are incomplete and fuzzy. On the other hand, principles and elements of ANN designs that appear to be important and successful can serve as guides for identifying them in the PNN, to be subsequently confirmed by bioanalytical tests. Hence progress in PNN is obviously essential for progress in ANN, as is progress in ANN helpful in PNN modeling, though its laboratory confirmation is still a far lengthier process. We discuss certain specific ANN schemes with respect to the above inter-relations with PNN. We feel that the progress in both PNN and ANN research provides a major link between the thrust in information technology developments and the thrust in biological science research, which are most probably the two major focus areas of research at the dawn of the 21st century.

  8. Physicochemical properties and digestibility of hydrothermally treated waxy rice starch.

    PubMed

    Zeng, Feng; Ma, Fei; Kong, Fansheng; Gao, Qunyu; Yu, Shujuan

    2015-04-01

    Waxy rice starch was subjected to annealing (ANN) and heat-moisture treatment (HMT). These starches were also treated by a combination of ANN and HMT. The impact of single and dual modifications (ANN-HMT and HMT-ANN) on the molecular weight (M(w)), crystalline structure, thermal properties, and the digestibility were investigated. The relative crystallinity and short-range order on the granule surface increased on ANN, whereas decreased on HMT. All treated starches showed lower M(w) than that of the native starch. Gelatinization onset temperature, peak temperature and conclusion temperature increased for both single and dual treatments. Increased slowly digestible starch content was found on HMT and ANN-HMT. However, resistant starch levels decreased in all treated starches as compared with native starch. The results would imply that hydrothermal treatment induced structural changes in waxy rice starch significantly affected its digestibility.

  9. Spatial Treatment of the Slab-geometry Discrete Ordinates Equations Using Artificial Neural Networks

    SciTech Connect

    Brantley, P S

    2001-03-23

    An artificial neural network (ANN) method is developed for treating the spatial variable of the one-group slab-geometry discrete ordinates (S{sub N}) equations in a homogeneous medium with linearly anisotropic scattering. This ANN method takes advantage of the function approximation capability of multilayer ANNs. The discrete ordinates angular flux is approximated by a multilayer ANN with a single input representing the spatial variable x and N outputs representing the angular flux in each of the discrete ordinates angular directions. A global objective function is formulated which measures how accurately the output of the ANN approximates the solution of the discrete ordinates equations and boundary conditions at specified spatial points. Minimization of this objective function determines the appropriate values for the parameters of the ANN. Numerical results are presented demonstrating the accuracy of the method for both fixed source and incident angular flux problems.

  10. Forecasting S&P 500 index using artificial neural networks and design of experiments

    NASA Astrophysics Data System (ADS)

    Niaki, Seyed Taghi Akhavan; Hoseinzade, Saeid

    2013-02-01

    The main objective of this research is to forecast the daily direction of Standard & Poor's 500 (S&P 500) index using an artificial neural network (ANN). In order to select the most influential features (factors) of the proposed ANN that affect the daily direction of S&P 500 (the response), design of experiments are conducted to determine the statistically significant factors among 27 potential financial and economical variables along with a feature defined as the number of nodes of the ANN. The results of employing the proposed methodology show that the ANN that uses the most influential features is able to forecast the daily direction of S&P 500 significantly better than the traditional logit model. Furthermore, experimental results of employing the proposed ANN on the trades in a test period indicate that ANN could significantly improve the trading profit as compared with the buy-and-hold strategy.

  11. Artificial neural networks and prostate cancer--tools for diagnosis and management.

    PubMed

    Hu, Xinhai; Cammann, Henning; Meyer, Hellmuth-A; Miller, Kurt; Jung, Klaus; Stephan, Carsten

    2013-03-01

    Artificial neural networks (ANNs) are mathematical models that are based on biological neural networks and are composed of interconnected groups of artificial neurons. ANNs are used to map and predict outcomes in complex relationships between given 'inputs' and sought-after 'outputs' and can also be used find patterns in datasets. In medicine, ANN applications have been used in cancer diagnosis, staging and recurrence prediction since the mid-1990s, when an enormous effort was initiated, especially in prostate cancer detection. Modern ANNs can incorporate new biomarkers and imaging data to improve their predictive power and can offer a number of advantages as clinical decision making tools, such as easy handling of distribution-free input parameters. Most importantly, ANNs consider nonlinear relationships among input data that cannot always be recognized by conventional analyses. In the future, complex medical diagnostic and treatment decisions will be increasingly based on ANNs and other multivariate models.

  12. Sleep scoring using artificial neural networks.

    PubMed

    Ronzhina, Marina; Janoušek, Oto; Kolářová, Jana; Nováková, Marie; Honzík, Petr; Provazník, Ivo

    2012-06-01

    Rapid development of computer technologies leads to the intensive automation of many different processes traditionally performed by human experts. One of the spheres characterized by the introduction of new high intelligence technologies substituting analysis performed by humans is sleep scoring. This refers to the classification task and can be solved - next to other classification methods - by use of artificial neural networks (ANN). ANNs are parallel adaptive systems suitable for solving of non-linear problems. Using ANN for automatic sleep scoring is especially promising because of new ANN learning algorithms allowing faster classification without decreasing the performance. Both appropriate preparation of training data as well as selection of the ANN model make it possible to perform effective and correct recognizing of relevant sleep stages. Such an approach is highly topical, taking into consideration the fact that there is no automatic scorer utilizing ANN technology available at present.

  13. Neural network modeling of the light profile in a novel photobioreactor.

    PubMed

    Salazar-Peña, R; Alcaraz-González, V; González-Álvarez, V; Snell-Castro, R; Méndez-Acosta, H O

    2014-06-01

    An artificial neural network (ANN) was implemented to model the light profile pattern inside a photobioreactor (PBR) that uses a toroidal light arrangement. The PBR uses Tequila vinasses as culture medium and purple non-sulfur bacteria Rhodopseudomonas palustris as biocatalyzer. The performance of the ANN was tested for a number of conditions and compared to those obtained by using deterministic models. Both ANN and deterministic models were validated experimentally. In all cases, at low biomass concentration, model predictions yielded determination coefficients greater than 0.9. Nevertheless, ANN yielded the more accurate predictions of the light pattern, at both low and high biomass concentration, when the bioreactor radius, the depth, the rotational speed of the stirrer and the biomass concentration were incorporated in the ANN structure. In comparison, most of the deterministic models failed to correlate the empirical data at high biomass concentration. These results show the usefulness of ANNs in the modeling of the light profile pattern in photobioreactors.

  14. A CO2 Laser Weld Shape-Predicting Neural Network

    SciTech Connect

    Fuerschbach, P.W.; Knorovsky, G.A.

    1998-10-05

    We describe two artificial neural networks (ANN) which predict CO2 partial penetration laser welds on grade 304 stainless steel. Given the laser irradiance and travel speed, one ANN (direct) predicts the resulting weld's depth, width, overall shape, energy transfer efficiency, melting efficiency and porosity likelihood in the weld fusion zone. Given the weld size and shape, the second ANN (inverse) predicts the irradiance and travel speed necessary to provide such a weld. The ANNs used 3 nodal layers and perception-type neurons. For the first ANN, with 2 inputs and 17 outputs (12 for shape, and 5 for size, efficiencies and porosity predictions), 12 to 17 intermediate layer neurons were necessary, while for the second, with 14 inputs and 2 outputs, 25 were necessary. Besides their description, data interpretation and weld schedule development via the ANNs will be shown.

  15. Automated development of artificial neural networks for clinical purposes: Application for predicting the outcome of choledocholithiasis surgery.

    PubMed

    Vukicevic, Arso M; Stojadinovic, Miroslav; Radovic, Milos; Djordjevic, Milena; Cirkovic, Bojana Andjelkovic; Pejovic, Tomislav; Jovicic, Gordana; Filipovic, Nenad

    2016-08-01

    Among various expert systems (ES), Artificial Neural Network (ANN) has shown to be suitable for the diagnosis of concurrent common bile duct stones (CBDS) in patients undergoing elective cholecystectomy. However, their application in practice remains limited since the development of ANNs represents a slow process that requires additional expertize from potential users. The aim of this study was to propose an ES for automated development of ANNs and validate its performances on the problem of prediction of CBDS. Automated development of the ANN was achieved by applying the evolutionary assembling approach, which assumes optimal configuring of the ANN parameters by using Genetic algorithm. Automated selection of optimal features for the ANN training was performed using a Backward sequential feature selection algorithm. The assessment of the developed ANN included the evaluation of predictive ability and clinical utility. For these purposes, we collected data from 303 patients who underwent surgery in the period from 2008 to 2014. The results showed that the total bilirubin, alanine aminotransferase, common bile duct diameter, number of stones, size of the smallest calculus, biliary colic, acute cholecystitis and pancreatitis had the best prognostic value of CBDS. Compared to the alternative approaches, the ANN obtained by the proposed ES had better sensitivity and clinical utility, which are considered to be the most important for the particular problem. Besides the fact that it enabled the development of ANNs with better performances, the proposed ES significantly reduced the complexity of ANNs' development compared to previous studies that required manual selection of optimal features and/or ANN configuration. Therefore, it is concluded that the proposed ES represents a robust and user-friendly framework that, apart from the prediction of CBDS, could advance and simplify the application of ANNs for solving a wider range of problems.

  16. Using Artificial Neural Networks to Assess Changes in Microbial Communities

    SciTech Connect

    Brandt, C.C.; Macnaughton, S.; Palumbo, A.V.; Pfiffner, S.M.; Schryver, J.C.

    1999-04-19

    We evaluated artificial neural networks (ANNs) as a technique for assessing changes in soil microbial communities following exposure to metals. We analyzed signature lipid biomarker (SLB) data collected from two soil microcosm experiments using traditional statistical techniques and ANN. Two phases of data analysis were done; pattern recognition and prediction. In general, the ANNs were better able to detect patterns and relationships in the SLB data than were the traditional statistical techniques.

  17. Monitoring Cetaceans in the North Pacific

    DTIC Science & Technology

    2009-04-01

    whale calls in the North Pacific Ocean: Seasonal and geographical variation 1996-2002. (by: Mary Ann Daher , Kathleen M. Stafford, Joseph E. George...correlates. (by: Kathleen M. Stafford, Sue E. Moore, Mary Ann Daher , Joseph E. George, David Rodriguez, and Kimberly Amaral) PEER-REVIEWED...remotely-sensed environmental variables to compare with current and future datasets. In 2007, a collaborative project with Ms. Mary Ann Daher of

  18. U.S. Army Corps of Engineers: Building Overhead Costs into Projects and Customers’ Views on Information Provided

    DTIC Science & Technology

    2013-06-01

    contact Anne-Marie Fennell at (202) 512-3841 or fennella@gao.gov. Page i GAO-13-528 Army Corps Overhead Process Letter 1...listed in appendix III. Sincerely yours, Anne-Marie Fennell Director, Natural Resources and Environment Agency Comments and Our Evaluation...Acknowledgments Page 31 GAO-13-528 Army Corps Overhead Process Anne-Marie Fennell , (202) 512-3841 or fennella@gao.gov In addition to the

  19. Applying backpropagation neural network in the control of medullary reflex pattern

    NASA Astrophysics Data System (ADS)

    Dalcin, Bruno Luiz Galluzzi; Cruz, Frederico Alan de Oliveira; Cortez, Célia Martins; Passos, Emmanuel Lopes

    2015-12-01

    We introduced in an artificial neural network (ANN) values of the data matrix that was built with results from simulations performed with the model for the control circuit of spinal reflex presented by Dalcin et al. (2005). Standard multi-layered feed-forward backpropagation network was used to train the ANNs. Results showed that the backpropagation ANN architecture supported the specific classificatory requirements of the study.

  20. Proceedings of the Digital/Electronic Terrain Board Symposium Held in Wichita, Kansas on 5-6 October 1989

    DTIC Science & Technology

    1990-02-01

    Command (TACOM) Thmal Image Model MW Timothy J. Rogne Frederick G. Smith OptiMetrics, Inc. 2008 Hogback Road, Suite 6 Ann Arbor, Michigan 48105 Grant R...OptiMetrics, Inc. 2008 Hogback Road, Suite 6 Ann Arbor, Michigan 48105-9748 ABSTRACT The Multi-Mission Area Sensor (MMAS) Study is to provide...Inc. Martin Marietta 2008 Hogback Road #6 P. 0. Box 179 Ann Arbor, MI 48105 Denver, CO 80201 298 Simonds, Robert Velten, Vince Boeing Aerospace US Air

  1. Artificial Neural Networks in Spectrometry and Neutron Dosimetry

    SciTech Connect

    Vega-Carrillo, H. R.; Martinez-Blanco, M. R.; Ortiz-Rodriguez, J. M.; Hernandez-Davila, V. M.

    2010-12-07

    The ANN technology has been applied to unfold the neutron spectra of three neutron sources and to estimate their dosimetric features. To compare these results, neutron spectra were also unfolded with the BUNKIUT code. Both unfolding procedures were carried out using the count rates of a Bonner sphere spectrometer. The spectra unfolded with ANN result similar to those unfolded with the BUNKIUT code. The H*(10) values obtained with ANN agrees well with H*(10) values calculated with the BUNKIUT code.

  2. Effects of single and dual physical modifications on pinhão starch.

    PubMed

    Pinto, Vânia Zanella; Vanier, Nathan Levien; Deon, Vinicius Gonçalves; Moomand, Khalid; El Halal, Shanise Lisie Mello; Zavareze, Elessandra da Rosa; Lim, Loong-Tak; Dias, Alvaro Renato Guerra

    2015-11-15

    Pinhão starch was modified by annealing (ANN), heat-moisture (HMT) or sonication (SNT) treatments. The starch was also modified by a combination of these treatments (ANN-HMT, ANN-SNT, HMT-ANN, HMT-SNT, SNT-ANN, SNT-HMT). Whole starch and debranched starch fractions were analyzed by gel-permeation chromatography. Moreover, crystallinity, morphology, swelling power, solubility, pasting and gelatinization characteristics were evaluated. Native and single ANN and SNT-treated starches exhibited a CA-type crystalline structure while other modified starches showed an A-type structure. The relative crystallinity increased in ANN-treated starches and decreased in single HMT- and SNT-treated starches. The ANN, HMT and SNT did not provide visible cracks, notches or grooves to pinhão starch granule. SNT applied as second treatment was able to increase the peak viscosity of single ANN- and HMT-treated starches. HMT used alone or in dual modifications promoted the strongest effect on gelatinization temperatures and enthalpy.

  3. 75 FR 9426 - Maryland; Major Disaster and Related Determinations

    Federal Register 2010, 2011, 2012, 2013, 2014

    2010-03-02

    ... Baltimore, Caroline, Cecil, Harford, Howard, Kent, Montgomery, and Queen Anne's for emergency protective measures, (Category B) under the Public Assistance program. The counties of Baltimore, Caroline,...

  4. Applications of artificial neural networks in medical science.

    PubMed

    Patel, Jigneshkumar L; Goyal, Ramesh K

    2007-09-01

    Computer technology has been advanced tremendously and the interest has been increased for the potential use of 'Artificial Intelligence (AI)' in medicine and biological research. One of the most interesting and extensively studied branches of AI is the 'Artificial Neural Networks (ANNs)'. Basically, ANNs are the mathematical algorithms, generated by computers. ANNs learn from standard data and capture the knowledge contained in the data. Trained ANNs approach the functionality of small biological neural cluster in a very fundamental manner. They are the digitized model of biological brain and can detect complex nonlinear relationships between dependent as well as independent variables in a data where human brain may fail to detect. Nowadays, ANNs are widely used for medical applications in various disciplines of medicine especially in cardiology. ANNs have been extensively applied in diagnosis, electronic signal analysis, medical image analysis and radiology. ANNs have been used by many authors for modeling in medicine and clinical research. Applications of ANNs are increasing in pharmacoepidemiology and medical data mining. In this paper, authors have summarized various applications of ANNs in medical science.

  5. Pattern recognition in lithology classification: modeling using neural networks, self-organizing maps and genetic algorithms

    NASA Astrophysics Data System (ADS)

    Sahoo, Sasmita; Jha, Madan K.

    2017-03-01

    Effective characterization of lithology is vital for the conceptualization of complex aquifer systems, which is a prerequisite for the development of reliable groundwater-flow and contaminant-transport models. However, such information is often limited for most groundwater basins. This study explores the usefulness and potential of a hybrid soft-computing framework; a traditional artificial neural network with gradient descent-momentum training (ANN-GDM) and a traditional genetic algorithm (GA) based ANN (ANN-GA) approach were developed and compared with a novel hybrid self-organizing map (SOM) based ANN (SOM-ANN-GA) method for the prediction of lithology at a basin scale. This framework is demonstrated through a case study involving a complex multi-layered aquifer system in India, where well-log sites were clustered on the basis of sand-layer frequencies; within each cluster, subsurface layers were reclassified into four depth classes based on the maximum drilling depth. ANN models for each depth class were developed using each of the three approaches. Of the three, the hybrid SOM-ANN-GA models were able to recognize incomplete geologic pattern more reasonably, followed by ANN-GA and ANN-GDM models. It is concluded that the hybrid soft-computing framework can serve as a promising tool for characterizing lithology in groundwater basins with missing lithologic patterns.

  6. Artificial Neural Networks: an overview and their use in the analysis of the AMPHORA-3 dataset.

    PubMed

    Buscema, Paolo Massimo; Massini, Giulia; Maurelli, Guido

    2014-10-01

    The Artificial Adaptive Systems (AAS) are theories with which generative algebras are able to create artificial models simulating natural phenomenon. Artificial Neural Networks (ANNs) are the more diffused and best-known learning system models in the AAS. This article describes an overview of ANNs, noting its advantages and limitations for analyzing dynamic, complex, non-linear, multidimensional processes. An example of a specific ANN application to alcohol consumption in Spain, as part of the EU AMPHORA-3 project, during 1961-2006 is presented. Study's limitations are noted and future needed research using ANN methodologies are suggested.

  7. Robust Bioinformatics Recognition with VLSI Biochip Microsystem

    NASA Technical Reports Server (NTRS)

    Lue, Jaw-Chyng L.; Fang, Wai-Chi

    2006-01-01

    A microsystem architecture for real-time, on-site, robust bioinformatic patterns recognition and analysis has been proposed. This system is compatible with on-chip DNA analysis means such as polymerase chain reaction (PCR)amplification. A corresponding novel artificial neural network (ANN) learning algorithm using new sigmoid-logarithmic transfer function based on error backpropagation (EBP) algorithm is invented. Our results show the trained new ANN can recognize low fluorescence patterns better than the conventional sigmoidal ANN does. A differential logarithmic imaging chip is designed for calculating logarithm of relative intensities of fluorescence signals. The single-rail logarithmic circuit and a prototype ANN chip are designed, fabricated and characterized.

  8. A gentle introduction to artificial neural networks.

    PubMed

    Zhang, Zhongheng

    2016-10-01

    Artificial neural network (ANN) is a flexible and powerful machine learning technique. However, it is under utilized in clinical medicine because of its technical challenges. The article introduces some basic ideas behind ANN and shows how to build ANN using R in a step-by-step framework. In topology and function, ANN is in analogue to the human brain. There are input and output signals transmitting from input to output nodes. Input signals are weighted before reaching output nodes according to their respective importance. Then the combined signal is processed by activation function. I simulated a simple example to illustrate how to build a simple ANN model using nnet() function. This function allows for one hidden layer with varying number of units in that layer. The basic structure of ANN can be visualized with plug-in plot.nnet() function. The plot function is powerful that it allows for varieties of adjustment to the appearance of the neural networks. Prediction with ANN can be performed with predict() function, similar to that of conventional generalized linear models. Finally, the prediction power of ANN is examined using confusion matrix and average accuracy. It appears that ANN is slightly better than conventional linear model.

  9. 75 FR 69861 - Airworthiness Directives; Cessna Aircraft Company (Cessna) 172, 175, 177, 180, 182, 185, 206, 207...

    Federal Register 2010, 2011, 2012, 2013, 2014

    2010-11-16

    ... INFORMATION CONTACT: Ann Johnson, Aerospace Engineer, FAA, Wichita Aircraft Certification Office, 1801 Airport... Figure 1, in the address for the Wichita Manufacturing Inspection District Office, change 1804 to...

  10. Students in Austin, Texas Learn About Space Exploration and Science

    NASA Video Gallery

    From NASA's International Space Station Mission Control Center, Christie Sauers, Orion Cockpit Working Group Deputy, participates in a Digital Learning Network (DLN) event with students at the Ann ...

  11. Corrosion current density prediction in reinforced concrete by imperialist competitive algorithm.

    PubMed

    Sadowski, Lukasz; Nikoo, Mehdi

    2014-01-01

    This study attempted to predict corrosion current density in concrete using artificial neural networks (ANN) combined with imperialist competitive algorithm (ICA) used to optimize weights of ANN. For that reason, temperature, AC resistivity over the steel bar, AC resistivity remote from the steel bar, and the DC resistivity over the steel bar are considered as input parameters and corrosion current density as output parameter. The ICA-ANN model has been compared with the genetic algorithm to evaluate its accuracy in three phases of training, testing, and prediction. The results showed that the ICA-ANN model enjoys more ability, flexibility, and accuracy.

  12. 2 CFR Appendix Viii to Part 200 - Nonprofit Organizations Exempted From Subpart E-Cost Principles of Part 200

    Code of Federal Regulations, 2014 CFR

    2014-01-01

    .... Environmental Institute of Michigan, Ann Arbor, Michigan 11. Georgia Institute of Technology/Georgia Tech Applied Research Corporation/Georgia Tech Research Institute, Atlanta, Georgia 12. Hanford...

  13. Forest Productivity for Soft Calibration of Soil Parameters in Eco-hydrologic Modeling

    NASA Astrophysics Data System (ADS)

    Garcia, E.; Tague, C.

    2014-12-01

    Calibration of soil drainage parameters in hydrologic models is typically achieved using statistics based on streamflow. Models that couple hydrology with ecosystem carbon and nutrient cycling also calculate estimates of carbon and nutrient stores and fluxes. Particularly in water-limited environments, these estimates will be sensitive to soil drainage parameters. We investigate the use of estimates of annual net primary productivity (annNPP) as an additional data source for soil parameter calibration. We combine literature-based estimates of annNPP with streamflow statistics to calibrate for soil parameters in three Western U.S. watersheds using a coupled eco-hydrology model. We show that for all sites, estimates of annNPP vary significantly across soil parameters selected solely using streamflow calibration. In all watersheds streamflow metrics select soil parameters that yield a range of annNPP estimates that can exceed literature-derived bounds for annNPP by 58-77%. Only 1-10% of the original soil parameter sets met both annNPP and streamflow criteria - a substantial reduction when compared to the percentage of acceptable parameter sets selected using annNPP or streamflow separately. Similarly, streamflow performance varies substantially across soil parameters selected based solely on annNPP criteria. Results show that annNPP in combination with streamflow-based metrics can better constrain soil parameters, although the usefulness varies across watersheds.

  14. 77 FR 66793 - Senior Executive Service: Membership of Performance Review Board

    Federal Register 2010, 2011, 2012, 2013, 2014

    2012-11-07

    ...: Allen, Colleen Brause, Jon Cappozola, Christa Casella, Michael Cataldo, Ann Chan, Carol Crumbly... INFORMATION CONTACT: Melissa Jackson, 202-712-1781. Dated: November 1, 2012. Kevin Kozlowski, ELR...

  15. Development and application of coarse-grained models for lipids

    NASA Astrophysics Data System (ADS)

    Cui, Qiang

    2013-03-01

    I'll discuss a number of topics that represent our efforts in developing reliable molecular models for describing chemical and physical processes involving biomembranes. This is an exciting yet challenging research area because of the multiple length and time scales that are present in the relevant problems. Accordingly, we attempt to (1) understand the value and limitation of popular coarse-grained (CG) models for lipid membranes with either a particle or continuum representation; (2) develop new CG models that are appropriate for the particular problem of interest. As specific examples, I'll discuss (1) a comparison of atomistic, MARTINI (a particle based CG model) and continuum descriptions of a membrane fusion pore; (2) the development of a modified MARTINI model (BMW-MARTINI) that features a reliable description of membrane/water interfacial electrostatics and its application to cell-penetration peptides and membrane-bending proteins. Motivated specifically by the recent studies of Wong and co-workers, we compare the self-assembly behaviors of lipids with cationic peptides that include either Arg residues or a combination of Lys and hydrophobic residues; in particular, we attempt to reveal factors that stabilize the cubic ``double diamond'' Pn3m phase over the inverted hexagonal HII phase. For example, to explicitly test the importance of the bidentate hydrogen-bonding capability of Arg to the stabilization of negative Gaussian curvature, we also compare results using variants of the BMW-MARTINI model that treat the side chain of Arg with different levels of details. Collectively, the results suggest that both the bidentate feature of Arg and the overall electrostatic properties of cationic peptides are important to the self-assembly behavior of these peptides with lipids. The results are expected to have general implications to the mechanism of peptides and proteins that stimulate pore formation in biomembranes. Work in collaboration with Zhe Wu, Leili Zhang

  16. The Redesign of Teacher Education for the Twenty-First Century. International Perspectives on the Preparation of Educational Personnel. Selected Papers from the Thirtieth Anniversary World Assembly of the International Council of Education for Teaching (Washington, DC, July 11-15, 1983).

    ERIC Educational Resources Information Center

    Yff, Joost, Ed.

    This volume is organized according to themes chosen for the 30th Annual World Assembly of the International Council on Education for Teaching (ICET). A keynote speech by Anne Flowers discussed "Teacher Education for the Twenty-First Century." The first theme, "The Redesign of Teacher Education," was discussed through presentations by Anne Flowers,…

  17. Vertical and Horizontal Migrations Affect Local and Integrated Water-Column Scattering Strengths

    DTIC Science & Technology

    2007-09-30

    P.A. 2007. Habitat coupling by mid-latitude, subtidal, marine mysids: Import-subsidized omnivores . Oceanogr. Mar. Biol. — Ann. Rev. 45: 89-138...Habitat coupling by mid-latitude, subtidal, marine mysids: Import-subsidized omnivores . Oceanogr. Mar. Biol. — Ann. Rev. 45: 89-138. [PUBLISHED

  18. Prediction of Soil Deformation in Tunnelling Using Artificial Neural Networks

    PubMed Central

    Lai, Jinxing

    2016-01-01

    In the past few decades, as a new tool for analysis of the tough geotechnical problems, artificial neural networks (ANNs) have been successfully applied to address a number of engineering problems, including deformation due to tunnelling in various types of rock mass. Unlike the classical regression methods in which a certain form for the approximation function must be presumed, ANNs do not require the complex constitutive models. Additionally, it is traced that the ANN prediction system is one of the most effective ways to predict the rock mass deformation. Furthermore, it could be envisaged that ANNs would be more feasible for the dynamic prediction of displacements in tunnelling in the future, especially if ANN models are combined with other research methods. In this paper, we summarized the state-of-the-art and future research challenges of ANNs on the tunnel deformation prediction. And the application cases as well as the improvement of ANN models were also presented. The presented ANN models can serve as a benchmark for effective prediction of the tunnel deformation with characters of nonlinearity, high parallelism, fault tolerance, learning, and generalization capability. PMID:26819587

  19. Yemen: Comparative Insurgency and Counterinsurgency

    DTIC Science & Technology

    2015-03-01

    COMPARATIVE INSURGENCY AND COUNTERINSURGENCY by Ryan Johnson March 2015 Thesis Advisor: Anne Marie Baylouny Second Reader: Thomas H. Johnson...AFRICA) from the NAVALPOSTGRADUATESCHOOL March 2015 Ryan Jolmson Approved by: Anne Mru·ie Baylouny Thesis Advisor Thomas H. Jolmson Second Reader...Framework ........................................................50  Figure 2.  Second Military Organizational Framework

  20. The Differential Impact of Women’s Participation in the Arab Spring

    DTIC Science & Technology

    2013-09-01

    IMPACT OF WOMEN’S PARITICIPATION IN THE ARAB SPRING by Sasha J. Kuhlow September 2013 Thesis Advisor: Anne Marie Baylouny Second Reader...Approved by: Anne Marie Baylouny Thesis Advisor Tristan J. Mabry Second Reader Mohammed M. Hafez Chair, Department of...of collective action. In cases where the sociocultural barriers of Middle Eastern culture may prevent women from participating publicly in social

  1. A New Artificial Neural Network Approach in Solving Inverse Kinematics of Robotic Arm (Denso VP6242)

    PubMed Central

    Dülger, L. Canan; Kapucu, Sadettin

    2016-01-01

    This paper presents a novel inverse kinematics solution for robotic arm based on artificial neural network (ANN) architecture. The motion of robotic arm is controlled by the kinematics of ANN. A new artificial neural network approach for inverse kinematics is proposed. The novelty of the proposed ANN is the inclusion of the feedback of current joint angles configuration of robotic arm as well as the desired position and orientation in the input pattern of neural network, while the traditional ANN has only the desired position and orientation of the end effector in the input pattern of neural network. In this paper, a six DOF Denso robotic arm with a gripper is controlled by ANN. The comprehensive experimental results proved the applicability and the efficiency of the proposed approach in robotic motion control. The inclusion of current configuration of joint angles in ANN significantly increased the accuracy of ANN estimation of the joint angles output. The new controller design has advantages over the existing techniques for minimizing the position error in unconventional tasks and increasing the accuracy of ANN in estimation of robot's joint angles. PMID:27610129

  2. Support and Seminorm Integrability Theorems for r-Semistable Probability Measures on LCTVS.

    DTIC Science & Technology

    1979-01-01

    lois indifinitment divisibles dans les espaces vectoriels localment convexes, Ann. Inst. Henri Poincare *, 13(1977), 27 - 43. [16] A. Tortrat, Second...compliment sur le support des lois ind~finiment divisibles, Ann. Inst. Henri Poincare , 14(1978), 349 - 354. (17] J. Yaun and T. Liang, On the supports

  3. On Your Mark! Get Set! Go!

    ERIC Educational Resources Information Center

    Rowland, Veronica

    2006-01-01

    This article describes how second- and third-grade students joined their teacher, Mary Ann McTiernan, a marathon runner from Cape Town, South Africa, in a one-mile run every Thursday morning while she was training. Mary Ann's students had been asking, "Where do you run?" "How far do you go?" "How fast can you run?"…

  4. Fast Spin Rotations by Optically Controlled Geometric Phases in a Charge-Tunable InAs Quantum Dot

    DTIC Science & Technology

    2010-04-23

    Truex, Xiaodong Xu, Bo Sun University of Michigan - Ann Arbor Regents of the University of Michigan 3003 S. State St Ann Arbor, MI 48109 -1274 REPORT...Truex,1 Xiaodong Xu,1 Bo Sun,1 D. G. Steel,1,* A. S. Bracker,2 D. Gammon,2 and L. J. Sham3 1The H.M. Randall Laboratory of Physics, The University of

  5. 30 CFR 941.700 - South Dakota Federal program.

    Code of Federal Regulations, 2011 CFR

    2011-07-01

    ... pollution control, S. D. Comp. Laws Ann. Chap. 34A-1. (7) Water pollution control, S. D. Comp. Laws Ann... use in exploration within one-half mile of a flowing water well or a domestic water well without the owner's permission (section 27), and the requirement to cap, plug, and seal all exploration test...

  6. 30 CFR 941.700 - South Dakota Federal program.

    Code of Federal Regulations, 2010 CFR

    2010-07-01

    ... pollution control, S. D. Comp. Laws Ann. Chap. 34A-1. (7) Water pollution control, S. D. Comp. Laws Ann... use in exploration within one-half mile of a flowing water well or a domestic water well without the owner's permission (section 27), and the requirement to cap, plug, and seal all exploration test...

  7. 30 CFR 941.700 - South Dakota Federal program.

    Code of Federal Regulations, 2012 CFR

    2012-07-01

    ... pollution control, S. D. Comp. Laws Ann. Chap. 34A-1. (7) Water pollution control, S. D. Comp. Laws Ann... use in exploration within one-half mile of a flowing water well or a domestic water well without the owner's permission (section 27), and the requirement to cap, plug, and seal all exploration test...

  8. The superior fault tolerance of artificial neural network training with a fault/noise injection-based genetic algorithm.

    PubMed

    Su, Feng; Yuan, Peijiang; Wang, Yangzhen; Zhang, Chen

    2016-10-01

    Artificial neural networks (ANNs) are powerful computational tools that are designed to replicate the human brain and adopted to solve a variety of problems in many different fields. Fault tolerance (FT), an important property of ANNs, ensures their reliability when significant portions of a network are lost. In this paper, a fault/noise injection-based (FIB) genetic algorithm (GA) is proposed to construct fault-tolerant ANNs. The FT performance of an FIB-GA was compared with that of a common genetic algorithm, the back-propagation algorithm, and the modification of weights algorithm. The FIB-GA showed a slower fitting speed when solving the exclusive OR (XOR) problem and the overlapping classification problem, but it significantly reduced the errors in cases of single or multiple faults in ANN weights or nodes. Further analysis revealed that the fit weights showed no correlation with the fitting errors in the ANNs constructed with the FIB-GA, suggesting a relatively even distribution of the various fitting parameters. In contrast, the output weights in the training of ANNs implemented with the use the other three algorithms demonstrated a positive correlation with the errors. Our findings therefore indicate that a combination of the fault/noise injection-based method and a GA is capable of introducing FT to ANNs and imply that the distributed ANNs demonstrate superior FT performance.

  9. Using support vector machines to develop pedotransfer functions for water retention of soils in Poland

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Pedotransfer functions (PTF), which estimate soil hydraulic parameters from better known soil properties, are the important data source for hydrologic modeling. Recently artificial neural networks (ANNs) became the tool of choice in PTF development. Training of ANN consists of finding of minimum of ...

  10. A New Artificial Neural Network Approach in Solving Inverse Kinematics of Robotic Arm (Denso VP6242).

    PubMed

    Almusawi, Ahmed R J; Dülger, L Canan; Kapucu, Sadettin

    2016-01-01

    This paper presents a novel inverse kinematics solution for robotic arm based on artificial neural network (ANN) architecture. The motion of robotic arm is controlled by the kinematics of ANN. A new artificial neural network approach for inverse kinematics is proposed. The novelty of the proposed ANN is the inclusion of the feedback of current joint angles configuration of robotic arm as well as the desired position and orientation in the input pattern of neural network, while the traditional ANN has only the desired position and orientation of the end effector in the input pattern of neural network. In this paper, a six DOF Denso robotic arm with a gripper is controlled by ANN. The comprehensive experimental results proved the applicability and the efficiency of the proposed approach in robotic motion control. The inclusion of current configuration of joint angles in ANN significantly increased the accuracy of ANN estimation of the joint angles output. The new controller design has advantages over the existing techniques for minimizing the position error in unconventional tasks and increasing the accuracy of ANN in estimation of robot's joint angles.

  11. Using support vector machines to develop pedotransfer functions for water retention of soils in Poland

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Pedotransfer functions (PTF), which estimate soil hydraulic parameters from better known soil properties, are the important data source for hydrologic modeling. Recently artificial neural networks (ANNs) became the tool of choice in PTF development. Training of ANN can be viewed as finding the minim...

  12. Inventing Music Education Games

    ERIC Educational Resources Information Center

    Ghere, David; Amram, Fred M. B.

    2007-01-01

    The first British patent describing an educational game designed for musical "amusement and instruction" was granted in 1801 to Ann Young of Edinburgh, Scotland. The authors' discovery of Young's game box has prompted an examination of the nature and purpose of the six games she designed. Ann Young's patent is discussed in the context of…

  13. Summary of the Spring 1978 Conference of the National Consortium on Testing; June 5, 1978.

    ERIC Educational Resources Information Center

    Haney, Walt

    Remarks made at several panel discussions are summarized in this narrative report. The discussion topics and speakers include: (1) public education and testing--Tom Tomlinson, Ann Kahn, Herb Mack, and Jean Nazzaro, with remarks by Patricia Albjerg Graham; (2) standards regarding testing--Walt Haney, Barbara Lerner, Ann Cook, Willo White, and Bob…

  14. Online Learning. Special Report.

    ERIC Educational Resources Information Center

    Training, 1998

    1998-01-01

    Special section includes "World Wide Weeds" (Ann M. Bauer), about trainers as webmasters; "Get the Picture?" (Frank Jossi)--the role of digital video in computer-based training; and "The Reluctant Executive" (Anne K. Fredrickson), how to get administrators into the information age. (JOW)

  15. Medical Surveillance Monthly Report (MSMR). Volume 19, Number 3, March 2012

    DTIC Science & Technology

    2012-03-01

    Engler, MD, Frances Allan-Martinez, FNP , Ann Morse, FNP , Laurie Duran, ANP P A G E 8 Predictive value of surveillance case definitions of Guillain...Members Following Smallpox Vaccination Jay R. Montgomery, MD; COL Renata Engler, MD, Frances Allan-Martinez, FNP , Ann Morse, FNP , Laurie Duran, ANP

  16. Artificial Neural Networks and Instructional Technology.

    ERIC Educational Resources Information Center

    Carlson, Patricia A.

    1991-01-01

    Artificial neural networks (ANN), part of artificial intelligence, are discussed. Such networks are fed sample cases (training sets), learn how to recognize patterns in the sample data, and use this experience in handling new cases. Two cognitive roles for ANNs (intelligent filters and spreading, associative memories) are examined. Prototypes…

  17. Artificial Neural Networks in Policy Research: A Current Assessment.

    ERIC Educational Resources Information Center

    Woelfel, Joseph

    1993-01-01

    Suggests that artificial neural networks (ANNs) exhibit properties that promise usefulness for policy researchers. Notes that ANNs have found extensive use in areas once reserved for multivariate statistical programs such as regression and multiple classification analysis and are developing an extensive community of advocates for processing text…

  18. Using Artificial Neural Networks in Educational Research: Some Comparisons with Linear Statistical Models.

    ERIC Educational Resources Information Center

    Everson, Howard T.; And Others

    This paper explores the feasibility of neural computing methods such as artificial neural networks (ANNs) and abductory induction mechanisms (AIM) for use in educational measurement. ANNs and AIMS methods are contrasted with more traditional statistical techniques, such as multiple regression and discriminant function analyses, for making…

  19. Curriculum Assessment Using Artificial Neural Network and Support Vector Machine Modeling Approaches: A Case Study. IR Applications. Volume 29

    ERIC Educational Resources Information Center

    Chen, Chau-Kuang

    2010-01-01

    Artificial Neural Network (ANN) and Support Vector Machine (SVM) approaches have been on the cutting edge of science and technology for pattern recognition and data classification. In the ANN model, classification accuracy can be achieved by using the feed-forward of inputs, back-propagation of errors, and the adjustment of connection weights. In…

  20. Modeling force-velocity relation in skeletal muscle isotonic contraction using an artificial neural network.

    PubMed

    Dariani, Sharareh; Keshavarz, Mansoor; Parviz, Mohsen; Raoufy, Mohammad Reza; Gharibzadeh, Shahriar

    2007-01-01

    The aim of this study is to design an artificial neural network (ANN) to model force-velocity relation in skeletal muscle isotonic contraction. We obtained the data set, including physiological and morphometric parameters, by myography and morphometric measurements on frog gastrocnemius muscle. Then, we designed a multilayer perceptron ANN, the inputs of which are muscle volume, muscle optimum length, tendon length, preload, and afterload. The output of the ANN is contraction velocity. The experimental data were divided randomly into two parts. The first part was used to train the ANN. In order to validate the model, the second part of experimental data, which was not used in training, was employed to the ANN and then, its output was compared with Hill model and the experimental data. The behavior of ANN in high forces was more similar to experimental data, but in low forces the Hill model had better results. Furthermore, extrapolation of ANN performance showed that our model is more or less able to simulate eccentric contraction. Our results indicate that ANNs represent a powerful tool to capture some essential features of muscle isotonic contraction.

  1. Statistical Classification for Cognitive Diagnostic Assessment: An Artificial Neural Network Approach

    ERIC Educational Resources Information Center

    Cui, Ying; Gierl, Mark; Guo, Qi

    2016-01-01

    The purpose of the current investigation was to describe how the artificial neural networks (ANNs) can be used to interpret student performance on cognitive diagnostic assessments (CDAs) and evaluate the performances of ANNs using simulation results. CDAs are designed to measure student performance on problem-solving tasks and provide useful…

  2. Automatic identification of human helminth eggs on microscopic fecal specimens using digital image processing and an artificial neural network.

    PubMed

    Yang, Y S; Park, D K; Kim, H C; Choi, M H; Chai, J Y

    2001-06-01

    In order to automate routine fecal examination for parasitic diseases, we propose in this study a computer processing algorithm using digital image processing techniques and an artificial neural network (ANN) classifier. The morphometric characteristics of eggs of human parasites in fecal specimens were extracted from microscopic images through digital image processing. An ANN then identified the parasite species based on those characteristics. We selected four morphometric features based on three morphological characteristics representing shape, shell smoothness, and size. A total of 82 microscopic images containing seven common human helminth eggs were used. The first stage (ANN-1) of the proposed ANN classification system isolated eggs from confusing artifacts. The second stage (ANN-2) classified eggs by species. The performance of ANN was evaluated by the tenfold cross-validation method to obviate the dependency on the selection of training samples. Cross-validation results showed 86.1% average correct classification ratio for ANN-1 and 90.3% for ANN-2 with small variances of 46.0 and 39.0, respectively. The algorithm developed will be an essential part of a completely automated fecal examination system.

  3. A self-adaptive genetic algorithm-artificial neural network algorithm with leave-one-out cross validation for descriptor selection in QSAR study.

    PubMed

    Wu, Jingheng; Mei, Juan; Wen, Sixiang; Liao, Siyan; Chen, Jincan; Shen, Yong

    2010-07-30

    Based on the quantitative structure-activity relationships (QSARs) models developed by artificial neural networks (ANNs), genetic algorithm (GA) was used in the variable-selection approach with molecule descriptors and helped to improve the back-propagation training algorithm as well. The cross validation techniques of leave-one-out investigated the validity of the generated ANN model and preferable variable combinations derived in the GAs. A self-adaptive GA-ANN model was successfully established by using a new estimate function for avoiding over-fitting phenomenon in ANN training. Compared with the variables selected in two recent QSAR studies that were based on stepwise multiple linear regression (MLR) models, the variables selected in self-adaptive GA-ANN model are superior in constructing ANN model, as they revealed a higher cross validation (CV) coefficient (Q(2)) and a lower root mean square deviation both in the established model and biological activity prediction. The introduced methods for validation, including leave-multiple-out, Y-randomization, and external validation, proved the superiority of the established GA-ANN models over MLR models in both stability and predictive power. Self-adaptive GA-ANN showed us a prospect of improving QSAR model.

  4. 40 CFR Appendix to Part 243 - Recommended Bibliography

    Code of Federal Regulations, 2011 CFR

    2011-07-01

    ... refuse collection equipment. New York. The American National Standards Institute. 2. Decision-Makers..., as PB 213 511). 5. National Sanitation Foundation standard no. 31 for polyethylene refuse bags. Ann... no. 32 for paper refuse sacks. Ann Arbor, The National Sanitation Foundation, Nov. 13, 1970. 6 p....

  5. 40 CFR Appendix to Part 243 - Recommended Bibliography

    Code of Federal Regulations, 2013 CFR

    2013-07-01

    ... refuse collection equipment. New York. The American National Standards Institute. 2. Decision-Makers..., as PB 213 511). 5. National Sanitation Foundation standard no. 31 for polyethylene refuse bags. Ann... no. 32 for paper refuse sacks. Ann Arbor, The National Sanitation Foundation, Nov. 13, 1970. 6 p....

  6. 40 CFR Appendix to Part 243 - Recommended Bibliography

    Code of Federal Regulations, 2012 CFR

    2012-07-01

    ... refuse collection equipment. New York. The American National Standards Institute. 2. Decision-Makers..., as PB 213 511). 5. National Sanitation Foundation standard no. 31 for polyethylene refuse bags. Ann... no. 32 for paper refuse sacks. Ann Arbor, The National Sanitation Foundation, Nov. 13, 1970. 6 p....

  7. 40 CFR Appendix to Part 243 - Recommended Bibliography

    Code of Federal Regulations, 2014 CFR

    2014-07-01

    ... refuse collection equipment. New York. The American National Standards Institute. 2. Decision-Makers..., as PB 213 511). 5. National Sanitation Foundation standard no. 31 for polyethylene refuse bags. Ann... no. 32 for paper refuse sacks. Ann Arbor, The National Sanitation Foundation, Nov. 13, 1970. 6 p....

  8. 40 CFR Appendix to Part 243 - Recommended Bibliography

    Code of Federal Regulations, 2010 CFR

    2010-07-01

    ... refuse collection equipment. New York. The American National Standards Institute. 2. Decision-Makers..., as PB 213 511). 5. National Sanitation Foundation standard no. 31 for polyethylene refuse bags. Ann... no. 32 for paper refuse sacks. Ann Arbor, The National Sanitation Foundation, Nov. 13, 1970. 6 p....

  9. Tissue Engineering and Regenerative Medicine

    DTIC Science & Technology

    2006-11-01

    Mark Furth Mark Van Dyke Shay Soker Steve Hodges Weixin Zhao YuanYuan Zhang Aaron Goldstein Alan Farney Ann Gleeson Ann Immekus Ben Watts Callie Crider...Myers Robyn Shaffer Saami Yazdani Samira Neshat Sang Jin Lee Sergio Rodriguez Shirin Zare So-Young Chun Steve Schultz Tamer AbouShawreb Tao Xu Ted Kincaid

  10. Parameters for the Evaluation of the Fate, Transport, and Environmental Impacts of Chemical Agents in Marine Environments

    DTIC Science & Technology

    2007-07-01

    ein Beitrag zur Kenntniss des Schwefels und seiner ringförmigen Verbindungen, Justus Liebigs Ann. Chem., 1908, 362, 133-173. 36 Paterno, E...Bloemer, H., Einige beiträgr zur kenntnis der organischen arsenverbindung. II. Arsentrichlorid und acetylen, Justus Liebigs Ann. Chem., 1923, 431

  11. Development of Elastomeric Polypeptide Biomaterials

    DTIC Science & Technology

    1988-05-25

    Vieland. Th., Hcinke. B. and Vogeler. J.. Justus Liebigs Ann. Cheni.. 655(1961) 189. 403 Inth American Peptide Symposium Washington Universit. In...relyophilized. 1915, 25, 403-413. (26) Wieland, Th.; Heinke. B.; Vogeler, J. Justus Liebiqs Ann. Chem. Dielectric Relaxation Measurements. The dielectric

  12. AFRRI (Armed Forces Radiobiology Research Institute) Reports, October, November, December 1986

    DTIC Science & Technology

    1986-12-01

    55,492 Beer, M., Stern, S., Carmalt, D. & Mohlhenrich, K. H. (1966) Biochemistry 5, 2283-2288 Behrend, R. & Roosen, O. (1889) Justus Liebigs Ann. Chem...227, 375-381 Chang, C. H., Ford, H. & Behrman, E. J. (1981) Inorg. Chim. Acta 55, 77-80 Criegee, R. (1936) Justus Liebigs Ann. Chem. 522, 75-93

  13. Development of Elastomeric Polypeptide Biomaterials

    DTIC Science & Technology

    1989-07-01

    Wieland, T., Heinke, B., and Vogeler, K. (1962). Justus Liebigs Ann. Chem. 655, 189-194. Yeh, H., Ornstein-Goldstein, N., Indik, Z., Sheppard, P...TssueAnalogues, (Williams, D.F., ed.) CRC Press, Inc., Boca Raton, Florida 89 (1985). 14. Weiland, Th., Heinke, B. and Vogeler, J., Justus Liebiqs Ann

  14. The House That Putin Built

    DTIC Science & Technology

    2005-06-01

    BUILT by Claudine Caluori June 2005 Thesis Co-Advisors: Anne Clunan Robert Looney THIS...Claudine Caluori Approved by: Anne Clunan Thesis Co-Advisor Robert Looney Thesis Co-Advisor Douglas Porch Chairman, Department of...Remington, Politics in Russia, (New York: Pearson Education, Inc. 2004), 49. 3 Robert D. English, Russia and the Idea of the West: Chapter 6: The New

  15. Dover Schools' Unintelligent Design

    ERIC Educational Resources Information Center

    Barlow, Dudley

    2006-01-01

    The author of this article was surprised to read in the December 21, 2005, Ann Arbor News that "The Ann Arbor-based Thomas More Law Center, which represented the Dover [Pennsylvania] School District in its federal case for the teaching of intelligent design, has threatened to sue Gull Lake [Michigan] Community Schools over its policy that…

  16. A Novel Method of Case Representation and Retrieval in CBR for E-Learning

    ERIC Educational Resources Information Center

    Khamparia, Aditya; Pandey, Babita

    2017-01-01

    In this paper we have discussed a novel method which has been developed for representation and retrieval of cases in case based reasoning (CBR) as a part of e-learning system which is based on various student features. In this approach we have integrated Artificial Neural Network (ANN) with Data mining (DM) and CBR. ANN is used to find the…

  17. Educational Reform and Vocational Education.

    ERIC Educational Resources Information Center

    Milne, Ann M., Ed.

    This document contains six studies that were commissioned for the National Assessment of Vocational Education. "Introduction" (Ann M. Milne) provides an overview of the reforms of the 1980s. "The Impact of Educational Reform on Vocational Education" (Marion Asche, Donald E. Elson, Ann Echols, Arthur Williams) examines primary…

  18. 76 FR 54978 - Special Immigrant Juvenile Petitions

    Federal Register 2010, 2011, 2012, 2013, 2014

    2011-09-06

    ... the physical, emotional or mental condition of the child requires.'' See Conn. Gen. Stat. Ann. section... neglected. See Conn. Gen. Stat. Ann. section 46b- 120(8),(9); 121(a). Petitioners are encouraged to include... directives issued by USCIS. This rule would establish clear guidance for petitioners and applicants...

  19. [Artificial neural networks for decision making in urologic oncology].

    PubMed

    Remzi, M; Djavan, B

    2007-06-01

    This chapter presents a detailed introduction regarding Artificial Neural Networks (ANNs) and their contribution to modern Urologic Oncology. It includes a description of ANNs methodology and points out the differences between Artifical Intelligence and traditional statistic models in terms of usefulness for patients and clinicians, and its advantages over current statistical analysis.

  20. Connectionist Modelling and Education.

    ERIC Educational Resources Information Center

    Evers, Colin W.

    2000-01-01

    Provides a detailed, technical introduction to the state of cognitive science research, in particular the rise of the "new cognitive science," especially artificial neural net (ANN) models. Explains one influential ANN model and describes diverse applications and their implications for education. (EV)