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Sample records for learning combination inventory

  1. Validity and Reliability of Revised Inventory of Learning Processes.

    Science.gov (United States)

    Gadzella, B. M.; And Others

    The Inventory of Learning Processes (ILP) was developed by Schmeck, Ribich, and Ramanaiah in 1977 as a self-report inventory to assess learning style through a behavioral-oriented approach. The ILP was revised by Schmeck in 1983. The Revised ILP contains six scales: (1) Deep Processing; (2) Elaborative Processing; (3) Shallow Processing; (4)…

  2. Feeding the ELT Students' Needs Through Kolb's Learning Styles Inventory

    Directory of Open Access Journals (Sweden)

    Ayfer SU BERGİL

    2017-12-01

    Full Text Available Contrary to learning styles seem the same as what abilities refer, they are related to them in the sense that they decipher how individuals desire to use their capabilities. There have been diverse learning styles theories intent to explain the individual differences on account of the acceleration and the amount of absorbed knowledge. Learning styles have been defined under the notions of cognitive, affective and physiological attributes that serve as nearly strong indicators of how learners distinguish, combine, and reciprocate to the learning phenomena which gains importance and provide basis for language education process as well. Thus, this study aims to determine the learning styles of English language teaching (ELT students studying at Amasya University, Faculty of Education in 2017-2018 academic year. The participants of the study consist of totally 109 out of 122 from 1st, 2nd, 3rd and 4th grade students of English Language Teaching Department. The data collection instrument was Kolb’s Learning Style Inventory including four sets of work labeled as Concrete Experience, Reflective Observation, Abstract Conceptualization, and Active Experimentation and the students were expected to rank order the 12 items listed for each category via assigning a 4 to the word which best characterizes their learning style, a 3 to the next best, a 2 to the next, and a 1 to the least characteristic word. By this way, ELT students’ dominant learning styles which refer to their learning profiles has been specified descriptively. Furthermore, the learning styles of ELT students has been interconnected with the content of the courses they need to take during their teacher education process and suggestions for the members of ELT departments has been provided based on the findings of these learning styles.

  3. Dynamic pricing and learning with finite inventories

    NARCIS (Netherlands)

    den Boer, A.V.; Zwart, Bert

    2013-01-01

    We study a dynamic pricing problem with finite inventory and parametric uncertainty on the demand distribution. Products are sold during selling seasons of finite length, and inventory that is unsold at the end of a selling season, perishes. The goal of the seller is to determine a pricing strategy

  4. Dynamic pricing and learning with finite inventories

    NARCIS (Netherlands)

    den Boer, A.V.; Zwart, Bert

    We study a dynamic pricing problem with finite inventory and parametric uncertainty on the demand distribution. Products are sold during selling seasons of finite length, and inventory that is unsold at the end of a selling season perishes. The goal of the seller is to determine a pricing strategy

  5. Dynamic Pricing and Learning with Finite Inventories

    NARCIS (Netherlands)

    A.P. Zwart (Bert); A.V. den Boer (Arnoud)

    2015-01-01

    htmlabstractWe study a dynamic pricing problem with finite inventory and parametric uncertainty on the demand distribution. Products are sold during selling seasons of finite length, and inventory that is unsold at the end of a selling season perishes. The goal of the seller is to determine a

  6. Dynamic pricing and learning with finite inventories

    NARCIS (Netherlands)

    Boer, den A.V.; Zwart, B.

    2015-01-01

    We study a dynamic pricing problem with finite inventory and parametric uncertainty on the demand distribution. Products are sold during selling seasons of finite length, and inventory that is unsold at the end of a selling season perishes. The goal of the seller is to determine a pricing strategy

  7. Dimensions of Mobile Augmented Reality for Learning: A First Inventory

    OpenAIRE

    Specht, Marcus; Ternier, Stefaan; Greller, Wolfgang

    2011-01-01

    Specht, M., Ternier, S., & Greller, W. (2011). Dimensions of Mobile Augmented Reality for Learning: A First Inventory. Journal of the Research for Educational Technology (RCET), 7(1), 117-127. Spring 2011.

  8. Dynamic Pricing and Learning with Finite Inventories

    OpenAIRE

    Zwart, Bert; Boer, Arnoud

    2015-01-01

    We study a dynamic pricing problem with finite inventory and parametric uncertainty on the demand distribution. Products are sold during selling seasons of finite length, and inventory that is unsold at the end of a selling season, perishes. The goal of the seller is to determine a pricing strategy that maximizes the expected revenue. Inference on the unknown parameters is made by maximum likelihood estimation. We propose a pricing strategy for this problem, and show that the Regret - which i...

  9. Assessing Experiential Learning Styles: A Methodological Reconstruction and Validation of the Kolb Learning Style Inventory

    Science.gov (United States)

    Manolis, Chris; Burns, David J.; Assudani, Rashmi; Chinta, Ravi

    2013-01-01

    To understand experiential learning, many have reiterated the need to be able to identify students' learning styles. Kolb's Learning Style Model is the most widely accepted learning style model and has received a substantial amount of empirical support. Kolb's Learning Style Inventory (LSI), although one of the most widely utilized instruments to…

  10. Developing Learning Style Inventory for Effective Instructional Design

    Science.gov (United States)

    Guven, Bulent; Ozbek, Ozge

    2007-01-01

    In the process of education, instead of classifying students according to their insufficiency, teachers should try to get to know them and determine their cognitive, sensorial, and kinetic characteristics. This study on improving learning style inventory, which aims to help classroom teachers determine students' attributes in individualized…

  11. Combined Log Inventory and Process Simulation Models for the Planning and Control of Sawmill Operations

    Science.gov (United States)

    Guillermo A. Mendoza; Roger J. Meimban; Philip A. Araman; William G. Luppold

    1991-01-01

    A log inventory model and a real-time hardwood process simulation model were developed and combined into an integrated production planning and control system for hardwood sawmills. The log inventory model was designed to monitor and periodically update the status of the logs in the log yard. The process simulation model was designed to estimate various sawmill...

  12. Evaluating learning and teaching using the Force Concept Inventory

    Science.gov (United States)

    Zitzewitz, Paul

    1997-04-01

    Teaching methods used in the calculus-based mechanics course for engineers and scientists (P150) at the University of Michigan-Dearborn were markedly changed in September, 1996. Lectures emphasize active learning with Mazur's ConcepTests, Sokoloff's Interactive Demonstrations, and Van Heuvelen's ALPS Kit worksheets. Students solve context-rich problems using Van Heuvelen's multiple representation format in cooperative groups in discussion sections. Labs were changed to use MBL emphasizing concepts and Experiment Problems to learn lab-based problem solving. Pre- and post-testing of 400 students with the Force Concept Inventory has demonstrated considerable success. The average increase in score has been 35-45methods as defined by Hake. The methods and results will be discussed. Detailed analyses of the FCI results will look at success in teaching specific concepts and the effect of student preparation in mathematics and high school physics.

  13. Pre-registration nursing student's quality of practice learning: Clinical learning environment inventory (actual) questionnaire.

    Science.gov (United States)

    Shivers, Eleanor; Hasson, Felicity; Slater, Paul

    2017-08-01

    Clinical learning is a vital component of nurse education and assessing student's experiences can provide useful insights for development. Whilst most research in this area has focused on the acute setting little attention has been given to all pre-registration nurses' experience across the clinical placements arenas. To examine of pre-registration nursing students (first, second and third year) assessment of their actual experiences of their most recent clinical learning clinical learning experience. A cross sectional survey involving a descriptive online anonymous questionnaire based on the clinical learning environment inventory tool. One higher education institution in the United Kingdom. Nursing students (n=147) enrolled in an undergraduate nursing degree. This questionnaire included demographic questions and the Clinical Learning Environment Inventory (CLEI) a 42 item tool measuring student's satisfaction with clinical placement. SPPS version 22 was employed to analyse data with descriptive and inferential statistics. Overall students were satisfied with their clinical learning experience across all placement areas. This was linked to the 6 constructs of the clinical learning environment inventory; personalization, innovation, individualization, task orientation, involvement, satisfaction. Significant differences in student experience were noted between age groups and student year but there was no difference noted between placement type, age and gender. Nursing students had a positive perception of their clinical learning experience, although there remains room for improvement. Enabling a greater understanding of students' perspective on the quality of clinical education is important for nursing education and future research. Copyright © 2017. Published by Elsevier Ltd.

  14. A New Formulation for the Combined Maritime Fleet Deployment and Inventory Management Problem

    OpenAIRE

    Dong, Bo; Bektas, Tolga; Chandra, Saurabh; Christiansen, Marielle; Fagerholt, Kjetil

    2017-01-01

    This paper addresses the fleet deployment problem and in particular the treatment of inventory in the maritime case. A new model based on time-continuous formulation for the combined maritime fleet deployment and inventory management problem in Roll-on Roll-off shipping is presented. Tests based on realistic data from the Ro-Ro business show that the model yields good solutions to the combined problem within reasonable time.

  15. Assessing learning styles of Saudi dental students using Kolb's Learning Style Inventory.

    Science.gov (United States)

    ALQahtani, Dalal A; Al-Gahtani, Sara M

    2014-06-01

    Experiential learning theory (ELT), a theory developed by David Kolb that considers experience to be very important for learning, classifies learners into four categories: Divergers, Assimilators, Convergers, and Accommodators. Kolb used his Learning Style Inventory (LSI) to validate ELT. Knowing the learning styles of students facilitates their understanding of themselves and thereby increases teaching efficiency. Few studies have been conducted that investigate learning preferences of students in the field of dentistry. This study was designed to distinguish learning styles among Saudi dental students and interns utilizing Kolb's LSI. The survey had a response rate of 62 percent (424 of 685 dental students), but surveys with incomplete answers or errors were excluded, resulting in 291 usable surveys (42 percent of the student population). The independent variables of this study were gender, clinical experience level, academic achievement as measured by grade point average (GPA), and specialty interest. The Diverging learning style was the dominant style among those in the sample. While the students preferred the Assimilating style during their early preclinical years, they preferred the Diverging style during their later clinical years. No associations were found between students' learning style and their gender, GPA, or specialty interest. Further research is needed to support these findings and demonstrate the impact of learning styles on dental students' learning.

  16. Learning about Severe Combined Immunodeficiency (SCID)

    Science.gov (United States)

    ... immunodeficiency From The Journal of Allergy and Clinical Immunology Learning About Severe Combined Immunodeficiency (SCID) What is ... immunodeficiency From The Journal of Allergy and Clinical Immunology Get Email Updates Privacy Copyright Contact Accessibility Plug- ...

  17. The Use of the Persian Translation of the Learning Transfer System Inventory in the Context of Agricultural Sustainability Learning in Iran

    Science.gov (United States)

    Zamani, Naser; Ataei, Pouria; Bates, Reid

    2016-01-01

    The Learning Transfer System Inventory considers 16 factors likely to influence the transfer of training to the workplace. This study uses the Persian translation of the inventory and applies it to agricultural sustainability learning in Iran. The aim is to examine the internal structure and predictive ability of the inventory as translated into…

  18. Perception of blended learning inventory (POBLI) - development and validation

    DEFF Research Database (Denmark)

    Lassesen, Berit; Rossen, Dorte Sidelmann; Stenalt, Maria Hvid

    and explore how the use of blended learning affects teachers’ approaches to teaching and students’ approaches to learning in higher education. So far, there has been relatively limited research on approaches to teaching in blended learning (González 2010; Lameras et al., 2012). In one study, Ellis et al....... In order to identify appropriate uses of blended learning in Higher Education and to enable the tailoring of teaching approaches to the different needs of an increasingly diverse student body, more knowledge is needed on how to integrate blended learning in educational settings and how best to address...... a new strategic focus on 'Educational IT’ with the purpose of strengthening teaching and learning through use of online interactions. Some of the major challenges in the development of this strategy include how to, identify rationales for using blended learning, stimulate pedagogical reflections...

  19. Third national inventory of nuclear liabilities - main findings, lessons learned

    International Nuclear Information System (INIS)

    Cantarella, Jacques; Roger, Brigitte

    2013-01-01

    The safe management of a country's radioactive substances in both the short and the long term implies a cost to its present society and necessitates financial resources to cover these costs. Once they are needed, these financial resources may prove to be insufficient or even completely lacking, leading to a nuclear liability. By virtue of article 9 of the Belgian law of 12 December 1997, the Belgian Government wishes to avoid the occurrence of such nuclear liabilities. This law charges ONDRAF/NIRAS, the Belgian Agency for Radioactive Waste and Enriched Fissile Materials with the mission to draw up a register of the localisation and the state of all nuclear sites and all sites containing radioactive substances, to estimate the costs of their decommissioning and remediation, to evaluate the existence and adequacy of the provisions for financing these future or current operations and to update the resulting inventory of nuclear liabilities on a five-yearly basis. This paper outlines the methodology put in place by ONDRAF/NIRAS to accomplish this assignment and highlights some of the results of this third inventory. It then focuses on the main recommendations ONDRAF/NIRAS made to the Belgian Government on the field of avoiding potential nuclear liabilities. (authors)

  20. Inventory of Innovative Learning Materials in Marine Science and Technology. UNESCO Reports in Marine Science 60.

    Science.gov (United States)

    Richards, Adrian F.; Richards, Efrosine A.

    The Inventory of Innovative Learning Materials in Marine Science and Technology includes 32 computer-, 148 video-, 16 film-, and 11 CD-ROM-based entries. They concern materials in biosciences (67), chemistry (5), geosciences (16), physics (23), technology (76) and other (20). This first, initial compilations is conceived as the basis for more…

  1. Comparison of Kalman filters in combining panel data from the annual inventory system of the South Korea National Forest Inventory

    Science.gov (United States)

    Tzeng Yih Lam; Raymond L. Czaplewski; Jong Su Yim; Kyeong Hak Lee; Sung Ho Kim; Rae Hyun Kim

    2013-01-01

    National Forest Inventories (NFIs) serve a primary purpose of providing crucial information for formulating national forest policy, environmental planning and reporting to international processes (Tomppo and others 2010). Pressure for timely and reliable forestry statistics urges countries to put a NFI in place or to consider alternative designs. Some countries, for...

  2. Further Validation of the Learning Alliance Inventory: The Roles of Working Alliance, Rapport, and Immediacy in Student Learning

    Science.gov (United States)

    Rogers, Daniel T.

    2015-01-01

    This study further examined the reliability and validity of the Learning Alliance Inventory (LAI), a self-report measure designed to assess the working alliance between a student and a teacher. The LAI was found to have good internal consistency and test--retest reliability, and it demonstrated the predicted convergence with measures of immediacy…

  3. Perception of Blended Learning Inventory (PoBLi)

    DEFF Research Database (Denmark)

    Lassesen, Berit; Stenalt, Maria Hvid; Rossen, Dorte Sidelmann

    -to-face med online læring (Blended Learning). I et studie fandt Ellis og kolleger (2006), at undervisere, der overvejende havde opfattelsen af, at de studerende lærte ved, at han/hun formidlede viden til dem, havde en simpel, fragmenteret opfattelse af potentialet ved BL. Derimod syntes en mere......) underviseres oplevelse af undervisningsmiljøet Resultater: Spørgeskema og resultaterne af de foreløbige analyser vil blive præsenteret og diskuteret. Perspektiver: PoBLi-projektet vil bidrage til den eksisterende forskning vedrørende rationalet for inddragelse af blended learning-formatet i...

  4. Reliability of the Cardiac Patients Learning Needs Inventory (CPLNI) for use in Portugal.

    Science.gov (United States)

    Galdeano, Luzia E; Furuya, Rejane K; Rodrigues, Manuel A; Dantas, Rosana A S; Rossi, Lídia A

    2014-06-01

    To perform the semantic validation and to evaluate the reliability and the presence of ceiling and floor effects of the Cardiac Patients Learning Needs Inventory in Portuguese patients with coronary artery disease. Information should be selected based on what patients know and need to learn, which means that the teaching process should be based on each person's needs. The Cardiac Patients Learning Needs Inventory is aimed at identifying the cardiac patients' individual learning needs. Methodological research design. Two hundred patients hospitalised at the coronary intensive care unit or at the cardiothoracic surgery unit of a public hospital in Lisbon answered the adapted version of the Cardiac Patients Learning Needs Inventory. Internal consistency was estimated based on Cronbach's alpha. Scores above 0·50 were considered acceptable. Stability was measured through test-retest and calculated using student's t test. Significance was set at 0·05. Patients' mean age was 65 years (SD = 11·8), and most were men (152; 76%). Cronbach's alpha for the total scale was high in the first and second measurement (0·91), and for seven domains, it was acceptable in the first and second measurement (range from 0·50-0·89). No statistically significant difference was found between mean scores on the first and second measurement. Lower diversity was observed in the answers, most of which ranged between important and very important (ceiling-effect). The adapted version for use in Portugal maintained the conceptual, semantic and idiomatic equivalences of the original version and showed adequate reliability. RELEVANCE TO CLINICAL PRACTICES: Owing to the lack of validated instruments translated into Portuguese, to measure cardiac patients' learning needs, this study entails important clinical and theoretical implications. © 2012 Blackwell Publishing Ltd.

  5. Anatomy education environment measurement inventory: A valid tool to measure the anatomy learning environment.

    Science.gov (United States)

    Hadie, Siti Nurma Hanim; Hassan, Asma'; Ismail, Zul Izhar Mohd; Asari, Mohd Asnizam; Khan, Aaijaz Ahmed; Kasim, Fazlina; Yusof, Nurul Aiman Mohd; Manan Sulong, Husnaida Abdul; Tg Muda, Tg Fatimah Murniwati; Arifin, Wan Nor; Yusoff, Muhamad Saiful Bahri

    2017-09-01

    Students' perceptions of the education environment influence their learning. Ever since the major medical curriculum reform, anatomy education has undergone several changes in terms of its curriculum, teaching modalities, learning resources, and assessment methods. By measuring students' perceptions concerning anatomy education environment, valuable information can be obtained to facilitate improvements in teaching and learning. Hence, it is important to use a valid inventory that specifically measures attributes of the anatomy education environment. In this study, a new 11-factor, 132-items Anatomy Education Environment Measurement Inventory (AEEMI) was developed using Delphi technique and was validated in a Malaysian public medical school. The inventory was found to have satisfactory content evidence (scale-level content validity index [total] = 0.646); good response process evidence (scale-level face validity index [total] = 0.867); and acceptable to high internal consistency, with the Raykov composite reliability estimates of the six factors are in the range of 0.604-0.876. The best fit model of the AEEMI is achieved with six domains and 25 items (X 2  = 415.67, P education environment in Malaysia. A concerted collaboration should be initiated toward developing a valid universal tool that, using the methods outlined in this study, measures the anatomy education environment across different institutions and countries. Anat Sci Educ 10: 423-432. © 2017 American Association of Anatomists. © 2017 American Association of Anatomists.

  6. Teaching Professionals Environmental Management: Combining Educational Learning and Practice Learning

    DEFF Research Database (Denmark)

    Jørgensen, Michael Søgaard; Jørgensen, Ulrik

    2003-01-01

    semesters. The target groups are professional environmental managers working in businesses including consultants, governmental institutions and organizations. To get access to the education the students must have a technical/nature science competence at master level or bachelor level combined with relevant...... job experience. Generally the participants have had 5-15 years of practical experience and many have been or are in the position of an internal or external job change towards new tasks that require new knowledge, methodologies or management skills. The education of "Masters of Environmental Management...... they can use in complex situations on the job is not simply a question of combining different university disciplines in the right blend and topping it with some experience. It involves combining science-based knowledge into thematic structures in carefully organized learning processes. The education...

  7. Combined methodology of optimization and life cycle inventory for a biomass gasification based BCHP system

    International Nuclear Information System (INIS)

    Wang, Jiang-Jiang; Yang, Kun; Xu, Zi-Long; Fu, Chao; Li, Li; Zhou, Zun-Kai

    2014-01-01

    Biomass gasification based building cooling, heating, and power (BCHP) system is an effective distributed energy system to improve the utilization of biomass resources. This paper proposes a combined methodology of optimization method and life cycle inventory (LCI) for the biomass gasification based BCHP system. The life cycle models including biomass planting, biomass collection-storage-transportation, BCHP plant construction and operation, and BCHP plant demolition and recycle, are constructed to obtain economic cost, energy consumption and CO 2 emission in the whole service-life. Then, the optimization model for the biomass BCHP system including variables, objective function and solution method are presented. Finally, a biomass BCHP case in Harbin, China, is optimized under different optimization objectives, the life-cycle performances including cost, energy and CO 2 emission are obtained and the grey incidence approach is employed to evaluate their comprehensive performances of the biomass BCHP schemes. The results indicate that the life-cycle cost, energy efficiency and CO 2 emission of the biomass BCHP system are about 41.9 $ MWh −1 , 41% and 59.60 kg MWh −1 respectively. The optimized biomass BCHP configuration to minimize the life-cycle cost is the best scheme to achieve comprehensive benefit including cost, energy consumption, renewable energy ratio, steel consumption, and CO 2 emission. - Highlights: • Propose the combined method of optimization and LCI for biomass BCHP system. • Optimize the biomass BCHP system to minimize the life-cycle cost, energy and emission. • Obtain the optimized life-cycle cost, energy efficiency and CO 2 emission. • Select the best biomass BCHP scheme using grey incidence approach

  8. Validation of the learning transfer system inventory in the South African context (Part 1

    Directory of Open Access Journals (Sweden)

    W J Coetsee

    2006-10-01

    Full Text Available The purpose of this study was to validate the Learning Transfer System Inventory (LTSI in the South African context. The sample used in this study was a convenience sample of 240 employees working for a Banking group. Exploratory factor analysis of the LTSI was used to determine if an interpretable factor structure of latent transfer system constructs when applied in the South African context could be identified. From the results it appears that the factor structure of the LTSI, as revealed by means of the exploratory approach, appears differently in the South African context.

  9. Validating Proposed Learning Progressions on Force and Motion Using the Force Concept Inventory: Findings from Singapore Secondary Schools

    Science.gov (United States)

    Fulmer, Gavin W.

    2015-01-01

    This study examines the validity of 2 proposed learning progressions on the force concept when tested using items from the Force Concept Inventory (FCI). This is the first study to compare students' performance with respect to learning progressions both for force and motion and for Newton's third law in parallel. It is also among the first studies…

  10. An inventory of the Aspergillus niger secretome by combining in silico predictions with shotgun proteomics data

    Directory of Open Access Journals (Sweden)

    Martens-Uzunova Elena S

    2010-10-01

    Full Text Available Abstract Background The ecological niche occupied by a fungal species, its pathogenicity and its usefulness as a microbial cell factory to a large degree depends on its secretome. Protein secretion usually requires the presence of a N-terminal signal peptide (SP and by scanning for this feature using available highly accurate SP-prediction tools, the fraction of potentially secreted proteins can be directly predicted. However, prediction of a SP does not guarantee that the protein is actually secreted and current in silico prediction methods suffer from gene-model errors introduced during genome annotation. Results A majority rule based classifier that also evaluates signal peptide predictions from the best homologs of three neighbouring Aspergillus species was developed to create an improved list of potential signal peptide containing proteins encoded by the Aspergillus niger genome. As a complement to these in silico predictions, the secretome associated with growth and upon carbon source depletion was determined using a shotgun proteomics approach. Overall, some 200 proteins with a predicted signal peptide were identified to be secreted proteins. Concordant changes in the secretome state were observed as a response to changes in growth/culture conditions. Additionally, two proteins secreted via a non-classical route operating in A. niger were identified. Conclusions We were able to improve the in silico inventory of A. niger secretory proteins by combining different gene-model predictions from neighbouring Aspergilli and thereby avoiding prediction conflicts associated with inaccurate gene-models. The expected accuracy of signal peptide prediction for proteins that lack homologous sequences in the proteomes of related species is 85%. An experimental validation of the predicted proteome confirmed in silico predictions.

  11. An inventory of the Aspergillus niger secretome by combining in silico predictions with shotgun proteomics data.

    Science.gov (United States)

    Braaksma, Machtelt; Martens-Uzunova, Elena S; Punt, Peter J; Schaap, Peter J

    2010-10-19

    The ecological niche occupied by a fungal species, its pathogenicity and its usefulness as a microbial cell factory to a large degree depends on its secretome. Protein secretion usually requires the presence of a N-terminal signal peptide (SP) and by scanning for this feature using available highly accurate SP-prediction tools, the fraction of potentially secreted proteins can be directly predicted. However, prediction of a SP does not guarantee that the protein is actually secreted and current in silico prediction methods suffer from gene-model errors introduced during genome annotation. A majority rule based classifier that also evaluates signal peptide predictions from the best homologs of three neighbouring Aspergillus species was developed to create an improved list of potential signal peptide containing proteins encoded by the Aspergillus niger genome. As a complement to these in silico predictions, the secretome associated with growth and upon carbon source depletion was determined using a shotgun proteomics approach. Overall, some 200 proteins with a predicted signal peptide were identified to be secreted proteins. Concordant changes in the secretome state were observed as a response to changes in growth/culture conditions. Additionally, two proteins secreted via a non-classical route operating in A. niger were identified. We were able to improve the in silico inventory of A. niger secretory proteins by combining different gene-model predictions from neighbouring Aspergilli and thereby avoiding prediction conflicts associated with inaccurate gene-models. The expected accuracy of signal peptide prediction for proteins that lack homologous sequences in the proteomes of related species is 85%. An experimental validation of the predicted proteome confirmed in silico predictions.

  12. Combining Service and Learning in Higher Education

    National Research Council Canada - National Science Library

    Gray, Maryann

    1999-01-01

    .... Hundreds of college and university presidents, most of the major higher education associations, and a number of highly influential scholars actively support the development of service-learning...

  13. Combined landslide inventory and susceptibility assessment based on different mapping units: an example from the Flemish Ardennes, Belgium

    Directory of Open Access Journals (Sweden)

    M. Van Den Eeckhaut

    2009-03-01

    Full Text Available For a 277 km2 study area in the Flemish Ardennes, Belgium, a landslide inventory and two landslide susceptibility zonations were combined to obtain an optimal landslide susceptibility assessment, in five classes. For the experiment, a regional landslide inventory, a 10 m × 10 m digital representation of topography, and lithological and soil hydrological information obtained from 1:50 000 scale maps, were exploited. In the study area, the regional inventory shows 192 landslides of the slide type, including 158 slope failures occurred before 1992 (model calibration set, and 34 failures occurred after 1992 (model validation set. The study area was partitioned in 2.78×106 grid cells and in 1927 topographic units. The latter are hydro-morphological units obtained by subdividing slope units based on terrain gradient. Independent models were prepared for the two terrain subdivisions using discriminant analysis. For grid cells, a single pixel was identified as representative of the landslide depletion area, and geo-environmental information for the pixel was obtained from the thematic maps. The landslide and geo-environmental information was used to model the propensity of the terrain to host landslide source areas. For topographic units, morphologic and hydrologic information and the proportion of lithologic and soil hydrological types in each unit, were used to evaluate landslide susceptibility, including the depletion and depositional areas. Uncertainty associated with the two susceptibility models was evaluated, and the model performance was tested using the independent landslide validation set. An heuristic procedure was adopted to combine the landslide inventory and the susceptibility zonations. The procedure makes optimal use of the available landslide and susceptibility information, minimizing the limitations inherent in the inventory and the susceptibility maps. For the established susceptibility classes, regulations to

  14. Combined landslide inventory and susceptibility assessment based on different mapping units: an example from the Flemish Ardennes, Belgium

    Science.gov (United States)

    van den Eeckhaut, M.; Reichenbach, P.; Guzzetti, F.; Rossi, M.; Poesen, J.

    2009-03-01

    For a 277 km2 study area in the Flemish Ardennes, Belgium, a landslide inventory and two landslide susceptibility zonations were combined to obtain an optimal landslide susceptibility assessment, in five classes. For the experiment, a regional landslide inventory, a 10 m × 10 m digital representation of topography, and lithological and soil hydrological information obtained from 1:50 000 scale maps, were exploited. In the study area, the regional inventory shows 192 landslides of the slide type, including 158 slope failures occurred before 1992 (model calibration set), and 34 failures occurred after 1992 (model validation set). The study area was partitioned in 2.78×106 grid cells and in 1927 topographic units. The latter are hydro-morphological units obtained by subdividing slope units based on terrain gradient. Independent models were prepared for the two terrain subdivisions using discriminant analysis. For grid cells, a single pixel was identified as representative of the landslide depletion area, and geo-environmental information for the pixel was obtained from the thematic maps. The landslide and geo-environmental information was used to model the propensity of the terrain to host landslide source areas. For topographic units, morphologic and hydrologic information and the proportion of lithologic and soil hydrological types in each unit, were used to evaluate landslide susceptibility, including the depletion and depositional areas. Uncertainty associated with the two susceptibility models was evaluated, and the model performance was tested using the independent landslide validation set. An heuristic procedure was adopted to combine the landslide inventory and the susceptibility zonations. The procedure makes optimal use of the available landslide and susceptibility information, minimizing the limitations inherent in the inventory and the susceptibility maps. For the established susceptibility classes, regulations to link terrain domains to appropriate land

  15. A Combined Liquefied Natural Gas Routing and Deteriorating Inventory Management Problem

    NARCIS (Netherlands)

    Ghiami, Y.; Van Woensel, Tom; Christiansen, Marielle; Laporte, Gilbert

    2015-01-01

    Liquefied Natural Gas (LNG) is becoming a more crucial source of energy due to its increased price competitiveness and environmental friendliness. We consider an inventory routing problem for inland distribution of LNG from storage facilities to filling stations. Here, an actor is responsible for

  16. A combined liquefied natural gas routing and deteriorating inventory management problem

    NARCIS (Netherlands)

    Ghiami, Y.; van Woensel, T.; Christiansen, Marielle; Laporte, G.; Corman, Fr.; Voss, St.; Negenborn, R.R.

    2015-01-01

    Liquefied Natural Gas (LNG) is becoming a more crucial source of energy due to its increased price competitiveness and environmental friendliness. We consider an inventory routing problem for inland distribution of LNG from storage facilities to filling stations. Here, an actor is responsible for

  17. Combining Service and Learning in Higher Education

    National Research Council Canada - National Science Library

    Gray, Maryann

    1999-01-01

    The Policy Debate In the past decade, colleges and universities have made greater efforts to involve students in community service, particularly service-learning, a special form of community service...

  18. The Learning and Study Strategies Inventory-High School Version: Issues of Factorial Invariance Across Gender and Ethnicity

    Science.gov (United States)

    Stevens, Tara; Tallent-Runnels, Mary K.

    2004-01-01

    The purpose of this study was to investigate the latent structure of the Learning and Study Strategies Inventory-High School (LASSI-HS) through confirmatory factor analysis and factorial invariance models. A simple modification of the three-factor structure was considered. Using a larger sample, cross-validation was completed and the equality of…

  19. The Psychometric Analysis of the Persian Version of the Strategy Inventory for Language Learning of Rebecca L. Oxford

    Science.gov (United States)

    Fazeli, Seyed Hossein

    2012-01-01

    The current study aims to analyze the psychometric qualities of the Persian adapted version of Strategy Inventory for Language Learning (SILL) developed by Rebecca L. Oxford (1990). Three instruments were used: Persian adapted version of SILL, a Background Questionnaire, and Test of English as a Foreign Language. Two hundred and thirteen Iranian…

  20. Adaptation of the Grasha Riechman Student Learning Style Survey and Teaching Style Inventory to assess individual teaching and learning styles in a quality improvement collaborative.

    Science.gov (United States)

    Ford, James H; Robinson, James M; Wise, Meg E

    2016-09-29

    NIATx200, a quality improvement collaborative, involved 201 substance abuse clinics. Each clinic was randomized to one of four implementation strategies: (a) interest circle calls, (b) learning sessions, (c) coach only or (d) a combination of all three. Each strategy was led by NIATx200 coaches who provided direct coaching or facilitated the interest circle and learning session interventions. Eligibility was limited to NIATx200 coaches (N = 18), and the executive sponsor/change leader of participating clinics (N = 389). Participants were invited to complete a modified Grasha Riechmann Student Learning Style Survey and Teaching Style Inventory. Principal components analysis determined participants' preferred learning and teaching styles. Responses were received from 17 (94.4 %) of the coaches. Seventy-two individuals were excluded from the initial sample of change leaders and executive sponsors (N = 389). Responses were received from 80 persons (25.2 %) of the contactable individuals. Six learning profiles for the executive sponsors and change leaders were identified: Collaborative/Competitive (N = 28, 36.4 %); Collaborative/Participatory (N = 19, 24.7 %); Collaborative only (N = 17, 22.1 %); Collaborative/Dependent (N = 6, 7.8 %); Independent (N = 3, 5.2 %); and Avoidant/Dependent (N = 3, 3.9 %). NIATx200 coaches relied primarily on one of four coaching profiles: Facilitator (N = 7, 41.2 %), Facilitator/Delegator (N = 6, 35.3 %), Facilitator/Personal Model (N = 3, 17.6 %) and Delegator (N = 1, 5.9 %). Coaches also supported their primary coaching profiles with one of eight different secondary coaching profiles. The study is one of the first to assess teaching and learning styles within a QIC. Results indicate that individual learners (change leaders and executive sponsors) and coaches utilize multiple approaches in the teaching and practice-based learning of quality improvement (QI) processes

  1. Combining emission inventory and isotope ratio analyses for quantitative source apportionment of heavy metals in agricultural soil.

    Science.gov (United States)

    Chen, Lian; Zhou, Shenglu; Wu, Shaohua; Wang, Chunhui; Li, Baojie; Li, Yan; Wang, Junxiao

    2018-08-01

    Two quantitative methods (emission inventory and isotope ratio analysis) were combined to apportion source contributions of heavy metals entering agricultural soils in the Lihe River watershed (Taihu region, east China). Source apportionment based on the emission inventory method indicated that for Cd, Cr, Cu, Pb, and Zn, the mean percentage input from atmospheric deposition was highest (62-85%), followed by irrigation (12-27%) and fertilization (1-14%). Thus, the heavy metals were derived mainly from industrial activities and traffic emissions. For Ni the combined percentage input from irrigation and fertilization was approximately 20% higher than that from atmospheric deposition, indicating that Ni was mainly derived from agricultural activities. Based on isotope ratio analysis, atmospheric deposition accounted for 57-93% of Pb entering soil, with the mean value of 69.3%, which indicates that this was the major source of Pb entering soil in the study area. The mean contributions of irrigation and fertilization to Pb pollution of soil ranged from 0% to 10%, indicating that they played only a marginally important role. Overall, the results obtained using the two methods were similar. This study provides a reliable approach for source apportionment of heavy metals entering agricultural soils in the study area, and clearly have potential application for future studies in other regions. Copyright © 2018 Elsevier Ltd. All rights reserved.

  2. Combining deep learning and satellite data to inform sustainable development

    Science.gov (United States)

    Lobell, D. B.

    2017-12-01

    Methods in machine learning, and in particular deep learning, are quickly advancing, in parallel with dramatic increases in the availability of fine resolution satellite data. The combination of both offers the possibility to improve understanding of some of the poorest regions of the world, where traditional data sources are limited. This talk will cover recent applications to track poverty at the village level in Africa, spot the onset of disease outbreaks in agriculture, and identify land use patterns and crop productivity.

  3. Self-control over combined video feedback and modeling facilitates motor learning.

    Science.gov (United States)

    Post, Phillip G; Aiken, Christopher A; Laughlin, David D; Fairbrother, Jeffrey T

    2016-06-01

    Allowing learners to control the video presentation of knowledge of performance (KP) or an expert model during practice has been shown to facilitate motor learning (Aiken, Fairbrother, & Post, 2012; Wulf, Raupach, & Pfeiffer, 2005). Split-screen replay features now allow for the simultaneous presentation of these modes of instructional support. It is uncertain, however, if such a combination incorporated into a self-control protocol would yield similar benefits seen in earlier self-control studies. Therefore, the purpose of the present study was to examine the effects of self-controlled split-screen replay on the learning of a golf chip shot. Participants completed 60 practice trials, three administrations of the Intrinsic Motivation Inventory, and a questionnaire on day one. Retention and transfer tests and a final motivation inventory were completed on day two. Results revealed significantly higher form and accuracy scores for the self-control group during transfer. The self-control group also had significantly higher scores on the perceived competence subscale, reported requesting feedback mostly after perceived poor trials, and recalled a greater number of critical task features compared to the yoked group. The findings for the performance measures were consistent with previous self-control research. Copyright © 2016 Elsevier B.V. All rights reserved.

  4. Talking and learning physics: Predicting future grades from network measures and Force Concept Inventory pretest scores

    Directory of Open Access Journals (Sweden)

    Jesper Bruun

    2013-07-01

    Full Text Available The role of student interactions in learning situations is a foundation of sociocultural learning theory, and social network analysis can be used to quantify student relations. We discuss how self-reported student interactions can be viewed as processes of meaning making and use this to understand how quantitative measures that describe the position in a network, called centrality measures, can be understood in terms of interactions that happen in the context of a university physics course. We apply this discussion to an empirical data set of self-reported student interactions. In a weekly administered survey, first year university students enrolled in an introductory physics course at a Danish university indicated with whom they remembered having communicated within different interaction categories. For three categories pertaining to (1 communication about how to solve physics problems in the course (called the PS category, (2 communications about the nature of physics concepts (called the CD category, and (3 social interactions that are not strictly related to the content of the physics classes (called the ICS category in the introductory mechanics course, we use the survey data to create networks of student interaction. For each of these networks, we calculate centrality measures for each student and correlate these measures with grades from the introductory course, grades from two subsequent courses, and the pretest Force Concept Inventory (FCI scores. We find highly significant correlations (p<0.001 between network centrality measures and grades in all networks. We find the highest correlations between network centrality measures and future grades. In the network composed of interactions regarding problem solving (the PS network, the centrality measures hide and PageRank show the highest correlations (r=-0.32 and r=0.33, respectively with future grades. In the CD network, the network measure target entropy shows the highest correlation

  5. Effects of Elicited Reflections combined with Tutor or Peer Feedback on Self-Regulated Learning and Learning Outcomes

    NARCIS (Netherlands)

    Van den Boom, Gerard; Paas, Fred; Van Merriënboer, Jeroen

    2009-01-01

    Van den Boom, G., Paas, F., & Van Merriënboer, J. J. G. (2007). Effects of elicited reflections combined with tutor or peer feedback on self-regulated learning and learning outcomes. Learning and Instruction, 17, 532-548.

  6. Advancing US GHG Inventory by Incorporating Survey Data using Machine-Learning Techniques

    Science.gov (United States)

    Alsaker, C.; Ogle, S. M.; Breidt, J.

    2017-12-01

    Crop management data are used in the National Greenhouse Gas Inventory that is compiled annually and reported to the United Nations Framework Convention on Climate Change. Emissions for carbon stock change and N2O emissions for US agricultural soils are estimated using the USDA National Resources Inventory (NRI). NRI provides basic information on land use and cropping histories, but it does not provide much detail on other management practices. In contrast, the Conservation Effects Assessment Project (CEAP) survey collects detailed crop management data that could be used in the GHG Inventory. The survey data were collected from NRI survey locations that are a subset of the NRI every 10 years. Therefore, imputation of the CEAP are needed to represent the management practices across all NRI survey locations both spatially and temporally. Predictive mean matching and an artificial neural network methods have been applied to develop imputation model under a multiple imputation framework. Temporal imputation involves adjusting the imputation model using state-level USDA Agricultural Resource Management Survey data. Distributional and predictive accuracy is assessed for the imputed data, providing not only management data needed for the inventory but also rigorous estimates of uncertainty.

  7. A fast-response production-inventory model for deteriorating seasonal products with learning in set-ups

    Directory of Open Access Journals (Sweden)

    Ibraheem Abdul

    2011-10-01

    Full Text Available The classical production-inventory model assumes that both demand and set-up costs are constant. However, in real manufacturing environment, managers usually embark on continuous improvement programmes that often lead to more effective use of tools and machineries and consequently reduction in set-up costs. In fact, constant emphasis on reduction of set-up costs is usually cited as one of the factors responsible for the efficiency of Japanese manufacturing methods. On the other hand, the demand for seasonal product is often characterized by a mixture of time-dependent patterns over the entire season. This paper investigates the effect of learning-based reduction in set-up costs on the optimal schedules and costs of a production-inventory system for deteriorating seasonal products. The demand pattern is a general three-phase ramp-type demand function that represents the various phases of demand commonly observed in many seasonal products in the market. A two-parameter Weibull-distribution function is used for the deterioration of items in order to make the model more generalized and realistic. The study further presents two different multi-period production strategies that can ensure a fast-response to customers’ demand and compare them with the usual single period strategy. The Numerical example and sensitivity analysis shows that learning-based reduction in set-up costs leads to higher production frequency and shorter production runs which are vital aspects of the just-in-time (JIT philosophy.

  8. Function approximation using combined unsupervised and supervised learning.

    Science.gov (United States)

    Andras, Peter

    2014-03-01

    Function approximation is one of the core tasks that are solved using neural networks in the context of many engineering problems. However, good approximation results need good sampling of the data space, which usually requires exponentially increasing volume of data as the dimensionality of the data increases. At the same time, often the high-dimensional data is arranged around a much lower dimensional manifold. Here we propose the breaking of the function approximation task for high-dimensional data into two steps: (1) the mapping of the high-dimensional data onto a lower dimensional space corresponding to the manifold on which the data resides and (2) the approximation of the function using the mapped lower dimensional data. We use over-complete self-organizing maps (SOMs) for the mapping through unsupervised learning, and single hidden layer neural networks for the function approximation through supervised learning. We also extend the two-step procedure by considering support vector machines and Bayesian SOMs for the determination of the best parameters for the nonlinear neurons in the hidden layer of the neural networks used for the function approximation. We compare the approximation performance of the proposed neural networks using a set of functions and show that indeed the neural networks using combined unsupervised and supervised learning outperform in most cases the neural networks that learn the function approximation using the original high-dimensional data.

  9. Combining traditional anatomy lectures with e-learning activities: how do students perceive their learning experience?

    Science.gov (United States)

    Lochner, Lukas; Wieser, Heike; Waldboth, Simone; Mischo-Kelling, Maria

    2016-02-21

    The purpose of this study was to investigate how students perceived their learning experience when combining traditional anatomy lectures with preparatory e-learning activities that consisted of fill-in-the-blank assignments, videos, and multiple-choice quizzes. A qualitative study was conducted to explore changes in study behaviour and perception of learning. Three group interviews with students were conducted and thematically analysed. Data was categorized into four themes: 1. Approaching the course material, 2. Understanding the material, 3. Consolidating the material, and 4. Perceived learning outcome. Students appreciated the clear structure of the course, and reported that online activities encouraged them towards a first engagement with the material. They felt that they were more active during in-class sessions, described self-study before the end-of-term exam as easier, and believed that contents would remain in their memories for a longer time. By adjusting already existing resources, lectures can be combined fairly easily and cost-effectively with preparatory e-learning activities. The creation of online components promote well-structured courses, can help minimize 'student passivity' as a characteristic element of lectures, and can support students in distributing their studies throughout the term, thus suggesting enhanced learning. Further research work should be designed to confirm the afore-mentioned findings through objective measurements of student learning outcomes.

  10. Combining traditional anatomy lectures with e-learning activities: how do students perceive their learning experience?

    Science.gov (United States)

    Wieser, Heike; Waldboth, Simone; Mischo-Kelling, Maria

    2016-01-01

    Objectives The purpose of this study was to investigate how students perceived their learning experience when combining traditional anatomy lectures with preparatory e-learning activities that consisted of fill-in-the-blank assignments, videos, and multiple-choice quizzes. Methods A qualitative study was conducted to explore changes in study behaviour and perception of learning. Three group interviews with students were conducted and thematically analysed. Results Data was categorized into four themes: 1. Approaching the course material, 2. Understanding the material, 3. Consolidating the material, and 4. Perceived learning outcome.  Students appreciated the clear structure of the course, and reported that online activities encouraged them towards a first engagement with the material. They felt that they were more active during in-class sessions, described self-study before the end-of-term exam as easier, and believed that contents would remain in their memories for a longer time. Conclusions By adjusting already existing resources, lectures can be combined fairly easily and cost-effectively with preparatory e-learning activities. The creation of online components promote well-structured courses, can help minimize ‘student passivity’ as a characteristic element of lectures, and can support students in distributing their studies throughout the term, thus suggesting enhanced learning. Further research work should be designed to confirm the afore-mentioned findings through objective measurements of student learning outcomes. PMID:26897012

  11. Learning and Study Strategies Inventory subtests and factors as predictors of National Board of Chiropractic Examiners Part 1 examination performance.

    Science.gov (United States)

    Schutz, Christine M; Dalton, Leanne; Tepe, Rodger E

    2013-01-01

    This study was designed to extend research on the relationship between chiropractic students' learning and study strategies and national board examination performance. Sixty-nine first trimester chiropractic students self-administered the Learning and Study Strategies Inventory (LASSI). Linear trends tests (for continuous variables) and Mantel-Haenszel trend tests (for categorical variables) were utilized to determine if the 10 LASSI subtests and 3 factors predicted low, medium and high levels of National Board of Chiropractic Examiners (NBCE) Part 1 scores. Multiple regression was performed to predict overall mean NBCE examination scores using the 3 LASSI factors as predictor variables. Four LASSI subtests (Anxiety, Concentration, Selecting Main Ideas, Test Strategies) and one factor (Goal Orientation) were significantly associated with NBCE examination levels. One factor (Goal Orientation) was a significant predictor of overall mean NBCE examination performance. Learning and study strategies are predictive of NBCE Part 1 examination performance in chiropractic students. The current study found LASSI subtests Anxiety, Concentration, Selecting Main Ideas, and Test Strategies, and the Goal-Orientation factor to be significant predictors of NBCE scores. The LASSI may be useful to educators in preparing students for academic success. Further research is warranted to explore the effects of learning and study strategies training on GPA and NBCE performance.

  12. Interactive Rhythm Learning System by Combining Tablet Computers and Robots

    Directory of Open Access Journals (Sweden)

    Chien-Hsing Chou

    2017-03-01

    Full Text Available This study proposes a percussion learning device that combines tablet computers and robots. This device comprises two systems: a rhythm teaching system, in which users can compose and practice rhythms by using a tablet computer, and a robot performance system. First, teachers compose the rhythm training contents on the tablet computer. Then, the learners practice these percussion exercises by using the tablet computer and a small drum set. The teaching system provides a new and user-friendly score editing interface for composing a rhythm exercise. It also provides a rhythm rating function to facilitate percussion training for children and improve the stability of rhythmic beating. To encourage children to practice percussion exercises, a robotic performance system is used to interact with the children; this system can perform percussion exercises for students to listen to and then help them practice the exercise. This interaction enhances children’s interest and motivation to learn and practice rhythm exercises. The results of experimental course and field trials reveal that the proposed system not only increases students’ interest and efficiency in learning but also helps them in understanding musical rhythms through interaction and composing simple rhythms.

  13. Best practices for learning physiology: combining classroom and online methods.

    Science.gov (United States)

    Anderson, Lisa C; Krichbaum, Kathleen E

    2017-09-01

    Physiology is a requisite course for many professional allied health programs and is a foundational science for learning pathophysiology, health assessment, and pharmacology. Given the demand for online learning in the health sciences, it is important to evaluate the efficacy of online and in-class teaching methods, especially as they are combined to form hybrid courses. The purpose of this study was to compare two hybrid physiology sections in which one section was offered mostly in-class (85% in-class), and the other section was offered mostly online (85% online). The two sections in 2 yr ( year 1 and year 2 ) were compared in terms of knowledge of physiology measured in exam scores and pretest-posttest improvement, and in measures of student satisfaction with teaching. In year 1 , there were some differences on individual exam scores between the two sections, but no significant differences in mean exam scores or in pretest-posttest improvements. However, in terms of student satisfaction, the mostly in-class students in year 1 rated the instructor significantly higher than did the mostly online students. Comparisons between in-class and online students in the year 2 cohort yielded data that showed that mean exam scores were not statistically different, but pre-post changes were significantly greater in the mostly online section; student satisfaction among mostly online students also improved significantly. Education researchers must investigate effective combinations of in-class and online methods for student learning outcomes, while maintaining the flexibility and convenience that online methods provide. Copyright © 2017 the American Physiological Society.

  14. Use of the 5E learning cycle model combined with problem-based learning for a fundamentals of nursing course.

    Science.gov (United States)

    Jun, Won Hee; Lee, Eun Ju; Park, Han Jong; Chang, Ae Kyung; Kim, Mi Ja

    2013-12-01

    The 5E learning cycle model has shown a positive effect on student learning in science education, particularly in courses with theory and practice components. Combining problem-based learning (PBL) with the 5E learning cycle was suggested as a better option for students' learning of theory and practice. The purpose of this study was to compare the effects of the traditional learning method with the 5E learning cycle model with PBL. The control group (n = 78) was subjected to a learning method that consisted of lecture and practice. The experimental group (n = 83) learned by using the 5E learning cycle model with PBL. The results showed that the experimental group had significantly improved self-efficacy, critical thinking, learning attitude, and learning satisfaction. Such an approach could be used in other countries to enhance students' learning of fundamental nursing. Copyright 2013, SLACK Incorporated.

  15. Assessment of learning and study strategies of university students in Qatar using an Arabic translation of the Learning and Study Strategies Inventory.

    Science.gov (United States)

    Alkhateeb, Haitham M; Nasser, Ramzi

    2014-06-01

    413 (119 men, 294 women) undergraduate university students in Qatar completed an Arabic version of the Learning and Study Strategies Inventory (LASSI) measuring Anxiety, Attitude, Concentration, Information Processing, Motivation, Self-testing, Selecting Main Ideas, Study Aids, Time Management, and Test Strategies. The students' learning and study strategies scores were similar to those reported in the literature. Factor analysis indicated the same general factors as in the original study. Internal consistency estimates ranged from .62 to .88. Nine of the 10 scales (i.e., all with the exception of the Study Aids) significantly correlated with students' GPAs. Scores obtained from these scales provide valid assessments of Qatar University students' use of learning and study strategies related to skill, will, and self-regulation components of strategic learning and also academic achievement. There also were statistically significant differences between higher and lower achieving students in their learning and study strategies. This study also explored the use of the LASSI as a predictive measure of academic achievement. Anxiety and test strategies were significant predictors of academic achievement as measured by students' GPA.

  16. The Learning Environment Associated with Information Technology Education in Taiwan: Combining Psychosocial and Physical Aspects

    Science.gov (United States)

    Liu, Chia-Ju; Zandvliet, David B.; Hou, I.-Ling

    2012-01-01

    This study investigated perceptions of senior high school students towards the Taiwanese information technology (IT) classroom with the What Is Happening in this Class? (WIHIC) survey and explored the physical learning environment of the IT classroom using the Computerised Classroom Environment Inventory (CCEI). The participants included 2,869…

  17. Applying a Danish version of the Learning Transfer System Inventory and testing it for different types of education

    DEFF Research Database (Denmark)

    Sørensen, Peter; Stegeager, Nikolaj W.M.; Bates, Reid

    2017-01-01

    in the original American LTSI. The study also found that the mean score differs in a statistically significant way between the different types of education. Specifically, LTSI may be more suitable in measuring transfer systems and therefore promoting transfer in relation to short courses offering training......The purpose of this study was to answer two research questions. First, will an exploratory factor analysis of a Danish version of the Learning Transfer System Inventory (LTSI) result in a factor structure which is consistent with the original American LTSI factor structure? Second, does the mean...... score in the factor analysis vary in a statistically significant way across different types of education, suggesting that the LTSI may be more suitable a measure in some educational contexts than others? To answer these questions survey data from 411 students following four different types of formal...

  18. Adaptação e validação do Cardiac Patients Learnings Needs Inventory para pacientes brasileiros Adaptación y validación del Cardiac Patients Learnings Needs Inventory para pacientes brasileños Adaptation and validation of Cardiac Patients' Learning Needs Inventory for Brazilian patients

    Directory of Open Access Journals (Sweden)

    Luzia Elaine Galdeano

    2012-01-01

    presentó mejor consistencia interna fue Factores de Riesgo (α= 0,91. CONCLUSIÓN: La versión adaptada mantuvo las equivalencias conceptuales, semánticasOBJECTIVES: To culturally adapt the Cardiac Patients' Learning Needs Inventory for use in Brazil and to test its reliability (internal consistency and stability in Brazilian patients with coronary artery disease. METHODS: The study included 65 patients with acute myocardial infarction, hospitalized in a public hospital in the state of São Paulo. For data collection, we used an instrument for sociodemographics characteristics and the Portuguese version of the Cardiac Patients' Learning Needs Inventory. Internal consistency was estimated based on Cronbach's alpha. The stability was established using the test-retest method and calculated using the Student's t-test. The level of significance was 0.05. RESULTS: We identified high internal consistency (0.96 in the first step, and 0.78 in the second. The domain that presented better internal consistency was Risk Factors (α = 0.91. CONCLUSION: The adapted version maintained conceptual equivalence, semantics and language of the original version, and presented adequate reliability and stability.

  19. Combining satellite imagery with forest inventory data to assess damage severity following a major blowdown event in northern Minnesota, USA

    Science.gov (United States)

    Mark D. Nelson; Sean P. Healey; W. Keith Moser; Mark H. Hansen

    2009-01-01

    Effects of a catastrophic blowdown event in northern Minnesota, USA were assessed using field inventory data, aerial sketch maps and satellite image data processed through the North American Forest Dynamics programme. Estimates were produced for forest area and net volume per unit area of live trees pre- and post-disturbance, and for changes in volume per unit area and...

  20. Los enfoques de aprendizaje en estudiantes universitarios Catalanes mediante el approaches and study skills inventory for students (ASSIST) = Learning Approaches of Catalan University Students Measured with the Approaches and Study Skills Inventory for Students (ASSIST)

    OpenAIRE

    Tesouro i Cid, Montserrat; Cañabate Ortiz, Dolors; Puiggalí, Joan

    2014-01-01

    The aim of this study is to measure the psychometric properties of a Catalan translation of the Approaches and Study Skills Inventory for Students (ASSIST), and to analyse the different learning styles used by university students, considering the influence of gender and type of studies. The instrument was administered to 834 students at the University of Girona. The results showed that most students interviewed had a deep approach to learning, although the analysis by gender showed that femal...

  1. Development and analysis of spectroscopic learning tools and the light and spectroscopy concept inventory for introductory college astronomy

    Science.gov (United States)

    Bardar, Erin M.

    Electromagnetic radiation is the fundamental carrier of astronomical information. Spectral features serve as the fingerprints of the universe, revealing many important properties of objects in the cosmos such as temperature, elemental compositions, and relative motion. Because of its importance to astronomical research, the nature of light and the electromagnetic spectrum is by far the most universally covered topic in astronomy education. Yet, to the surprise and disappointment of instructors, many students struggle to understand underlying fundamental concepts related to light and spectroscopic phenomena. This dissertation describes research into introductory college astronomy students' understanding of light and spectroscopy concepts, through the development and analysis of both instructional materials and an assessment instrument. The purpose of this research was two-fold: (1) to develop a novel suite of spectroscopic learning tools that enhance student understanding of light and spectroscopy and (2) to design and validate a Light and Spectroscopy Concept Inventory (LSCI) with the sensitivity to distinguish the relative effectiveness of various teaching interventions within the context of introductory college astronomy. Through a systematic investigation that included multiple rounds of clinical interviews, open-ended written surveys, and multiple-choice testing, introductory college astronomy students' commonly held misconceptions and reasoning difficulties were explored for concepts relating to: (1) The nature of the electromagnetic spectrum, including the interrelationships of wavelength, frequency, energy, and speed; (2) interpretation of Doppler shift; (3) properties of blackbody radiation; and (4) the connection between spectral features and underlying physical processes. These difficulties guided the development of instructional materials including six unique "homelab" exercises, a binocular spectrometer, a spectral analysis software tool, and the 26

  2. BAR-CODE BASED WEIGHT MEASUREMENT STATION FOR PHYSICAL INVENTORY TAKING OF PLUTONIUM OXIDE CONTAINERS AT THE MINING AND CHEMICAL COMBINE RADIOCHEMICAL REPROCESSING PLANT NEAR KRASNOYARSK, SIBERIA

    International Nuclear Information System (INIS)

    SUDA, S.

    1999-01-01

    This paper describes the technical tasks being implemented to computerize the physical inventory taking (PIT) at the Mining and Chemical Combine (Gorno-Khimichesky Kombinat, GKhK) radiochemical plant under the US/Russian cooperative nuclear material protection, control, and accounting (MPC and A) program. Under the MPC and A program, Lab-to-Lab task agreements with GKhK were negotiated that involved computerized equipment for item verification and confirmatory measurement of the Pu containers. Tasks under Phase I cover the work for demonstrating the plan and procedures for carrying out the comparison of the Pu container identification on the container with the computerized inventory records. In addition to the records validation, the verification procedures include the application of bar codes and bar coded TIDs to the Pu containers. Phase II involves the verification of the Pu content. A plan and procedures are being written for carrying out confirmatory measurements on the Pu containers

  3. Learning Human Actions by Combining Global Dynamics and Local Appearance.

    Science.gov (United States)

    Luo, Guan; Yang, Shuang; Tian, Guodong; Yuan, Chunfeng; Hu, Weiming; Maybank, Stephen J

    2014-12-01

    In this paper, we address the problem of human action recognition through combining global temporal dynamics and local visual spatio-temporal appearance features. For this purpose, in the global temporal dimension, we propose to model the motion dynamics with robust linear dynamical systems (LDSs) and use the model parameters as motion descriptors. Since LDSs live in a non-Euclidean space and the descriptors are in non-vector form, we propose a shift invariant subspace angles based distance to measure the similarity between LDSs. In the local visual dimension, we construct curved spatio-temporal cuboids along the trajectories of densely sampled feature points and describe them using histograms of oriented gradients (HOG). The distance between motion sequences is computed with the Chi-Squared histogram distance in the bag-of-words framework. Finally we perform classification using the maximum margin distance learning method by combining the global dynamic distances and the local visual distances. We evaluate our approach for action recognition on five short clips data sets, namely Weizmann, KTH, UCF sports, Hollywood2 and UCF50, as well as three long continuous data sets, namely VIRAT, ADL and CRIM13. We show competitive results as compared with current state-of-the-art methods.

  4. The Relationship Between the California Critical Thinking Disposition Inventory and Student Learning Outcomes in Baccalaureate Nursing Students.

    Science.gov (United States)

    Searing, Lisabeth Meade; Kooken, Wendy Carter

    2016-04-01

    Critical thinking is the foundation for nurses' decision making. One school of nursing used the California Critical Thinking Disposition Inventory (CCTDI) to document improvement in critical thinking dispositions. A retrospective study of 96 nursing students' records examined the relationships between the CCTDI and learning outcomes. Correlational statistics assessed relationships between CCTDI scores and cumulative grade point averages (GPA) and scores on two Health Education Systems Incorporated (HESI) examinations. Ordinal regression assessed predictive relationships between CCTDI scores and science course grades and NCLEX-RN success. First-year CCTDI scores did not predict first-year science grades. Senior-year CCTDI scores did not correlate with cumulative GPA or HESI RN Exit Exam scores, but were weakly correlated with HESI Pharmacology Exam scores. CCTDI scores did not predict NCLEX-RN success. This study did not identify meaningful relationships between critical thinking dispositions, as measured by the CCTDI, and important learning outcomes. The results do not support the efficacy of using the CCTDI in nursing education. Copyright 2016, SLACK Incorporated.

  5. Combining lived experience with the facilitation of enquiry-based learning: a 'trigger' for transformative learning.

    Science.gov (United States)

    Stacey, G; Oxley, R; Aubeeluck, A

    2015-09-01

    What is known on the subject The values underpinning recovery-orientated practice are recited in the literature and influential in the content of mental health nurse education internationally. However, scepticism exists regarding the degree to which students' assimilate the principles of recovery into their practice due to the troublesome and challenging nature of learning at a transformational level, also known as threshold concept learning. Evaluation suggests that this combination of educational approaches positively influences students' prior understandings, beliefs and values in relation to the prospect for people with significant mental health problems to recover. The components of threshold concepts are useful as a deductive framework for the evaluation of educational initiatives which attempt to initiate transformative learning. While this forum clearly holds significant potential for student development, support and preparation is needed for both the student and the facilitator in order to enable the possibility of learning which influences attitudes, beliefs and practice. The aim of this paper is to discuss the potential for combining lived experience of mental distress with the facilitation of enquiry-based learning (EBL) to act as a trigger for transformative learning in the context of promoting the understanding of mental health 'recovery' in nurse education.The values underpinning recovery-orientated practice are recited in the literature and influential in mental health nurse education internationally. However, scepticism exists regarding the degree to which students assimilate into their practice. An open-ended was distributed to a cohort of pre-registration nursing students receiving the co-facilitated EBL (n = 112). Data demonstrated how the specific attributes of this educational approach were identified by students as impacting positively on ill-informed preconceptions, understanding of complex theory and their future practice. Results were

  6. Intrinsic Motivation Inventory: Psychometric Properties in the Context of First Language and Mathematics Learning

    Directory of Open Access Journals (Sweden)

    Vera Monteiro

    2015-09-01

    Full Text Available Intrinsic Motivation Inventory (IMI is a multidimensional measurement grounded on the Self-Determination Theory (SDT used in assessing the subjective experiences of participants when developing an activity. The aim of this study is to analyze the characteristics of IMI among Portuguese students, testing four organizational models (unidimensional, multidimensional, hierarchical and bi-factor. A total of 3685 students from the 5th to the 12th grades (50.4% boys participated in the study (M = 13.67, SD = 2.26. Two versions of IMI were used (First Language and Mathematics with twenty-one items distributed over five subscales: Enjoyment, Perceived Competence, Pressure/Tension, Perceived Choice and Value/Utility. The confirmatory factor analysis corroborated the multidimensionality of intrinsic motivation, and that the bi-factor model presented the best fit indexes. This model showed the existence of one general factor, resulting from the contribution of all individual dimensions and the particularities of most of them. Furthermore, results also highlighted satisfactory reliability scores both through Cronbach's alpha scores and Composite reliability scores. These results indicate that this scale is appropriate to evaluate the underlying constructs of the theoretical model of SDT and allows for the calculation of a global measure of intrinsic motivation, as well as specific measures for their predictors.

  7. Medical students’ perception of the learning environment at King Saud University Medical College, Saudi Arabia, using DREEM Inventory

    Directory of Open Access Journals (Sweden)

    Soliman MM

    2017-03-01

    score for students’ social self-perceptions ranged from 2.85 to 4.33 (overall mean score: 24.33. The general perceptions of the students in all five sub-scales were positive.Conclusion: The overall student’s perception about the educational environment was satisfactory. This study was important to evaluate the students’ perception of the learning environment among medical graduates of the reformed curriculum and provided guidance on areas of improvement in the curriculum. Keywords: medical students, perception, learning environment, DREEM inventory, Saudi Arabia

  8. COMBINING COOPERATIVE LEARNING WITH READING ALOUD BY TEACHERS

    Directory of Open Access Journals (Sweden)

    George Jacobs

    2004-06-01

    Full Text Available This article begins with a section that describes cooperative learning and explains eight cooperative learning principles. The second section discusses the interface between cooperative learning and language pedagogy. Next is a section about the why and how of reading aloud by teachers. The heart of the article resides in the last and longest section which describes techniques for integrating cooperative learning with reading aloud by teachers. These techniques include ones that can be used before, while and after the teacher has read aloud to the class.

  9. Combining theories to reach multi-faceted insights into learning opportunities in doctoral supervision

    DEFF Research Database (Denmark)

    Kobayashi, Sofie; Rump, Camilla Østerberg

    The aim of this paper is to illustrate how theories can be combined to explore opportunities for learning in doctoral supervision. While our earlier research into learning dynamics in doctoral supervision in life science research (Kobayashi, 2014) has focused on illustrating learning opportunitie...

  10. Managing a closed-loop supply chain inventory system with learning effects

    Science.gov (United States)

    Jauhari, Wakhid Ahmad; Dwicahyani, Anindya Rachma; Hendaryani, Oktiviandri; Kurdhi, Nughthoh Arfawi

    2018-02-01

    In this paper, we propose a closed-loop supply chain model consisting of a retailer and a manufacturer. We intend to investigate the impact of learning in regular production, remanufacturing and reworking. The customer demand is assumed deterministic and will be satisfied from both regular production and remanufacturing process. The return rate of used items depends on quality. We propose a mathematical model with the objective is to maximize the joint total profit by simultaneously determining the length of ordering cycle for the retailer and the number of regular production and remanufacturing cycle. The algorithm is suggested for finding the optimal solution. A numerical example is presented to illustrate the application of using a proposed model. The results show that the integrated model performs better in reducing total cost compared to the independent model. The total cost is most affected by the changes in the values of unit production cost and acceptable quality level. In addition, the changes in the defective items proportion and the fraction of holding costs significantly influence the retailer's ordering period.

  11. The Effect of Known-and-Unknown Word Combinations on Intentional Vocabulary Learning

    Science.gov (United States)

    Kasahara, Kiwamu

    2011-01-01

    The purpose of this study is to examine whether learning a known-and-unknown word combination is superior in terms of retention and retrieval of meaning to learning a single unknown word. The term "combination" in this study means a two-word collocation of a familiar word and a word that is new to the participants. Following the results of…

  12. Combining Correlation-Based and Reward-Based Learning in Neural Control for Policy Improvement

    DEFF Research Database (Denmark)

    Manoonpong, Poramate; Kolodziejski, Christoph; Wörgötter, Florentin

    2013-01-01

    Classical conditioning (conventionally modeled as correlation-based learning) and operant conditioning (conventionally modeled as reinforcement learning or reward-based learning) have been found in biological systems. Evidence shows that these two mechanisms strongly involve learning about...... associations. Based on these biological findings, we propose a new learning model to achieve successful control policies for artificial systems. This model combines correlation-based learning using input correlation learning (ICO learning) and reward-based learning using continuous actor–critic reinforcement...... learning (RL), thereby working as a dual learner system. The model performance is evaluated by simulations of a cart-pole system as a dynamic motion control problem and a mobile robot system as a goal-directed behavior control problem. Results show that the model can strongly improve pole balancing control...

  13. Improving Nursing Students' Learning Outcomes in Fundamentals of Nursing Course through Combination of Traditional and e-Learning Methods.

    Science.gov (United States)

    Sheikhaboumasoudi, Rouhollah; Bagheri, Maryam; Hosseini, Sayed Abbas; Ashouri, Elaheh; Elahi, Nasrin

    2018-01-01

    Fundamentals of nursing course are prerequisite to providing comprehensive nursing care. Despite development of technology on nursing education, effectiveness of using e-learning methods in fundamentals of nursing course is unclear in clinical skills laboratory for nursing students. The aim of this study was to compare the effect of blended learning (combining e-learning with traditional learning methods) with traditional learning alone on nursing students' scores. A two-group post-test experimental study was administered from February 2014 to February 2015. Two groups of nursing students who were taking the fundamentals of nursing course in Iran were compared. Sixty nursing students were selected as control group (just traditional learning methods) and experimental group (combining e-learning with traditional learning methods) for two consecutive semesters. Both groups participated in Objective Structured Clinical Examination (OSCE) and were evaluated in the same way using a prepared checklist and questionnaire of satisfaction. Statistical analysis was conducted through SPSS software version 16. Findings of this study reflected that mean of midterm (t = 2.00, p = 0.04) and final score (t = 2.50, p = 0.01) of the intervention group (combining e-learning with traditional learning methods) were significantly higher than the control group (traditional learning methods). The satisfaction of male students in intervention group was higher than in females (t = 2.60, p = 0.01). Based on the findings, this study suggests that the use of combining traditional learning methods with e-learning methods such as applying educational website and interactive online resources for fundamentals of nursing course instruction can be an effective supplement for improving nursing students' clinical skills.

  14. Combining Formal Logic and Machine Learning for Sentiment Analysis

    DEFF Research Database (Denmark)

    Petersen, Niklas Christoffer; Villadsen, Jørgen

    2014-01-01

    This paper presents a formal logical method for deep structural analysis of the syntactical properties of texts using machine learning techniques for efficient syntactical tagging. To evaluate the method it is used for entity level sentiment analysis as an alternative to pure machine learning...

  15. The use of a hands-on model in learning the regulation of an inducible operon and the development of a gene regulation concept inventory

    Science.gov (United States)

    Stefanski, Katherine M.

    A central concept in genetics is the regulation of gene expression. Inducible gene expression is often taught in undergraduate biology courses using the lac operon of Escherichia coli (E. coli ). With national calls for reform in undergraduate biology education and a body of literature that supports the use of active learning techniques including hands-on learning and analogies we were motivated to develop a hands-on analogous model of the lac operon. The model was developed over two iterations and was administered to genetics students. To determine the model's worth as a learning tool a concept inventory (CI) was developed using rigorous protocols. Concept inventories are valuable tools which can be used to assess students' understanding of a topic and pinpoint commonly held misconceptions as well as the value of educational tools. Through in-class testing (n =115) the lac operon concept inventory (LOCI) was demonstrated to be valid, predictive, and reliable (? coefficient = 0.994). LOCI scores for students who participated in the hands-on activity (n = 67) were 7.5% higher (t = -2.281, P operon. We were able to determine the efficacy of the activity and identify misconceptions held by students about the lac operon because of the use of a valid and reliable CI.

  16. Combining University Student Self-Regulated Learning Indicators and Engagement with Online Learning Events to Predict Academic Performance

    Science.gov (United States)

    Pardo, Abelardo; Han, Feifei; Ellis, Robert A.

    2017-01-01

    Self-regulated learning theories are used to understand the reasons for different levels of university student academic performance. Similarly, learning analytics research proposes the combination of detailed data traces derived from technology-mediated tasks with a variety of algorithms to predict student academic performance. The former approach…

  17. Combined detection of depression and anxiety in epilepsy patients using the Neurological Disorders Depression Inventory for Epilepsy and the World Health Organization well-being index

    DEFF Research Database (Denmark)

    Hansen, Christian Pilebæk; Amiri, Moshgan

    2015-01-01

    PURPOSE: To validate the Danish version of the Neurological Disorders Depression Inventory for Epilepsy (NDDI-E), and compare it with the World Health Organization index for psychological well-being (WHO-5) as screening tests for depression and anxiety in epilepsy patients. METHODS: Epilepsy...... outpatients filled out NDDI-E and WHO-5. A Mini International Neuropsychiatric Interview (MINI) as gold standard for psychiatric diagnoses was carried out with every patient. RESULTS: We included 124 epilepsy patients. According to MINI, 5% had depression without anxiety, 6% anxiety without depression, and 6...... there are 17% false positives. CONCLUSION: NDDI-E in Danish is valid and slightly better than WHO-5 in the detection of depression in epilepsy patients. WHO-5 is valid for the detection of anxiety disorders. Combined use of NDDI-E and WHO-5 is recommended, since 95% of all epilepsy patients with depression and...

  18. Multiple-instance learning as a classifier combining problem

    DEFF Research Database (Denmark)

    Li, Yan; Tax, David M. J.; Duin, Robert P. W.

    2013-01-01

    In multiple-instance learning (MIL), an object is represented as a bag consisting of a set of feature vectors called instances. In the training set, the labels of bags are given, while the uncertainty comes from the unknown labels of instances in the bags. In this paper, we study MIL with the ass...

  19. Nigerian Physiotherapy Clinical Students' Perception of Their Learning Environment Measured by the Dundee Ready Education Environment Measure Inventory

    Science.gov (United States)

    Odole, Adesola C.; Oyewole, Olufemi O.; Ogunmola, Oluwasolape T.

    2014-01-01

    The identification of the learning environment and the understanding of how students learn will help teacher to facilitate learning and plan a curriculum to achieve the learning outcomes. The purpose of this study was to investigate undergraduate physiotherapy clinical students' perception of University of Ibadan's learning environment. Using the…

  20. Combining Formal, Non-Formal and Informal Learning for Workforce Skill Development

    Science.gov (United States)

    Misko, Josie

    2008-01-01

    This literature review, undertaken for Australian Industry Group, shows how multiple variations and combinations of formal, informal and non-formal learning, accompanied by various government incentives and organisational initiatives (including job redesign, cross-skilling, multi-skilling, diversified career pathways, action learning projects,…

  1. Combining generative and discriminative representation learning for lung CT analysis with convolutional restricted Boltzmann machines

    DEFF Research Database (Denmark)

    van Tulder, Gijs; de Bruijne, Marleen

    2016-01-01

    The choice of features greatly influences the performance of a tissue classification system. Despite this, many systems are built with standard, predefined filter banks that are not optimized for that particular application. Representation learning methods such as restricted Boltzmann machines may...... outperform these standard filter banks because they learn a feature description directly from the training data. Like many other representation learning methods, restricted Boltzmann machines are unsupervised and are trained with a generative learning objective; this allows them to learn representations from...... unlabeled data, but does not necessarily produce features that are optimal for classification. In this paper we propose the convolutional classification restricted Boltzmann machine, which combines a generative and a discriminative learning objective. This allows it to learn filters that are good both...

  2. Dropout Prediction in E-Learning Courses through the Combination of Machine Learning Techniques

    Science.gov (United States)

    Lykourentzou, Ioanna; Giannoukos, Ioannis; Nikolopoulos, Vassilis; Mpardis, George; Loumos, Vassili

    2009-01-01

    In this paper, a dropout prediction method for e-learning courses, based on three popular machine learning techniques and detailed student data, is proposed. The machine learning techniques used are feed-forward neural networks, support vector machines and probabilistic ensemble simplified fuzzy ARTMAP. Since a single technique may fail to…

  3. Improving Learning Analytics--Combining Observational and Self-Report Data on Student Learning

    Science.gov (United States)

    Ellis, Robert A.; Han, Feifei; Pardo, Abelardo

    2017-01-01

    The field of education technology is embracing a use of learning analytics to improve student experiences of learning. Along with exponential growth in this area is an increasing concern of the interpretability of the analytics from the student experience and what they can tell us about learning. This study offers a way to address some of the…

  4. Combining Face-to-Face Learning with Online Learning in Virtual Worlds

    Science.gov (United States)

    Berns, Anke; Gonzalez-Pardo, Antonio; Camacho, David

    2012-01-01

    This paper focuses on the development of videogame-like applications in a 3D virtual environment as a complement to the face-to-face teaching and learning. With the changing role of teaching and learning and the increasing use of "blended learning," instructors are increasingly expected to explore new ways to attend to the needs of their…

  5. Inventory parameters

    CERN Document Server

    Sharma, Sanjay

    2017-01-01

    This book provides a detailed overview of various parameters/factors involved in inventory analysis. It especially focuses on the assessment and modeling of basic inventory parameters, namely demand, procurement cost, cycle time, ordering cost, inventory carrying cost, inventory stock, stock out level, and stock out cost. In the context of economic lot size, it provides equations related to the optimum values. It also discusses why the optimum lot size and optimum total relevant cost are considered to be key decision variables, and uses numerous examples to explain each of these inventory parameters separately. Lastly, it provides detailed information on parameter estimation for different sectors/products. Written in a simple and lucid style, it offers a valuable resource for a broad readership, especially Master of Business Administration (MBA) students.

  6. Development of radiation oncology learning system combined with multi-institutional radiotherapy database (ROGAD)

    International Nuclear Information System (INIS)

    Takemura, Akihiro; Iinuma, Masahiro; Kou, Hiroko; Harauchi, Hajime; Inamura, Kiyonari

    1999-01-01

    We have constructed and are operating a multi-institutional radiotherapy database ROGAD (Radiation Oncology Greater Area Database) since 1992. One of it's purpose is 'to optimize individual radiotherapy plans'. We developed Radiation oncology learning system combined with ROGAD' which conforms to that purpose. Several medical doctors evaluated our system. According to those evaluations, we are now confident that our system is able to contribute to improvement of radiotherapy results. Our final target is to generate a good cyclic relationship among three components: radiotherapy results according to ''Radiation oncology learning system combined with ROGAD.'; The growth of ROGAD; and radiation oncology learning system. (author)

  7. Combining Education and Practice Learning in Environmental Management and Cleaner Technology

    DEFF Research Database (Denmark)

    Jørgensen, Ulrik; Jørgensen, Michael Søgaard

    2004-01-01

    to overcome these problems are discussed. The educational principles are presented as a combination of educational learning and practice learning named as reflexive learning. The experience from working with reflexive learning is discussed and relation to the role it can play in creating profes......This chapter argues for a new role for universities in adding the training of (existing) professionals to the core agenda in parallel to academic education and scientific research. Based on experiences from Denmark new challenges both to academic knowledge and training are presented and way...

  8. Image Denoising Algorithm Combined with SGK Dictionary Learning and Principal Component Analysis Noise Estimation

    Directory of Open Access Journals (Sweden)

    Wenjing Zhao

    2018-01-01

    Full Text Available SGK (sequential generalization of K-means dictionary learning denoising algorithm has the characteristics of fast denoising speed and excellent denoising performance. However, the noise standard deviation must be known in advance when using SGK algorithm to process the image. This paper presents a denoising algorithm combined with SGK dictionary learning and the principal component analysis (PCA noise estimation. At first, the noise standard deviation of the image is estimated by using the PCA noise estimation algorithm. And then it is used for SGK dictionary learning algorithm. Experimental results show the following: (1 The SGK algorithm has the best denoising performance compared with the other three dictionary learning algorithms. (2 The SGK algorithm combined with PCA is superior to the SGK algorithm combined with other noise estimation algorithms. (3 Compared with the original SGK algorithm, the proposed algorithm has higher PSNR and better denoising performance.

  9. Using the stress and adversity inventory as a teaching tool leads to significant learning gains in two courses on stress and health.

    Science.gov (United States)

    Slavich, George M; Toussaint, Loren

    2014-10-01

    The ability to measure cumulative stress exposure is important for research and teaching in stress and health, but until recently, no structured system has existed for assessing exposure to stress over the lifespan. Here, we report the results of two experimental studies that examined the pedagogical efficacy of using an automated system for assessing life stress, called the Stress and Adversity Inventory (STRAIN), for teaching courses on stress and health. In Study 1, a randomized, wait-list controlled experiment was conducted with 20 college students to test whether the STRAIN, coupled with a related lecture and discussion, promoted learning about stress and health. Results showed that this experiential lesson led to significant learning gains. To disentangle the effects of completing the STRAIN from participating in the lecture and discussion, we subsequently conducted Study 2 on 144 students using a 2 (STRAIN versus control activity) by 2 (STRAIN-specific lecture versus general stress lecture) repeated-measures design. Although the STRAIN-specific lecture was sufficient for promoting learning, completing the STRAIN also generated significant learning gains when paired with only the general stress lecture. Together, these studies suggest that the STRAIN is an effective tool for promoting experiential learning and teaching students about stress and health. Copyright © 2013 John Wiley & Sons, Ltd.

  10. Providing pervasive Learning eXperiences by Combining Internet of Things and e-Learning standards

    Directory of Open Access Journals (Sweden)

    Aroua TAAMALLAH

    2015-12-01

    Full Text Available Nowadays, learning is more and more taking place anywhere and anytime. This implies that e-learning environments are expanded from only virtual learning environments to both virtual and physical ones. Thanks to the evolution of Internet, ICT (Information and Communication Technology and Internet of Things, new learning scenarios could be experienced by learners either individually or collaboratively. These learning scenarios are Pervasive in such a way that they allow to mix virtual and physical learning environments as well. They are therefore characterized by possible interactions of the learner with the physical environment, the Learner's contextual data detection as well as the adaptation of pedagogical strategies and services according to this context. This paper aims to take advantage of this trend and keep up also with existing e-Learning standards such as IMS LD and LOM. The solution proposed is therefore to extend these standards models with that of Internet of Things and to provide an adaptation approach of learning activities based on learner's context and her/his track using the eXperience API. In this context and in order to allow both reasoning capabilities and interoperability between the proposed models Ontological representations and implementation are therefore proposed. Moreover a technical architecture highlighting the required software components and their interactions is provided. And finally, a relevant pervasive learning scenario is implemented and experimented.

  11. Honeybees in a virtual reality environment learn unique combinations of colour and shape.

    Science.gov (United States)

    Rusch, Claire; Roth, Eatai; Vinauger, Clément; Riffell, Jeffrey A

    2017-10-01

    Honeybees are well-known models for the study of visual learning and memory. Whereas most of our knowledge of learned responses comes from experiments using free-flying bees, a tethered preparation would allow fine-scale control of the visual stimuli as well as accurate characterization of the learned responses. Unfortunately, conditioning procedures using visual stimuli in tethered bees have been limited in their efficacy. In this study, using a novel virtual reality environment and a differential training protocol in tethered walking bees, we show that the majority of honeybees learn visual stimuli, and need only six paired training trials to learn the stimulus. We found that bees readily learn visual stimuli that differ in both shape and colour. However, bees learn certain components over others (colour versus shape), and visual stimuli are learned in a non-additive manner with the interaction of specific colour and shape combinations being crucial for learned responses. To better understand which components of the visual stimuli the bees learned, the shape-colour association of the stimuli was reversed either during or after training. Results showed that maintaining the visual stimuli in training and testing phases was necessary to elicit visual learning, suggesting that bees learn multiple components of the visual stimuli. Together, our results demonstrate a protocol for visual learning in restrained bees that provides a powerful tool for understanding how components of a visual stimulus elicit learned responses as well as elucidating how visual information is processed in the honeybee brain. © 2017. Published by The Company of Biologists Ltd.

  12. Combining Project-Based Learning and Community-Based Research in a Research Methodology Course: The Lessons Learned

    Science.gov (United States)

    Arantes do Amaral, João Alberto; Lino dos Santos, Rebeca Júlia Rodrigues

    2018-01-01

    In this article, we present our findings regarding the course "Research Methodology," offered to 22 first-year undergraduate students studying Administration at the Federal University of São Paulo, Osasco, Brazil. The course, which combined community-based research and project-based learning, was developed during the second semester of…

  13. Riparian Inventory

    Data.gov (United States)

    Kansas Data Access and Support Center — This dataset is a digital representation of the 1:24,000 Land Use Riparian Areas Inventory for the state of Kansas. The dataset includes a 100 foot buffer around all...

  14. Combining MLC and SVM Classifiers for Learning Based Decision Making: Analysis and Evaluations.

    Science.gov (United States)

    Zhang, Yi; Ren, Jinchang; Jiang, Jianmin

    2015-01-01

    Maximum likelihood classifier (MLC) and support vector machines (SVM) are two commonly used approaches in machine learning. MLC is based on Bayesian theory in estimating parameters of a probabilistic model, whilst SVM is an optimization based nonparametric method in this context. Recently, it is found that SVM in some cases is equivalent to MLC in probabilistically modeling the learning process. In this paper, MLC and SVM are combined in learning and classification, which helps to yield probabilistic output for SVM and facilitate soft decision making. In total four groups of data are used for evaluations, covering sonar, vehicle, breast cancer, and DNA sequences. The data samples are characterized in terms of Gaussian/non-Gaussian distributed and balanced/unbalanced samples which are then further used for performance assessment in comparing the SVM and the combined SVM-MLC classifier. Interesting results are reported to indicate how the combined classifier may work under various conditions.

  15. Combining MLC and SVM Classifiers for Learning Based Decision Making: Analysis and Evaluations

    Directory of Open Access Journals (Sweden)

    Yi Zhang

    2015-01-01

    Full Text Available Maximum likelihood classifier (MLC and support vector machines (SVM are two commonly used approaches in machine learning. MLC is based on Bayesian theory in estimating parameters of a probabilistic model, whilst SVM is an optimization based nonparametric method in this context. Recently, it is found that SVM in some cases is equivalent to MLC in probabilistically modeling the learning process. In this paper, MLC and SVM are combined in learning and classification, which helps to yield probabilistic output for SVM and facilitate soft decision making. In total four groups of data are used for evaluations, covering sonar, vehicle, breast cancer, and DNA sequences. The data samples are characterized in terms of Gaussian/non-Gaussian distributed and balanced/unbalanced samples which are then further used for performance assessment in comparing the SVM and the combined SVM-MLC classifier. Interesting results are reported to indicate how the combined classifier may work under various conditions.

  16. The combination of appetitive and aversive reinforcers and the nature of their interaction during auditory learning.

    Science.gov (United States)

    Ilango, A; Wetzel, W; Scheich, H; Ohl, F W

    2010-03-31

    Learned changes in behavior can be elicited by either appetitive or aversive reinforcers. It is, however, not clear whether the two types of motivation, (approaching appetitive stimuli and avoiding aversive stimuli) drive learning in the same or different ways, nor is their interaction understood in situations where the two types are combined in a single experiment. To investigate this question we have developed a novel learning paradigm for Mongolian gerbils, which not only allows rewards and punishments to be presented in isolation or in combination with each other, but also can use these opposite reinforcers to drive the same learned behavior. Specifically, we studied learning of tone-conditioned hurdle crossing in a shuttle box driven by either an appetitive reinforcer (brain stimulation reward) or an aversive reinforcer (electrical footshock), or by a combination of both. Combination of the two reinforcers potentiated speed of acquisition, led to maximum possible performance, and delayed extinction as compared to either reinforcer alone. Additional experiments, using partial reinforcement protocols and experiments in which one of the reinforcers was omitted after the animals had been previously trained with the combination of both reinforcers, indicated that appetitive and aversive reinforcers operated together but acted in different ways: in this particular experimental context, punishment appeared to be more effective for initial acquisition and reward more effective to maintain a high level of conditioned responses (CRs). The results imply that learning mechanisms in problem solving were maximally effective when the initial punishment of mistakes was combined with the subsequent rewarding of correct performance. Copyright 2010 IBRO. Published by Elsevier Ltd. All rights reserved.

  17. An approach for investigation of secure access processes at a combined e-learning environment

    Science.gov (United States)

    Romansky, Radi; Noninska, Irina

    2017-12-01

    The article discuses an approach to investigate processes for regulation the security and privacy control at a heterogenous e-learning environment realized as a combination of traditional and cloud means and tools. Authors' proposal for combined architecture of e-learning system is presented and main subsystems and procedures are discussed. A formalization of the processes for using different types resources (public, private internal and private external) is proposed. The apparatus of Markovian chains (MC) is used for modeling and analytical investigation of the secure access to the resources is used and some assessments are presented.

  18. Psychometric Properties of the Epistemological Development in Teaching Learning Questionnaire (EDTLQ): An Inventory to Measure Higher Order Epistemological Development

    Science.gov (United States)

    Kjellström, Sofia; Golino, Hudson; Hamer, Rebecca; Van Rossum, Erik Jan; Almers, Ellen

    2016-01-01

    Qualitative research supports a developmental dimension in views on teaching and learning, but there are currently no quantitative tools to measure the full range of this development. To address this, we developed the Epistemological Development in Teaching and Learning Questionnaire (EDTLQ). In the current study the psychometric properties of the…

  19. Kolb's Learning Style Inventory-1985: Validity Issues and Relations with Metacognitive Knowledge about Problem-Solving Strategies

    Science.gov (United States)

    Metallidou, Panayiota; Platsidou, Maria

    2008-01-01

    This study aimed at investigating: (a) the psychometric properties of Kolb's LSI-1985 in a Greek sample of pre-service and in-service teachers (N=338), (b) group differences in their learning styles and (c) possible relations between the participants' learning styles and their metacognitive knowledge about the frequency of using various…

  20. Examining the benefits of combining two learning strategies on recall of functional information in persons with multiple sclerosis.

    Science.gov (United States)

    Goverover, Yael; Basso, Michael; Wood, Hali; Chiaravalloti, Nancy; DeLuca, John

    2011-12-01

    Forgetfulness occurs commonly in people with multiple sclerosis (MS), but few treatments alleviate this problem. This study examined the combined effect of two cognitive rehabilitation strategies to improve learning and memory in MS: self-generation and spaced learning. The hypothesis was that the combination of spaced learning and self-generation would yield better learning and memory recall performance than spaced learning alone. Using a within groups design, 20 participants with MS and 18 healthy controls (HC) were presented with three tasks (learning names, appointment, and object location), each in three learning conditions (Massed, Spaced Learning, and combination of spaced and generated information). Participants were required to recall the information they learned in each of these conditions immediately and 30 min following the initial presentation. The combination of spaced learning and self-generation yielded better recall than did spaced learning alone. In turn, spaced learning resulted in better recall than the massed rehearsal condition. These findings reveal that the combination of these two learning strategies may possess utility as a cognitive rehabilitation strategy.

  1. Personal computer versus personal computer/mobile device combination users' preclinical laboratory e-learning activity.

    Science.gov (United States)

    Kon, Haruka; Kobayashi, Hiroshi; Sakurai, Naoki; Watanabe, Kiyoshi; Yamaga, Yoshiro; Ono, Takahiro

    2017-11-01

    The aim of the present study was to clarify differences between personal computer (PC)/mobile device combination and PC-only user patterns. We analyzed access frequency and time spent on a complete denture preclinical website in order to maximize website effectiveness. Fourth-year undergraduate students (N=41) in the preclinical complete denture laboratory course were invited to participate in this survey during the final week of the course to track login data. Students accessed video demonstrations and quizzes via our e-learning site/course program, and were instructed to view online demonstrations before classes. When the course concluded, participating students filled out a questionnaire about the program, their opinions, and devices they had used to access the site. Combination user access was significantly more frequent than PC-only during supplementary learning time, indicating that students with mobile devices studied during lunch breaks and before morning classes. Most students had favorable opinions of the e-learning site, but a few combination users commented that some videos were too long and that descriptive answers were difficult on smartphones. These results imply that mobile devices' increased accessibility encouraged learning by enabling more efficient time use between classes. They also suggest that e-learning system improvements should cater to mobile device users by reducing video length and including more short-answer questions. © 2016 John Wiley & Sons Australia, Ltd.

  2. Collaborative Learning in Architectural Education: Benefits of Combining Conventional Studio, Virtual Design Studio and Live Projects

    Science.gov (United States)

    Rodriguez, Carolina; Hudson, Roland; Niblock, Chantelle

    2018-01-01

    Combinations of Conventional Studio and Virtual Design Studio (VDS) have created valuable learning environments that take advantage of different instruments of communication and interaction. However, past experiences have reported limitations in regards to student engagement and motivation, especially when the studio projects encourage abstraction…

  3. Capstone Teaching Models: Combining Simulation, Analytical Intuitive Learning Processes, History and Effectiveness

    Science.gov (United States)

    Reid, Maurice; Brown, Steve; Tabibzadeh, Kambiz

    2012-01-01

    For the past decade teaching models have been changing, reflecting the dynamics, complexities, and uncertainties of today's organizations. The traditional and the more current active models of learning have disadvantages. Simulation provides a platform to combine the best aspects of both types of teaching practices. This research explores the…

  4. Combining Self-Explaining with Computer Architecture Diagrams to Enhance the Learning of Assembly Language Programming

    Science.gov (United States)

    Hung, Y.-C.

    2012-01-01

    This paper investigates the impact of combining self explaining (SE) with computer architecture diagrams to help novice students learn assembly language programming. Pre- and post-test scores for the experimental and control groups were compared and subjected to covariance (ANCOVA) statistical analysis. Results indicate that the SE-plus-diagram…

  5. Elemental representation and configural mappings: combining elemental and configural theories of associative learning.

    Science.gov (United States)

    McLaren, I P L; Forrest, C L; McLaren, R P

    2012-09-01

    In this article, we present our first attempt at combining an elemental theory designed to model representation development in an associative system (based on McLaren, Kaye, & Mackintosh, 1989) with a configural theory that models associative learning and memory (McLaren, 1993). After considering the possible advantages of such a combination (and some possible pitfalls), we offer a hybrid model that allows both components to produce the phenomena that they are capable of without introducing unwanted interactions. We then successfully apply the model to a range of phenomena, including latent inhibition, perceptual learning, the Espinet effect, and first- and second-order retrospective revaluation. In some cases, we present new data for comparison with our model's predictions. In all cases, the model replicates the pattern observed in our experimental results. We conclude that this line of development is a promising one for arriving at general theories of associative learning and memory.

  6. Development of radiation oncology learning system combined with multi-institutional radiotherapy database (ROGAD)

    Energy Technology Data Exchange (ETDEWEB)

    Takemura, Akihiro; Iinuma, Masahiro; Kou, Hiroko [Kanazawa Univ. (Japan). School of Medicine; Harauchi, Hajime; Inamura, Kiyonari

    1999-09-01

    We have constructed and are operating a multi-institutional radiotherapy database ROGAD (Radiation Oncology Greater Area Database) since 1992. One of it's purpose is 'to optimize individual radiotherapy plans'. We developed Radiation oncology learning system combined with ROGAD' which conforms to that purpose. Several medical doctors evaluated our system. According to those evaluations, we are now confident that our system is able to contribute to improvement of radiotherapy results. Our final target is to generate a good cyclic relationship among three components: radiotherapy results according to ''Radiation oncology learning system combined with ROGAD.'; The growth of ROGAD; and radiation oncology learning system. (author)

  7. The Effect of Contextual Teaching and Learning Combined with Peer Tutoring towards Learning Achievement on Human Digestive System Concept

    Directory of Open Access Journals (Sweden)

    Farhah Abadiyah

    2017-11-01

    Full Text Available This research aims to know the influence of contextual teaching and learning (CTL combined with peer tutoring toward learning achievement on human digestive system concept. This research was conducted at one of State Senior High School in South Tangerang in the academic year of 2016/2017. The research method was quasi experiment with nonequivalent pretest-postest control group design. The sample was taken by simple random sampling. The total of the sampels were 86 students which consisted of 44 students as a controlled group and 42 students as an experimental group. The research instrument was objective test which consisted of 25 multiple choice items of each pretest and posttest. The research also used observation sheets for teacher and students activity. The result of data analysis using t-test on the two groups show that the value of tcount was 2.40 and ttable was 1.99 on significant level α = 0,05, so that tcount > ttable.. This result indicated that there was influence of contextual teaching and learning (CTL combined with peer tutoring toward learning achievement on human digestive system concept.

  8. On Combining Multiple-Instance Learning and Active Learning for Computer-Aided Detection of Tuberculosis

    NARCIS (Netherlands)

    Melendez Rodriguez, J.C.; Ginneken, B. van; Maduskar, P.; Philipsen, R.H.H.M.; Ayles, H.; Sanchez, C.I.

    2016-01-01

    The major advantage of multiple-instance learning (MIL) applied to a computer-aided detection (CAD) system is that it allows optimizing the latter with case-level labels instead of accurate lesion outlines as traditionally required for a supervised approach. As shown in previous work, a MIL-based

  9. An integer batch scheduling model considering learning, forgetting, and deterioration effects for a single machine to minimize total inventory holding cost

    Science.gov (United States)

    Yusriski, R.; Sukoyo; Samadhi, T. M. A. A.; Halim, A. H.

    2018-03-01

    This research deals with a single machine batch scheduling model considering the influenced of learning, forgetting, and machine deterioration effects. The objective of the model is to minimize total inventory holding cost, and the decision variables are the number of batches (N), batch sizes (Q[i], i = 1, 2, .., N) and the sequence of processing the resulting batches. The parts to be processed are received at the right time and the right quantities, and all completed parts must be delivered at a common due date. We propose a heuristic procedure based on the Lagrange method to solve the problem. The effectiveness of the procedure is evaluated by comparing the resulting solution to the optimal solution obtained from the enumeration procedure using the integer composition technique and shows that the average effectiveness is 94%.

  10. A Machine Learning Method for Co-Registration and Individual Tree Matching of Forest Inventory and Airborne Laser Scanning Data

    Directory of Open Access Journals (Sweden)

    Sebastian Lamprecht

    2017-05-01

    Full Text Available Determining the exact position of a forest inventory plot—and hence the position of the sampled trees—is often hampered by a poor Global Navigation Satellite System (GNSS signal quality beneath the forest canopy. Inaccurate geo-references hamper the performance of models that aim to retrieve useful information from spatially high remote sensing data (e.g., species classification or timber volume estimation. This restriction is even more severe on the level of individual trees. The objective of this study was to develop a post-processing strategy to improve the positional accuracy of GNSS-measured sample-plot centers and to develop a method to automatically match trees within a terrestrial sample plot to aerial detected trees. We propose a new method which uses a random forest classifier to estimate the matching probability of each terrestrial-reference and aerial detected tree pair, which gives the opportunity to assess the reliability of the results. We investigated 133 sample plots of the Third German National Forest Inventory (BWI, 2011–2012 within the German federal state of Rhineland-Palatinate. For training and objective validation, synthetic forest stands have been modeled using the Waldplaner 2.0 software. Our method has achieved an overall accuracy of 82.7% for co-registration and 89.1% for tree matching. With our method, 60% of the investigated plots could be successfully relocated. The probabilities provided by the algorithm are an objective indicator of the reliability of a specific result which could be incorporated into quantitative models to increase the performance of forest attribute estimations.

  11. Combining Digital Archives Content with Serious Game Approach to Create a Gamified Learning Experience

    Directory of Open Access Journals (Sweden)

    D.-T. Shih

    2015-08-01

    Full Text Available This paper presents an interdisciplinary to develop content-aware application that combines game with learning on specific categories of digital archives. The employment of content-oriented game enhances the gamification and efficacy of learning in culture education on architectures and history of Hsinchu County, Taiwan. The gamified form of the application is used as a backbone to support and provide a strong stimulation to engage users in learning art and culture, therefore this research is implementing under the goal of “The Digital ARt/ARchitecture Project”. The purpose of the abovementioned project is to develop interactive serious game approaches and applications for Hsinchu County historical archives and architectures. Therefore, we present two applications, “3D AR for Hukou Old ” and “Hsinchu County History Museum AR Tour” which are in form of augmented reality (AR. By using AR imaging techniques to blend real object and virtual content, the users can immerse in virtual exhibitions of Hukou Old Street and Hsinchu County History Museum, and to learn in ubiquitous computing environment. This paper proposes a content system that includes tools and materials used to create representations of digitized cultural archives including historical artifacts, documents, customs, religion, and architectures. The Digital ARt / ARchitecture Project is based on the concept of serious game and consists of three aspects: content creation, target management, and AR presentation. The project focuses on developing a proper approach to serve as an interactive game, and to offer a learning opportunity for appreciating historic architectures by playing AR cards. Furthermore, the card game aims to provide multi-faceted understanding and learning experience to help user learning through 3D objects, hyperlinked web data, and the manipulation of learning mode, and then effectively developing their learning levels on cultural and historical archives in

  12. Combining Digital Archives Content with Serious Game Approach to Create a Gamified Learning Experience

    Science.gov (United States)

    Shih, D.-T.; Lin, C. L.; Tseng, C.-Y.

    2015-08-01

    This paper presents an interdisciplinary to develop content-aware application that combines game with learning on specific categories of digital archives. The employment of content-oriented game enhances the gamification and efficacy of learning in culture education on architectures and history of Hsinchu County, Taiwan. The gamified form of the application is used as a backbone to support and provide a strong stimulation to engage users in learning art and culture, therefore this research is implementing under the goal of "The Digital ARt/ARchitecture Project". The purpose of the abovementioned project is to develop interactive serious game approaches and applications for Hsinchu County historical archives and architectures. Therefore, we present two applications, "3D AR for Hukou Old " and "Hsinchu County History Museum AR Tour" which are in form of augmented reality (AR). By using AR imaging techniques to blend real object and virtual content, the users can immerse in virtual exhibitions of Hukou Old Street and Hsinchu County History Museum, and to learn in ubiquitous computing environment. This paper proposes a content system that includes tools and materials used to create representations of digitized cultural archives including historical artifacts, documents, customs, religion, and architectures. The Digital ARt / ARchitecture Project is based on the concept of serious game and consists of three aspects: content creation, target management, and AR presentation. The project focuses on developing a proper approach to serve as an interactive game, and to offer a learning opportunity for appreciating historic architectures by playing AR cards. Furthermore, the card game aims to provide multi-faceted understanding and learning experience to help user learning through 3D objects, hyperlinked web data, and the manipulation of learning mode, and then effectively developing their learning levels on cultural and historical archives in Hsinchu County.

  13. Obtaining Global Picture From Single Point Observations by Combining Data Assimilation and Machine Learning Tools

    Science.gov (United States)

    Shprits, Y.; Zhelavskaya, I. S.; Kellerman, A. C.; Spasojevic, M.; Kondrashov, D. A.; Ghil, M.; Aseev, N.; Castillo Tibocha, A. M.; Cervantes Villa, J. S.; Kletzing, C.; Kurth, W. S.

    2017-12-01

    Increasing volume of satellite measurements requires deployment of new tools that can utilize such vast amount of data. Satellite measurements are usually limited to a single location in space, which complicates the data analysis geared towards reproducing the global state of the space environment. In this study we show how measurements can be combined by means of data assimilation and how machine learning can help analyze large amounts of data and can help develop global models that are trained on single point measurement. Data Assimilation: Manual analysis of the satellite measurements is a challenging task, while automated analysis is complicated by the fact that measurements are given at various locations in space, have different instrumental errors, and often vary by orders of magnitude. We show results of the long term reanalysis of radiation belt measurements along with fully operational real-time predictions using data assimilative VERB code. Machine Learning: We present application of the machine learning tools for the analysis of NASA Van Allen Probes upper-hybrid frequency measurements. Using the obtained data set we train a new global predictive neural network. The results for the Van Allen Probes based neural network are compared with historical IMAGE satellite observations. We also show examples of predictions of geomagnetic indices using neural networks. Combination of machine learning and data assimilation: We discuss how data assimilation tools and machine learning tools can be combine so that physics-based insight into the dynamics of the particular system can be combined with empirical knowledge of it's non-linear behavior.

  14. The Use of a Hybrid Strategy Combining Problem-based Learning and Magisterial Lectures to Enhance Learning

    Directory of Open Access Journals (Sweden)

    Carlos Alberto Acosta-Nassar

    2014-09-01

    Full Text Available This paper addresses the problem of capturing the attention of intermediate level students in the Thermodynamics 1 course from the Mechanical and Agricultural Engineering Program, with the purpose of helping students improve their learning process. A hybrid teaching strategy was proposed based on Problem-based Learning (PBL principles combined with magisterial lectures. Digital and traditional didactic resources were also used in order to find the best mean to minimize the lack of attention in learners. The strategy was developed by sensitizing students to get involved in their formation process. PowerPoint presentations, video clips, the traditional white board and an ultra slim digital tablet board were used to develop the theoretical issues and present the solutions to the problems chosen for the PBL strategy. Finally, the strategy was evaluated and results were analyzed, indicating that using a hybrid strategy combining PBL and traditional magisterial lectures is an optimal resource to improve the learning process of students taking Thermodynamics 1. In addition, it was also concluded that the ultra slim digital tablet board is the optimal didactic resource.

  15. Orthographic learning in children with isolated and combined reading and spelling deficits.

    Science.gov (United States)

    Mehlhase, Heike; Bakos, Sarolta; Landerl, Karin; Schulte-Körne, Gerd; Moll, Kristina

    2018-05-07

    Dissociations between reading and spelling problems are likely to be associated with different underlying cognitive deficits, and with different deficits in orthographic learning. In order to understand these differences, the current study examined orthographic learning using a printed-word learning paradigm. Children (4th grade) with isolated reading, isolated spelling and combined reading and spelling problems were compared to children with age appropriate reading and spelling skills on their performance during learning novel words and symbols (non-verbal control condition), and during immediate and delayed reading and spelling recall tasks. No group differences occurred in the non-verbal control condition. In the verbal condition, initial learning was intact in all groups, but differences occurred during recall tasks. Children with reading fluency deficits showed slower reading times, while children with spelling deficits were less accurate, both in reading and spelling recall. Children with isolated spelling problems showed no difficulties in immediate spelling recall, but had problems in remembering the spellings 2 hours later. The results suggest that different orthographic learning deficits underlie reading fluency and spelling problems: Children with isolated reading fluency deficits have no difficulties in building-up orthographic representations, but access to these representations is slowed down while children with isolated spelling deficits have problems in storing precise orthographic representations in long-term memory.

  16. Combining bimodal presentation schemes and buzz groups improves clinical reasoning and learning at morning report.

    Science.gov (United States)

    Balslev, Thomas; Rasmussen, Astrid Bruun; Skajaa, Torjus; Nielsen, Jens Peter; Muijtjens, Arno; De Grave, Willem; Van Merriënboer, Jeroen

    2014-12-11

    Abstract Morning reports offer opportunities for intensive work-based learning. In this controlled study, we measured learning processes and outcomes with the report of paediatric emergency room patients. Twelve specialists and 12 residents were randomised into four groups and discussed the same two paediatric cases. The groups differed in their presentation modality (verbal only vs. verbal + text) and the use of buzz groups (with vs. without). The verbal interactions were analysed for clinical reasoning processes. Perceptions of learning and judgment of learning were reported in a questionnaire. Diagnostic accuracy was assessed by a 20-item multiple-choice test. Combined bimodal presentation and buzz groups increased the odds ratio of clinical reasoning to occur in the discussion of cases by a factor of 1.90 (p = 0.013), indicating superior reasoning for buzz groups working with bimodal materials. For specialists, a positive effect of bimodal presentation was found on perceptions of learning (p presentation on diagnostic accuracy was noted in the specialists (p presentation and buzz group discussion of emergency cases improves clinicians' clinical reasoning and learning.

  17. Improving estimates of forest disturbance by combining observations from Landsat time series with U.S. Forest Service Forest Inventory and Analysis data

    Science.gov (United States)

    Todd A. Schroeder; Sean P. Healey; Gretchen G. Moisen; Tracey S. Frescino; Warren B. Cohen; Chengquan Huang; Robert E. Kennedy; Zhiqiang Yang

    2014-01-01

    With earth's surface temperature and human population both on the rise a new emphasis has been placed on monitoring changes to forested ecosystems the world over. In the United States the U.S. Forest Service Forest Inventory and Analysis (FIA) program monitors the forested land base with field data collected over a permanent network of sample plots. Although these...

  18. Optimization of Inventory

    OpenAIRE

    PROKOPOVÁ, Nikola

    2017-01-01

    The subject of this thesis is optimization of inventory in selected organization. Inventory optimization is a very important topic in each organization because it reduces storage costs. At the beginning the inventory theory is presented. It shows the meaning and types of inventory, inventory control and also different methods and models of inventory control. Inventory optimization in the enterprise can be reached by using models of inventory control. In the second part the company on which is...

  19. Combined impact of exercise and temperature in learning and memory performance of fluoride toxicated rats.

    Science.gov (United States)

    Basha, P Mahaboob; Sujitha, N S

    2012-12-01

    In previous studies, we investigated a link between high fluoride exposure and functional IQ deficits in rats. This study is an extension conducted to explore the combined influence of physical exercise and temperature stress on the learning ability and memory in rats and to assess whether any positive modulation could be attenuated due to exercise regimen subjected to F-toxicated animals at different temperatures. Accumulation of ingested fluoride resulted significant inhibition in acetylcholinesterase activity (P learning phase [F (5, 35) = 19.065; P temperatures, high (35 °C) and low temperatures (20 °C) led to a slower acquisition and poor retention of the task when compared to thermo neutral temperatures (25 and 30 °C). Thus exercise up-regulate antioxidant defenses and promote learning abilities in fluorotic population.

  20. Representation and Integration: Combining Robot Control, High-Level Planning, and Action Learning

    DEFF Research Database (Denmark)

    Petrick, Ronald; Kraft, Dirk; Mourao, Kira

    We describe an approach to integrated robot control, high-level planning, and action effect learning that attempts to overcome the representational difficulties that exist between these diverse areas. Our approach combines ideas from robot vision, knowledgelevel planning, and connectionist machine......-level action specifications, suitable for planning, from a robot’s interactions with the world. We present a detailed overview of our approach and show how it supports the learning of certain aspects of a high-level lepresentation from low-level world state information....... learning, and focuses on the representational needs of these components.We also make use of a simple representational unit called an instantiated state transition fragment (ISTF) and a related structure called an object-action complex (OAC). The goal of this work is a general approach for inducing high...

  1. Monocular perceptual learning of contrast detection facilitates binocular combination in adults with anisometropic amblyopia.

    Science.gov (United States)

    Chen, Zidong; Li, Jinrong; Liu, Jing; Cai, Xiaoxiao; Yuan, Junpeng; Deng, Daming; Yu, Minbin

    2016-02-01

    Perceptual learning in contrast detection improves monocular visual function in adults with anisometropic amblyopia; however, its effect on binocular combination remains unknown. Given that the amblyopic visual system suffers from pronounced binocular functional loss, it is important to address how the amblyopic visual system responds to such training strategies under binocular viewing conditions. Anisometropic amblyopes (n = 13) were asked to complete two psychophysical supra-threshold binocular summation tasks: (1) binocular phase combination and (2) dichoptic global motion coherence before and after monocular training to investigate this question. We showed that these participants benefited from monocular training in terms of binocular combination. More importantly, the improvements observed with the area under log CSF (AULCSF) were found to be correlated with the improvements in binocular phase combination.

  2. Adaptive rival penalized competitive learning and combined linear predictor model for financial forecast and investment.

    Science.gov (United States)

    Cheung, Y M; Leung, W M; Xu, L

    1997-01-01

    We propose a prediction model called Rival Penalized Competitive Learning (RPCL) and Combined Linear Predictor method (CLP), which involves a set of local linear predictors such that a prediction is made by the combination of some activated predictors through a gating network (Xu et al., 1994). Furthermore, we present its improved variant named Adaptive RPCL-CLP that includes an adaptive learning mechanism as well as a data pre-and-post processing scheme. We compare them with some existing models by demonstrating their performance on two real-world financial time series--a China stock price and an exchange-rate series of US Dollar (USD) versus Deutschmark (DEM). Experiments have shown that Adaptive RPCL-CLP not only outperforms the other approaches with the smallest prediction error and training costs, but also brings in considerable high profits in the trading simulation of foreign exchange market.

  3. Combining different Technologies in a Funerary Archaeology content and language integrated Learning (CLIL) Course

    OpenAIRE

    Cignoni, Laura; Fornaciari, Gino

    2009-01-01

    The aim of this paper is to describe a project in which Italian undergraduate students at the Palaeopathology Division of Pisa University will attend a two-year Content and Language Integrated Learning (CLIL) course combining the study of funerary archaeology with English as vehicular language. At the presence of a subject and language teacher working together, the trainees will use different types of technology including devices such as electronic blackboards and Word applications with user-...

  4. Monocular perceptual learning of contrast detection facilitates binocular combination in adults with anisometropic amblyopia

    OpenAIRE

    Chen, Zidong; Li, Jinrong; Liu, Jing; Cai, Xiaoxiao; Yuan, Junpeng; Deng, Daming; Yu, Minbin

    2016-01-01

    Perceptual learning in contrast detection improves monocular visual function in adults with anisometropic amblyopia; however, its effect on binocular combination remains unknown. Given that the amblyopic visual system suffers from pronounced binocular functional loss, it is important to address how the amblyopic visual system responds to such training strategies under binocular viewing conditions. Anisometropic amblyopes (n?=?13) were asked to complete two psychophysical supra-threshold binoc...

  5. Combining Unsupervised and Supervised Statistical Learning Methods for Currency Exchange Rate Forecasting

    OpenAIRE

    Vasiljeva, Polina

    2016-01-01

    In this thesis we revisit the challenging problem of forecasting currency exchange rate. We combine machine learning methods such as agglomerative hierarchical clustering and random forest to construct a two-step approach for predicting movements in currency exchange prices of the Swedish krona and the US dollar. We use a data set with over 200 predictors comprised of different financial and macro-economic time series and their transformations. We perform forecasting for one week ahead with d...

  6. Empowerment of Students Critical Thinking Skills Through Implementation of Think Talk Write Combined Problem Based Learning

    OpenAIRE

    Yanuarta, Lidya; Gofur, Abdul; Indriwati, Sri Endah

    2016-01-01

    Critical thinking is a complex reflection process that helps individuals become more analytical in their thinking. Empower critical thinking in students need to be done so that students can resolve the problems that exist in their life and are able to apply alternative solutions to problems in a different situations. Therefore, Think Talk Write (TTW) combined Problem Based Learning (PBL) were needed to empowered the critical thinking skills so that students were able to face the challenges of...

  7. Using video games to combine learning and assessment in mathematics education

    OpenAIRE

    Kristian Juha Mikael Kiili; Keith Devlin; Arttu Perttula; Pauliina Tuomi; Antero Lindstedt

    2015-01-01

    One problem with most education systems is that learning and (summative) assessment are generally treated as quite separate things in schools. We argue that video games can provide an opportunity to combine these processes in an engaging and effective way. The present study focuses on investigating the effectiveness and the assessment power of two different mathematics video games, Semideus and Wuzzit Trouble. In the current study, we validated the Semideus game as a rational number test inst...

  8. A cross-cultural validation of the Technology-Rich Outcomes-Focused Learning Environment Inventory (TROFLEI) in Turkey and the USA

    Science.gov (United States)

    Welch, Anita G.; Cakir, Mustafa; Peterson, Claudette M.; Ray, Chris M.

    2012-04-01

    Background . Studies exploring the relationship between students' achievement and the quality of the classroom learning environments have shown that there is a strong relationship between these two concepts. Learning environment instruments are constantly being revised and updated, including for use in different cultures, which requires continued validation efforts. Purpose The purpose of this study was to establish cross-cultural reliability and validity of the Technology-Rich Outcomes-Focused Learning Environment Inventory (TROFLEI) in both Turkey and the USA. Sample Approximately 980 students attending grades 9-12 in Turkey and 130 students attending grades 9-12 in the USA participated in the study. Design and method Scale reliability analyses and confirmatory factor analysis (CFA) were performed separately for Turkish and US participants for both actual and preferred responses to each scale to confirm the structure of the TROFLEI across these two distinct samples. Results Cronbach's alpha reliability coefficients, ranging from α = 0.820 to 0.931 for Turkish participants and from α = 0.778 to 0.939 for US participants, indicated that all scales have satisfactory internal consistency for both samples. Confirmatory factor analyses resulted in evidence of adequate model fit across both samples for both actual and preferred responses, with the root mean square error of approximation ranging from 0.052 to 0.057 and the comparative fit index ranging from 0.920 to 0.982. Conclusions This study provides initial evidence that the TROFLEI is valid for use in both the Turkish and US high-school populations (grades 9-12). However, the psychometric properties should be examined further with different populations, such as middle-school students (grades 6-8).

  9. On Combining Elements of Different Ways of Learning, Methods and Knowledge

    Directory of Open Access Journals (Sweden)

    Dušana Findeisen

    2013-12-01

    Full Text Available The paper deals with different thinkers' attitude towards methods in adult education. It examines the value of some elements of »trial and error learning« and »non-directive learning«. Like a multifaceted approach based on elements drawn from different methods, the way we learn can also be eclectic.  To illustrate this assertion, the author analyses the »anti method« used by Maurice Pialat, a French film director, contrasting it with methods in which the aim is set in advance and the process leading towards it is organised in sequences. This is most often the case in script-based shooting of films, directing a theatre performance or running adult education. Moreover, the author argues that learning about how to do something is combined with learning about how to be. She further emphasises that methods should not be used to impose one’s knowledge and one’s reality on the learner, thus destroying circumstances necessary for gaining or creating knowledge.

  10. Inventory Abstraction

    International Nuclear Information System (INIS)

    Leigh, C.

    2000-01-01

    The purpose of the inventory abstraction as directed by the development plan (CRWMS M and O 1999b) is to: (1) Interpret the results of a series of relative dose calculations (CRWMS M and O 1999c, 1999d). (2) Recommend, including a basis thereof, a set of radionuclides that should be modeled in the Total System Performance Assessment in Support of the Site Recommendation (TSPA-SR) and the Total System Performance Assessment in Support of the Final Environmental Impact Statement (TSPA-FEIS). (3) Provide initial radionuclide inventories for the TSPA-SR and TSPA-FEIS models. (4) Answer the U.S. Nuclear Regulatory Commission (NRC)'s Issue Resolution Status Report ''Key Technical Issue: Container Life and Source Term'' (CLST IRSR) (NRC 1999) key technical issue (KTI): ''The rate at which radionuclides in SNF [Spent Nuclear Fuel] are released from the EBS [Engineered Barrier System] through the oxidation and dissolution of spent fuel'' (Subissue 3). The scope of the radionuclide screening analysis encompasses the period from 100 years to 10,000 years after the potential repository at Yucca Mountain is sealed for scenarios involving the breach of a waste package and subsequent degradation of the waste form as required for the TSPA-SR calculations. By extending the time period considered to one million years after repository closure, recommendations are made for the TSPA-FEIS. The waste forms included in the inventory abstraction are Commercial Spent Nuclear Fuel (CSNF), DOE Spent Nuclear Fuel (DSNF), High-Level Waste (HLW), naval Spent Nuclear Fuel (SNF), and U.S. Department of Energy (DOE) plutonium waste. The intended use of this analysis is in TSPA-SR and TSPA-FEIS. Based on the recommendations made here, models for release, transport, and possibly exposure will be developed for the isotopes that would be the highest contributors to the dose given a release to the accessible environment. The inventory abstraction is important in assessing system performance because

  11. INVENTORY ABSTRACTION

    International Nuclear Information System (INIS)

    Ragan, G.

    2001-01-01

    The purpose of the inventory abstraction, which has been prepared in accordance with a technical work plan (CRWMS M andO 2000e for/ICN--02 of the present analysis, and BSC 2001e for ICN 03 of the present analysis), is to: (1) Interpret the results of a series of relative dose calculations (CRWMS M andO 2000c, 2000f). (2) Recommend, including a basis thereof, a set of radionuclides that should be modeled in the Total System Performance Assessment in Support of the Site Recommendation (TSPA-SR) and the Total System Performance Assessment in Support of the Final Environmental Impact Statement (TSPA-FEIS). (3) Provide initial radionuclide inventories for the TSPA-SR and TSPA-FEIS models. (4) Answer the U.S. Nuclear Regulatory Commission (NRC)'s Issue Resolution Status Report ''Key Technical Issue: Container Life and Source Term'' (CLST IRSR) key technical issue (KTI): ''The rate at which radionuclides in SNF [spent nuclear fuel] are released from the EBS [engineered barrier system] through the oxidation and dissolution of spent fuel'' (NRC 1999, Subissue 3). The scope of the radionuclide screening analysis encompasses the period from 100 years to 10,000 years after the potential repository at Yucca Mountain is sealed for scenarios involving the breach of a waste package and subsequent degradation of the waste form as required for the TSPA-SR calculations. By extending the time period considered to one million years after repository closure, recommendations are made for the TSPA-FEIS. The waste forms included in the inventory abstraction are Commercial Spent Nuclear Fuel (CSNF), DOE Spent Nuclear Fuel (DSNF), High-Level Waste (HLW), naval Spent Nuclear Fuel (SNF), and U.S. Department of Energy (DOE) plutonium waste. The intended use of this analysis is in TSPA-SR and TSPA-FEIS. Based on the recommendations made here, models for release, transport, and possibly exposure will be developed for the isotopes that would be the highest contributors to the dose given a release

  12. Note on ‘Combining an Improved Multi-delivery Policy into a Single-producer Multi-retailer Integrated Inventory System with Scrap in Production’

    OpenAIRE

    Chung-li Chou; Wen Kuei Wu; Singa W. Chiu

    2014-01-01

    In a recent study, Chiu et al. (2014) employed a mathematical modeling and conventional optimization technique to determine the optimal production-shipment policy for a single-producer multi-retailer integrated inventory system with scrap and an improved product distribution policy. This study replaces their optimization process of using differential calculus with an algebraic derivation. Such a simplified approach enables practitioners, who may have insufficient knowledge of calculus, to man...

  13. Forest Carbon Storage in the Northern Midwest, USA: A Bottom-Up Scaling Approach Combining Local Meteorological and Biometric Data With Regional Forest Inventories

    Science.gov (United States)

    Curtis, P. S.; Gough, C. M.; Vogel, C. S.

    2005-12-01

    Carbon (C) storage increasingly is considered an important part of the economic return of forestlands, making easily parameterized models for assessing current and future C storage important for both ecosystem and money managers. For the deciduous forests of the northern midwest, USA, detailed information relating annual C storage to local site characteristics can be combined with spatially extensive forest inventories to produce simple, robust models of C storage useful at a variety of scales. At the University of Michigan Biological Station (45o35`' N, 84o42`' W) we measured C storage, or net ecosystem production (NEP), in 65 forest stands varying in age, disturbance history, and productivity (site index) using biometric methods, and independently measured net C exchange at the landscape level using meteorological methods. Our biometric and meteorological estimates of NEP converged to within 1% of each other over five years, providing important confirmation of the robustness of these two approaches applied within northern deciduous forests (Gough et al. 2005). We found a significant relationship between NEP, stand age ( A, yrs), and site index ( Is, m), where NEP = 0.134 + 0.022 * (LN[ A* Is]) (r2 = 0.50, P database (ncrs2.fs.fed.us/4801/fiadb/) to estimate forest C storage at different scales across the upper midwest, Great Lakes region. Model estimates were validated against independent estimates of C storage for other forests in the region. At the local ecosystem-level (~1 km2) C storage averaged 1.52 Mg ha-1 yr-1. Scaling to the two-county area surrounding our meteorological and biometric study sites, average stand age decreased and site index increased, resulting in estimated storage of 1.62 Mg C ha-1 yr-1, or 0.22 Tg C yr-1 in the 1350 km2 of deciduous forest in this area. For the state of Michigan (31,537 km2 of deciduous forest), average uptake was estimated at 1.55 Mg C ha-1 yr-1, or 4.9 Tg C yr-1 total storage. For the three state region encompassing

  14. Influences of combined traffic noise on the ability of learning and memory in mice

    Directory of Open Access Journals (Sweden)

    Guo-Qing Di

    2018-01-01

    Full Text Available Objective: The present study aimed to evaluate the influences of combined traffic noise (CTN on the ability of learning and memory in mice. Materials and Methods: The Institute of Cancer Research (ICR mice were exposed to CTN from highways and high-speed railways for 42 days, whose day–night equivalent continuous A-weighted sound pressure level (Ldn was 70 dB(A. On the basis of behavioral reactions in Morris water maze (MWM and the concentrations of amino acid neurotransmitters in the hippocampus, the impacts of CTN on learning and memory in mice were examined. Results: The MWM test showed that the ability of learning and memory in mice was improved after short-term exposure (6–10 days, the first batch to 70 dB(A CTN, which showed the excitatory effect of stimuli. Long-term exposure (26–30 days, the third batch; 36–40 days, the fourth batch led to the decline of learning and memory ability, which indicated the inhibitory effect of stimuli. Assays testing amino acid neurotransmitters showed that the glutamate level of the experimental group was higher than that of the control group in the first batch. However, the former was lower than the latter in the third and fourth batches. Both, behavioral reactions and the concentrations of amino acid neurotransmitters, testified that short-term exposure and long-term exposure resulted in excitatory effect and inhibitory effect on the ability of learning and memory, respectively. Conclusion: The effects of 70 dB(A CTN on the ability of learning and memory were closely related to the exposure duration. Furthermore, those effects were regulated and controlled by the level of glutamate in the hippocampus.

  15. Production inventory model for two-level trade credit financing under the effect of preservation technology and learning in supply chain

    Directory of Open Access Journals (Sweden)

    Sunil Kumar

    2015-12-01

    Full Text Available The present study investigated the inventory model for a retailer under two levels of trade credit to reflect the supply chain management. Supplier offers trade credit period of M to the retailer while in turn retailer provides a trade credit period of N to his/her customers. The supplier is willing to provide the retailer a full trade credit period for payments and the retailer offers the partial trade credit period to his/her customers. Here, selling items are considered as perishable items such as fruits, fresh fishes, gasoline, photographic films, etc. so that its potential worth decreases. It is assumed that decay in potential worth of items can be increased by using preservation technology. The demand is considered as the function of selling price and trade credit. Ordering cost can be reducing due to learning by doing phenomenon. By applying convex fractional programming results, we obtain necessary and sufficient conditions of an optimal solution. Some theorems are developed to determine retailer’s optimal ordering policies and numerical examples are given to illustrate these theorems. In addition, some managerial insights from the numerical examples are also concluded.

  16. Multiple benefits through intelligent combination. Economic inventory optimization through the use of photovoltaics; Mehrfachnutzen durch intelligente Kombination. Wirtschaftliche Bestandsoptimierung durch Nutzung von Photovoltaik

    Energy Technology Data Exchange (ETDEWEB)

    Anon.

    2013-10-15

    By installing a PV system the roof areas are additionally used for power generation. To ensure the operability permanently, they must be carefully planned, built and maintained. Based on three demonstration examples it is shown how inventory optimization can be achieved by maintaining high quality standards (tennis hall Oberthal and Ottweiler, warehouse roof of the building material dealer Lauer). [German] Durch die Installation einer PV-Anlage werden die Dachflaechen zusaetzlich zur Energiegewinnung genutzt. Um die Funktionsfaehigkeit dauerhaft zu gewaehrleisten, muessen sie sorgfaeltig geplant, gebaut und gewartet werden. Anhand von drei Demonstrationsbeispielen (Tennishalle Oberthal und Ottweiler, Lagerhallendach des Baustoffhaendlers Lauer) wird gezeigt, wie die Bestandsoptimierung unter Einhaltung hoher Qualitaetsstandards geloest werden kann.

  17. Assessment of a combined dry anaerobic digestion and post-composting treatment facility for source-separated organic household waste, using material and substance flow analysis and life cycle inventory

    DEFF Research Database (Denmark)

    Jensen, Morten Bang; Møller, Jacob; Scheutz, Charlotte

    2017-01-01

    with low uncertainties for non-volatile substances, while balances for nitrogen, carbon, volatile solids and total organic carbon showed larger but reasonable uncertainties, due to volatilisation and emissions into the air. Material and substance flow analyses were performed in order to obtain transfer...... to the biogas, 24% to the compost, 13% to residues and 40% into the atmosphere. For nitrogen, 69% was transferred to the compost, 10% volatilised to the biofilter, 11% directly into the atmosphere and 10% to residues. Finally, a full life cycle inventory was conducted for the combined dry anaerobic digestion...

  18. E-Learning Optimization: The Relative and Combined Effects of Mental Practice and Modeling on Enhanced Podcast-Based Learning--A Randomized Controlled Trial

    Science.gov (United States)

    Alam, Fahad; Boet, Sylvain; Piquette, Dominique; Lai, Anita; Perkes, Christopher P.; LeBlanc, Vicki R.

    2016-01-01

    Enhanced podcasts increase learning, but evidence is lacking on how they should be designed to optimize their effectiveness. This study assessed the impact two learning instructional design methods (mental practice and modeling), either on their own or in combination, for teaching complex cognitive medical content when incorporated into enhanced…

  19. Using Optimal Combination of Teaching-Learning Methods (Open Book Assignment and Group Tutorials) as Revision Exercises to Improve Learning Outcome in Low Achievers in Biochemistry

    Science.gov (United States)

    Rajappa, Medha; Bobby, Zachariah; Nandeesha, H.; Suryapriya, R.; Ragul, Anithasri; Yuvaraj, B.; Revathy, G.; Priyadarssini, M.

    2016-01-01

    Graduate medical students of India are taught Biochemistry by didactic lectures and they hardly get any opportunity to clarify their doubts and reinforce the concepts which they learn in these lectures. We used a combination of teaching-learning (T-L) methods (open book assignment followed by group tutorials) to study their efficacy in improving…

  20. QSAR modelling using combined simple competitive learning networks and RBF neural networks.

    Science.gov (United States)

    Sheikhpour, R; Sarram, M A; Rezaeian, M; Sheikhpour, E

    2018-04-01

    The aim of this study was to propose a QSAR modelling approach based on the combination of simple competitive learning (SCL) networks with radial basis function (RBF) neural networks for predicting the biological activity of chemical compounds. The proposed QSAR method consisted of two phases. In the first phase, an SCL network was applied to determine the centres of an RBF neural network. In the second phase, the RBF neural network was used to predict the biological activity of various phenols and Rho kinase (ROCK) inhibitors. The predictive ability of the proposed QSAR models was evaluated and compared with other QSAR models using external validation. The results of this study showed that the proposed QSAR modelling approach leads to better performances than other models in predicting the biological activity of chemical compounds. This indicated the efficiency of simple competitive learning networks in determining the centres of RBF neural networks.

  1. Cooperative learning combined with short periods of lecturing: A good alternative in teaching biochemistry.

    Science.gov (United States)

    Fernández-Santander, Ana

    2008-01-01

    The informal activities of cooperative learning and short periods of lecturing has been combined and used in the university teaching of biochemistry as part of the first year course of Optics and Optometry in the academic years 2004-2005 and 2005-2006. The lessons were previously elaborated by the teacher and included all that is necessary to understand the topic (text, figures, graphics, diagrams, pictures, etc.). Additionally, a questionnaire was prepared for every chapter. All lessons contained three parts: objectives, approach and development, and the assessment of the topic. Team work, responsibility, and communication skills were some of the abilities developed with this new methodology. Students worked collaboratively in small groups of two or three following the teacher's instructions with short periods of lecturing that clarified misunderstood concepts. Homework was minimized. On comparing this combined methodology with the traditional one (only lecture), students were found to exhibit a higher satisfaction with the new method. They were more involved in the learning process and had a better attitude toward the subject. The use of this new methodology showed a significant increase in the mean score of the students' academic results. The rate of students who failed the subject was significantly inferior in comparison with those who failed in the previous years when only lecturing was applied. This combined methodology helped the teacher to observe the apprenticeship process of students better and to act as a facilitator in the process of building students' knowledge. Copyright © 2008 International Union of Biochemistry and Molecular Biology, Inc.

  2. Unpacking "Active Learning": A Combination of Flipped Classroom and Collaboration Support Is More Effective but Collaboration Support Alone Is Not

    Science.gov (United States)

    Rau, Martina A.; Kennedy, Kristopher; Oxtoby, Lucas; Bollom, Mark; Moore, John W.

    2017-01-01

    Much evidence shows that instruction that actively engages students with learning materials is more effective than traditional, lecture-centric instruction. These "active learning" models comprise an extremely heterogeneous set of instructional methods: they often include collaborative activities, flipped classrooms, or a combination of…

  3. A combination of HARMONIE short time direct normal irradiance forecasts and machine learning: The #hashtdim procedure

    Science.gov (United States)

    Gastón, Martín; Fernández-Peruchena, Carlos; Körnich, Heiner; Landelius, Tomas

    2017-06-01

    The present work describes the first approach of a new procedure to forecast Direct Normal Irradiance (DNI): the #hashtdim that treats to combine ground information and Numerical Weather Predictions. The system is centered in generate predictions for the very short time. It combines the outputs from the Numerical Weather Prediction Model HARMONIE with an adaptive methodology based on Machine Learning. The DNI predictions are generated with 15-minute and hourly temporal resolutions and presents 3-hourly updates. Each update offers forecasts to the next 12 hours, the first nine hours are generated with 15-minute temporal resolution meanwhile the last three hours present hourly temporal resolution. The system is proved over a Spanish emplacement with BSRN operative station in south of Spain (PSA station). The #hashtdim has been implemented in the framework of the Direct Normal Irradiance Nowcasting methods for optimized operation of concentrating solar technologies (DNICast) project, under the European Union's Seventh Programme for research, technological development and demonstration framework.

  4. Taste aversion learning produced by combined treatment with subthreshold radiation and lithium chloride

    International Nuclear Information System (INIS)

    Rabin, B.M.; Hunt, W.A.; Lee, J.

    1987-01-01

    These experiments were designed to determine whether treatment with two subthreshold doses of radiation or lithium chloride, either alone or in combination, could lead to taste aversion learning. The first experiment determined the thresholds for a radiation-induced taste aversion at 15-20 rad and for lithium chloride at 0.30-0.45 mEq/kg. In the second experiment it was shown that exposing rats to two doses of 15 rad separated by up to 3 hr produced a taste aversion. Treatment with two injections of lithium chloride (0.30 mEq/kg) did not produce a significant reduction in preference. Combined treatment with radiation and lithium chloride did produce a taste aversion when the two treatments were administered within 1 hr of each other. The results are discussed in terms of the implications of these findings for understanding the nature of the unconditioned stimuli leading to the acquisition of a conditioned taste aversion

  5. Inventory differences: An evaluation methodology

    International Nuclear Information System (INIS)

    Heinberg, C.L.; Roberts, N.J.

    1987-01-01

    This paper discusses an evaluation methodology which is used for inventory differences at the Los Alamos National Laboratory. It is recognized that there are various methods which can be, and are being, used to evaluate process inventory differences at DOE facilities. The purpose of this paper is to share our thoughts on the subject and our techniques with those who are responsible for the evaluation of inventory differences at their facility. One of the most dangerous aspects of any evaluation technique, especially one as complex as most inventory difference evaluations tend to be, is to fail to look at the tools being used as indicators. There is a tendency to look at the results of an evaluation by one technique as an absolute. At the Los Alamos National Laboratory, several tools are used and the final evaluation is based on a combination of the observed results of a many-faceted evaluation. The tools used and some examples are presented

  6. Automatic plankton image classification combining multiple view features via multiple kernel learning.

    Science.gov (United States)

    Zheng, Haiyong; Wang, Ruchen; Yu, Zhibin; Wang, Nan; Gu, Zhaorui; Zheng, Bing

    2017-12-28

    Plankton, including phytoplankton and zooplankton, are the main source of food for organisms in the ocean and form the base of marine food chain. As the fundamental components of marine ecosystems, plankton is very sensitive to environment changes, and the study of plankton abundance and distribution is crucial, in order to understand environment changes and protect marine ecosystems. This study was carried out to develop an extensive applicable plankton classification system with high accuracy for the increasing number of various imaging devices. Literature shows that most plankton image classification systems were limited to only one specific imaging device and a relatively narrow taxonomic scope. The real practical system for automatic plankton classification is even non-existent and this study is partly to fill this gap. Inspired by the analysis of literature and development of technology, we focused on the requirements of practical application and proposed an automatic system for plankton image classification combining multiple view features via multiple kernel learning (MKL). For one thing, in order to describe the biomorphic characteristics of plankton more completely and comprehensively, we combined general features with robust features, especially by adding features like Inner-Distance Shape Context for morphological representation. For another, we divided all the features into different types from multiple views and feed them to multiple classifiers instead of only one by combining different kernel matrices computed from different types of features optimally via multiple kernel learning. Moreover, we also applied feature selection method to choose the optimal feature subsets from redundant features for satisfying different datasets from different imaging devices. We implemented our proposed classification system on three different datasets across more than 20 categories from phytoplankton to zooplankton. The experimental results validated that our system

  7. Combining high-resolution gross domestic product data with home and personal care product market research data to generate a subnational emission inventory for Asia.

    Science.gov (United States)

    Hodges, Juliet Elizabeth Natasha; Vamshi, Raghu; Holmes, Christopher; Rowson, Matthew; Miah, Taqmina; Price, Oliver Richard

    2014-04-01

    Environmental risk assessment of chemicals is reliant on good estimates of product usage information and robust exposure models. Over the past 20 to 30 years, much progress has been made with the development of exposure models that simulate the transport and distribution of chemicals in the environment. However, little progress has been made in our ability to estimate chemical emissions of home and personal care (HPC) products. In this project, we have developed an approach to estimate subnational emission inventory of chemical ingredients used in HPC products for 12 Asian countries including Bangladesh, Cambodia, China, India, Indonesia, Laos, Malaysia, Pakistan, Philippines, Sri Lanka, Thailand, and Vietnam (Asia-12). To develop this inventory, we have coupled a 1 km grid of per capita gross domestic product (GDP) estimates with market research data of HPC product sales. We explore the necessity of accounting for a population's ability to purchase HPC products in determining their subnational distribution in regions where wealth is not uniform. The implications of using high resolution data on inter- and intracountry subnational emission estimates for a range of hypothetical and actual HPC product types were explored. It was demonstrated that for low value products (500 US$ per capita/annum required to purchase product) the implications on emissions being assigned to subnational regions can vary by several orders of magnitude. The implications of this on conducting national or regional level risk assessments may be significant. Further work is needed to explore the implications of this variability in HPC emissions to enable the HPC industry and/or governments to advance risk-based chemical management policies in emerging markets. © 2013 SETAC.

  8. Predicting protein complexes using a supervised learning method combined with local structural information.

    Science.gov (United States)

    Dong, Yadong; Sun, Yongqi; Qin, Chao

    2018-01-01

    The existing protein complex detection methods can be broadly divided into two categories: unsupervised and supervised learning methods. Most of the unsupervised learning methods assume that protein complexes are in dense regions of protein-protein interaction (PPI) networks even though many true complexes are not dense subgraphs. Supervised learning methods utilize the informative properties of known complexes; they often extract features from existing complexes and then use the features to train a classification model. The trained model is used to guide the search process for new complexes. However, insufficient extracted features, noise in the PPI data and the incompleteness of complex data make the classification model imprecise. Consequently, the classification model is not sufficient for guiding the detection of complexes. Therefore, we propose a new robust score function that combines the classification model with local structural information. Based on the score function, we provide a search method that works both forwards and backwards. The results from experiments on six benchmark PPI datasets and three protein complex datasets show that our approach can achieve better performance compared with the state-of-the-art supervised, semi-supervised and unsupervised methods for protein complex detection, occasionally significantly outperforming such methods.

  9. The Combined Influence of Air Pollution and Home Learning Environment on Early Cognitive Skills in Children

    Directory of Open Access Journals (Sweden)

    Lanair A. Lett

    2017-10-01

    Full Text Available Cognitive skills are one component of school readiness that reflect a child’s neurodevelopment and are influenced by environmental and social factors. Most studies assess the impact of these factors individually, without taking into consideration the complex interactions of multiple factors. The objective of this study was to examine the joint association of markers of environmental pollution and of social factors on early cognitive skills in an urban cohort of children. For this, we chose isophorone in ambient air as a marker of industrial air pollution. Low quality home learning environments was chosen as a marker of the social factors contributing to cognitive development. Using a subpopulation from the Early Childhood Longitudinal Study, Birth Cohort (N = 4050, isophorone exposure was assigned using the 2002 National Air Toxics Assessment. Home learning environment was assessed with a modified version of the Home Observation for Measurement of the Environment (HOME Inventory, and standardized math assessment scores were used as a measure of early cognitive skills. Multiple linear regression was used to estimate the effect of both exposures on math scores. After adjustment for confounders, children living in areas with ambient isophorone in the upper quintile of exposure (>0.49 ng/m3 had math scores that were 1.63 points lower than their less exposed peers [95% CI: −2.91, −0.34], and children with lower HOME scores (at or below 9 out of 12 had math scores that were 1.20 points lower than children with better HOME scores [95% CI: −2.30, −0.10]. In adjusted models accounting for identified confounders and both exposures of interest, both high isophorone exposure and low HOME score remained independently associated with math scores [−1.48, 95% CI: −2.79, −0.18; −1.05, 95% CI: −2.15, 0.05, respectively]. There was no statistical evidence of interaction between the two exposures, although children with both higher isophorone

  10. The Combined Influence of Air Pollution and Home Learning Environment on Early Cognitive Skills in Children.

    Science.gov (United States)

    Lett, Lanair A; Stingone, Jeanette A; Claudio, Luz

    2017-10-26

    Cognitive skills are one component of school readiness that reflect a child's neurodevelopment and are influenced by environmental and social factors. Most studies assess the impact of these factors individually, without taking into consideration the complex interactions of multiple factors. The objective of this study was to examine the joint association of markers of environmental pollution and of social factors on early cognitive skills in an urban cohort of children. For this, we chose isophorone in ambient air as a marker of industrial air pollution. Low quality home learning environments was chosen as a marker of the social factors contributing to cognitive development. Using a subpopulation from the Early Childhood Longitudinal Study, Birth Cohort (N = 4050), isophorone exposure was assigned using the 2002 National Air Toxics Assessment. Home learning environment was assessed with a modified version of the Home Observation for Measurement of the Environment (HOME) Inventory, and standardized math assessment scores were used as a measure of early cognitive skills. Multiple linear regression was used to estimate the effect of both exposures on math scores. After adjustment for confounders, children living in areas with ambient isophorone in the upper quintile of exposure (>0.49 ng/m³) had math scores that were 1.63 points lower than their less exposed peers [95% CI: -2.91, -0.34], and children with lower HOME scores (at or below 9 out of 12) had math scores that were 1.20 points lower than children with better HOME scores [95% CI: -2.30, -0.10]. In adjusted models accounting for identified confounders and both exposures of interest, both high isophorone exposure and low HOME score remained independently associated with math scores [-1.48, 95% CI: -2.79, -0.18; -1.05, 95% CI: -2.15, 0.05, respectively]. There was no statistical evidence of interaction between the two exposures, although children with both higher isophorone exposure and a low HOME score had a

  11. Characterizing representational learning: A combined simulation and tutorial on perturbation theory

    Directory of Open Access Journals (Sweden)

    Antje Kohnle

    2017-11-01

    Full Text Available Analyzing, constructing, and translating between graphical, pictorial, and mathematical representations of physics ideas and reasoning flexibly through them (“representational competence” is a key characteristic of expertise in physics but is a challenge for learners to develop. Interactive computer simulations and University of Washington style tutorials both have affordances to support representational learning. This article describes work to characterize students’ spontaneous use of representations before and after working with a combined simulation and tutorial on first-order energy corrections in the context of quantum-mechanical time-independent perturbation theory. Data were collected from two institutions using pre-, mid-, and post-tests to assess short- and long-term gains. A representational competence level framework was adapted to devise level descriptors for the assessment items. The results indicate an increase in the number of representations used by students and the consistency between them following the combined simulation tutorial. The distributions of representational competence levels suggest a shift from perceptual to semantic use of representations based on their underlying meaning. In terms of activity design, this study illustrates the need to support students in making sense of the representations shown in a simulation and in learning to choose the most appropriate representation for a given task. In terms of characterizing representational abilities, this study illustrates the usefulness of a framework focusing on perceptual, syntactic, and semantic use of representations.

  12. Characterizing representational learning: A combined simulation and tutorial on perturbation theory

    Science.gov (United States)

    Kohnle, Antje; Passante, Gina

    2017-12-01

    Analyzing, constructing, and translating between graphical, pictorial, and mathematical representations of physics ideas and reasoning flexibly through them ("representational competence") is a key characteristic of expertise in physics but is a challenge for learners to develop. Interactive computer simulations and University of Washington style tutorials both have affordances to support representational learning. This article describes work to characterize students' spontaneous use of representations before and after working with a combined simulation and tutorial on first-order energy corrections in the context of quantum-mechanical time-independent perturbation theory. Data were collected from two institutions using pre-, mid-, and post-tests to assess short- and long-term gains. A representational competence level framework was adapted to devise level descriptors for the assessment items. The results indicate an increase in the number of representations used by students and the consistency between them following the combined simulation tutorial. The distributions of representational competence levels suggest a shift from perceptual to semantic use of representations based on their underlying meaning. In terms of activity design, this study illustrates the need to support students in making sense of the representations shown in a simulation and in learning to choose the most appropriate representation for a given task. In terms of characterizing representational abilities, this study illustrates the usefulness of a framework focusing on perceptual, syntactic, and semantic use of representations.

  13. Synergistic target combination prediction from curated signaling networks: Machine learning meets systems biology and pharmacology.

    Science.gov (United States)

    Chua, Huey Eng; Bhowmick, Sourav S; Tucker-Kellogg, Lisa

    2017-10-01

    Given a signaling network, the target combination prediction problem aims to predict efficacious and safe target combinations for combination therapy. State-of-the-art in silico methods use Monte Carlo simulated annealing (mcsa) to modify a candidate solution stochastically, and use the Metropolis criterion to accept or reject the proposed modifications. However, such stochastic modifications ignore the impact of the choice of targets and their activities on the combination's therapeutic effect and off-target effects, which directly affect the solution quality. In this paper, we present mascot, a method that addresses this limitation by leveraging two additional heuristic criteria to minimize off-target effects and achieve synergy for candidate modification. Specifically, off-target effects measure the unintended response of a signaling network to the target combination and is often associated with toxicity. Synergy occurs when a pair of targets exerts effects that are greater than the sum of their individual effects, and is generally a beneficial strategy for maximizing effect while minimizing toxicity. mascot leverages on a machine learning-based target prioritization method which prioritizes potential targets in a given disease-associated network to select more effective targets (better therapeutic effect and/or lower off-target effects); and on Loewe additivity theory from pharmacology which assesses the non-additive effects in a combination drug treatment to select synergistic target activities. Our experimental study on two disease-related signaling networks demonstrates the superiority of mascot in comparison to existing approaches. Copyright © 2017 Elsevier Inc. All rights reserved.

  14. Combining Graphic Arts, Hollywood and the Internet to Improve Distance Learning in Science and Math

    Science.gov (United States)

    Tso-Varela, S.; Friedberg, R.; Lipnick, D.

    We on the Navajo Reservation face the daunting problem of trying to educate a widely scattered student population over a landmass (25,000+ sq. miles) larger than all the New England states combined. Compounding this problem is the fact that English is a second language for many students and that many of our students lack basic foundation skills. One of the obvious answers is Distance Learning Programs. But, in the past Distance Learning Programs have been notably ineffective on the Navajo Reservation. An experimental Internet Astronomy that we taught last summer showed conclusively that we must specifically tailor our Distance Learning courses to a Navajo audience. As with many college level science courses, our experimental course was English intensive and there lies the crux of the problem. With the help of our colleague institutions, Los Alamos National Laboratory, University of California at Berkeley, University of New Mexico, Kennesaw State University, and New Mexico Highlands University, we undertook to replace 90% of the traditional verbiage with art, an idiom much accepted on the Navajo Reservation. We used the Walt Disney Studios as a model. Specifically, we studied the Pvt. Snafu cartoons used by the War Department in World War II. We tried to emulate their style and techniques. We developed our own cartoon characters, Astroboy, Professor Tso and Roxanne. We combined high quality graphic art, animation, cartooning, Navajo cultural elements, Internet hyperlinks and voiceovers to tell the story of Astronomy 101 Lab. In addition we have added remedial math resources and other helpful resources to our web site. We plan to test initial efforts in an experimental Internet course this summer.

  15. J&K Fitness Supply Company: Auditing Inventory

    Science.gov (United States)

    Clikeman, Paul M.

    2012-01-01

    This case provides auditing students with an opportunity to perform substantive tests of inventory using realistic-looking source documents. The learning objectives are to help students understand: (1) the procedures auditors perform in order to test inventory; (2) the source documents used in auditing inventory; and (3) the types of misstatements…

  16. How are learning strategies reflected in the eyes? Combining results from self-reports and eye-tracking.

    Science.gov (United States)

    Catrysse, Leen; Gijbels, David; Donche, Vincent; De Maeyer, Sven; Lesterhuis, Marije; Van den Bossche, Piet

    2018-03-01

    Up until now, empirical studies in the Student Approaches to Learning field have mainly been focused on the use of self-report instruments, such as interviews and questionnaires, to uncover differences in students' general preferences towards learning strategies, but have focused less on the use of task-specific and online measures. This study aimed at extending current research on students' learning strategies by combining general and task-specific measurements of students' learning strategies using both offline and online measures. We want to clarify how students process learning contents and to what extent this is related to their self-report of learning strategies. Twenty students with different generic learning profiles (according to self-report questionnaires) read an expository text, while their eye movements were registered to answer questions on the content afterwards. Eye-tracking data were analysed with generalized linear mixed-effects models. The results indicate that students with an all-high profile, combining both deep and surface learning strategies, spend more time on rereading the text than students with an all-low profile, scoring low on both learning strategies. This study showed that we can use eye-tracking to distinguish very strategic students, characterized using cognitive processing and regulation strategies, from low strategic students, characterized by a lack of cognitive and regulation strategies. These students processed the expository text according to how they self-reported. © 2017 The British Psychological Society.

  17. Achieving effective learning effects in the blended course: a combined approach of online self-regulated learning and collaborative learning with initiation.

    Science.gov (United States)

    Tsai, Chia-Wen

    2011-09-01

    In many countries, undergraduates are required to take at least one introductory computer course to enhance their computer literacy and computing skills. However, the application software education in Taiwan can hardly be deemed as effective in developing students' practical computing skills. The author applied online self-regulated learning (SRL) and collaborative learning (CL) with initiation in a blended computing course and examined the effects of different combinations on enhancing students' computing skills. Four classes, comprising 221 students, participated in this study. The online SRL and CL with initiation (G1, n = 53), online CL with initiation (G2, n = 68), and online CL without initiation (G3, n = 68) were experimental groups, and the last class, receiving traditional lecture (G4, n = 32), was the control group. The results of this study show that students who received the intervention of online SRL and CL with initiation attained significantly best grades for practical computing skills, whereas those that received the traditional lectures had statistically poorest grades among the four classes. The implications for schools and educators who plan to provide online or blended learning for their students, particularly in computing courses, are also provided in this study.

  18. Forest inventory in Myanmar

    Energy Technology Data Exchange (ETDEWEB)

    Bo, Sit [Forest Resource Div., Forest Department (Myanmar)

    1993-10-01

    Forest inventory in Myanmar started in 1850s. Up till 1975, Myanmar Forest Department conducted forest inventories covering approximately one forest division every year. The National Forest Survey and Inventory Project funded by UNDP and assisted by FAO commenced in 1981 and the National Forest Management and Inventory project followed in 1986. Up till end March 1993, pre-investment inventory has covered 26.7 million acres, reconnaissance inventory 5.4 million acres and management inventory has carried out in 12 townships

  19. Forest inventory in Myanmar

    International Nuclear Information System (INIS)

    Sit Bo

    1993-01-01

    Forest inventory in Myanmar started in 1850s. Up till 1975, Myanmar Forest Department conducted forest inventories covering approximately one forest division every year. The National Forest Survey and Inventory Project funded by UNDP and assisted by FAO commenced in 1981 and the National Forest Management and Inventory project followed in 1986. Up till end March 1993, pre-investment inventory has covered 26.7 million acres, reconnaissance inventory 5.4 million acres and management inventory has carried out in 12 townships

  20. A Mobile Outdoor Augmented Reality Method Combining Deep Learning Object Detection and Spatial Relationships for Geovisualization.

    Science.gov (United States)

    Rao, Jinmeng; Qiao, Yanjun; Ren, Fu; Wang, Junxing; Du, Qingyun

    2017-08-24

    The purpose of this study was to develop a robust, fast and markerless mobile augmented reality method for registration, geovisualization and interaction in uncontrolled outdoor environments. We propose a lightweight deep-learning-based object detection approach for mobile or embedded devices; the vision-based detection results of this approach are combined with spatial relationships by means of the host device's built-in Global Positioning System receiver, Inertial Measurement Unit and magnetometer. Virtual objects generated based on geospatial information are precisely registered in the real world, and an interaction method based on touch gestures is implemented. The entire method is independent of the network to ensure robustness to poor signal conditions. A prototype system was developed and tested on the Wuhan University campus to evaluate the method and validate its results. The findings demonstrate that our method achieves a high detection accuracy, stable geovisualization results and interaction.

  1. A Mobile Outdoor Augmented Reality Method Combining Deep Learning Object Detection and Spatial Relationships for Geovisualization

    Directory of Open Access Journals (Sweden)

    Jinmeng Rao

    2017-08-01

    Full Text Available The purpose of this study was to develop a robust, fast and markerless mobile augmented reality method for registration, geovisualization and interaction in uncontrolled outdoor environments. We propose a lightweight deep-learning-based object detection approach for mobile or embedded devices; the vision-based detection results of this approach are combined with spatial relationships by means of the host device’s built-in Global Positioning System receiver, Inertial Measurement Unit and magnetometer. Virtual objects generated based on geospatial information are precisely registered in the real world, and an interaction method based on touch gestures is implemented. The entire method is independent of the network to ensure robustness to poor signal conditions. A prototype system was developed and tested on the Wuhan University campus to evaluate the method and validate its results. The findings demonstrate that our method achieves a high detection accuracy, stable geovisualization results and interaction.

  2. A Mobile Outdoor Augmented Reality Method Combining Deep Learning Object Detection and Spatial Relationships for Geovisualization

    Science.gov (United States)

    Rao, Jinmeng; Qiao, Yanjun; Ren, Fu; Wang, Junxing; Du, Qingyun

    2017-01-01

    The purpose of this study was to develop a robust, fast and markerless mobile augmented reality method for registration, geovisualization and interaction in uncontrolled outdoor environments. We propose a lightweight deep-learning-based object detection approach for mobile or embedded devices; the vision-based detection results of this approach are combined with spatial relationships by means of the host device’s built-in Global Positioning System receiver, Inertial Measurement Unit and magnetometer. Virtual objects generated based on geospatial information are precisely registered in the real world, and an interaction method based on touch gestures is implemented. The entire method is independent of the network to ensure robustness to poor signal conditions. A prototype system was developed and tested on the Wuhan University campus to evaluate the method and validate its results. The findings demonstrate that our method achieves a high detection accuracy, stable geovisualization results and interaction. PMID:28837096

  3. Machine Learning Approach to Optimizing Combined Stimulation and Medication Therapies for Parkinson's Disease.

    Science.gov (United States)

    Shamir, Reuben R; Dolber, Trygve; Noecker, Angela M; Walter, Benjamin L; McIntyre, Cameron C

    2015-01-01

    Deep brain stimulation (DBS) of the subthalamic region is an established therapy for advanced Parkinson's disease (PD). However, patients often require time-intensive post-operative management to balance their coupled stimulation and medication treatments. Given the large and complex parameter space associated with this task, we propose that clinical decision support systems (CDSS) based on machine learning algorithms could assist in treatment optimization. Develop a proof-of-concept implementation of a CDSS that incorporates patient-specific details on both stimulation and medication. Clinical data from 10 patients, and 89 post-DBS surgery visits, were used to create a prototype CDSS. The system was designed to provide three key functions: (1) information retrieval; (2) visualization of treatment, and; (3) recommendation on expected effective stimulation and drug dosages, based on three machine learning methods that included support vector machines, Naïve Bayes, and random forest. Measures of medication dosages, time factors, and symptom-specific pre-operative response to levodopa were significantly correlated with post-operative outcomes (P < 0.05) and their effect on outcomes was of similar magnitude to that of DBS. Using those results, the combined machine learning algorithms were able to accurately predict 86% (12/14) of the motor improvement scores at one year after surgery. Using patient-specific details, an appropriately parameterized CDSS could help select theoretically optimal DBS parameter settings and medication dosages that have potential to improve the clinical management of PD patients. Copyright © 2015 Elsevier Inc. All rights reserved.

  4. Combining Fog Computing with Sensor Mote Machine Learning for Industrial IoT.

    Science.gov (United States)

    Lavassani, Mehrzad; Forsström, Stefan; Jennehag, Ulf; Zhang, Tingting

    2018-05-12

    Digitalization is a global trend becoming ever more important to our connected and sustainable society. This trend also affects industry where the Industrial Internet of Things is an important part, and there is a need to conserve spectrum as well as energy when communicating data to a fog or cloud back-end system. In this paper we investigate the benefits of fog computing by proposing a novel distributed learning model on the sensor device and simulating the data stream in the fog, instead of transmitting all raw sensor values to the cloud back-end. To save energy and to communicate as few packets as possible, the updated parameters of the learned model at the sensor device are communicated in longer time intervals to a fog computing system. The proposed framework is implemented and tested in a real world testbed in order to make quantitative measurements and evaluate the system. Our results show that the proposed model can achieve a 98% decrease in the number of packets sent over the wireless link, and the fog node can still simulate the data stream with an acceptable accuracy of 97%. We also observe an end-to-end delay of 180 ms in our proposed three-layer framework. Hence, the framework shows that a combination of fog and cloud computing with a distributed data modeling at the sensor device for wireless sensor networks can be beneficial for Industrial Internet of Things applications.

  5. Combining Benford's Law and machine learning to detect money laundering. An actual Spanish court case.

    Science.gov (United States)

    Badal-Valero, Elena; Alvarez-Jareño, José A; Pavía, Jose M

    2018-01-01

    This paper is based on the analysis of the database of operations from a macro-case on money laundering orchestrated between a core company and a group of its suppliers, 26 of which had already been identified by the police as fraudulent companies. In the face of a well-founded suspicion that more companies have perpetrated criminal acts and in order to make better use of what are very limited police resources, we aim to construct a tool to detect money laundering criminals. We combine Benford's Law and machine learning algorithms (logistic regression, decision trees, neural networks, and random forests) to find patterns of money laundering criminals in the context of a real Spanish court case. After mapping each supplier's set of accounting data into a 21-dimensional space using Benford's Law and applying machine learning algorithms, additional companies that could merit further scrutiny are flagged up. A new tool to detect money laundering criminals is proposed in this paper. The tool is tested in the context of a real case. Copyright © 2017 Elsevier B.V. All rights reserved.

  6. Combining machine learning, crowdsourcing and expert knowledge to detect chemical-induced diseases in text.

    Science.gov (United States)

    Bravo, Àlex; Li, Tong Shu; Su, Andrew I; Good, Benjamin M; Furlong, Laura I

    2016-01-01

    Drug toxicity is a major concern for both regulatory agencies and the pharmaceutical industry. In this context, text-mining methods for the identification of drug side effects from free text are key for the development of up-to-date knowledge sources on drug adverse reactions. We present a new system for identification of drug side effects from the literature that combines three approaches: machine learning, rule- and knowledge-based approaches. This system has been developed to address the Task 3.B of Biocreative V challenge (BC5) dealing with Chemical-induced Disease (CID) relations. The first two approaches focus on identifying relations at the sentence-level, while the knowledge-based approach is applied both at sentence and abstract levels. The machine learning method is based on the BeFree system using two corpora as training data: the annotated data provided by the CID task organizers and a new CID corpus developed by crowdsourcing. Different combinations of results from the three strategies were selected for each run of the challenge. In the final evaluation setting, the system achieved the highest Recall of the challenge (63%). By performing an error analysis, we identified the main causes of misclassifications and areas for improving of our system, and highlighted the need of consistent gold standard data sets for advancing the state of the art in text mining of drug side effects.Database URL: https://zenodo.org/record/29887?ln¼en#.VsL3yDLWR_V. © The Author(s) 2016. Published by Oxford University Press.

  7. Energy Education Materials Inventory

    Energy Technology Data Exchange (ETDEWEB)

    1979-08-01

    The two volumes of the Energy Education Materials Inventory (EEMI) comprise an annotated bibliography of widely available energy education materials and reference sources. This systematic listing is designed to provide a source book which will facilitate access to these educational resources and hasten the inclusion of energy-focused learning experiences in kindergarten through grade twelve. EEMI Volume II expands Volume I and contains items that have become available since its completion in May, 1976. The inventory consists of three major parts. A core section entitled Media contains titles and descriptive information on educational materials, categorized according to medium. The other two major sections - Grade Level and Subject - are cross indexes of the items for which citations appear in the Media Section. These contain titles categorized according to grade level and subject and show the page numbers of the full citations. The general subject area covered includes the following: alternative energy sources (wood, fuel from organic wastes, geothermal energy, nuclear power, solar energy, tidal power, wind energy); energy conservation, consumption, and utilization; energy policy and legislation, environmental/social aspects of energy technology; and fossil fuels (coal, natural gas, petroleum). (RWR)

  8. Neuromodulatory adaptive combination of correlation-based learning in cerebellum and reward-based learning in basal ganglia for goal-directed behavior control.

    Science.gov (United States)

    Dasgupta, Sakyasingha; Wörgötter, Florentin; Manoonpong, Poramate

    2014-01-01

    Goal-directed decision making in biological systems is broadly based on associations between conditional and unconditional stimuli. This can be further classified as classical conditioning (correlation-based learning) and operant conditioning (reward-based learning). A number of computational and experimental studies have well established the role of the basal ganglia in reward-based learning, where as the cerebellum plays an important role in developing specific conditioned responses. Although viewed as distinct learning systems, recent animal experiments point toward their complementary role in behavioral learning, and also show the existence of substantial two-way communication between these two brain structures. Based on this notion of co-operative learning, in this paper we hypothesize that the basal ganglia and cerebellar learning systems work in parallel and interact with each other. We envision that such an interaction is influenced by reward modulated heterosynaptic plasticity (RMHP) rule at the thalamus, guiding the overall goal directed behavior. Using a recurrent neural network actor-critic model of the basal ganglia and a feed-forward correlation-based learning model of the cerebellum, we demonstrate that the RMHP rule can effectively balance the outcomes of the two learning systems. This is tested using simulated environments of increasing complexity with a four-wheeled robot in a foraging task in both static and dynamic configurations. Although modeled with a simplified level of biological abstraction, we clearly demonstrate that such a RMHP induced combinatorial learning mechanism, leads to stabler and faster learning of goal-directed behaviors, in comparison to the individual systems. Thus, in this paper we provide a computational model for adaptive combination of the basal ganglia and cerebellum learning systems by way of neuromodulated plasticity for goal-directed decision making in biological and bio-mimetic organisms.

  9. Combining Human Computing and Machine Learning to Make Sense of Big (Aerial) Data for Disaster Response.

    Science.gov (United States)

    Ofli, Ferda; Meier, Patrick; Imran, Muhammad; Castillo, Carlos; Tuia, Devis; Rey, Nicolas; Briant, Julien; Millet, Pauline; Reinhard, Friedrich; Parkan, Matthew; Joost, Stéphane

    2016-03-01

    results suggest that the platform we have developed to combine crowdsourcing and machine learning to make sense of large volumes of aerial images can be used for disaster response.

  10. Identifying Human Phenotype Terms by Combining Machine Learning and Validation Rules

    Directory of Open Access Journals (Sweden)

    Manuel Lobo

    2017-01-01

    Full Text Available Named-Entity Recognition is commonly used to identify biological entities such as proteins, genes, and chemical compounds found in scientific articles. The Human Phenotype Ontology (HPO is an ontology that provides a standardized vocabulary for phenotypic abnormalities found in human diseases. This article presents the Identifying Human Phenotypes (IHP system, tuned to recognize HPO entities in unstructured text. IHP uses Stanford CoreNLP for text processing and applies Conditional Random Fields trained with a rich feature set, which includes linguistic, orthographic, morphologic, lexical, and context features created for the machine learning-based classifier. However, the main novelty of IHP is its validation step based on a set of carefully crafted manual rules, such as the negative connotation analysis, that combined with a dictionary can filter incorrectly identified entities, find missed entities, and combine adjacent entities. The performance of IHP was evaluated using the recently published HPO Gold Standardized Corpora (GSC, where the system Bio-LarK CR obtained the best F-measure of 0.56. IHP achieved an F-measure of 0.65 on the GSC. Due to inconsistencies found in the GSC, an extended version of the GSC was created, adding 881 entities and modifying 4 entities. IHP achieved an F-measure of 0.863 on the new GSC.

  11. Combining extreme learning machines using support vector machines for breast tissue classification.

    Science.gov (United States)

    Daliri, Mohammad Reza

    2015-01-01

    In this paper, we present a new approach for breast tissue classification using the features derived from electrical impedance spectroscopy. This method is composed of a feature extraction method, feature selection phase and a classification step. The feature extraction phase derives the features from the electrical impedance spectra. The extracted features consist of the impedivity at zero frequency (I0), the phase angle at 500 KHz, the high-frequency slope of phase angle, the impedance distance between spectral ends, the area under spectrum, the normalised area, the maximum of the spectrum, the distance between impedivity at I0 and the real part of the maximum frequency point and the length of the spectral curve. The system uses the information theoretic criterion as a strategy for feature selection and the combining extreme learning machines (ELMs) for the classification phase. The results of several ELMs are combined using the support vector machines classifier, and the result of classification is reported as a measure of the performance of the system. The results indicate that the proposed system achieves high accuracy in classification of breast tissues using the electrical impedance spectroscopy.

  12. Prediction of HDR quality by combining perceptually transformed display measurements with machine learning

    Science.gov (United States)

    Choudhury, Anustup; Farrell, Suzanne; Atkins, Robin; Daly, Scott

    2017-09-01

    We present an approach to predict overall HDR display quality as a function of key HDR display parameters. We first performed subjective experiments on a high quality HDR display that explored five key HDR display parameters: maximum luminance, minimum luminance, color gamut, bit-depth and local contrast. Subjects rated overall quality for different combinations of these display parameters. We explored two models | a physical model solely based on physically measured display characteristics and a perceptual model that transforms physical parameters using human vision system models. For the perceptual model, we use a family of metrics based on a recently published color volume model (ICT-CP), which consists of the PQ luminance non-linearity (ST2084) and LMS-based opponent color, as well as an estimate of the display point spread function. To predict overall visual quality, we apply linear regression and machine learning techniques such as Multilayer Perceptron, RBF and SVM networks. We use RMSE and Pearson/Spearman correlation coefficients to quantify performance. We found that the perceptual model is better at predicting subjective quality than the physical model and that SVM is better at prediction than linear regression. The significance and contribution of each display parameter was investigated. In addition, we found that combined parameters such as contrast do not improve prediction. Traditional perceptual models were also evaluated and we found that models based on the PQ non-linearity performed better.

  13. Effectiveness of teaching and learning mathematics for Thai university engineering students through a combination of activity and lecture based classroom

    Directory of Open Access Journals (Sweden)

    Parinya S. Ngiamsunthorn

    2014-04-01

    Full Text Available There are concerns of developing effective pedagogical practices for teaching mathematics for engineering students as many engineering students experience difficulties in learning compulsory mathematics subjects in their first and second years of the degree. This paper aims to investigate the effectiveness of using a variety of teaching and learning approaches including lecture based learning, activity based learning, e-learning via learning management system (LMS and practice or tutorial session in mathematics subjects for engineering students. This study was carried out on 160 students who need to enroll three basic mathematics subjects (MTH101, MTH102 and MTH201 for an engineering degree during academic year 2011 – 2012. The students were divided into three groups according to their majors of study. The first two groups of students were given a combination of various teaching approaches for only one semester (either MTH102 or MTH201, while the last group was given a combination of various teaching approaches for two semesters (both MTH102 and MTH201. To evaluate the effectiveness of teaching and learning, examination results, questionnaires on attitude towards teaching and learning, and a formal university teaching evaluation by students were collected and analyzed. It is found that different students perceive mathematics contents from different teaching methods according to their preferred learning styles. Moreover, most students in all groups performed at least the same or better in their final subject (MTH201. However, there is an interesting finding that low proficiency students in earlier mathematics subjects who received a combination of various teaching approaches for two semesters can improve their examination results better than other groups, on average. This is also reflected from an increasing average score on teaching evaluation from this group of students about teaching techniques.

  14. Assessment of a combined dry anaerobic digestion and post-composting treatment facility for source-separated organic household waste, using material and substance flow analysis and life cycle inventory.

    Science.gov (United States)

    Jensen, Morten Bang; Møller, Jacob; Scheutz, Charlotte

    2017-08-01

    The fate of total solids, volatile solids, total organic carbon, fossil carbon, biogenic carbon and 17 substances (As, Ca, CaCO 3 , Cd, Cl, Cr, Cu, H, Hg, K, Mg, N, Ni, O, P, Pb, S, Zn) in a combined dry anaerobic digestion and post-composting facility were assessed. Mass balances showed good results with low uncertainties for non-volatile substances, while balances for nitrogen, carbon, volatile solids and total organic carbon showed larger but reasonable uncertainties, due to volatilisation and emissions into the air. Material and substance flow analyses were performed in order to obtain transfer coefficients for a combined dry anaerobic digestion and post-composting facility. All metals passed through the facility and ended up in compost or residues, but all concentrations of metals in the compost complied with legislation. About 23% of the carbon content of the organic waste was transferred to the biogas, 24% to the compost, 13% to residues and 40% into the atmosphere. For nitrogen, 69% was transferred to the compost, 10% volatilised to the biofilter, 11% directly into the atmosphere and 10% to residues. Finally, a full life cycle inventory was conducted for the combined dry anaerobic digestion and post-composting facility, including waste received, fuel consumption, energy use, gaseous emissions, products, energy production and chemical composition of the compost produced. Copyright © 2017. Published by Elsevier Ltd.

  15. Modafinil combined with cognitive training is associated with improved learning in healthy volunteers--a randomised controlled trial.

    Science.gov (United States)

    Gilleen, J; Michalopoulou, P G; Reichenberg, A; Drake, R; Wykes, T; Lewis, S W; Kapur, S

    2014-04-01

    Improving cognition in people with neuropsychiatric disorders remains a major clinical target. By themselves pharmacological and non-pharmacological approaches have shown only modest effects in improving cognition. In the present study we tested a recently-proposed methodology to combine CT with a 'cognitive-enhancing' drug to improve cognitive test scores and expanded on previous approaches by delivering combination drug and CT, over a long intervention of repeated sessions, and used multiple tasks to reveal the cognitive processes being enhanced. We also aimed to determine whether gains from this combination approach generalised to untrained tests. In this proof of principle randomised-controlled trial thirty-three healthy volunteers were randomised to receive either modafinil or placebo combined with daily cognitive training over two weeks. Volunteers were trained on tasks of new-language learning, working memory and verbal learning following 200 mg modafinil or placebo for ten days. Improvements in trained and untrained tasks were measured. Rate of new-language learning was significantly enhanced with modafinil, and effects were greatest over the first five sessions. Modafinil improved within-day learning rather than between-day retention. No enhancement of gains with modafinil was observed in working memory nor rate of verbal learning. Gains in all tasks were retained post drug-administration, but transfer effects to broad cognitive abilities were not seen. This study shows that combining CT with modafinil specifically elevates learning over early training sessions compared to CT with placebo and provides a proof of principle experimental paradigm for pharmacological enhancement of cognitive remediation. Copyright © 2014 Elsevier B.V. and ECNP. All rights reserved.

  16. Combining Quality Work-Integrated Learning and Career Development Learning through the Use of the SOAR Model to Enhance Employability

    Science.gov (United States)

    Reddan, Gregory; Rauchle, Maja

    2017-01-01

    This paper presents students' perceptions of the benefits to employability of a suite of courses that incorporate both work-integrated learning (WIL) and career development learning (CDL). Field Project A and Field Project B are elective courses in the Bachelor of Exercise Science at Griffith University. These courses engage students in active and…

  17. Does Combining the Embodiment and Personalization Principles of Multimedia Learning Affect Learning the Culture of a Foreign Language?

    Science.gov (United States)

    Wang, Yanlin; Crooks, Steven M.

    2015-01-01

    The purpose of this study was to investigate how social cues associated with the personalization and embodiment principles in multimedia learning affect the learning and attitude of students studying the culture of a foreign language. University students were randomly assigned to one of two experimental conditions that consisted of an…

  18. Housing Inventory Count

    Data.gov (United States)

    Department of Housing and Urban Development — This report displays the data communities reported to HUD about the nature of their dedicated homeless inventory, referred to as their Housing Inventory Count (HIC)....

  19. Integrated inventory information system

    Digital Repository Service at National Institute of Oceanography (India)

    Sarupria, J.S.; Kunte, P.D.

    The nature of oceanographic data and the management of inventory level information are described in Integrated Inventory Information System (IIIS). It is shown how a ROSCOPO (report on observations/samples collected during oceanographic programme...

  20. World Glacier Inventory

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The World Glacier Inventory (WGI) contains information for over 130,000 glaciers. Inventory parameters include geographic location, area, length, orientation,...

  1. HHS Enterprise Data Inventory

    Data.gov (United States)

    U.S. Department of Health & Human Services — The Enterprise Data Inventory (EDI) is the comprehensive inventory listing of agency data resources including public, restricted public, and non-public datasets.

  2. Science Inventory | US EPA

    Science.gov (United States)

    The Science Inventory is a searchable database of research products primarily from EPA's Office of Research and Development. Science Inventory records provide descriptions of the product, contact information, and links to available printed material or websites.

  3. National Wetlands Inventory Polygons

    Data.gov (United States)

    Minnesota Department of Natural Resources — Wetland area features mapped as part of the National Wetlands Inventory (NWI). The National Wetlands Inventory is a national program sponsored by the US Fish and...

  4. Simultaneous learning and filtering without delusions: a Bayes-optimal combination of Predictive Inference and Adaptive Filtering.

    Science.gov (United States)

    Kneissler, Jan; Drugowitsch, Jan; Friston, Karl; Butz, Martin V

    2015-01-01

    Predictive coding appears to be one of the fundamental working principles of brain processing. Amongst other aspects, brains often predict the sensory consequences of their own actions. Predictive coding resembles Kalman filtering, where incoming sensory information is filtered to produce prediction errors for subsequent adaptation and learning. However, to generate prediction errors given motor commands, a suitable temporal forward model is required to generate predictions. While in engineering applications, it is usually assumed that this forward model is known, the brain has to learn it. When filtering sensory input and learning from the residual signal in parallel, a fundamental problem arises: the system can enter a delusional loop when filtering the sensory information using an overly trusted forward model. In this case, learning stalls before accurate convergence because uncertainty about the forward model is not properly accommodated. We present a Bayes-optimal solution to this generic and pernicious problem for the case of linear forward models, which we call Predictive Inference and Adaptive Filtering (PIAF). PIAF filters incoming sensory information and learns the forward model simultaneously. We show that PIAF is formally related to Kalman filtering and to the Recursive Least Squares linear approximation method, but combines these procedures in a Bayes optimal fashion. Numerical evaluations confirm that the delusional loop is precluded and that the learning of the forward model is more than 10-times faster when compared to a naive combination of Kalman filtering and Recursive Least Squares.

  5. Simultaneous Learning and Filtering without Delusions: A Bayes-Optimal Derivation of Combining Predictive Inference and AdaptiveFiltering

    Directory of Open Access Journals (Sweden)

    Jan eKneissler

    2015-04-01

    Full Text Available Predictive coding appears to be one of the fundamental working principles of brain processing. Amongst other aspects, brains often predict the sensory consequences of their own actions. Predictive coding resembles Kalman filtering, where incoming sensory information is filtered to produce prediction errors for subsequent adaptation and learning. However, to generate prediction errors given motor commands, a suitable temporal forward model is required to generate predictions. While in engineering applications, it is usually assumed that this forward model is known, the brain has to learn it. When filtering sensory input and learning from the residual signal in parallel, a fundamental problem arises: the system can enter a delusional loop when filtering the sensory information using an overly trusted forward model. In this case, learning stalls before accurate convergence because uncertainty about the forward model is not properly accommodated. We present a Bayes-optimal solution to this generic and pernicious problem for the case of linear forward models, which we call Predictive Inference and Adaptive Filtering (PIAF. PIAF filters incoming sensory information and learns the forward model simultaneously. We show that PIAF is formally related to Kalman filtering and to the Recursive Least Squares linear approximation method, but combines these procedures in a Bayes optimal fashion. Numerical evaluations confirm that the delusional loop is precluded and that the learning of the forward model is more than ten-times faster when compared to a naive combination of Kalman filtering and Recursive Least Squares.

  6. A new semi-supervised learning model combined with Cox and SP-AFT models in cancer survival analysis.

    Science.gov (United States)

    Chai, Hua; Li, Zi-Na; Meng, De-Yu; Xia, Liang-Yong; Liang, Yong

    2017-10-12

    Gene selection is an attractive and important task in cancer survival analysis. Most existing supervised learning methods can only use the labeled biological data, while the censored data (weakly labeled data) far more than the labeled data are ignored in model building. Trying to utilize such information in the censored data, a semi-supervised learning framework (Cox-AFT model) combined with Cox proportional hazard (Cox) and accelerated failure time (AFT) model was used in cancer research, which has better performance than the single Cox or AFT model. This method, however, is easily affected by noise. To alleviate this problem, in this paper we combine the Cox-AFT model with self-paced learning (SPL) method to more effectively employ the information in the censored data in a self-learning way. SPL is a kind of reliable and stable learning mechanism, which is recently proposed for simulating the human learning process to help the AFT model automatically identify and include samples of high confidence into training, minimizing interference from high noise. Utilizing the SPL method produces two direct advantages: (1) The utilization of censored data is further promoted; (2) the noise delivered to the model is greatly decreased. The experimental results demonstrate the effectiveness of the proposed model compared to the traditional Cox-AFT model.

  7. The Combined Use of Hypnosis and Sensory and Motor Stimulation in Assisting Children with Developmental Learning Problems.

    Science.gov (United States)

    Jampolsky, Gerald G.

    Hypnosis was combined with sensory and motor stimulation to remediate reversal problems in five children (6 1/2- 9-years-old). Under hypnosis Ss were given the suggestion that they learn their numbers through feel and then given 1 hour of structured instruction daily for 10 days. Instruction stressed conditioning, vibratory memory, touch memory,…

  8. Research on Motivation in Collaborative Learning: Moving beyond the Cognitive-Situative Divide and Combining Individual and Social Processes

    Science.gov (United States)

    Jarvela, Sanna; Volet, Simone; Jarvenoja, Hanna

    2010-01-01

    In this article we propose that in order to advance our understanding of motivation in collaborative learning we should move beyond the cognitive-situative epistemological divide and combine individual and social processes. Our claim is that although recent research has recognized the importance of social aspects in emerging and sustained…

  9. Reification in the Learning of Square Roots in a Ninth Grade Classroom: Combining Semiotic and Discursive Approaches

    Science.gov (United States)

    Shinno, Yusuke

    2018-01-01

    This paper reports on combining semiotic and discursive approaches to reification in classroom interactions. It focuses on the discursive characteristics and semiotic processes involved in the teaching and learning of square roots in a ninth grade classroom in Japan. The purpose of this study is to characterize the development of mathematical…

  10. Combined Effects of Note-Taking/-Reviewing on Learning and the Enhancement through Interventions: A Meta-Analytic Review

    Science.gov (United States)

    Kobayashi, Keiichi

    2006-01-01

    Meta-analyses of 33 studies were conducted to examine (1) how much the combination of taking and reviewing notes contributes to school learning, and (2) whether interventions in the note-taking/-reviewing procedure enhance note-taking/-reviewing effects, and if so, how much and under what conditions. Syntheses of findings from…

  11. Learning to Generate Sequences with Combination of Hebbian and Non-hebbian Plasticity in Recurrent Spiking Neural Networks.

    Science.gov (United States)

    Panda, Priyadarshini; Roy, Kaushik

    2017-01-01

    Synaptic Plasticity, the foundation for learning and memory formation in the human brain, manifests in various forms. Here, we combine the standard spike timing correlation based Hebbian plasticity with a non-Hebbian synaptic decay mechanism for training a recurrent spiking neural model to generate sequences. We show that inclusion of the adaptive decay of synaptic weights with standard STDP helps learn stable contextual dependencies between temporal sequences, while reducing the strong attractor states that emerge in recurrent models due to feedback loops. Furthermore, we show that the combined learning scheme suppresses the chaotic activity in the recurrent model substantially, thereby enhancing its' ability to generate sequences consistently even in the presence of perturbations.

  12. Combining forces. Distributed Leadership and a professional learning community in primary and secondary education

    NARCIS (Netherlands)

    Hulsbos, Frank; Van Langevelde, Stefan; Evers, Arnoud

    2018-01-01

    This report describes an in depth case study of two good practice schools where a professional learning community and distributed leadership are highly developed. The goal of this study was to learn what conditions in the school support a professional learning community and distributed leadership.

  13. Module Seven: Combination Circuits and Voltage Dividers; Basic Electricity and Electronics Individualized Learning System.

    Science.gov (United States)

    Bureau of Naval Personnel, Washington, DC.

    In this module the student will learn to apply the rules previously learned for series and parallel circuits to more complex circuits called series-parallel circuits, discover the utility of a common reference when making reference to voltage values, and learn how to obtain a required voltage from a voltage divider network. The module is divided…

  14. Application and evaluation of a combination of socratice and learning through discussion techniques

    Directory of Open Access Journals (Sweden)

    EJ van Aswegen

    2001-09-01

    Full Text Available This article has its genesis in the inquirer’s interest in the need for internalizing critical thinking, creative thinking and reflective skills in adult learners. As part of a broader study the inquirer used a combination of two techniques over a period of nine months, namely: Socratic discussion/questioning and Learning Through Discussion Technique. The inquirer within this inquiry elected mainly qualitative methods, because they were seen as more adaptable to dealing with multiple realities and more sensitive and adaptable to the many shaping influences and value patterns that may be encountered (Lincoln & Guba, 1989. Purposive sampling was used and sample size (n =10 was determined by the willingness of potential participants to enlist in the chosen techniques. Feedback from participants was obtained: (1 verbally after each discussion session, and (2 in written format after completion of the course content. The final/ summative evaluation was obtained through a semi-structured questionnaire. This was deemed necessary, in that the participants were already studying for the end of the year examination. For the purpose of this condensed report the inquirer reflected only on the feedback obtained with the help of the questionnaire. The empirical study showed that in spite of various adaptation problems experienced, eight (8 of the ten (10 participants felt positive toward the applied techniques.

  15. Combining machine learning and matching techniques to improve causal inference in program evaluation.

    Science.gov (United States)

    Linden, Ariel; Yarnold, Paul R

    2016-12-01

    Program evaluations often utilize various matching approaches to emulate the randomization process for group assignment in experimental studies. Typically, the matching strategy is implemented, and then covariate balance is assessed before estimating treatment effects. This paper introduces a novel analytic framework utilizing a machine learning algorithm called optimal discriminant analysis (ODA) for assessing covariate balance and estimating treatment effects, once the matching strategy has been implemented. This framework holds several key advantages over the conventional approach: application to any variable metric and number of groups; insensitivity to skewed data or outliers; and use of accuracy measures applicable to all prognostic analyses. Moreover, ODA accepts analytic weights, thereby extending the methodology to any study design where weights are used for covariate adjustment or more precise (differential) outcome measurement. One-to-one matching on the propensity score was used as the matching strategy. Covariate balance was assessed using standardized difference in means (conventional approach) and measures of classification accuracy (ODA). Treatment effects were estimated using ordinary least squares regression and ODA. Using empirical data, ODA produced results highly consistent with those obtained via the conventional methodology for assessing covariate balance and estimating treatment effects. When ODA is combined with matching techniques within a treatment effects framework, the results are consistent with conventional approaches. However, given that it provides additional dimensions and robustness to the analysis versus what can currently be achieved using conventional approaches, ODA offers an appealing alternative. © 2016 John Wiley & Sons, Ltd.

  16. Teamwork: improved eQTL mapping using combinations of machine learning methods.

    Directory of Open Access Journals (Sweden)

    Marit Ackermann

    Full Text Available Expression quantitative trait loci (eQTL mapping is a widely used technique to uncover regulatory relationships between genes. A range of methodologies have been developed to map links between expression traits and genotypes. The DREAM (Dialogue on Reverse Engineering Assessments and Methods initiative is a community project to objectively assess the relative performance of different computational approaches for solving specific systems biology problems. The goal of one of the DREAM5 challenges was to reverse-engineer genetic interaction networks from synthetic genetic variation and gene expression data, which simulates the problem of eQTL mapping. In this framework, we proposed an approach whose originality resides in the use of a combination of existing machine learning algorithms (committee. Although it was not the best performer, this method was by far the most precise on average. After the competition, we continued in this direction by evaluating other committees using the DREAM5 data and developed a method that relies on Random Forests and LASSO. It achieved a much higher average precision than the DREAM best performer at the cost of slightly lower average sensitivity.

  17. Using video games to combine learning and assessment in mathematics education

    Directory of Open Access Journals (Sweden)

    Kristian Juha Mikael Kiili

    2015-12-01

    Full Text Available One problem with most education systems is that learning and (summative assessment are generally treated as quite separate things in schools. We argue that video games can provide an opportunity to combine these processes in an engaging and effective way. The present study focuses on investigating the effectiveness and the assessment power of two different mathematics video games, Semideus and Wuzzit Trouble. In the current study, we validated the Semideus game as a rational number test instrument. We used it as a pre- and a post-test for a three-hour intervention in which we studied the effectiveness of Wuzzit Trouble, a game built on whole number arithmetic and designed to enhance mathematical thinking and problem solving skills. The results showed that (1 games can be used to assess mathematical knowledge validly, and (2 even short game-based interventions can be very effective. Based on the results, we argue that game-based assessment can create a more complete picture of mathematical knowledge than simply measuring students' accuracy, providing indicators of student misconceptions and conceptual change processes

  18. Application and evaluation of a combination of socratice and learning through discussion techniques.

    Science.gov (United States)

    van Aswegen, E J; Brink, H I; Steyn, P J

    2001-11-01

    This article has its genesis in the inquirer's interest in the need for internalizing critical thinking, creative thinking and reflective skills in adult learners. As part of a broader study the inquirer used a combination of two techniques over a period of nine months, namely: Socratic discussion/questioning and Learning Through Discussion Technique. The inquirer within this inquiry elected mainly qualitative methods, because they were seen as more adaptable to dealing with multiple realities and more sensitive and adaptable to the many shaping influences and value patterns that may be encountered (Lincoln & Guba, 1989). Purposive sampling was used and sample size (n = 10) was determined by the willingness of potential participants to enlist in the chosen techniques. Feedback from participants was obtained: (1) verbally after each discussion session, and (2) in written format after completion of the course content. The final/summative evaluation was obtained through a semi-structured questionnaire. This was deemed necessary, in that the participants were already studying for the end of the year examination. For the purpose of this condensed report the inquirer reflected only on the feedback obtained with the help of the questionnaire. The empirical study showed that in spite of various adaptation problems experienced, eight (8) of the ten (10) participants felt positive toward the applied techniques.

  19. A Combination of Machine Learning and Cerebellar Models for the Motor Control and Learning of a Modular Robot

    DEFF Research Database (Denmark)

    Baira Ojeda, Ismael; Tolu, Silvia; Pacheco, Moises

    2017-01-01

    We scaled up a bio-inspired control architecture for the motor control and motor learning of a real modular robot. In our approach, the Locally Weighted Projection Regression algorithm (LWPR) and a cerebellar microcircuit coexist, forming a Unit Learning Machine. The LWPR optimizes the input space...... and learns the internal model of a single robot module to command the robot to follow a desired trajectory with its end-effector. The cerebellar microcircuit refines the LWPR output delivering corrective commands. We contrasted distinct cerebellar circuits including analytical models and spiking models...

  20. The Coopersmith Self-Esteem Inventory As a Predictor of Feelings and Communication Satisfaction Toward Parents Among Learning Disabled, Emotionally Disturbed, and Normal Adolescents.

    Science.gov (United States)

    Omizo, Michael M.; And Others

    1985-01-01

    This study examined the predictive validity of the Coopersmith Self Esteem Inventory with adolescents relative to each of the criterion measures representing communication satisfaction toward each parent and feelings toward each parent, and the differential validity of the self-esteem, communication satisfaction, and feelings toward each parent…

  1. Functional Assessment Inventory Manual.

    Science.gov (United States)

    Crewe, Nancy M.; Athelstan, Gary T.

    This manual, which provides extensive new instructions for administering the Functional Assessment Inventory (FAI), is intended to enable counselors to begin using the inventory without undergoing any special training. The first two sections deal with the need for functional assessment and issues in the development and use of the inventory. The…

  2. Concepts for inventory verification in critical facilities

    International Nuclear Information System (INIS)

    Cobb, D.D.; Sapir, J.L.; Kern, E.A.; Dietz, R.J.

    1978-12-01

    Materials measurement and inventory verification concepts for safeguarding large critical facilities are presented. Inspection strategies and methods for applying international safeguards to such facilities are proposed. The conceptual approach to routine inventory verification includes frequent visits to the facility by one inspector, and the use of seals and nondestructive assay (NDA) measurements to verify the portion of the inventory maintained in vault storage. Periodic verification of the reactor inventory is accomplished by sampling and NDA measurement of in-core fuel elements combined with measurements of integral reactivity and related reactor parameters that are sensitive to the total fissile inventory. A combination of statistical sampling and NDA verification with measurements of reactor parameters is more effective than either technique used by itself. Special procedures for assessment and verification for abnormal safeguards conditions are also considered. When the inspection strategies and inventory verification methods are combined with strict containment and surveillance methods, they provide a high degree of assurance that any clandestine attempt to divert a significant quantity of fissile material from a critical facility inventory will be detected. Field testing of specific hardware systems and procedures to determine their sensitivity, reliability, and operational acceptability is recommended. 50 figures, 21 tables

  3. Inventory - Dollars and sense

    International Nuclear Information System (INIS)

    Samson, J.R.

    1992-01-01

    Nuclear utilities are becoming more aware of the importance of having an inventory investment that supports two opposing philosophies. The business philosophy wants a minimal inventory investment to support a better return on invested dollars. This increase in return comes from having the dollars available to invest versus having the money tied up in inventory sitting on the shelf. The opposing viewpoint is taken by maintenance/operations organizations, which desire the maximum inventory available on-site to repair any component at any time to keep the units on-line at all times. Financial managers also want to maintain cash flow throughout operations so that plants run without interruptions. Inventory management is therefore a mixture of financial logistics with an operation perspective in mind. A small amount of common sense and accurate perception also help. The challenge to the materials/inventory manager is to optimize effectiveness of the inventory by having high material availability at the lowest possible cost

  4. Learning outcomes afforded by self-assessed, segmented video–print combinations

    OpenAIRE

    Jack Koumi

    2015-01-01

    Learning affordances of video and print are examined in order to assess the learning outcomes afforded by hybrid video–print learning packages. The affordances discussed for print are: navigability, surveyability and legibility. Those discussed for video are: design for constructive reflection, provision of realistic experiences, presentational attributes, motivational influences and teacher personalisation. The video affordances are examined through a framework of pedagogic design principles...

  5. Machine Learning on Images: Combining Passive Microwave and Optical Data to Estimate Snow Water Equivalent

    Science.gov (United States)

    Dozier, J.; Tolle, K.; Bair, N.

    2014-12-01

    We have a problem that may be a specific example of a generic one. The task is to estimate spatiotemporally distributed estimates of snow water equivalent (SWE) in snow-dominated mountain environments, including those that lack on-the-ground measurements. Several independent methods exist, but all are problematic. The remotely sensed date of disappearance of snow from each pixel can be combined with a calculation of melt to reconstruct the accumulated SWE for each day back to the last significant snowfall. Comparison with streamflow measurements in mountain ranges where such data are available shows this method to be accurate, but the big disadvantage is that SWE can only be calculated retroactively after snow disappears, and even then only for areas with little accumulation during the melt season. Passive microwave sensors offer real-time global SWE estimates but suffer from several issues, notably signal loss in wet snow or in forests, saturation in deep snow, subpixel variability in the mountains owing to the large (~25 km) pixel size, and SWE overestimation in the presence of large grains such as depth and surface hoar. Throughout the winter and spring, snow-covered area can be measured at sub-km spatial resolution with optical sensors, with accuracy and timeliness improved by interpolating and smoothing across multiple days. So the question is, how can we establish the relationship between Reconstruction—available only after the snow goes away—and passive microwave and optical data to accurately estimate SWE during the snow season, when the information can help forecast spring runoff? Linear regression provides one answer, but can modern machine learning techniques (used to persuade people to click on web advertisements) adapt to improve forecasts of floods and droughts in areas where more than one billion people depend on snowmelt for their water resources?

  6. Learning "Math on the Move": Effectiveness of a Combined Numeracy and Physical Activity Program for Primary School Children.

    Science.gov (United States)

    Vetter, Melanie; O'Connor, Helen; O'Dwyer, Nicholas; Orr, Rhonda

    2018-03-27

    Physically active learning that combines physical activity with core curriculum areas is emerging in school-based health interventions. This study investigates the effectiveness of learning an important numeracy skill of times tables (TT) while concurrently engaging in aerobic activity compared with a seated classroom approach. Grade-4 primary school students were randomly allocated to physical activity (P) or classroom (C) groups and received the alternate condition in the following term. P group received moderate to vigorous exercise (20 min, 3 times per week, 6 wk) while simultaneously learning selected TT. C group received similar learning, but seated. Changes in TT accuracy, general numeracy, aerobic fitness, and body mass index were assessed. Data were expressed as mean (SEM) and between-condition effect size (ES; 95% confidence interval). Participants [N = 85; 55% male, 9.8 (0.3) y, 36.4% overweight/obese] improved similarly on TT in both conditions [C group: 2.2% (1.1%); P group: 2.5% (1.3%); ES = 0.03; -0.30 to 0.36; P = .86]. Improvement in general numeracy was significantly greater for P group than C group [C group: 0.7% (1.2%); P group: 5.3% (1.4%); ES = 0.42; 0.08 to 0.75; P < .03]. An improvement in aerobic fitness for P group (P < .01) was not significantly greater than C group [C group: 0.8 (0.6); P group: 2.2 (0.5) mL·kg·min -1 ; ES = 0.32; -0.01 to 0.66; P = .06]. Body mass index was unchanged. Combined movement with learning TT was effective. Physically active learning paradigms may contribute to meeting daily physical activity guidelines while supporting or even boosting learning.

  7. Teaching Inventory Management Simulation Using E-Learning Software: Blackboard, Elluminate Live!, and Jing (doi: 10.3991/ijac.v1i2.568)

    OpenAIRE

    Joel Lee Oberstone

    2008-01-01

    Introducing the nuances of inventory management systems to undergraduate business students can be a daunting task. Beyond the traditional focus of the selection of order quantity and reorder point lie more murky considerations such as the impact that stockout cost and supplier selection have on these key parameters, including profit. The purpose of this paper is to illustrate how students can cultivate insights of business simulation settings through easy-to-run, downloadable Excel spreadshee...

  8. Blended Learning as a Potentially Winning Combination of Face-to-Face and Online Learning: An Exploratory Study

    Science.gov (United States)

    Auster, Carol J.

    2016-01-01

    Blended learning, in the form of screencasts to be viewed online outside of class, was incorporated into three sections of an introductory sociology course in a liberal arts college setting. The screencasts were used to introduce concepts and theories to provide more time for discussion in class and more opportunity for students to review concepts…

  9. Combining multi agent paradigm and memetic computing for personalized and adaptive learning experiences

    NARCIS (Netherlands)

    Acampora, G.; Gaeta, M.; Loia, V.

    2011-01-01

    Learning is a critical support mechanism for industrial and academic organizations to enhance the skills of employees and students and, consequently, the overall competitiveness in the new economy. The remarkable velocity and volatility of modern knowledge require novel learning methods offering

  10. Combining Machine Learning and Natural Language Processing to Assess Literary Text Comprehension

    Science.gov (United States)

    Balyan, Renu; McCarthy, Kathryn S.; McNamara, Danielle S.

    2017-01-01

    This study examined how machine learning and natural language processing (NLP) techniques can be leveraged to assess the interpretive behavior that is required for successful literary text comprehension. We compared the accuracy of seven different machine learning classification algorithms in predicting human ratings of student essays about…

  11. Revealing the inventory of type III effectors in Pantoea agglomerans gall-forming pathovars using draft genome sequences and a machine-learning approach.

    Science.gov (United States)

    Nissan, Gal; Gershovits, Michael; Morozov, Michael; Chalupowicz, Laura; Sessa, Guido; Manulis-Sasson, Shulamit; Barash, Isaac; Pupko, Tal

    2018-02-01

    Pantoea agglomerans, a widespread epiphytic bacterium, has evolved into a hypersensitive response and pathogenicity (hrp)-dependent and host-specific gall-forming pathogen by the acquisition of a pathogenicity plasmid containing a type III secretion system (T3SS) and its effectors (T3Es). Pantoea agglomerans pv. betae (Pab) elicits galls on beet (Beta vulgaris) and gypsophila (Gypsophila paniculata), whereas P. agglomerans pv. gypsophilae (Pag) incites galls on gypsophila and a hypersensitive response (HR) on beet. Draft genome sequences were generated and employed in combination with a machine-learning approach and a translocation assay into beet roots to identify the pools of T3Es in the two pathovars. The genomes of the sequenced Pab4188 and Pag824-1 strains have a similar size (∼5 MB) and GC content (∼55%). Mutational analysis revealed that, in Pab4188, eight T3Es (HsvB, HsvG, PseB, DspA/E, HopAY1, HopX2, HopAF1 and HrpK) contribute to pathogenicity on beet and gypsophila. In Pag824-1, nine T3Es (HsvG, HsvB, PthG, DspA/E, HopAY1, HopD1, HopX2, HopAF1 and HrpK) contribute to pathogenicity on gypsophila, whereas the PthG effector triggers HR on beet. HsvB, HsvG, PthG and PseB appear to endow pathovar specificities to Pab and Pag, and no homologous T3Es were identified for these proteins in other phytopathogenic bacteria. Conversely, the remaining T3Es contribute to the virulence of both pathovars, and homologous T3Es were found in other phytopathogenic bacteria. Remarkably, HsvG and HsvB, which act as host-specific transcription factors, displayed the largest contribution to disease development. © 2016 BSPP AND JOHN WILEY & SONS LTD.

  12. A Novel Teaching Tool Combined With Active-Learning to Teach Antimicrobial Spectrum Activity.

    Science.gov (United States)

    MacDougall, Conan

    2017-03-25

    Objective. To design instructional methods that would promote long-term retention of knowledge of antimicrobial pharmacology, particularly the spectrum of activity for antimicrobial agents, in pharmacy students. Design. An active-learning approach was used to teach selected sessions in a required antimicrobial pharmacology course. Students were expected to review key concepts from the course reader prior to the in-class sessions. During class, brief concept reviews were followed by active-learning exercises, including a novel schematic method for learning antimicrobial spectrum of activity ("flower diagrams"). Assessment. At the beginning of the next quarter (approximately 10 weeks after the in-class sessions), 360 students (three yearly cohorts) completed a low-stakes multiple-choice examination on the concepts in antimicrobial spectrum of activity. When data for students was pooled across years, the mean number of correct items was 75.3% for the items that tested content delivered with the active-learning method vs 70.4% for items that tested content delivered via traditional lecture (mean difference 4.9%). Instructor ratings on student evaluations of the active-learning approach were high (mean scores 4.5-4.8 on a 5-point scale) and student comments were positive about the active-learning approach and flower diagrams. Conclusion. An active-learning approach led to modestly higher scores in a test of long-term retention of pharmacology knowledge and was well-received by students.

  13. Vendor-managed inventory

    DEFF Research Database (Denmark)

    Govindan, Kannan

    2013-01-01

    Vendor-managed inventory (VMI) represents the methodology through which the upstream stage of a supply chain (vendor) takes responsibility for managing the inventories at the downstream stage (customer) based on previously agreed limits. VMI is another method by which supply chains can be managed...... review, we have identified six dimensions of VMI: namely, inventory, transportation, manufacturing, general benefits, coordination/collaboration, and information sharing. In addition, there are, three methodological classifications: modelling, simulation, and case studies. Finally, we will consider...

  14. Predictions of new AB O3 perovskite compounds by combining machine learning and density functional theory

    Science.gov (United States)

    Balachandran, Prasanna V.; Emery, Antoine A.; Gubernatis, James E.; Lookman, Turab; Wolverton, Chris; Zunger, Alex

    2018-04-01

    We apply machine learning (ML) methods to a database of 390 experimentally reported A B O3 compounds to construct two statistical models that predict possible new perovskite materials and possible new cubic perovskites. The first ML model classified the 390 compounds into 254 perovskites and 136 that are not perovskites with a 90% average cross-validation (CV) accuracy; the second ML model further classified the perovskites into 22 known cubic perovskites and 232 known noncubic perovskites with a 94% average CV accuracy. We find that the most effective chemical descriptors affecting our classification include largely geometric constructs such as the A and B Shannon ionic radii, the tolerance and octahedral factors, the A -O and B -O bond length, and the A and B Villars' Mendeleev numbers. We then construct an additional list of 625 A B O3 compounds assembled from charge conserving combinations of A and B atoms absent from our list of known compounds. Then, using the two ML models constructed on the known compounds, we predict that 235 of the 625 exist in a perovskite structure with a confidence greater than 50% and among them that 20 exist in the cubic structure (albeit, the latter with only ˜50 % confidence). We find that the new perovskites are most likely to occur when the A and B atoms are a lanthanide or actinide, when the A atom is an alkali, alkali earth, or late transition metal atom, or when the B atom is a p -block atom. We also compare the ML findings with the density functional theory calculations and convex hull analyses in the Open Quantum Materials Database (OQMD), which predicts the T =0 K ground-state stability of all the A B O3 compounds. We find that OQMD predicts 186 of 254 of the perovskites in the experimental database to be thermodynamically stable within 100 meV/atom of the convex hull and predicts 87 of the 235 ML-predicted perovskite compounds to be thermodynamically stable within 100 meV/atom of the convex hull, including 6 of these to

  15. Endogenous Business Cycle Dynamics within Metzlers Inventory Model: Adding an Inventory Floor.

    Science.gov (United States)

    Sushko, Irina; Wegener, Michael; Westerhoff, Frank; Zaklan, Georg

    2009-04-01

    Metzlers inventory model may produce dampened fluctuations in economic activity, thus contributing to our understanding of business cycle dynamics. For some parameter combinations, however, the model generates oscillations with increasing amplitude, implying that the inventory stock of firms eventually turns negative. Taking this observation into account, we reformulate Metzlers model by simply putting a floor to the inventory level. Within the new piecewise linear model, endogenous business cycle dynamics may now be triggered via a center bifurcation, i.e. for certain parameter combinations production changes are (quasi-)periodic.

  16. National Wetlands Inventory Lines

    Data.gov (United States)

    Minnesota Department of Natural Resources — Linear wetland features (including selected streams, ditches, and narrow wetland bodies) mapped as part of the National Wetlands Inventory (NWI). The National...

  17. Learning-based adaptive prescribed performance control of postcapture space robot-target combination without inertia identifications

    Science.gov (United States)

    Wei, Caisheng; Luo, Jianjun; Dai, Honghua; Bian, Zilin; Yuan, Jianping

    2018-05-01

    In this paper, a novel learning-based adaptive attitude takeover control method is investigated for the postcapture space robot-target combination with guaranteed prescribed performance in the presence of unknown inertial properties and external disturbance. First, a new static prescribed performance controller is developed to guarantee that all the involved attitude tracking errors are uniformly ultimately bounded by quantitatively characterizing the transient and steady-state performance of the combination. Then, a learning-based supplementary adaptive strategy based on adaptive dynamic programming is introduced to improve the tracking performance of static controller in terms of robustness and adaptiveness only utilizing the input/output data of the combination. Compared with the existing works, the prominent advantage is that the unknown inertial properties are not required to identify in the development of learning-based adaptive control law, which dramatically decreases the complexity and difficulty of the relevant controller design. Moreover, the transient and steady-state performance is guaranteed a priori by designer-specialized performance functions without resorting to repeated regulations of the controller parameters. Finally, the three groups of illustrative examples are employed to verify the effectiveness of the proposed control method.

  18. Learning from doing: the case for combining normalisation process theory and participatory learning and action research methodology for primary healthcare implementation research.

    Science.gov (United States)

    de Brún, Tomas; O'Reilly-de Brún, Mary; O'Donnell, Catherine A; MacFarlane, Anne

    2016-08-03

    The implementation of research findings is not a straightforward matter. There are substantive and recognised gaps in the process of translating research findings into practice and policy. In order to overcome some of these translational difficulties, a number of strategies have been proposed for researchers. These include greater use of theoretical approaches in research focused on implementation, and use of a wider range of research methods appropriate to policy questions and the wider social context in which they are placed. However, questions remain about how to combine theory and method in implementation research. In this paper, we respond to these proposals. Focussing on a contemporary social theory, Normalisation Process Theory, and a participatory research methodology, Participatory Learning and Action, we discuss the potential of their combined use for implementation research. We note ways in which Normalisation Process Theory and Participatory Learning and Action are congruent and may therefore be used as heuristic devices to explore, better understand and support implementation. We also provide examples of their use in our own research programme about community involvement in primary healthcare. Normalisation Process Theory alone has, to date, offered useful explanations for the success or otherwise of implementation projects post-implementation. We argue that Normalisation Process Theory can also be used to prospectively support implementation journeys. Furthermore, Normalisation Process Theory and Participatory Learning and Action can be used together so that interventions to support implementation work are devised and enacted with the expertise of key stakeholders. We propose that the specific combination of this theory and methodology possesses the potential, because of their combined heuristic force, to offer a more effective means of supporting implementation projects than either one might do on its own, and of providing deeper understandings of

  19. Examining Change in Metacognitive Knowledge and Metacognitive Control During Motor Learning: What Can be Learned by Combining Methodological Approaches?

    Directory of Open Access Journals (Sweden)

    Claire Sangster Jokić

    2014-04-01

    Full Text Available Growing recognition of the importance of understanding metacognitive behaviour as it occurs in everyday learning situations has prompted an expansion of the methodological approaches used to examine metacognition. This becomes especially pertinent when examining the process of metacognitive change, where 'on-line' observational approaches able to capture metacognitive performance as it occurs during socially-mediated learning are being increasingly applied. This study applied a mixed methods approach to examine children's metacognitive performance as it was exhibited during participation in an intervention program aimed at addressing motor performance difficulties. Participants in the study were ten 7-9 year old children with developmental coordination disorder (DCD, a condition characterized by poor motor coordination and difficulty acquiring motor-based tasks. All participants engaged in a 10-session program in which children were taught to use a problem-solving strategy for addressing motor performance difficulties. To examine children's metacognitive performance, sessions were video-taped and subsequently analysed using a quantitative observational coding method and an in-depth qualitative review of therapist-child interactions. This allowed for a fine-grained analysis of children's demonstration of metacognitive knowledge and control and how such performance evolved over the course of the program. Of particular interest was the finding that while children were often able to express task-specific knowledge, they failed to apply this knowledge during practice. Conversely, children were often able to demonstrate performance-based evidence for metacognitive control but were not able to make conscious reports of such skill following practice. This finding is consistent with models of metacognitive development which suggest that the emergence of performance-based metacognitive skills precede the ability for the conscious expression of

  20. Utilizing a Simulation Exercise to Illustrate Critical Inventory Management Concepts

    Science.gov (United States)

    Umble, Elisabeth; Umble, Michael

    2013-01-01

    Most undergraduate business students simply do not appreciate the elegant mathematical beauty of inventory models. So how does an instructor capture students' interest and keep them engaged in the learning process when teaching inventory management concepts? This paper describes a competitive and energizing in-class simulation game that introduces…

  1. A Control Systems Concept Inventory Test Design and Assessment

    Science.gov (United States)

    Bristow, M.; Erkorkmaz, K.; Huissoon, J. P.; Jeon, Soo; Owen, W. S.; Waslander, S. L.; Stubley, G. D.

    2012-01-01

    Any meaningful initiative to improve the teaching and learning in introductory control systems courses needs a clear test of student conceptual understanding to determine the effectiveness of proposed methods and activities. The authors propose a control systems concept inventory. Development of the inventory was collaborative and iterative. The…

  2. Computer Science Concept Inventories: Past and Future

    Science.gov (United States)

    Taylor, C.; Zingaro, D.; Porter, L.; Webb, K. C.; Lee, C. B.; Clancy, M.

    2014-01-01

    Concept Inventories (CIs) are assessments designed to measure student learning of core concepts. CIs have become well known for their major impact on pedagogical techniques in other sciences, especially physics. Presently, there are no widely used, validated CIs for computer science. However, considerable groundwork has been performed in the form…

  3. Denmark's National Inventory Report

    DEFF Research Database (Denmark)

    Illerup, J. B.; Lyck, E.; Winther, M.

    This report is Denmark's National Inventory Report reported to the Conference of the Parties under the United Nations Framework Convention on Climate Change (UNFCCC) due by 15 April 2001. The report contains information on Denmark's inventories for all years' from 1990 to 1999 for CO2, CH4, N2O, CO...

  4. Uncertainties in emission inventories

    NARCIS (Netherlands)

    Aardenne, van J.A.

    2002-01-01

    Emission inventories provide information about the amount of a pollutant that is emitted to the atmosphere as a result of a specific anthropogenic or natural process at a given time or place. Emission inventories can be used for either policy or scientific purposes. For

  5. Denmark's National Inventory Report

    DEFF Research Database (Denmark)

    Illerup, J. B.; Lyck, E.; Winther, M.

    This report is Denmark's National Inventory Report reported to the Conference of the Parties under the United Nations Framework Convention on Climate Change (UNFCCC) due by 15 April 2001. The report contains information on Denmark's inventories for all years' from 1990 to 1999 for CO2, CH4, N2O, ......, NMVOC, SO2, HFCs, PFCs and SF6....

  6. Predicting human splicing branchpoints by combining sequence-derived features and multi-label learning methods.

    Science.gov (United States)

    Zhang, Wen; Zhu, Xiaopeng; Fu, Yu; Tsuji, Junko; Weng, Zhiping

    2017-12-01

    Alternative splicing is the critical process in a single gene coding, which removes introns and joins exons, and splicing branchpoints are indicators for the alternative splicing. Wet experiments have identified a great number of human splicing branchpoints, but many branchpoints are still unknown. In order to guide wet experiments, we develop computational methods to predict human splicing branchpoints. Considering the fact that an intron may have multiple branchpoints, we transform the branchpoint prediction as the multi-label learning problem, and attempt to predict branchpoint sites from intron sequences. First, we investigate a variety of intron sequence-derived features, such as sparse profile, dinucleotide profile, position weight matrix profile, Markov motif profile and polypyrimidine tract profile. Second, we consider several multi-label learning methods: partial least squares regression, canonical correlation analysis and regularized canonical correlation analysis, and use them as the basic classification engines. Third, we propose two ensemble learning schemes which integrate different features and different classifiers to build ensemble learning systems for the branchpoint prediction. One is the genetic algorithm-based weighted average ensemble method; the other is the logistic regression-based ensemble method. In the computational experiments, two ensemble learning methods outperform benchmark branchpoint prediction methods, and can produce high-accuracy results on the benchmark dataset.

  7. Combining fMRI and behavioral measures to examine the process of human learning.

    Science.gov (United States)

    Karuza, Elisabeth A; Emberson, Lauren L; Aslin, Richard N

    2014-03-01

    Prior to the advent of fMRI, the primary means of examining the mechanisms underlying learning were restricted to studying human behavior and non-human neural systems. However, recent advances in neuroimaging technology have enabled the concurrent study of human behavior and neural activity. We propose that the integration of behavioral response with brain activity provides a powerful method of investigating the process through which internal representations are formed or changed. Nevertheless, a review of the literature reveals that many fMRI studies of learning either (1) focus on outcome rather than process or (2) are built on the untested assumption that learning unfolds uniformly over time. We discuss here various challenges faced by the field and highlight studies that have begun to address them. In doing so, we aim to encourage more research that examines the process of learning by considering the interrelation of behavioral measures and fMRI recording during learning. Copyright © 2013 Elsevier Inc. All rights reserved.

  8. Approaches and Study Skills Inventory for Students (ASSIST) in an Introductory Course in Chemistry

    Science.gov (United States)

    Brown, Stephen; White, Sue; Wakeling, Lara; Naiker, Mani

    2015-01-01

    Approaches to study and learning may enhance or undermine educational outcomes, and thus it is important for educators to be knowledgeable about their students' approaches to study and learning. The Approaches and Study Skills Inventory for Students (ASSIST)--a 52 item inventory which identifies three learning styles (Deep, Strategic, and…

  9. Inventory control strategies

    International Nuclear Information System (INIS)

    Primrose, D.

    1998-01-01

    Finning International Inc. is in the business of selling, financing and servicing Caterpillar and complementary equipment. Its main markets are in western Canada, Britain and Chile. This paper discusses the parts inventory strategies system for Finning (Canada). The company's territory covers British Columbia, Alberta, the Yukon and the Northwest Territories. Finning's parts inventory consists of 80,000 component units valued at more than $150 M. Distribution centres are located in Langley, British Columbia and Edmonton, Alberta. To make inventory and orders easier to control, Finning has designed a computer-based system, with software written exclusively for Caterpillar dealers. The system makes use of a real time electronic interface with all Finning locations, plus all Caterpillar facilities and other dealers in North America. Details of the system are discussed, including territorial stocking procedures, addition to stock, exhaustion of stock, automatic/suggest order controls, surplus inventory management, and procedures for jointly managed inventory. 3 tabs., 1 fig

  10. Optimal fuel inventory strategies

    International Nuclear Information System (INIS)

    Caspary, P.J.; Hollibaugh, J.B.; Licklider, P.L.; Patel, K.P.

    1990-01-01

    In an effort to maintain their competitive edge, most utilities are reevaluating many of their conventional practices and policies in an effort to further minimize customer revenue requirements without sacrificing system reliability. Over the past several years, Illinois Power has been rethinking its traditional fuel inventory strategies, recognizing that coal supplies are competitive and plentiful and that carrying charges on inventory are expensive. To help the Company achieve one of its strategic corporate goals, an optimal fuel inventory study was performed for its five major coal-fired generating stations. The purpose of this paper is to briefly describe Illinois Power's system and past practices concerning coal inventories, highlight the analytical process behind the optimal fuel inventory study, and discuss some of the recent experiences affecting coal deliveries and economic dispatch

  11. Exploring Bhavana samskara using Tinospora cordifolia and Phyllanthus emblica combination for learning and memory in mice

    Directory of Open Access Journals (Sweden)

    Harshad Onkarrao Malve

    2015-01-01

    Full Text Available Background: Current medications for dementia and enhancement of learning and memory are limited hence we need to explore traditional medicinal systems like Ayurveda to investigate agents that can improve learning and enhance memory. Objective: The present study was carried out to evaluate effects and mechanisms of Ayurveda drug formulations, Tinospora cordifolia (Tc and Phyllanthus emblica (Pe with and without Bhavana samskara on learning and memory of mice. Materials and Methods: After approval of Animal Ethics Committee, Swiss albino mice were divided into seven groups, administered orally: Distilled water, Rivastigmine (2.4 mg/kg, Tc (100 mg/kg, Pe (300 mg/kg, formulation 1 (Tc + Pe: 400 mg/kg and formulation 2 (Tc + Pe + Ocimum sanctum: 400 mg/kg daily for 15 days. Piracetam (200 mg/kg was injected daily intraperitoneally for 8 days. The mice underwent a learning session using elevated plus maze. Memory was tested 24 hours later. Results: Mice pretreated with all the drugs showed a trend toward reducing transfer latencies but values were comparable to vehicle control. In all drug-treated groups, a significant reduction in transfer latency was observed after 24 h. Improvement in learning and memory by both formulations were comparable to individual plant drugs, Tc and Pe. Conclusion: The plant drugs showed improvements in learning and memory. The fixed-dose formulations with Bhavana samskara, showed encouraging results as compared to individual agents but the difference was not statistically significant. Hence, the concept of Bhavana samskara could not be explored in the present study. However, these drugs showed comparable or better effects than the modern medicinal agents thus, their therapeutic potential as nootropics needs to be explored further.

  12. Inventory Control System by Using Vendor Managed Inventory (VMI)

    OpenAIRE

    Dona Sabila Alzena; Mustafid Mustafid; Suryono Suryono

    2018-01-01

    The inventory control system has a strategic role for the business in managing inventory operations. Management of conventional inventory creates problems in the stock of goods that often runs into vacancies and excess goods at the retail level. This study aims to build inventory control system that can maintain the stability of goods availability at the retail level. The implementation of Vendor Managed Inventory (VMI) method on inventory control system provides transparency of sales data an...

  13. Combining brain stimulation and video game to promote long-term transfer of learning and cognitive enhancement.

    Science.gov (United States)

    Looi, Chung Yen; Duta, Mihaela; Brem, Anna-Katharine; Huber, Stefan; Nuerk, Hans-Christoph; Cohen Kadosh, Roi

    2016-02-23

    Cognitive training offers the potential for individualised learning, prevention of cognitive decline, and rehabilitation. However, key research challenges include ecological validity (training design), transfer of learning and long-term effects. Given that cognitive training and neuromodulation affect neuroplasticity, their combination could promote greater, synergistic effects. We investigated whether combining transcranial direct current stimulation (tDCS) with cognitive training could further enhance cognitive performance compared to training alone, and promote transfer within a short period of time. Healthy adults received real or sham tDCS over their dorsolateral prefrontal cortices during two 30-minute mathematics training sessions involving body movements. To examine the role of training, an active control group received tDCS during a non-mathematical task. Those who received real tDCS performed significantly better in the game than the sham group, and showed transfer effects to working memory, a related but non-numerical cognitive domain. This transfer effect was absent in active and sham control groups. Furthermore, training gains were more pronounced amongst those with lower baseline cognitive abilities, suggesting the potential for reducing cognitive inequalities. All effects associated with real tDCS remained 2 months post-training. Our study demonstrates the potential benefit of this approach for long-term enhancement of human learning and cognition.

  14. Exploration of problem-based learning combined with standardized patient in the teaching of basic science of ophthalmology

    Directory of Open Access Journals (Sweden)

    Jin Yan

    2015-08-01

    Full Text Available AIM:To investigate the effect of problem-based learning(PBLcombined with standardized patient(SPin the teaching of basic science of ophthalmology. METHODS: Sixty-four students of Optometry in grade 2012 were randomly divided into experimental group(n=32and control group(n=32. Traditional teaching method was implemented in control group while PBL combined with SP was applied in experimental group. At the end of term students were interviewed using self-administered questionnaire to obtain their evaluation for teaching effect. Measurement data were expressed as (-overx±s and analyzed by independent samples t test. Enumeration data were analyzed by χ2 test, and PRESULTS:The mean scores of theory test(83.22±3.75and experimental test(94.28±2.20in experimental group were significantly higher than theory test(70.72±3.95and experimental test(85.44±3.52in control group(all PPPCONCLUSION:Using PBL combined with SP teaching mode in basic science of ophthalmology can highly improve learning enthusiasm of students and cultivate self-learning ability of students, practice ability and ability of clinical analysis.

  15. E-learning optimization: the relative and combined effects of mental practice and modeling on enhanced podcast-based learning-a randomized controlled trial.

    Science.gov (United States)

    Alam, Fahad; Boet, Sylvain; Piquette, Dominique; Lai, Anita; Perkes, Christopher P; LeBlanc, Vicki R

    2016-10-01

    Enhanced podcasts increase learning, but evidence is lacking on how they should be designed to optimize their effectiveness. This study assessed the impact two learning instructional design methods (mental practice and modeling), either on their own or in combination, for teaching complex cognitive medical content when incorporated into enhanced podcasts. Sixty-three medical students were randomised to one of four versions of an airway management enhanced podcast: (1) control: narrated presentation; (2) modeling: narration with video demonstration of skills; (3) mental practice: narrated presentation with guided mental practice; (4) combined: modeling and mental practice. One week later, students managed a manikin-based simulated airway crisis. Knowledge acquisition was assessed by baseline and retention multiple-choice quizzes. Two blinded raters assessed all videos obtained from simulated crises to measure the students' skills using a key-elements scale, critical error checklist, and the Ottawa global rating scale (GRS). Baseline knowledge was not different between all four groups (p = 0.65). One week later, knowledge retention was significantly higher for (1) both the mental practice and modeling group than the control group (p = 0.01; p = 0.01, respectively) and (2) the combined mental practice and modeling group compared to all other groups (all ps = 0.01). Regarding skills acquisition, the control group significantly under-performed in comparison to all other groups on the key-events scale (all ps ≤ 0.05), the critical error checklist (all ps ≤ 0.05), and the Ottawa GRS (all ps ≤ 0.05). The combination of mental practice and modeling led to greater improvement on the key events checklist (p = 0.01) compared to either strategy alone. However, the combination of the two strategies did not result in any further learning gains on the two other measures of clinical performance (all ps > 0.05). The effectiveness of enhanced podcasts for

  16. Exploring Student-Generated Animations, Combined with a Representational Pedagogy, as a Tool for Learning in Chemistry

    Science.gov (United States)

    Yaseen, Zeynep; Aubusson, Peter

    2018-02-01

    This article describes an investigation into teaching and learning with student-generated animations combined with a representational pedagogy. In particular, it reports on interactive discussions that were stimulated by the students' own animations as well as their critiques of experts' animations. Animations representing views of states of matter provided a vehicle by which to investigate learning in a series of lessons. The study was implemented with Year 11 high school students. After students constructed, presented and discussed their animations, they watched and critiqued experts' animations. They were then interviewed about the teaching-learning process. Most students (91%) spoke positively about follow-up discussion classes, saying that their previous conceptions and understanding of states of matter had improved. They explained that they had identified some alternative conceptions, which they had held regarding states of matter and explained how their conceptions had changed. They reported that the teaching/learning process had helped them to develop a deeper understanding of the changing states of matter.

  17. On combining principal components with Fisher's linear discriminants for supervised learning

    NARCIS (Netherlands)

    Pechenizkiy, M.; Tsymbal, A.; Puuronen, S.

    2006-01-01

    "The curse of dimensionality" is pertinent to many learning algorithms, and it denotes the drastic increase of computational complexity and classification error in high dimensions. In this paper, principal component analysis (PCA), parametric feature extraction (FE) based on Fisher’s linear

  18. Patterns of Learning in Verbal Discrimination as an Interaction of Social Reinforcement and Sex Combinations

    Science.gov (United States)

    Ratliff, Richard G.; And Others

    1976-01-01

    A total of 540 college students were run in two verbal discrimination learning studies (the second, a replication of the first) with one of three verbal reward conditions. In both studies, equal numbers of male and female subjects were run in each reward condition by each male and female experimenter. (MS)

  19. Combining Feminist Pedagogy and Transactional Distance to Create Gender-Sensitive Technology-Enhanced Learning

    Science.gov (United States)

    Herman, Clem; Kirkup, Gill

    2017-01-01

    In this paper, we argue for a new synthesis of two pedagogic theories: feminist pedagogy and transactional distance, which explain why and how distance education has been such a positive system for women in a national distance learning university. We illustrate this with examples of positive action initiatives for women. The concept of…

  20. Combining Generative and Discriminative Representation Learning for Lung CT Analysis With Convolutional Restricted Boltzmann Machines

    NARCIS (Netherlands)

    G. van Tulder (Gijs); M. de Bruijne (Marleen)

    2016-01-01

    textabstractThe choice of features greatly influences the performance of a tissue classification system. Despite this, many systems are built with standard, predefined filter banks that are not optimized for that particular application. Representation learning methods such as restricted Boltzmann

  1. Games and Machine Learning: A Powerful Combination in an Artificial Intelligence Course

    Science.gov (United States)

    Wallace, Scott A.; McCartney, Robert; Russell, Ingrid

    2010-01-01

    Project MLeXAI [Machine Learning eXperiences in Artificial Intelligence (AI)] seeks to build a set of reusable course curriculum and hands on laboratory projects for the artificial intelligence classroom. In this article, we describe two game-based projects from the second phase of project MLeXAI: Robot Defense--a simple real-time strategy game…

  2. Heparan Sulfate Induces Necroptosis in Murine Cardiomyocytes: A Medical-In silico Approach Combining In vitro Experiments and Machine Learning.

    Science.gov (United States)

    Zechendorf, Elisabeth; Vaßen, Phillip; Zhang, Jieyi; Hallawa, Ahmed; Martincuks, Antons; Krenkel, Oliver; Müller-Newen, Gerhard; Schuerholz, Tobias; Simon, Tim-Philipp; Marx, Gernot; Ascheid, Gerd; Schmeink, Anke; Dartmann, Guido; Thiemermann, Christoph; Martin, Lukas

    2018-01-01

    Life-threatening cardiomyopathy is a severe, but common, complication associated with severe trauma or sepsis. Several signaling pathways involved in apoptosis and necroptosis are linked to trauma- or sepsis-associated cardiomyopathy. However, the underling causative factors are still debatable. Heparan sulfate (HS) fragments belong to the class of danger/damage-associated molecular patterns liberated from endothelial-bound proteoglycans by heparanase during tissue injury associated with trauma or sepsis. We hypothesized that HS induces apoptosis or necroptosis in murine cardiomyocytes. By using a novel Medical- In silico approach that combines conventional cell culture experiments with machine learning algorithms, we aimed to reduce a significant part of the expensive and time-consuming cell culture experiments and data generation by using computational intelligence (refinement and replacement). Cardiomyocytes exposed to HS showed an activation of the intrinsic apoptosis signal pathway via cytochrome C and the activation of caspase 3 (both p  machine learning algorithms.

  3. Interactive Inventory Monitoring

    Science.gov (United States)

    Garud, Sumedha

    2013-01-01

    Method and system for monitoring present location and/or present status of a target inventory item, where the inventory items are located on one or more inventory shelves or other inventory receptacles that communicate with an inventory base station through use of responders such as RFIDs. A user operates a hand held interrogation and display (lAD) module that communicates with, or is part of the base station to provide an initial inquiry. lnformation on location(s) of the larget invenlory item is also indicated visibly and/or audibly on the receptacle(s) for the user. Status information includes an assessment of operation readiness and a time, if known, that the specified inventory item or class was last removed or examined or modified. Presentation of a user access level may be required for access to the target inventgory item. Another embodiment provides inventory informatin for a stack as a sight-impaired or hearing-impaired person adjacent to that stack.

  4. SBA Network Components & Software Inventory

    Data.gov (United States)

    Small Business Administration — SBA’s Network Components & Software Inventory contains a complete inventory of all devices connected to SBA’s network including workstations, servers, routers,...

  5. Combining Distance and Face-To Teaching and Learning in Spatial Computations

    Science.gov (United States)

    Gulland, E.-K.; Schut, A. G. T.; Veenendaal, B.

    2011-09-01

    Retention and passing rates as well as student engagement in computer programming and problem solving units are a major concern in tertiary spatial science courses. A number of initiatives were implemented to improve this. A pilot study reviews the changes made to the teaching and learning environment, including the addition of new resources and modifications to assessments, and investigates their effectiveness. In particular, the study focuses on the differences between students studying in traditional, oncampus mode and distance, e-learning mode. Student results and retention rates from 2009-2011, data from in-lecture clicker response units and two anonymous surveys collected in 2011 were analysed. Early results indicate that grades improved for engaged students but pass rates or grades of the struggling cohort of students did not improve significantly.

  6. Growing adaptive machines combining development and learning in artificial neural networks

    CERN Document Server

    Bredeche, Nicolas; Doursat, René

    2014-01-01

    The pursuit of artificial intelligence has been a highly active domain of research for decades, yielding exciting scientific insights and productive new technologies. In terms of generating intelligence, however, this pursuit has yielded only limited success. This book explores the hypothesis that adaptive growth is a means of moving forward. By emulating the biological process of development, we can incorporate desirable characteristics of natural neural systems into engineered designs, and thus move closer towards the creation of brain-like systems. The particular focus is on how to design artificial neural networks for engineering tasks. The book consists of contributions from 18 researchers, ranging from detailed reviews of recent domains by senior scientists, to exciting new contributions representing the state of the art in machine learning research. The book begins with broad overviews of artificial neurogenesis and bio-inspired machine learning, suitable both as an introduction to the domains and as a...

  7. Combining D-cycloserine with appetitive extinction learning modulates amygdala activity during recall.

    Science.gov (United States)

    Ebrahimi, Claudia; Koch, Stefan P; Friedel, Eva; Crespo, Ilsoray; Fydrich, Thomas; Ströhle, Andreas; Heinz, Andreas; Schlagenhauf, Florian

    2017-07-01

    Appetitive Pavlovian conditioning plays a crucial role in the pathogenesis of drug addiction and conditioned reward cues can trigger craving and relapse even after long phases of abstinence. Promising preclinical work showed that the NMDA-receptor partial agonist D-cycloserine (DCS) facilitates Pavlovian extinction learning of fear and drug cues. Furthermore, DCS-augmented exposure therapy seems to be beneficial in various anxiety disorders, while the supposed working mechanism of DCS during human appetitive or aversive extinction learning is still not confirmed. To test the hypothesis that DCS administration before extinction training improves extinction learning, healthy adults (n=32) underwent conditioning, extinction, and extinction recall on three successive days in a randomized, double-blind, placebo-controlled fMRI design. Monetary wins and losses served as unconditioned stimuli during conditioning to probe appetitive and aversive learning. An oral dose of 50mg of DCS or placebo was administered 1h before extinction training and DCS effects during extinction recall were evaluated on a behavioral and neuronal level. We found attenuated amygdala activation in the DCS compared to the placebo group during recall of the extinguished appetitive cue, along with evidence for enhanced functional amygdala-vmPFC coupling in the DCS group. While the absence of additional physiological measures of conditioned responses during recall in this study prevent the evaluation of a behavioral DCS effect, our neuronal findings are in accordance with recent theories linking successful extinction recall in humans to modulatory top-down influences from the vmPFC that inhibit amygdala activation. Our results should encourage further translational studies concerning the usefulness of DCS to target maladaptive Pavlovian reward associations. Copyright © 2017 Elsevier Inc. All rights reserved.

  8. F-SVM: Combination of Feature Transformation and SVM Learning via Convex Relaxation

    OpenAIRE

    Wu, Xiaohe; Zuo, Wangmeng; Zhu, Yuanyuan; Lin, Liang

    2015-01-01

    The generalization error bound of support vector machine (SVM) depends on the ratio of radius and margin, while standard SVM only considers the maximization of the margin but ignores the minimization of the radius. Several approaches have been proposed to integrate radius and margin for joint learning of feature transformation and SVM classifier. However, most of them either require the form of the transformation matrix to be diagonal, or are non-convex and computationally expensive. In this ...

  9. Combining video games and constructionist design to support deep learning in play

    OpenAIRE

    Holbert, Nathan; Weintrop, David; Wilensky, Uri; Sengupta, Pratim; Killingsworth, Stephen; Krinks, Kyra; Clark, Doug; Brady, Corey; Shapiro, R. Benjamin; Russ, Rosemary S.; Klopfer, Eric

    2014-01-01

    This effort has produced many interesting games though it is unclear if “educational video games” have achieved their promise. Similarly, for many years constructionists have engaged children in learning across a variety of contexts, including game design. While these programs have been successful, their exploratory nature leads to concerns about content coverage. In this symposium we discuss the potential of blending these two design traditions. Constructionist video games infuse tradi...

  10. Combining advanced networked technology and pedagogical methods to improve collaborative distance learning.

    Science.gov (United States)

    Staccini, Pascal; Dufour, Jean-Charles; Raps, Hervé; Fieschi, Marius

    2005-01-01

    Making educational material be available on a network cannot be reduced to merely implementing hypermedia and interactive resources on a server. A pedagogical schema has to be defined to guide students for learning and to provide teachers with guidelines to prepare valuable and upgradeable resources. Components of a learning environment, as well as interactions between students and other roles such as author, tutor and manager, can be deduced from cognitive foundations of learning, such as the constructivist approach. Scripting the way a student will to navigate among information nodes and interact with tools to build his/her own knowledge can be a good way of deducing the features of the graphic interface related to the management of the objects. We defined a typology of pedagogical resources, their data model and their logic of use. We implemented a generic and web-based authoring and publishing platform (called J@LON for Join And Learn On the Net) within an object-oriented and open-source programming environment (called Zope) embedding a content management system (called Plone). Workflow features have been used to mark the progress of students and to trace the life cycle of resources shared by the teaching staff. The platform integrated advanced on line authoring features to create interactive exercises and support live courses diffusion. The platform engine has been generalized to the whole curriculum of medical studies in our faculty; it also supports an international master of risk management in health care and will be extent to all other continuous training diploma.

  11. What we have learned about the Higgs boson from the bosonic channels and more inclusive combinations of data

    CERN Document Server

    Yuan, Li; The ATLAS collaboration

    2015-01-01

    This talk will review the status of what has been learned from LHC run-1 about the properties of the observed Higgs boson mostly from the bosonic decay channels, but also from latest/final inclusive analyses of the coupling structure. The focus of the talk should be the measurement of the Higgs boson mass (with focus on the combination of ATLAS and CMS), the status of the spin and CP properties and the analysis of the coupling structure. The talk is aimed to present the final LHC run-1 results from ATLAS and CMS.

  12. Manpower allocation in a cellular manufacturing system considering the impact of learning, training and combination of learning and training in operator skills

    Directory of Open Access Journals (Sweden)

    Masoud

    2017-01-01

    Full Text Available In this article, a manpower allocation and cell loading problem is studied, where demand is sto-chastic. The inter-cell and intra-cell movements are considered and attention is focused on as-signing operators with different skill levels to operations, because cell performance in addition to load cell is dependent on manpower. The purpose of this article is manpower allocation in cellu-lar manufacturing with consideration to learning and training policies. The manpower skill levels are determined in order to enhance production rate. The main contribution of this approach is the scenarios of training and learning in addition to the combination of training and learning being simulated. By using these three scenarios, the skill level of workers increase which reduces the processing time. In this regard cell layout is static where processing times and customer demand follow a normal distribution. As one of the significant costs of industrial unit is related to pro-duction cost, this study has attempted to reduce these costs by increasing the skill level of opera-tor which causes to reduce the processing time. Scenarios are evaluated by using a simulation method that finally attained results indicate this simulation provides better manpower assign-ments.

  13. Learning Activities That Combine Science Magic Activities with the 5E Instructional Model to Influence Secondary-School Students' Attitudes to Science

    Science.gov (United States)

    Lin, Jang-Long; Cheng, Meng-Fei; Chang, Ying-Chi; Li, Hsiao-Wen; Chang, Jih-Yuan; Lin, Deng-Min

    2014-01-01

    The purpose of this study was to investigate how learning materials based on Science Magic activities affect student attitudes to science. A quasi-experimental design was conducted to explore the combination of Science Magic with the 5E Instructional Model to develop learning materials for teaching a science unit about friction. The participants…

  14. National Emission Inventory (NEI)

    Data.gov (United States)

    U.S. Environmental Protection Agency — This data exchange allows states to submit data to the US Environmental Protection Agency's National Emissions Inventory (NEI). NEI is a national database of air...

  15. National Emission Inventory

    Data.gov (United States)

    U.S. Environmental Protection Agency — The National Emission Inventory contains measured, modeled, and estimated data for emissions of all known source categories in the US (stationary sources, fires,...

  16. Toxics Release Inventory (TRI)

    Data.gov (United States)

    U.S. Environmental Protection Agency — The Toxics Release Inventory (TRI) is a dataset compiled by the U.S. Environmental Protection Agency (EPA). It contains information on the release and waste...

  17. Business Process Inventory

    Data.gov (United States)

    Office of Personnel Management — Inventory of maps and descriptions of the business processes of the U.S. Office of Personnel Management (OPM), with an emphasis on the processes of the Office of the...

  18. National Wetlands Inventory Points

    Data.gov (United States)

    Minnesota Department of Natural Resources — Wetland point features (typically wetlands that are too small to be as area features at the data scale) mapped as part of the National Wetlands Inventory (NWI). The...

  19. Asset Inventory Database

    Data.gov (United States)

    US Agency for International Development — AIDM is used to track USAID assets such as furniture, computers, and equipment. Using portable bar code readers, receiving and inventory personnel can capture...

  20. NCRN Hemlock Inventory Data

    Data.gov (United States)

    Department of the Interior — ​Data associated with the 2015 hemlock inventory project in NCR. Eastern hemlock (Tsuga canadensis) is a coniferous tree native to the NE and Appalachian regions of...

  1. Logistics and Inventory System -

    Data.gov (United States)

    Department of Transportation — The Logistics and Inventory System (LIS) is the agencys primary supply/support automation tool. The LIS encompasses everything from order entry by field specialists...

  2. Public Waters Inventory Maps

    Data.gov (United States)

    Minnesota Department of Natural Resources — This theme is a scanned and rectified version of the Minnesota DNR - Division of Waters "Public Waters Inventory" (PWI) maps. DNR Waters utilizes a small scale...

  3. VA Enterprise Data Inventory

    Data.gov (United States)

    Department of Veterans Affairs — The Department of Veterans Affairs Enterprise Data Inventory accounts for all of the datasets used in the agency's information systems. This entry was approved for...

  4. Combining AI Methods for Learning Bots in a Real-Time Strategy Game

    OpenAIRE

    Robin Baumgarten; Simon Colton; Mark Morris

    2009-01-01

    We describe an approach for simulating human game-play in strategy games using a variety of AI techniques, including simulated annealing, decision tree learning, and case-based reasoning. We have implemented an AI-bot that uses these techniques to form a novel approach for planning fleet movements and attacks in DEFCON, a nuclear war simulation strategy game released in 2006 by Introversion Software Ltd. The AI-bot retrieves plans from a case-base of recorded games, then uses these to generat...

  5. The effect of flipped teaching combined with modified team-based learning on student performance in physiology.

    Science.gov (United States)

    Gopalan, Chaya; Klann, Megan C

    2017-09-01

    Flipped classroom is a hybrid educational format that shifts guided teaching out of class, thus allowing class time for student-centered learning. Although this innovative teaching format is gaining attention, there is limited evidence on the effectiveness of flipped teaching on student performance. We compared student performance and student attitudes toward flipped teaching with that of traditional lectures using a partial flipped study design. Flipped teaching expected students to have completed preclass material, such as assigned reading, instructor-prepared lecture video(s), and PowerPoint slides. In-class activities included the review of difficult topics, a modified team-based learning (TBL) session, and an individual assessment. In the unflipped teaching format, students were given PowerPoint slides and reading assignment before their scheduled lectures. The class time consisted of podium-style lecture, which was captured in real time and was made available for students to use as needed. Comparison of student performance between flipped and unflipped teaching showed that flipped teaching improved student performance by 17.5%. This was true of students in both the upper and lower half of the class. A survey conducted during this study indicated that 65% of the students changed the way they normally studied, and 69% of the students believed that they were more prepared for class with flipped learning than in the unflipped class. These findings suggest that flipped teaching, combined with TBL, is more effective than the traditional lecture. Copyright © 2017 the American Physiological Society.

  6. A Hybrid Machine Learning Method for Fusing fMRI and Genetic Data: Combining both Improves Classification of Schizophrenia

    Directory of Open Access Journals (Sweden)

    Honghui Yang

    2010-10-01

    Full Text Available We demonstrate a hybrid machine learning method to classify schizophrenia patients and healthy controls, using functional magnetic resonance imaging (fMRI and single nucleotide polymorphism (SNP data. The method consists of four stages: (1 SNPs with the most discriminating information between the healthy controls and schizophrenia patients are selected to construct a support vector machine ensemble (SNP-SVME. (2 Voxels in the fMRI map contributing to classification are selected to build another SVME (Voxel-SVME. (3 Components of fMRI activation obtained with independent component analysis (ICA are used to construct a single SVM classifier (ICA-SVMC. (4 The above three models are combined into a single module using a majority voting approach to make a final decision (Combined SNP-fMRI. The method was evaluated by a fully-validated leave-one-out method using 40 subjects (20 patients and 20 controls. The classification accuracy was: 0.74 for SNP-SVME, 0.82 for Voxel-SVME, 0.83 for ICA-SVMC, and 0.87 for Combined SNP-fMRI. Experimental results show that better classification accuracy was achieved by combining genetic and fMRI data than using either alone, indicating that genetic and brain function representing different, but partially complementary aspects, of schizophrenia etiopathology. This study suggests an effective way to reassess biological classification of individuals with schizophrenia, which is also potentially useful for identifying diagnostically important markers for the disorder.

  7. Combining structural modeling with ensemble machine learning to accurately predict protein fold stability and binding affinity effects upon mutation.

    Directory of Open Access Journals (Sweden)

    Niklas Berliner

    Full Text Available Advances in sequencing have led to a rapid accumulation of mutations, some of which are associated with diseases. However, to draw mechanistic conclusions, a biochemical understanding of these mutations is necessary. For coding mutations, accurate prediction of significant changes in either the stability of proteins or their affinity to their binding partners is required. Traditional methods have used semi-empirical force fields, while newer methods employ machine learning of sequence and structural features. Here, we show how combining both of these approaches leads to a marked boost in accuracy. We introduce ELASPIC, a novel ensemble machine learning approach that is able to predict stability effects upon mutation in both, domain cores and domain-domain interfaces. We combine semi-empirical energy terms, sequence conservation, and a wide variety of molecular details with a Stochastic Gradient Boosting of Decision Trees (SGB-DT algorithm. The accuracy of our predictions surpasses existing methods by a considerable margin, achieving correlation coefficients of 0.77 for stability, and 0.75 for affinity predictions. Notably, we integrated homology modeling to enable proteome-wide prediction and show that accurate prediction on modeled structures is possible. Lastly, ELASPIC showed significant differences between various types of disease-associated mutations, as well as between disease and common neutral mutations. Unlike pure sequence-based prediction methods that try to predict phenotypic effects of mutations, our predictions unravel the molecular details governing the protein instability, and help us better understand the molecular causes of diseases.

  8. Combining AI Methods for Learning Bots in a Real-Time Strategy Game

    Directory of Open Access Journals (Sweden)

    Robin Baumgarten

    2009-01-01

    Full Text Available We describe an approach for simulating human game-play in strategy games using a variety of AI techniques, including simulated annealing, decision tree learning, and case-based reasoning. We have implemented an AI-bot that uses these techniques to form a novel approach for planning fleet movements and attacks in DEFCON, a nuclear war simulation strategy game released in 2006 by Introversion Software Ltd. The AI-bot retrieves plans from a case-base of recorded games, then uses these to generate a new plan using a method based on decision tree learning. In addition, we have implemented more sophisticated control over low-level actions that enable the AI-bot to synchronize bombing runs, and used a simulated annealing approach for assigning bombing targets to planes and opponent cities to missiles. We describe how our AI-bot operates, and the experimentation we have performed in order to determine an optimal configuration for it. With this configuration, our AI-bot beats Introversion's finite state machine automated player in 76.7% of 150 matches played. We briefly introduce the notion of ability versus enjoyability and discuss initial results of a survey we conducted with human players.

  9. Enhanced Quality Control in Pharmaceutical Applications by Combining Raman Spectroscopy and Machine Learning Techniques

    Science.gov (United States)

    Martinez, J. C.; Guzmán-Sepúlveda, J. R.; Bolañoz Evia, G. R.; Córdova, T.; Guzmán-Cabrera, R.

    2018-06-01

    In this work, we applied machine learning techniques to Raman spectra for the characterization and classification of manufactured pharmaceutical products. Our measurements were taken with commercial equipment, for accurate assessment of variations with respect to one calibrated control sample. Unlike the typical use of Raman spectroscopy in pharmaceutical applications, in our approach the principal components of the Raman spectrum are used concurrently as attributes in machine learning algorithms. This permits an efficient comparison and classification of the spectra measured from the samples under study. This also allows for accurate quality control as all relevant spectral components are considered simultaneously. We demonstrate our approach with respect to the specific case of acetaminophen, which is one of the most widely used analgesics in the market. In the experiments, commercial samples from thirteen different laboratories were analyzed and compared against a control sample. The raw data were analyzed based on an arithmetic difference between the nominal active substance and the measured values in each commercial sample. The principal component analysis was applied to the data for quantitative verification (i.e., without considering the actual concentration of the active substance) of the difference in the calibrated sample. Our results show that by following this approach adulterations in pharmaceutical compositions can be clearly identified and accurately quantified.

  10. Games and machine learning: a powerful combination in an artificial intelligence course

    Science.gov (United States)

    Wallace, Scott A.; McCartney, Robert; Russell, Ingrid

    2010-03-01

    Project MLeXAI (Machine Learning eXperiences in Artificial Intelligence (AI)) seeks to build a set of reusable course curriculum and hands on laboratory projects for the artificial intelligence classroom. In this article, we describe two game-based projects from the second phase of project MLeXAI: Robot Defense - a simple real-time strategy game and Checkers - a classic turn-based board game. From the instructors' prospective, we examine aspects of design and implementation as well as the challenges and rewards of using the curricula. We explore students' responses to the projects via the results of a common survey. Finally, we compare the student perceptions from the game-based projects to non-game based projects from the first phase of Project MLeXAI.

  11. Combining Machine Learning and Nanofluidic Technology To Diagnose Pancreatic Cancer Using Exosomes.

    Science.gov (United States)

    Ko, Jina; Bhagwat, Neha; Yee, Stephanie S; Ortiz, Natalia; Sahmoud, Amine; Black, Taylor; Aiello, Nicole M; McKenzie, Lydie; O'Hara, Mark; Redlinger, Colleen; Romeo, Janae; Carpenter, Erica L; Stanger, Ben Z; Issadore, David

    2017-11-28

    Circulating exosomes contain a wealth of proteomic and genetic information, presenting an enormous opportunity in cancer diagnostics. While microfluidic approaches have been used to successfully isolate cells from complex samples, scaling these approaches for exosome isolation has been limited by the low throughput and susceptibility to clogging of nanofluidics. Moreover, the analysis of exosomal biomarkers is confounded by substantial heterogeneity between patients and within a tumor itself. To address these challenges, we developed a multichannel nanofluidic system to analyze crude clinical samples. Using this platform, we isolated exosomes from healthy and diseased murine and clinical cohorts, profiled the RNA cargo inside of these exosomes, and applied a machine learning algorithm to generate predictive panels that could identify samples derived from heterogeneous cancer-bearing individuals. Using this approach, we classified cancer and precancer mice from healthy controls, as well as pancreatic cancer patients from healthy controls, in blinded studies.

  12. The Combined Effects of Classroom Teaching and Learning Strategy Use on Students' Chemistry Self-Efficacy

    Science.gov (United States)

    Cheung, Derek

    2015-02-01

    For students to be successful in school chemistry, a strong sense of self-efficacy is essential. Chemistry self-efficacy can be defined as students' beliefs about the extent to which they are capable of performing specific chemistry tasks. According to Bandura (Psychol. Rev. 84:191-215, 1977), students acquire information about their level of self-efficacy from four sources: performance accomplishments, vicarious experiences, verbal persuasion, and physiological states. No published studies have investigated how instructional strategies in chemistry lessons can provide students with positive experiences with these four sources of self-efficacy information and how the instructional strategies promote students' chemistry self-efficacy. In this study, questionnaire items were constructed to measure student perceptions about instructional strategies, termed efficacy-enhancing teaching, which can provide positive experiences with the four sources of self-efficacy information. Structural equation modeling was then applied to test a hypothesized mediation model, positing that efficacy-enhancing teaching positively affects students' chemistry self-efficacy through their use of deep learning strategies such as metacognitive control strategies. A total of 590 chemistry students at nine secondary schools in Hong Kong participated in the survey. The mediation model provided a good fit to the student data. Efficacy-enhancing teaching had a direct effect on students' chemistry self-efficacy. Efficacy-enhancing teaching also directly affected students' use of deep learning strategies, which in turn affected students' chemistry self-efficacy. The implications of these findings for developing secondary school students' chemistry self-efficacy are discussed.

  13. Feature combination networks for the interpretation of statistical machine learning models: application to Ames mutagenicity.

    Science.gov (United States)

    Webb, Samuel J; Hanser, Thierry; Howlin, Brendan; Krause, Paul; Vessey, Jonathan D

    2014-03-25

    A new algorithm has been developed to enable the interpretation of black box models. The developed algorithm is agnostic to learning algorithm and open to all structural based descriptors such as fragments, keys and hashed fingerprints. The algorithm has provided meaningful interpretation of Ames mutagenicity predictions from both random forest and support vector machine models built on a variety of structural fingerprints.A fragmentation algorithm is utilised to investigate the model's behaviour on specific substructures present in the query. An output is formulated summarising causes of activation and deactivation. The algorithm is able to identify multiple causes of activation or deactivation in addition to identifying localised deactivations where the prediction for the query is active overall. No loss in performance is seen as there is no change in the prediction; the interpretation is produced directly on the model's behaviour for the specific query. Models have been built using multiple learning algorithms including support vector machine and random forest. The models were built on public Ames mutagenicity data and a variety of fingerprint descriptors were used. These models produced a good performance in both internal and external validation with accuracies around 82%. The models were used to evaluate the interpretation algorithm. Interpretation was revealed that links closely with understood mechanisms for Ames mutagenicity. This methodology allows for a greater utilisation of the predictions made by black box models and can expedite further study based on the output for a (quantitative) structure activity model. Additionally the algorithm could be utilised for chemical dataset investigation and knowledge extraction/human SAR development.

  14. Development of a Solar System Concept Inventory

    Science.gov (United States)

    Hornstein, Seth D.; Duncan, D.; S, C. A. T.

    2009-01-01

    Concept inventories can provide useful insight into students’ understanding of key physical concepts. Knowing what your students have learned during a course is a valuable tool for improving your own teaching. Unfortunately, current astronomy concept inventories are not suitable for an introductory solar system course because they either cover too broad of a range of topics (e.g. Astronomy Diagnostic Test) or are too narrowly focused (e.g. Greenhouse Effect Concept Inventory, Lunar Phase Concept Inventory). We have developed the Solar System Concept Inventory (SSCI) to cover those topics commonly taught in an introductory solar system course. The topics included on the SSCI were selected by having faculty identify the key concepts they address when teaching about the solar system. SSCI topics include formation mechanisms, planetary interiors, atmospheric effects, and small solar system bodies. Student interviews were conducted to identify common naive ideas and reasoning difficulties relating to these key topics. Preliminary development of the SSCI was completed at the University of Colorado and involved over 400 students. A larger, national, multi-institutional field test is planned for Spring 2009 as a Collaboration of Astronomy Teaching Scholars (CATS) research project. We present here the results from the preliminary development and proposed changes for the next stage of research. We would like to thank the NSF for funding under Grant No. 0715517, a CCLI Phase III Grant for the Collaboration of Astronomy Teaching Scholars (CATS) Program.

  15. Development of the Solar System Concept Inventory

    Science.gov (United States)

    Hornstein, S.; Prather, E.

    2009-12-01

    Concept inventories can provide useful insight into students’ understanding of key physical concepts. Knowing what your students have learned during a course is a valuable tool for improving your own teaching. Unfortunately, current astronomy concept inventories are not suitable for an introductory solar system course because they either cover too broad of a range of topics (e.g. Astronomy Diagnostic Test) or are too narrowly focused (e.g. Greenhouse Effect Concept Inventory, Lunar Phase Concept Inventory). We have developed the Solar System Concept Inventory (SSCI) to cover those topics commonly taught in an introductory solar system course. The topics included on the SSCI were selected by having faculty identify the key concepts they address when teaching about the solar system. SSCI topics include formation mechanisms, planetary interiors, atmospheric effects, and small solar system bodies. Student interviews were conducted to identify common naive ideas and reasoning difficulties relating to these key topics. The SSCI has been through two semesters of national, multi-institutional field-testing, involving over 1500 students. After the first semester of testing, question statistics were used to flag ineffective questions and flagged questions were revised or eliminated. We will present an overall outline of the SSCI development as well as our question-flagging criteria and question analyses from the latest round of field-testing. We would like to thank the NSF for funding under Grant No. 0715517, a CCLI Phase III Grant for the Collaboration of Astronomy Teaching Scholars (CATS) Program.

  16. Hydrogen inventory in gallium

    International Nuclear Information System (INIS)

    Mazayev, S.N.; Prokofiev, Yu.G.

    1994-01-01

    Investigations of hydrogen inventory in gallium (99.9%) were carried out after saturation both from molecular phase and from glow discharge plasma at room temperature, 370 and 520 K. Saturation took place during 3000 s under hydrogen pressure of 20 Pa, and ion flux was about 1x10 15 ions/cm 2 s with an energy about 400 eV during discharge. Hydrogen concentration in Ga at room temperature and that for 370 K by the saturation from gaseous phase was (2-3)x10 14 cm -3 Pa -1/2 . Hydrogen concentration at temperature 520 K increased by five times. Inventory at room temperature for irradiation from discharge was 7x10 16 cm -3 at the dose about 3x10 18 ions/cm 2 . It was more than inventory at temperature 520 K by four times and more than maximum inventory from gaseous phase at 520 K by a factor of 10. Inventory increased when temperature decreased. Diffusion coefficient D=0.003 exp(-2300/RT) cm 2 /s, was estimated from temperature dependence. ((orig.))

  17. Nuclear materials inventory plan

    International Nuclear Information System (INIS)

    Doerr, R.W.; Nichols, D.H.

    1982-03-01

    In any processing, manufacturing, or active storage facility it is impractical to assume that any physical security system can prevent the diversion of Special Nuclear Material (SNM). It is, therefore, the responsibility of any DOE Contractor, Licensee, or other holder of SNM to provide assurance that loss or diversion of a significant quantity of SNM is detectable. This ability to detect must be accomplishable within a reasonable time interval and can be accomplished only by taking physical inventories. The information gained and decisions resulting from these inventories can be no better than the SNM accounting system and the quality of measurements performed for each receipt, removal and inventory. Inventories interrupt processing or production operations, increase personnel exposures, and can add significantly to the cost of any operation. Therefore, realistic goals for the inventory must be defined and the relationship of the inherent parameters used in its validation be determined. Purpose of this document is to provide a statement of goals and a plan of action to achieve them

  18. Prediction of hot spot residues at protein-protein interfaces by combining machine learning and energy-based methods

    Directory of Open Access Journals (Sweden)

    Pontil Massimiliano

    2009-10-01

    Full Text Available Abstract Background Alanine scanning mutagenesis is a powerful experimental methodology for investigating the structural and energetic characteristics of protein complexes. Individual amino-acids are systematically mutated to alanine and changes in free energy of binding (ΔΔG measured. Several experiments have shown that protein-protein interactions are critically dependent on just a few residues ("hot spots" at the interface. Hot spots make a dominant contribution to the free energy of binding and if mutated they can disrupt the interaction. As mutagenesis studies require significant experimental efforts, there is a need for accurate and reliable computational methods. Such methods would also add to our understanding of the determinants of affinity and specificity in protein-protein recognition. Results We present a novel computational strategy to identify hot spot residues, given the structure of a complex. We consider the basic energetic terms that contribute to hot spot interactions, i.e. van der Waals potentials, solvation energy, hydrogen bonds and Coulomb electrostatics. We treat them as input features and use machine learning algorithms such as Support Vector Machines and Gaussian Processes to optimally combine and integrate them, based on a set of training examples of alanine mutations. We show that our approach is effective in predicting hot spots and it compares favourably to other available methods. In particular we find the best performances using Transductive Support Vector Machines, a semi-supervised learning scheme. When hot spots are defined as those residues for which ΔΔG ≥ 2 kcal/mol, our method achieves a precision and a recall respectively of 56% and 65%. Conclusion We have developed an hybrid scheme in which energy terms are used as input features of machine learning models. This strategy combines the strengths of machine learning and energy-based methods. Although so far these two types of approaches have mainly been

  19. Using optimal combination of teaching-learning methods (open book assignment and group tutorials) as revision exercises to improve learning outcome in low achievers in biochemistry.

    Science.gov (United States)

    Rajappa, Medha; Bobby, Zachariah; Nandeesha, H; Suryapriya, R; Ragul, Anithasri; Yuvaraj, B; Revathy, G; Priyadarssini, M

    2016-07-08

    Graduate medical students of India are taught Biochemistry by didactic lectures and they hardly get any opportunity to clarify their doubts and reinforce the concepts which they learn in these lectures. We used a combination of teaching-learning (T-L) methods (open book assignment followed by group tutorials) to study their efficacy in improving the learning outcome. About 143 graduate medical students were classified into low (75%: group 3, n = 46) achievers, based on their internal assessment marks. After the regular teaching module on the topics "Vitamins and Enzymology", all the students attempted an open book assignment without peer consultation. Then all the students participated in group tutorials. The effects on the groups were evaluated by pre and posttests at the end of each phase, with the same set of MCQs. Gain from group tutorials and overall gain was significantly higher in the low achievers, compared to other groups. High and medium achievers obtained more gain from open book assignment, than group tutorials. The overall gain was significantly higher than the gain obtained from open book assignment or group tutorials, in all three groups. All the three groups retained the gain even after 1 week of the exercise. Hence, optimal use of novel T-L methods (open book assignment followed by group tutorials) as revision exercises help in strengthening concepts in Biochemistry in this oft neglected group of low achievers in graduate medical education. © 2016 by The International Union of Biochemistry and Molecular Biology, 44(4):321-325, 2016. © 2016 The International Union of Biochemistry and Molecular Biology.

  20. Sentinel-2 for rapid operational landslide inventory mapping

    Science.gov (United States)

    Stumpf, André; Marc, Odin; Malet, Jean-Philippe; Michea, David

    2017-04-01

    Landslide inventory mapping after major triggering events such as heavy rainfalls or earthquakes is crucial for disaster response, the assessment of hazards, and the quantification of sediment budgets and empirical scaling laws. Numerous studies have already demonstrated the utility of very-high resolution satellite and aerial images for the elaboration of inventories based on semi-automatic methods or visual image interpretation. Nevertheless, such semi-automatic methods are rarely used in an operational context after major triggering events; this is partly due to access limitations on the required input datasets (i.e. VHR satellite images) and to the absence of dedicated services (i.e. processing chain) available for the landslide community. Several on-going initiatives allow to overcome these limitations. First, from a data perspective, the launch of the Sentinel-2 mission offers opportunities for the design of an operational service that can be deployed for landslide inventory mapping at any time and everywhere on the globe. Second, from an implementation perspective, the Geohazards Exploitation Platform (GEP) of the European Space Agency (ESA) allows the integration and diffusion of on-line processing algorithms in a high computing performance environment. Third, from a community perspective, the recently launched Landslide Pilot of the Committee on Earth Observation Satellites (CEOS), has targeted the take-off of such service as a main objective for the landslide community. Within this context, this study targets the development of a largely automatic, supervised image processing chain for landslide inventory mapping from bi-temporal (before and after a given event) Sentinel-2 optical images. The processing chain combines change detection methods, image segmentation, higher-level image features (e.g. texture, shape) and topographic variables. Based on a few representative examples provided by a human operator, a machine learning model is trained and

  1. Combining Human and Machine Learning to Map Cropland in the 21st Century's Major Agricultural Frontier

    Science.gov (United States)

    Estes, L. D.; Debats, S. R.; Caylor, K. K.; Evans, T. P.; Gower, D.; McRitchie, D.; Searchinger, T.; Thompson, D. R.; Wood, E. F.; Zeng, L.

    2016-12-01

    In the coming decades, large areas of new cropland will be created to meet the world's rapidly growing food demands. Much of this new cropland will be in sub-Saharan Africa, where food needs will increase most and the area of remaining potential farmland is greatest. If we are to understand the impacts of global change, it is critical to accurately identify Africa's existing croplands and how they are changing. Yet the continent's smallholder-dominated agricultural systems are unusually challenging for remote sensing analyses, making accurate area estimates difficult to obtain, let alone important details related to field size and geometry. Fortunately, the rapidly growing archives of moderate to high-resolution satellite imagery hosted on open servers now offer an unprecedented opportunity to improve landcover maps. We present a system that integrates two critical components needed to capitalize on this opportunity: 1) human image interpretation and 2) machine learning (ML). Human judgment is needed to accurately delineate training sites within noisy imagery and a highly variable cover type, while ML provides the ability to scale and to interpret large feature spaces that defy human comprehension. Because large amounts of training data are needed (a major impediment for analysts), we use a crowdsourcing platform that connects amazon.com's Mechanical Turk service to satellite imagery hosted on open image servers. Workers map visible fields at pre-assigned sites, and are paid according to their mapping accuracy. Initial tests show overall high map accuracy and mapping rates >1800 km2/hour. The ML classifier uses random forests and randomized quasi-exhaustive feature selection, and is highly effective in classifying diverse agricultural types in southern Africa (AUC > 0.9). We connect the ML and crowdsourcing components to make an interactive learning framework. The ML algorithm performs an initial classification using a first batch of crowd-sourced maps, using

  2. Fukushima Daiichi Radionuclide Inventories

    Energy Technology Data Exchange (ETDEWEB)

    Cardoni, Jeffrey N. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Jankovsky, Zachary Kyle [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)

    2016-09-01

    Radionuclide inventories are generated to permit detailed analyses of the Fukushima Daiichi meltdowns. This is necessary information for severe accident calculations, dose calculations, and source term and consequence analyses. Inventories are calculated using SCALE6 and compared to values predicted by international researchers supporting the OECD/NEA's Benchmark Study on the Accident at Fukushima Daiichi Nuclear Power Station (BSAF). Both sets of inventory information are acceptable for best-estimate analyses of the Fukushima reactors. Consistent nuclear information for severe accident codes, including radionuclide class masses and core decay powers, are also derived from the SCALE6 analyses. Key nuclide activity ratios are calculated as functions of burnup and nuclear data in order to explore the utility for nuclear forensics and support future decommissioning efforts.

  3. Shortening the Xerostomia Inventory

    Science.gov (United States)

    Thomson, William Murray; van der Putten, Gert-Jan; de Baat, Cees; Ikebe, Kazunori; Matsuda, Ken-ichi; Enoki, Kaori; Hopcraft, Matthew; Ling, Guo Y

    2011-01-01

    Objectives To determine the validity and properties of the Summated Xerostomia Inventory-Dutch Version in samples from Australia, The Netherlands, Japan and New Zealand. Study design Six cross-sectional samples of older people from The Netherlands (N = 50), Australia (N = 637 and N = 245), Japan (N = 401) and New Zealand (N = 167 and N = 86). Data were analysed using the Summated Xerostomia Inventory-Dutch Version. Results Almost all data-sets revealed a single extracted factor which explained about half of the variance, with Cronbach’s alpha values of at least 0.70. When mean scale scores were plotted against a “gold standard” xerostomia question, statistically significant gradients were observed, with the highest score seen in those who always had dry mouth, and the lowest in those who never had it. Conclusion The Summated Xerostomia Inventory-Dutch Version is valid for measuring xerostomia symptoms in clinical and epidemiological research. PMID:21684773

  4. Combining machine learning and ontological data handling for multi-source classification of nature conservation areas

    Science.gov (United States)

    Moran, Niklas; Nieland, Simon; Tintrup gen. Suntrup, Gregor; Kleinschmit, Birgit

    2017-02-01

    Manual field surveys for nature conservation management are expensive and time-consuming and could be supplemented and streamlined by using Remote Sensing (RS). RS is critical to meet requirements of existing laws such as the EU Habitats Directive (HabDir) and more importantly to meet future challenges. The full potential of RS has yet to be harnessed as different nomenclatures and procedures hinder interoperability, comparison and provenance. Therefore, automated tools are needed to use RS data to produce comparable, empirical data outputs that lend themselves to data discovery and provenance. These issues are addressed by a novel, semi-automatic ontology-based classification method that uses machine learning algorithms and Web Ontology Language (OWL) ontologies that yields traceable, interoperable and observation-based classification outputs. The method was tested on European Union Nature Information System (EUNIS) grasslands in Rheinland-Palatinate, Germany. The developed methodology is a first step in developing observation-based ontologies in the field of nature conservation. The tests show promising results for the determination of the grassland indicators wetness and alkalinity with an overall accuracy of 85% for alkalinity and 76% for wetness.

  5. Managing the 1920s' Chilean educational crisis: A historical view combined with machine learning.

    Science.gov (United States)

    Rengifo, Francisca; Ruz, Gonzalo A; Mascareño, Aldo

    2018-01-01

    In the first decades of the 20th century, political actors diagnosed the incubation of a crisis in the Chilean schooling process. Low rates of enrollment, literacy, and attendance, inefficiency in the use of resources, poverty, and a reduced number of schools were the main factors explaining the crisis. As a response, the Law on Compulsory Primary Education, considering mandatory for children between 6 and 14 years old to attend any school for at least four years, was passed in 1920. Using data from Censuses of the Republic of Chile from 1920 and 1930, reports of the Ministry of Justice, the Ministry of Education, and the Statistical Yearbooks between 1895 and 1930, we apply machine learning techniques (clustering and decision trees) to assess the impact of this law on the Chilean schooling process between 1920 and 1930. We conclude that the law had a positive impact on the schooling indicators in this period. Even though it did not overcome the differences between urban and rural zones, it brought about a general improvement of the schooling process and a more efficient use of resources and infrastructure in both big urban centers and small-urban and rural zones, thereby managing the so-called crisis of the Republic.

  6. Combining Metabolite-Based Pharmacophores with Bayesian Machine Learning Models for Mycobacterium tuberculosis Drug Discovery.

    Science.gov (United States)

    Ekins, Sean; Madrid, Peter B; Sarker, Malabika; Li, Shao-Gang; Mittal, Nisha; Kumar, Pradeep; Wang, Xin; Stratton, Thomas P; Zimmerman, Matthew; Talcott, Carolyn; Bourbon, Pauline; Travers, Mike; Yadav, Maneesh; Freundlich, Joel S

    2015-01-01

    Integrated computational approaches for Mycobacterium tuberculosis (Mtb) are useful to identify new molecules that could lead to future tuberculosis (TB) drugs. Our approach uses information derived from the TBCyc pathway and genome database, the Collaborative Drug Discovery TB database combined with 3D pharmacophores and dual event Bayesian models of whole-cell activity and lack of cytotoxicity. We have prioritized a large number of molecules that may act as mimics of substrates and metabolites in the TB metabolome. We computationally searched over 200,000 commercial molecules using 66 pharmacophores based on substrates and metabolites from Mtb and further filtering with Bayesian models. We ultimately tested 110 compounds in vitro that resulted in two compounds of interest, BAS 04912643 and BAS 00623753 (MIC of 2.5 and 5 μg/mL, respectively). These molecules were used as a starting point for hit-to-lead optimization. The most promising class proved to be the quinoxaline di-N-oxides, evidenced by transcriptional profiling to induce mRNA level perturbations most closely resembling known protonophores. One of these, SRI58 exhibited an MIC = 1.25 μg/mL versus Mtb and a CC50 in Vero cells of >40 μg/mL, while featuring fair Caco-2 A-B permeability (2.3 x 10-6 cm/s), kinetic solubility (125 μM at pH 7.4 in PBS) and mouse metabolic stability (63.6% remaining after 1 h incubation with mouse liver microsomes). Despite demonstration of how a combined bioinformatics/cheminformatics approach afforded a small molecule with promising in vitro profiles, we found that SRI58 did not exhibit quantifiable blood levels in mice.

  7. Separating depressive comorbidity from panic disorder: A combined functional magnetic resonance imaging and machine learning approach.

    Science.gov (United States)

    Lueken, Ulrike; Straube, Benjamin; Yang, Yunbo; Hahn, Tim; Beesdo-Baum, Katja; Wittchen, Hans-Ulrich; Konrad, Carsten; Ströhle, Andreas; Wittmann, André; Gerlach, Alexander L; Pfleiderer, Bettina; Arolt, Volker; Kircher, Tilo

    2015-09-15

    Depression is frequent in panic disorder (PD); yet, little is known about its influence on the neural substrates of PD. Difficulties in fear inhibition during safety signal processing have been reported as a pathophysiological feature of PD that is attenuated by depression. We investigated the impact of comorbid depression in PD with agoraphobia (AG) on the neural correlates of fear conditioning and the potential of machine learning to predict comorbidity status on the individual patient level based on neural characteristics. Fifty-nine PD/AG patients including 26 (44%) with a comorbid depressive disorder (PD/AG+DEP) underwent functional magnetic resonance imaging (fMRI). Comorbidity status was predicted using a random undersampling tree ensemble in a leave-one-out cross-validation framework. PD/AG-DEP patients showed altered neural activation during safety signal processing, while +DEP patients exhibited generally decreased dorsolateral prefrontal and insular activation. Comorbidity status was correctly predicted in 79% of patients (sensitivity: 73%; specificity: 85%) based on brain activation during fear conditioning (corrected for potential confounders: accuracy: 73%; sensitivity: 77%; specificity: 70%). No primary depressed patients were available; only medication-free patients were included. Major depression and dysthymia were collapsed (power considerations). Neurofunctional activation during safety signal processing differed between patients with or without comorbid depression, a finding which may explain heterogeneous results across previous studies. These findings demonstrate the relevance of comorbidity when investigating neurofunctional substrates of anxiety disorders. Predicting individual comorbidity status may translate neurofunctional data into clinically relevant information which might aid in planning individualized treatment. The study was registered with the ISRCTN80046034. Copyright © 2015 Elsevier B.V. All rights reserved.

  8. Accurate prediction of stability changes in protein mutants by combining machine learning with structure based computational mutagenesis.

    Science.gov (United States)

    Masso, Majid; Vaisman, Iosif I

    2008-09-15

    Accurate predictive models for the impact of single amino acid substitutions on protein stability provide insight into protein structure and function. Such models are also valuable for the design and engineering of new proteins. Previously described methods have utilized properties of protein sequence or structure to predict the free energy change of mutants due to thermal (DeltaDeltaG) and denaturant (DeltaDeltaG(H2O)) denaturations, as well as mutant thermal stability (DeltaT(m)), through the application of either computational energy-based approaches or machine learning techniques. However, accuracy associated with applying these methods separately is frequently far from optimal. We detail a computational mutagenesis technique based on a four-body, knowledge-based, statistical contact potential. For any mutation due to a single amino acid replacement in a protein, the method provides an empirical normalized measure of the ensuing environmental perturbation occurring at every residue position. A feature vector is generated for the mutant by considering perturbations at the mutated position and it's ordered six nearest neighbors in the 3-dimensional (3D) protein structure. These predictors of stability change are evaluated by applying machine learning tools to large training sets of mutants derived from diverse proteins that have been experimentally studied and described. Predictive models based on our combined approach are either comparable to, or in many cases significantly outperform, previously published results. A web server with supporting documentation is available at http://proteins.gmu.edu/automute.

  9. Adaptive online monitoring for ICU patients by combining just-in-time learning and principal component analysis.

    Science.gov (United States)

    Li, Xuejian; Wang, Youqing

    2016-12-01

    Offline general-type models are widely used for patients' monitoring in intensive care units (ICUs), which are developed by using past collected datasets consisting of thousands of patients. However, these models may fail to adapt to the changing states of ICU patients. Thus, to be more robust and effective, the monitoring models should be adaptable to individual patients. A novel combination of just-in-time learning (JITL) and principal component analysis (PCA), referred to learning-type PCA (L-PCA), was proposed for adaptive online monitoring of patients in ICUs. JITL was used to gather the most relevant data samples for adaptive modeling of complex physiological processes. PCA was used to build an online individual-type model and calculate monitoring statistics, and then to judge whether the patient's status is normal or not. The adaptability of L-PCA lies in the usage of individual data and the continuous updating of the training dataset. Twelve subjects were selected from the Physiobank's Multi-parameter Intelligent Monitoring for Intensive Care II (MIMIC II) database, and five vital signs of each subject were chosen. The proposed method was compared with the traditional PCA and fast moving-window PCA (Fast MWPCA). The experimental results demonstrated that the fault detection rates respectively increased by 20 % and 47 % compared with PCA and Fast MWPCA. L-PCA is first introduced into ICU patients monitoring and achieves the best monitoring performance in terms of adaptability to changes in patient status and sensitivity for abnormality detection.

  10. Combination of a Flipped Classroom Format and a Virtual Patient Case to Enhance Active Learning in a Required Therapeutics Course

    Science.gov (United States)

    Lichvar, Alicia Beth; Hedges, Ashley; Benedict, Neal J.

    2016-01-01

    Objective. To design and evaluate the integration of a virtual patient activity in a required therapeutics course already using a flipped-classroom teaching format. Design. A narrative-branched, dynamic virtual-patient case was designed to replace the static written cases that students worked through during the class, which was dedicated to teaching the complications of liver disease. Students completed pre- and posttests before and after completing the virtual patient case. Examination scores were compared to those in the previous year. Assessment. Students’ posttest scores were higher compared to pretest scores (33% vs 50%). Overall median examination scores were higher compared to the historical control group (70% vs 80%), as well as scores on questions assessing higher-level learning (67% vs 83%). A majority of students (68%) felt the virtual patient helped them apply knowledge gained in the pre-class video lecture. Students preferred this strategy to usual in-class activities (33%) or indicated it was of equal value (37%). Conclusion. The combination of a pre-class video lecture with an in-class virtual patient case is an effective active-learning strategy. PMID:28179724

  11. Combination of a Flipped Classroom Format and a Virtual Patient Case to Enhance Active Learning in a Required Therapeutics Course.

    Science.gov (United States)

    Lichvar, Alicia Beth; Hedges, Ashley; Benedict, Neal J; Donihi, Amy C

    2016-12-25

    Objective. To design and evaluate the integration of a virtual patient activity in a required therapeutics course already using a flipped-classroom teaching format. Design. A narrative-branched, dynamic virtual-patient case was designed to replace the static written cases that students worked through during the class, which was dedicated to teaching the complications of liver disease. Students completed pre- and posttests before and after completing the virtual patient case. Examination scores were compared to those in the previous year. Assessment. Students' posttest scores were higher compared to pretest scores (33% vs 50%). Overall median examination scores were higher compared to the historical control group (70% vs 80%), as well as scores on questions assessing higher-level learning (67% vs 83%). A majority of students (68%) felt the virtual patient helped them apply knowledge gained in the pre-class video lecture. Students preferred this strategy to usual in-class activities (33%) or indicated it was of equal value (37%). Conclusion. The combination of a pre-class video lecture with an in-class virtual patient case is an effective active-learning strategy.

  12. New combinations of ‘flipped classroom with just in time teaching’ and learning analytics of student responses

    Directory of Open Access Journals (Sweden)

    Alfredo Prieto Martín

    2018-01-01

    Full Text Available The results obtained thanks to the flipped classroom with ‘just I¡in time’ teaching method are reviewed. This method allowed to know what the students did not understand after trying to study the instructive materials assigned to them. To achieve that the students work before class methods of marketing and gamification were developed. Methods for the analysis of student responses were also developed. The JiTT method allowes the teacher know in advance those aspects that are most interesting or most dificult to understand for the students as well as their most urgent doubts. Finally, we have developed methods to use the urgent doubts of the students to generate formative feedback and activities to do in the classroom. In the method named “flipped learning forte” the teacher answer the urgent doubts of his students. In the method named ‘flip in colours’ the teacher classify the doubts by their posible utility in the classroom using a color code. With the combined application of these methods in university courses the failure rate of the students has decreased and the mean grade in the exams for the assessment of learning has increased in more than one standard deviation. The rate of students that attain the level of mastery has increased, as well as the student evaluations about the teachers of these courses. Finally, the reasons underlying the efficacy of the proposed flipped method are discussed.

  13. A Meta-Analysis Method to Advance Design of Technology-Based Learning Tool: Combining Qualitative and Quantitative Research to Understand Learning in Relation to Different Technology Features

    Science.gov (United States)

    Zhang, Lin

    2014-01-01

    Educators design and create various technology tools to scaffold students' learning. As more and more technology designs are incorporated into learning, growing attention has been paid to the study of technology-based learning tool. This paper discusses the emerging issues, such as how can learning effectiveness be understood in relation to…

  14. Unified Communications for Space Inventory Management

    Science.gov (United States)

    Gifford, Kevin K.; Fink, Patrick W.; Barton, Richard; Ngo, Phong H.

    2009-01-01

    To help assure mission success for long-duration exploration activities, NASA is actively pursuing wireless technologies that promote situational awareness and autonomy. Wireless technologies are typically extensible, offer freedom from wire tethers, readily support redundancy, offer potential for decreased wire weight, and can represent dissimilar implementation for increased reliability. In addition, wireless technologies can enable additional situational awareness that otherwise would be infeasible. For example, addition of wired sensors, the need for which might not have been apparent at the outset of a program, night be extremely costly due in part to the necessary routing of cables through the vehicle. RFID, or radio frequency identification, is a wireless technology with the potential for significant savings and increased reliability and safety in space operations. Perhaps the most obvious savings relate to the application of inventory management. A fully automated inventory management system is highly desirable for long-term sustaining operations in space environments. This assertion is evidenced by inventory activities on the International Space Station, which represents the most extensive inventory tracking experience base in the history of space operations. In the short tern, handheld RFID readers offer substantial savings owing to reduced crew time for inventory audits. Over the long term, a combination of improved RFID technology and operational concepts modified to fully utilize the technology should result in space based inventory management that is highly reliable and requires very little crew time. In addition to inventory management, RFID is likely to find space applications in real-time location and tracking systems. These could vary from coarse-resolution RFID portals to the high resolution afforded by ultra-wideband (UWB) RFID. Longer range RFID technologies that leverage passive surface acoustic wave (SAW) devices are being investigated to

  15. Purchasing and inventory management techniques for optimizing inventory investment

    International Nuclear Information System (INIS)

    McFarlane, I.; Gehshan, T.

    1993-01-01

    In an effort to reduce operations and maintenance costs among nuclear plants, many utilities are taking a closer look at their inventory investment. Various approaches for inventory reduction have been used and discussed, but these approaches are often limited to an inventory management perspective. Interaction with purchasing and planning personnel to reduce inventory investment is a necessity in utility efforts to become more cost competitive. This paper addresses the activities that purchasing and inventory management personnel should conduct in an effort to optimize inventory investment while maintaining service-level goals. Other functions within a materials management organization, such as the warehousing and investment recovery functions, can contribute to optimizing inventory investment. However, these are not addressed in this paper because their contributions often come after inventory management and purchasing decisions have been made

  16. Operative and diagnostic hysteroscopy: A novel learning model combining new animal models and virtual reality simulation.

    Science.gov (United States)

    Bassil, Alfred; Rubod, Chrystèle; Borghesi, Yves; Kerbage, Yohan; Schreiber, Elie Servan; Azaïs, Henri; Garabedian, Charles

    2017-04-01

    Hysteroscopy is one of the most common gynaecological procedure. Training for diagnostic and operative hysteroscopy can be achieved through numerous previously described models like animal models or virtual reality simulation. We present our novel combined model associating virtual reality and bovine uteruses and bladders. End year residents in obstetrics and gynaecology attended a full day workshop. The workshop was divided in theoretical courses from senior surgeons and hands-on training in operative hysteroscopy and virtual reality Essure ® procedures using the EssureSim™ and Pelvicsim™ simulators with multiple scenarios. Theoretical and operative knowledge was evaluated before and after the workshop and General Points Averages (GPAs) were calculated and compared using a Student's T test. GPAs were significantly higher after the workshop was completed. The biggest difference was observed in operative knowledge (0,28 GPA before workshop versus 0,55 after workshop, pvirtual reality simulation is an efficient model not described before. Copyright © 2017 Elsevier B.V. All rights reserved.

  17. Rapid inventory taking system

    International Nuclear Information System (INIS)

    Marsden, P.S.S.F.

    1980-01-01

    A data processing system designed to facilitate inventory taking is described. The process depends upon the earliest possible application of computer techniques and the elimination of manual operations. Data is recorded in optical character recognition (OCR) 'A' form and read by a hand held wand reader. Limited validation checks are applied before recording on mini-tape cassettes. 5 refs

  18. Experimental inventory verification system

    International Nuclear Information System (INIS)

    Steverson, C.A.; Angerman, M.I.

    1991-01-01

    As Low As Reasonably Achievable (ALARA) goals and Department of Energy (DOE) inventory requirements are frequently in conflict at facilities across the DOE complex. The authors wish, on one hand, to verify the presence of correct amounts of nuclear materials that are in storage or in process; yet on the other hand, we wish to achieve ALARA goals by keeping individual and collective exposures as low as social, technical, economic, practical, and public policy considerations permit. The Experimental Inventory Verification System (EIVSystem) is a computer-based, camera-driven system that utilizes image processing technology to detect change in vault areas. Currently in the test and evaluation phase at Idaho National Engineering Laboratory, this system guards personnel. The EIVSystem continually monitors the vault, providing proof of changed status for objects sorted within the vault. This paper reports that these data could provide the basis for reducing inventory requirements when no change has occurred, thus helping implement ALARA policy; the data will also help describe there target area of an inventory when change has been shown to occur

  19. Marine Education Knowledge Inventory.

    Science.gov (United States)

    Hounshell, Paul B.; Hampton, Carolyn

    This 35-item, multiple-choice Marine Education Knowledge Inventory was developed for use in upper elementary/middle schools to measure a student's knowledge of marine science. Content of test items is drawn from oceanography, ecology, earth science, navigation, and the biological sciences (focusing on marine animals). Steps in the construction of…

  20. Calculating Optimal Inventory Size

    Directory of Open Access Journals (Sweden)

    Ruby Perez

    2010-01-01

    Full Text Available The purpose of the project is to find the optimal value for the Economic Order Quantity Model and then use a lean manufacturing Kanban equation to find a numeric value that will minimize the total cost and the inventory size.

  1. Life Cycle Inventory Analysis

    DEFF Research Database (Denmark)

    Bjørn, Anders; Moltesen, Andreas; Laurent, Alexis

    2018-01-01

    of different sources. The output is a compiled inventory of elementary flows that is used as basis of the subsequent life cycle impact assessment phase. This chapter teaches how to carry out this task through six steps: (1) identifying processes for the LCI model of the product system; (2) planning...

  2. The Danish CORINAIR Inventories

    DEFF Research Database (Denmark)

    Winther, M.; Illerup, J. B.; Fenhann, J.

    CORINAIR is the most comprehensive European air emission inventory programme. It consists of a defined emission calculation methodology and software for storing and further data processing. In CORINAIR 28 different emission species are estimated in 11 main sectors which are further sub-divided, a...

  3. Shortening the xerostomia inventory

    NARCIS (Netherlands)

    Thomson, W.M.; Putten, G.J. van der; Baat, C. de; Ikebe, K.; Matsuda, K.; Enoki, K.; Hopcraft, M.S.; Ling, G.Y.

    2011-01-01

    OBJECTIVES: The aim of this study was to determine the validity and properties of the Summated Xerostomia Inventory-Dutch Version in samples from Australia, The Netherlands, Japan, and New Zealand. STUDY DESIGN: Six cross-sectional samples of older people from The Netherlands (n = 50), Australia (n

  4. Student Attitude Inventory - 1971.

    Science.gov (United States)

    Gillmore, Gerald M.; Aleamoni, Lawrence M.

    This 42-item Student Attitude Inventory (SAI) was administered to entering college freshmen at the University of Illinois (see TM 001 015). The SAI items are divided into nine categories on the basis of content as follows: voting behavior, drug usage, financial, Viet Nam war, education, religious behavior, pollution, housing, and alienation. A…

  5. Initial Radionuclide Inventories

    Energy Technology Data Exchange (ETDEWEB)

    H. Miller

    2004-09-19

    The purpose of this analysis is to provide an initial radionuclide inventory (in grams per waste package) and associated uncertainty distributions for use in the Total System Performance Assessment for the License Application (TSPA-LA) in support of the license application for the repository at Yucca Mountain, Nevada. This document is intended for use in postclosure analysis only. Bounding waste stream information and data were collected that capture probable limits. For commercially generated waste, this analysis considers alternative waste stream projections to bound the characteristics of wastes likely to be encountered using arrival scenarios that potentially impact the commercial spent nuclear fuel (CSNF) waste stream. For TSPA-LA, this radionuclide inventory analysis considers U.S. Department of Energy (DOE) high-level radioactive waste (DHLW) glass and two types of spent nuclear fuel (SNF): CSNF and DOE-owned (DSNF). These wastes are placed in two groups of waste packages: the CSNF waste package and the codisposal waste package (CDSP), which are designated to contain DHLW glass and DSNF, or DHLW glass only. The radionuclide inventory for naval SNF is provided separately in the classified ''Naval Nuclear Propulsion Program Technical Support Document'' for the License Application. As noted previously, the radionuclide inventory data presented here is intended only for TSPA-LA postclosure calculations. It is not applicable to preclosure safety calculations. Safe storage, transportation, and ultimate disposal of these wastes require safety analyses to support the design and licensing of repository equipment and facilities. These analyses will require radionuclide inventories to represent the radioactive source term that must be accommodated during handling, storage and disposition of these wastes. This analysis uses the best available information to identify the radionuclide inventory that is expected at the last year of last emplacement

  6. The effects of cocaine, alcohol and cocaine/alcohol combinations in conditioned taste aversion learning.

    Science.gov (United States)

    Busse, Gregory D; Verendeev, Andrey; Jones, Jermaine; Riley, Anthony L

    2005-09-01

    We have recently reported that alcohol attenuates cocaine place preferences. Although the basis for this effect is unknown, alcohol may attenuate cocaine reward by potentiating its aversive effects. To examine this possibility, these experiments assessed the effects of alcohol on cocaine-induced taste aversions under conditions similar to those that resulted in attenuated place preferences. Specifically, Experiments 1 and 2 assessed the effects of alcohol (0.5 g/kg) on taste aversions induced by 20, 30 and 40 mg/kg cocaine. Experiment 3 examined the role of intertrial interval in the effects of alcohol (0.5 g/kg) on cocaine (30 mg/kg) taste aversions. In Experiments 1 and 2, cocaine was effective at conditioning aversions. Alcohol produced no measurable effect. Combining cocaine and alcohol produced no greater aversion than cocaine alone (and, in fact, weakened aversions at the lowest dose of cocaine). In Experiment 3, varying the intertrial interval from 3 days (as in the case of Experiments 1 and 2) to 1 day (a procedure identical to that in which alcohol attenuated cocaine place preferences) resulted in significant alcohol- and cocaine-induced taste aversions. Nonetheless, alcohol remained ineffective in potentiating cocaine aversions. Thus, under these conditions alcohol does not potentiate cocaine's aversiveness. These results were discussed in terms of their implication for the effects of alcohol on cocaine-induced place preferences. Further, the effects of alcohol on place preferences conditioned by cocaine were discussed in relation to other assessments of the effects of alcohol on the affective properties of cocaine and the implications of these interactions for alcohol and cocaine co-use.

  7. Identifying Environmental and Social Factors Predisposing to Pathological Gambling Combining Standard Logistic Regression and Logic Learning Machine.

    Science.gov (United States)

    Parodi, Stefano; Dosi, Corrado; Zambon, Antonella; Ferrari, Enrico; Muselli, Marco

    2017-12-01

    Identifying potential risk factors for problem gambling (PG) is of primary importance for planning preventive and therapeutic interventions. We illustrate a new approach based on the combination of standard logistic regression and an innovative method of supervised data mining (Logic Learning Machine or LLM). Data were taken from a pilot cross-sectional study to identify subjects with PG behaviour, assessed by two internationally validated scales (SOGS and Lie/Bet). Information was obtained from 251 gamblers recruited in six betting establishments. Data on socio-demographic characteristics, lifestyle and cognitive-related factors, and type, place and frequency of preferred gambling were obtained by a self-administered questionnaire. The following variables associated with PG were identified: instant gratification games, alcohol abuse, cognitive distortion, illegal behaviours and having started gambling with a relative or a friend. Furthermore, the combination of LLM and LR indicated the presence of two different types of PG, namely: (a) daily gamblers, more prone to illegal behaviour, with poor money management skills and who started gambling at an early age, and (b) non-daily gamblers, characterised by superstitious beliefs and a higher preference for immediate reward games. Finally, instant gratification games were strongly associated with the number of games usually played. Studies on gamblers habitually frequently betting shops are rare. The finding of different types of PG by habitual gamblers deserves further analysis in larger studies. Advanced data mining algorithms, like LLM, are powerful tools and potentially useful in identifying risk factors for PG.

  8. Entropy method combined with extreme learning machine method for the short-term photovoltaic power generation forecasting

    International Nuclear Information System (INIS)

    Tang, Pingzhou; Chen, Di; Hou, Yushuo

    2016-01-01

    As the world’s energy problem becomes more severe day by day, photovoltaic power generation has opened a new door for us with no doubt. It will provide an effective solution for this severe energy problem and meet human’s needs for energy if we can apply photovoltaic power generation in real life, Similar to wind power generation, photovoltaic power generation is uncertain. Therefore, the forecast of photovoltaic power generation is very crucial. In this paper, entropy method and extreme learning machine (ELM) method were combined to forecast a short-term photovoltaic power generation. First, entropy method is used to process initial data, train the network through the data after unification, and then forecast electricity generation. Finally, the data results obtained through the entropy method with ELM were compared with that generated through generalized regression neural network (GRNN) and radial basis function neural network (RBF) method. We found that entropy method combining with ELM method possesses higher accuracy and the calculation is faster.

  9. Statistical Methods for Estimating the Uncertainty in the Best Basis Inventories

    International Nuclear Information System (INIS)

    WILMARTH, S.R.

    2000-01-01

    This document describes the statistical methods used to determine sample-based uncertainty estimates for the Best Basis Inventory (BBI). For each waste phase, the equation for the inventory of an analyte in a tank is Inventory (Kg or Ci) = Concentration x Density x Waste Volume. the total inventory is the sum of the inventories in the different waste phases. Using tanks sample data: statistical methods are used to obtain estimates of the mean concentration of an analyte the density of the waste, and their standard deviations. The volumes of waste in the different phases, and their standard deviations, are estimated based on other types of data. The three estimates are multiplied to obtain the inventory estimate. The standard deviations are combined to obtain a standard deviation of the inventory. The uncertainty estimate for the Best Basis Inventory (BBI) is the approximate 95% confidence interval on the inventory

  10. Denmark's National Inventory Report 2010

    DEFF Research Database (Denmark)

    Nielsen, Ole-Kenneth; Lyck, Erik; Mikkelsen, Mette Hjorth

    2010-01-01

    This report is Denmark's National Inventory Report 2010. The report contains information on Denmark's emission inventories for all years' from 1990 to 2008 for CO2, CH4, N2O, HFCs, PFCs and SF6, NOx, CO, NMVOC, SO2.......This report is Denmark's National Inventory Report 2010. The report contains information on Denmark's emission inventories for all years' from 1990 to 2008 for CO2, CH4, N2O, HFCs, PFCs and SF6, NOx, CO, NMVOC, SO2....

  11. Procedure for taking physical inventories

    International Nuclear Information System (INIS)

    Anon.

    1981-01-01

    This session is intended to apprise one of the various aspects of procedures and routines that Exxon Nuclear uses with respect to its nuclear materials physical inventory program. The presentation describes how plant physical inventories are planned and taken. The description includes the planning and preparation for taking the inventory, the clean-out procedures for converting in-process material to measurable items, the administrative procedures for establishing independent inventory teams and for inventorying each inventory area, the verification procedures used to include previously measured tamper-safed items in the inventory, and lastly, procedures used to reconcile the inventory and calculate MUF (materials unaccounted for). The purpose of the session is to enable participants to: (1) understand the planning and pre-inventorty procedures and their importance; (2) understand the need for and the required intensity of clean-out procedures; (3) understand how inventory teams are formed, and how the inventory is conducted; (4) understand the distinction between inventory previously measured tamper-safed items and other materials not so characterized; (5) understand the reconciliation procedures; and (6) calculate a MUF given the book and inventory results

  12. Evaluating Global Emission Inventories of Biogenic Bromocarbons

    Science.gov (United States)

    Hossaini, Ryan; Mantle, H.; Chipperfield, M. P.; Montzka, S. A.; Hamer, P.; Ziska, F.; Quack, B.; Kruger, K.; Tegtmeier, S.; Atlas, E.; hide

    2013-01-01

    ) based on combining the CHBr3 and CH2Br2 inventories which give best agreement with the compilation of observations in the tropics.

  13. Inventory Control System by Using Vendor Managed Inventory (VMI

    Directory of Open Access Journals (Sweden)

    Dona Sabila Alzena

    2018-01-01

    Full Text Available The inventory control system has a strategic role for the business in managing inventory operations. Management of conventional inventory creates problems in the stock of goods that often runs into vacancies and excess goods at the retail level. This study aims to build inventory control system that can maintain the stability of goods availability at the retail level. The implementation of Vendor Managed Inventory (VMI method on inventory control system provides transparency of sales data and inventory of goods at retailer level to supplier. Inventory control is performed by calculating safety stock and reorder point of goods based on sales data received by the system. Rule-based reasoning is provided on the system to facilitate the monitoring of inventory status information, thereby helping the process of inventory updates appropriately. Utilization of SMS technology is also considered as a medium of collecting sales data in real-time due to the ease of use. The results of this study indicate that inventory control using VMI ensures the availability of goods ± 70% and can reduce the accumulation of goods ± 30% at the retail level.

  14. Inventory Control System by Using Vendor Managed Inventory (VMI)

    Science.gov (United States)

    Sabila, Alzena Dona; Mustafid; Suryono

    2018-02-01

    The inventory control system has a strategic role for the business in managing inventory operations. Management of conventional inventory creates problems in the stock of goods that often runs into vacancies and excess goods at the retail level. This study aims to build inventory control system that can maintain the stability of goods availability at the retail level. The implementation of Vendor Managed Inventory (VMI) method on inventory control system provides transparency of sales data and inventory of goods at retailer level to supplier. Inventory control is performed by calculating safety stock and reorder point of goods based on sales data received by the system. Rule-based reasoning is provided on the system to facilitate the monitoring of inventory status information, thereby helping the process of inventory updates appropriately. Utilization of SMS technology is also considered as a medium of collecting sales data in real-time due to the ease of use. The results of this study indicate that inventory control using VMI ensures the availability of goods ± 70% and can reduce the accumulation of goods ± 30% at the retail level.

  15. Effect of combination of Phyllanthus emblica, Tinospora cordifolia, and Ocimum sanctum on spatial learning and memory in rats

    Directory of Open Access Journals (Sweden)

    Harshad O Malve

    2014-01-01

    Full Text Available Background: There has been a steady rise in number of patients suffering from dementia including dementia associated with Alzheimer′s disease. Effective treatment of Alzheimer′s disease dementia is an unmet medical need. Objective: To evaluate effects of formulation containing combination of Phyllanthus emblica (Pe and Tinospora cordifolia (Tc with and without Ocimum sanctum (Os on learning and memory performance of normal and memory impaired rats in complex maze and compare with effects of Tinospora cordifolia and Phyllanthus emblica alone. Materials and Methods: Wistar rats; either sex (100-150 g were divided in seven groups Control, Piracetam, Rivastigmine, Tc, Pe, Formulation 1 (Tc + Pe, and Formulation 2 (Tc + Pe + Os.The study was divided in four parts: In part 1 memory enhancement was tested in normal rats. In part 2, 3, and 4 the effects of drugs were tested in Scopolamine-, Diazepam-, and Cyclosporine-induced amnesia. Hebb-Williams maze was used to test for learning and memory. Time required to trace food and number of errors in maze were noted. Results: In normal rats, all test drugs showed significant reduction in time required to trace the food and number of errors after 24 h compared with vehicle control. Formulations 1 and 2 reduced the time required to trace food and number of errors and the results were comparable with positive control groups and comparators Tc and Pe. Formulations 1 and 2 reversed amnesia produced by Scopolamine, Diazepam, and Cyclosporine when compared with vehicle control and showed comparable results with those of positive control groups and comparators Tc and Pe. Conclusion: Formulations 1 and 2 demonstrated nootropic activity and both the formulations showed comparable nootropic activity with that of Tc and Pe alone.

  16. National Biological Monitoring Inventory

    International Nuclear Information System (INIS)

    Burgess, R.L.

    1979-01-01

    The National Biological Monitoring Inventory, initiated in 1975, currently consists of four computerized data bases and voluminous manual files. MAIN BIOMON contains detailed information on 1,021 projects, while MINI BIOMON provides skeletal data for over 3,000 projects in the 50 states, Puerto Rico, the Virgin Islands, plus a few in Canada and Mexico. BIBLIO BIOMON and DIRECTORY BIOMON complete the computerized data bases. The structure of the system provides for on-line search capabilities to generate details of agency sponsorship, indications of funding levels, taxonomic and geographic coverage, length of program life, managerial focus or emphasis, and condition of the data. Examples of each of these are discussed and illustrated, and potential use of the Inventory in a variety of situations is emphasized

  17. Resolving inventory differences

    International Nuclear Information System (INIS)

    Weber, J.H.; Clark, J.P.

    1991-01-01

    Determining the cause of an inventory difference (ID) that exceeds warning or alarm limits should not only involve investigation into measurement methods and reexamination of the model assumptions used in the calculation of the limits, but also result in corrective actions that improve the quality of the accountability measurements. An example illustrating methods used by Savannah River Site (SRS) personnel to resolve an ID is presented that may be useful to other facilities faced with a similar problem. After first determining that no theft or diversion of material occurred and correcting any accountability calculation errors, investigation into the IDs focused on volume and analytical measurements, limit of error of inventory difference (LEID) modeling assumptions, and changes in the measurement procedures and methods prior to the alarm. There had been a gradual gain trend in IDs prior to the alarm which was reversed by the alarm inventory. The majority of the NM in the facility was stored in four large tanks which helped identify causes for the alarm. The investigation, while indicating no diversion or theft, resulted in changes in the analytical method and in improvements in the measurement and accountability that produced a 67% improvement in the LEID

  18. Procedure for taking physical inventories

    International Nuclear Information System (INIS)

    Boston, R.A.

    1984-01-01

    Physical inventories are taken periodically to meet Company, State and IAEA requirements. Those physical inventories may be verified by IAEA and/or State inspectors. This presentation describes in an introductory but detailed manner the approaches and procedures used in planning, preparing, conducting, reconciling and reporting physical inventories for the Model Plant. Physical inventories are taken for plant accounting purposes to provide an accurate basis for starting and closing the plant material balance. Physical inventories are also taken for safeguards purposes to provide positive assurance that the nuclear materials of concern are indeed present and accounted for

  19. Spatial learning, monoamines and oxidative stress in rats exposed to 900 MHz electromagnetic field in combination with iron overload.

    Science.gov (United States)

    Maaroufi, Karima; Had-Aissouni, Laurence; Melon, Christophe; Sakly, Mohsen; Abdelmelek, Hafedh; Poucet, Bruno; Save, Etienne

    2014-01-01

    The increasing use of mobile phone technology over the last decade raises concerns about the impact of high frequency electromagnetic fields (EMF) on health. More recently, a link between EMF, iron overload in the brain and neurodegenerative disorders including Parkinson's and Alzheimer's diseases has been suggested. Co-exposure to EMF and brain iron overload may have a greater impact on brain tissues and cognitive processes than each treatment by itself. To examine this hypothesis, Long-Evans rats submitted to 900 MHz exposure or combined 900 MHz EMF and iron overload treatments were tested in various spatial learning tasks (navigation task in the Morris water maze, working memory task in the radial-arm maze, and object exploration task involving spatial and non spatial processing). Biogenic monoamines and metabolites (dopamine, serotonin) and oxidative stress were measured. Rats exposed to EMF were impaired in the object exploration task but not in the navigation and working memory tasks. They also showed alterations of monoamine content in several brain areas but mainly in the hippocampus. Rats that received combined treatment did not show greater behavioral and neurochemical deficits than EMF-exposed rats. None of the two treatments produced global oxidative stress. These results show that there is an impact of EMF on the brain and cognitive processes but this impact is revealed only in a task exploiting spontaneous exploratory activity. In contrast, there are no synergistic effects between EMF and a high content of iron in the brain. Copyright © 2013 Elsevier B.V. All rights reserved.

  20. Neuromodulatory Adaptive Combination of Correlation-based Learning in Cerebellum and Reward-based Learning in Basal Ganglia for Goal-directed Behavior Control

    DEFF Research Database (Denmark)

    Dasgupta, Sakyasingha; Wörgötter, Florentin; Manoonpong, Poramate

    2014-01-01

    Goal-directed decision making in biological systems is broadly based on associations between conditional and unconditional stimuli. This can be further classified as classical conditioning (correlation-based learning) and operant conditioning (reward-based learning). A number of computational...... and experimental studies have well established the role of the basal ganglia in reward-based learning, where as the cerebellum plays an important role in developing specific conditioned responses. Although viewed as distinct learning systems, recent animal experiments point toward their complementary role...... in behavioral learning, and also show the existence of substantial two-way communication between these two brain structures. Based on this notion of co-operative learning, in this paper we hypothesize that the basal ganglia and cerebellar learning systems work in parallel and interact with each other. We...

  1. Effect of an EBM course in combination with case method learning sessions: an RCT on professional performance, job satisfaction, and self-efficacy of occupational physicians

    NARCIS (Netherlands)

    Hugenholtz, Nathalie I. R.; Schaafsma, Frederieke G.; Nieuwenhuijsen, Karen; van Dijk, Frank J. H.

    2008-01-01

    Objective An intervention existing of an evidence-based medicine (EBM) course in combination with case method learning sessions (CMLSs) was designed to enhance the professional performance, self-efficacy and job satisfaction of occupational physicians. Methods A cluster randomized controlled trial

  2. Validating the Satisfaction and Continuance Intention of E-Learning Systems: Combining TAM and IS Success Models

    Science.gov (United States)

    Lin, Tung-Cheng; Chen, Ching-Jen

    2012-01-01

    Many e-learning studies have evaluated learning attitudes and behaviors, based on TAM. However, a successful e-learning system (ELS) should take both system and information quality into account by applying ISM developed by Delone and McLean. In addition, the acceptance for information system depends on the perceived usefulness and ease of use…

  3. Combination of mass spectrometry-based targeted lipidomics and supervised machine learning algorithms in detecting adulterated admixtures of white rice.

    Science.gov (United States)

    Lim, Dong Kyu; Long, Nguyen Phuoc; Mo, Changyeun; Dong, Ziyuan; Cui, Lingmei; Kim, Giyoung; Kwon, Sung Won

    2017-10-01

    The mixing of extraneous ingredients with original products is a common adulteration practice in food and herbal medicines. In particular, authenticity of white rice and its corresponding blended products has become a key issue in food industry. Accordingly, our current study aimed to develop and evaluate a novel discrimination method by combining targeted lipidomics with powerful supervised learning methods, and eventually introduce a platform to verify the authenticity of white rice. A total of 30 cultivars were collected, and 330 representative samples of white rice from Korea and China as well as seven mixing ratios were examined. Random forests (RF), support vector machines (SVM) with a radial basis function kernel, C5.0, model averaged neural network, and k-nearest neighbor classifiers were used for the classification. We achieved desired results, and the classifiers effectively differentiated white rice from Korea to blended samples with high prediction accuracy for the contamination ratio as low as five percent. In addition, RF and SVM classifiers were generally superior to and more robust than the other techniques. Our approach demonstrated that the relative differences in lysoGPLs can be successfully utilized to detect the adulterated mixing of white rice originating from different countries. In conclusion, the present study introduces a novel and high-throughput platform that can be applied to authenticate adulterated admixtures from original white rice samples. Copyright © 2017 Elsevier Ltd. All rights reserved.

  4. Combining Multiple Hypothesis Testing with Machine Learning Increases the Statistical Power of Genome-wide Association Studies

    Science.gov (United States)

    Mieth, Bettina; Kloft, Marius; Rodríguez, Juan Antonio; Sonnenburg, Sören; Vobruba, Robin; Morcillo-Suárez, Carlos; Farré, Xavier; Marigorta, Urko M.; Fehr, Ernst; Dickhaus, Thorsten; Blanchard, Gilles; Schunk, Daniel; Navarro, Arcadi; Müller, Klaus-Robert

    2016-01-01

    The standard approach to the analysis of genome-wide association studies (GWAS) is based on testing each position in the genome individually for statistical significance of its association with the phenotype under investigation. To improve the analysis of GWAS, we propose a combination of machine learning and statistical testing that takes correlation structures within the set of SNPs under investigation in a mathematically well-controlled manner into account. The novel two-step algorithm, COMBI, first trains a support vector machine to determine a subset of candidate SNPs and then performs hypothesis tests for these SNPs together with an adequate threshold correction. Applying COMBI to data from a WTCCC study (2007) and measuring performance as replication by independent GWAS published within the 2008–2015 period, we show that our method outperforms ordinary raw p-value thresholding as well as other state-of-the-art methods. COMBI presents higher power and precision than the examined alternatives while yielding fewer false (i.e. non-replicated) and more true (i.e. replicated) discoveries when its results are validated on later GWAS studies. More than 80% of the discoveries made by COMBI upon WTCCC data have been validated by independent studies. Implementations of the COMBI method are available as a part of the GWASpi toolbox 2.0. PMID:27892471

  5. The ABAG biogenic emissions inventory project

    Science.gov (United States)

    Carson-Henry, C. (Editor)

    1982-01-01

    The ability to identify the role of biogenic hydrocarbon emissions in contributing to overall ozone production in the Bay Area, and to identify the significance of that role, were investigated in a joint project of the Association of Bay Area Governments (ABAG) and NASA/Ames Research Center. Ozone, which is produced when nitrogen oxides and hydrocarbons combine in the presence of sunlight, is a primary factor in air quality planning. In investigating the role of biogenic emissions, this project employed a pre-existing land cover classification to define areal extent of land cover types. Emission factors were then derived for those cover types. The land cover data and emission factors were integrated into an existing geographic information system, where they were combined to form a Biogenic Hydrocarbon Emissions Inventory. The emissions inventory information was then integrated into an existing photochemical dispersion model.

  6. Danish emission inventories for stationary combustion plants. Inventories until 2008

    Energy Technology Data Exchange (ETDEWEB)

    Nielsen, Malene; Nielsen, Ole-Kenneth; Plejdrup, M.; Hjelgaard, K.

    2010-10-15

    Emission inventories for stationary combustion plants are presented and the methodologies and assumptions used for the inventories are described. The pollutants considered are SO{sub 2}, NO{sub x}, NMVOC, CH{sub 4}, CO, CO{sub 2}, N{sub 2}O, NH{sub 3}, particulate matter, heavy metals, dioxins, HCB and PAH. The CO{sub 2} emission in 2008 was 16 % lower than in 1990. However, fluctuations in the emission level are large as a result of electricity import/export. The emission of CH{sub 4} has increased due to increased use of lean-burn gas engines in combined heating and power (CHP) plants. However, the emission has decreased in recent years due to structural changes in the Danish electricity market. The N{sub 2}O emission was higher in 2008 than in 1990 but the fluctuations in the time-series are significant. A considerable decrease of the SO{sub 2}, NO{sub x} and heavy metal emissions is mainly a result of decreased emissions from large power plants and waste incineration plants. The combustion of wood in residential plants has increased considerably in recent years resulting in increased emission of PAH, particulate matter and CO. The emission of NMVOC has increased since 1990 as a result of both the increased combustion of wood in residential plants and the increased emission from lean-burn gas engines. The dioxin emission decreased since 1990 due to flue gas cleaning on waste incineration plants. However in recent years the emission has increased as a result of the increased combustion of wood in residential plants. (Author)

  7. Combined Treatment With Environmental Enrichment and (-)-Epigallocatechin-3-Gallate Ameliorates Learning Deficits and Hippocampal Alterations in a Mouse Model of Down Syndrome.

    Science.gov (United States)

    Catuara-Solarz, Silvina; Espinosa-Carrasco, Jose; Erb, Ionas; Langohr, Klaus; Gonzalez, Juan Ramon; Notredame, Cedric; Dierssen, Mara

    2016-01-01

    Intellectual disability in Down syndrome (DS) is accompanied by altered neuro-architecture, deficient synaptic plasticity, and excitation-inhibition imbalance in critical brain regions for learning and memory. Recently, we have demonstrated beneficial effects of a combined treatment with green tea extract containing (-)-epigallocatechin-3-gallate (EGCG) and cognitive stimulation in young adult DS individuals. Although we could reproduce the cognitive-enhancing effects in mouse models, the underlying mechanisms of these beneficial effects are unknown. Here, we explored the effects of a combined therapy with environmental enrichment (EE) and EGCG in the Ts65Dn mouse model of DS at young age. Our results show that combined EE-EGCG treatment improved corticohippocampal-dependent learning and memory. Cognitive improvements were accompanied by a rescue of cornu ammonis 1 (CA1) dendritic spine density and a normalization of the proportion of excitatory and inhibitory synaptic markers in CA1 and dentate gyrus.

  8. Inventory of armourstone

    Directory of Open Access Journals (Sweden)

    Le Turdu Valéry

    2016-01-01

    Full Text Available Natural armourstone is widely used for hydraulic works, both in the coastal domain and in border of rivers and torrents, especially to protect against flood and the effects of waves and currents. To meet the expectations associated with this resource, an inventory of armourstone quarries was realized on a national scale in France. This inventory informs not only about the localization of quarries but also about the quality and the availability of materials. To fully optimize this inventory in a dynamic format, the association of all actors of the sector was preferred to archival research. This partnership approach led to project deliverables that can constitute durably a shared reference. The database can indeed be updated regularly thanks to the contacts established with the professionals of quarries. The access to this database is offered to a wide public: maritime and fluvial ports, local authorities in charge of planning and managing structures that protect against flood and other hydraulic hazards. This new database was organized considering its importance on the operational plan. This led to a hierarchical organization at two levels for each quarry face: first level, a synthesis sheet brings the essential information to realize choices upstream to the operational phases. Second level, a detailed specification sheet presents the technical characteristics observed in the past on the considered face. The atlas has two information broadcasting formats: a pdf file with browsing functions and a geographical information system that allows remote request of the database. These two media have their own updating rhythms, annual for the first and continue for the second.

  9. Perishable Inventory Challenges

    DEFF Research Database (Denmark)

    Damgaard, Cecilie Maria; Nguyen, Vivi Thuy; Hvolby, Hans-Henrik

    2012-01-01

    in the retail supply chains. The goal is to find and evaluate the parameters which affect the decision making process, when finding the optimal order quantity and order time. The paper takes a starting point in the retail industry but links to other industries.......The paper investigates how inventory control of perishable items is managed and line up some possible options of improvement. This includes a review of relevant literature dealing with the challenges of determining ordering policies for perishable products and a study of how the current procedures...

  10. Development of the HD-Teen Inventory.

    Science.gov (United States)

    Driessnack, Martha; Williams, Janet K; Barnette, J Jackson; Sparbel, Kathleen J; Paulsen, Jane S

    2012-05-01

    Adolescents, who have a parent with Huntington Disease (HD), not only are at genetic risk for HD but also are witness to its onset and devastating clinical progression as their parent declines. To date, no mechanism has been developed to direct health care providers to the atypical adolescent experiences of these teens. The purpose of this report is to describe the process of developing the HD-Teen Inventory clinical assessment tool. Forty-eight teens and young adults from 19 U.S. states participated in the evaluation of the HD-Teen Inventory tool. Following item analysis, the number of items was reduced and item frequency and reaction scales were combined, based on the strong correlation (r = .94). The resultant tool contains 15 inventory and 2 open-ended response items. The HD-Teen Inventory emerged as a more compact and efficient tool for identifying the most salient concerns of at-risk teens in HD families in research and/or clinical practice.

  11. Biomass energy inventory and mapping system

    Energy Technology Data Exchange (ETDEWEB)

    Kasile, J.D. [Ohio State Univ., Columbus, OH (United States)

    1993-12-31

    A four-stage biomass energy inventory and mapping system was conducted for the entire State of Ohio. The product is a set of maps and an inventory of the State of Ohio. The set of amps and an inventory of the State`s energy biomass resource are to a one kilometer grid square basis on the Universal Transverse Mercator (UTM) system. Each square kilometer is identified and mapped showing total British Thermal Unit (BTU) energy availability. Land cover percentages and BTU values are provided for each of nine biomass strata types for each one kilometer grid square. LANDSAT satellite data was used as the primary stratifier. The second stage sampling was the photointerpretation of randomly selected one kilometer grid squares that exactly corresponded to the LANDSAT one kilometer grid square classification orientation. Field sampling comprised the third stage of the energy biomass inventory system and was combined with the fourth stage sample of laboratory biomass energy analysis using a Bomb calorimeter and was then used to assign BTU values to the photointerpretation and to adjust the LANDSAT classification. The sampling error for the whole system was 3.91%.

  12. Ragweed (Ambrosia) pollen source inventory for Austria.

    Science.gov (United States)

    Karrer, G; Skjøth, C A; Šikoparija, B; Smith, M; Berger, U; Essl, F

    2015-08-01

    This study improves the spatial coverage of top-down Ambrosia pollen source inventories for Europe by expanding the methodology to Austria, a country that is challenging in terms of topography and the distribution of ragweed plants. The inventory combines annual ragweed pollen counts from 19 pollen-monitoring stations in Austria (2004-2013), 657 geographical observations of Ambrosia plants, a Digital Elevation Model (DEM), local knowledge of ragweed ecology and CORINE land cover information from the source area. The highest mean annual ragweed pollen concentrations were generally recorded in the East of Austria where the highest densities of possible growth habitats for Ambrosia were situated. Approximately 99% of all observations of Ambrosia populations were below 745m. The European infection level varies from 0.1% at Freistadt in Northern Austria to 12.8% at Rosalia in Eastern Austria. More top-down Ambrosia pollen source inventories are required for other parts of Europe. A method for constructing top-down pollen source inventories for invasive ragweed plants in Austria, a country that is challenging in terms of topography and ragweed distribution. Crown Copyright © 2015. Published by Elsevier B.V. All rights reserved.

  13. Problem-based scenarios with laptops: an effective combination for cross-curricular learning in mathematics, science and language

    Directory of Open Access Journals (Sweden)

    Viktor Freiman

    2011-12-01

    Full Text Available Many educational systems consider using one-to-one access to the laptop as a way to improve teaching and learning. A two-year action research project on the use of laptop computers by New Brunswick (Canada grade 7 and 8 Francophone students aimed to better understand the impact of laptops on learning. Two problem-based learning (PBL interdisciplinary scenarios (math, science, language arts were implemented in eight experimental classes to measure and document students’ actual learning process, particularly in terms of their ability to scientifically investigate authentic problems, to reason mathematically, and to communicate. On-site observations, video-recording, journals, samples of students’ work, and interviews were used to collect qualitative data. Based on our findings, we argue that laptops in and of themselves may not automatically lead to better results on standardized tests, but rather create opportunities to enrich learning with more open-ended, constructive, collaborative, reflective, and cognitively complex learning tasks.

  14. Blended Learning Model on Hands-On Approach for In-Service Secondary School Teachers: Combination of E-Learning and Face-to-Face Discussion

    Science.gov (United States)

    Ho, Vinh-Thang; Nakamori, Yoshiteru; Ho, Tu-Bao; Lim, Cher Ping

    2016-01-01

    The purpose of this study was to examine the effectiveness of a blended learning model on hands-on approach for in-service secondary school teachers using a quasi-experimental design. A 24-h teacher-training course using the blended learning model was administered to 117 teachers, while face-to-face instruction was given to 60 teachers. The…

  15. A psychometric evaluation of the digital logic concept inventory

    Science.gov (United States)

    Herman, Geoffrey L.; Zilles, Craig; Loui, Michael C.

    2014-10-01

    Concept inventories hold tremendous promise for promoting the rigorous evaluation of teaching methods that might remedy common student misconceptions and promote deep learning. The measurements from concept inventories can be trusted only if the concept inventories are evaluated both by expert feedback and statistical scrutiny (psychometric evaluation). Classical Test Theory and Item Response Theory provide two psychometric frameworks for evaluating the quality of assessment tools. We discuss how these theories can be applied to assessment tools generally and then apply them to the Digital Logic Concept Inventory (DLCI). We demonstrate that the DLCI is sufficiently reliable for research purposes when used in its entirety and as a post-course assessment of students' conceptual understanding of digital logic. The DLCI can also discriminate between students across a wide range of ability levels, providing the most information about weaker students' ability levels.

  16. NRC inventory of dams

    International Nuclear Information System (INIS)

    Lear, G.E.; Thompson, O.O.

    1983-01-01

    The NRC Inventory of Dams has been prepared as required by the charter of the NRC Dam Safety Officer. The inventory lists 51 dams associated with nuclear power plant sites and 14 uranium mill tailings dams (licensed by NRC) in the US as of February 1, 1982. Of the 85 listed nuclear power plants (148 units), 26 plants obtain cooling water from impoundments formed by dams. The 51 dams associated with the plants are: located on a plant site (29 dams at 15 plant sites); located off site but provide plant cooling water (18 dams at 11 additional plant sites); and located upstream from a plant (4 dams) - they have been identified as dams whose failure, and ensuing plant flooding, could result in a radiological risk to the public health and safety. The dams that might be considered NRC's responsibility in terms of the federal dam safety program are identified. This group of dams (20 on nuclear power plant sites and 14 uranium mill tailings dams) was obtained by eliminating dams that do not pose a flooding hazard (e.g., submerged dams) and dams that are regulated by another federal agency. The report includes the principal design features of all dams and related useful information

  17. DeepAnomaly: Combining Background Subtraction and Deep Learning for Detecting Obstacles and Anomalies in an Agricultural Field

    Directory of Open Access Journals (Sweden)

    Peter Christiansen

    2016-11-01

    Full Text Available Convolutional neural network (CNN-based systems are increasingly used in autonomous vehicles for detecting obstacles. CNN-based object detection and per-pixel classification (semantic segmentation algorithms are trained for detecting and classifying a predefined set of object types. These algorithms have difficulties in detecting distant and heavily occluded objects and are, by definition, not capable of detecting unknown object types or unusual scenarios. The visual characteristics of an agriculture field is homogeneous, and obstacles, like people, animals and other obstacles, occur rarely and are of distinct appearance compared to the field. This paper introduces DeepAnomaly, an algorithm combining deep learning and anomaly detection to exploit the homogenous characteristics of a field to perform anomaly detection. We demonstrate DeepAnomaly as a fast state-of-the-art detector for obstacles that are distant, heavily occluded and unknown. DeepAnomaly is compared to state-of-the-art obstacle detectors including “Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks” (RCNN. In a human detector test case, we demonstrate that DeepAnomaly detects humans at longer ranges (45–90 m than RCNN. RCNN has a similar performance at a short range (0–30 m. However, DeepAnomaly has much fewer model parameters and (182 ms/25 ms = a 7.28-times faster processing time per image. Unlike most CNN-based methods, the high accuracy, the low computation time and the low memory footprint make it suitable for a real-time system running on a embedded GPU (Graphics Processing Unit.

  18. Combined use of two supervised learning algorithms to model sea turtle behaviours from tri-axial acceleration data.

    Science.gov (United States)

    Jeantet, L; Dell'Amico, F; Forin-Wiart, M-A; Coutant, M; Bonola, M; Etienne, D; Gresser, J; Regis, S; Lecerf, N; Lefebvre, F; de Thoisy, B; Le Maho, Y; Brucker, M; Châtelain, N; Laesser, R; Crenner, F; Handrich, Y; Wilson, R; Chevallier, D

    2018-05-23

    Accelerometers are becoming ever more important sensors in animal-attached technology, providing data that allow determination of body posture and movement and thereby helping to elucidate behaviour in animals that are difficult to observe. We sought to validate the identification of sea turtle behaviours from accelerometer signals by deploying tags on the carapace of a juvenile loggerhead ( Caretta caretta ), an adult hawksbill ( Eretmochelys imbricata ) and an adult green turtle ( Chelonia mydas ) at Aquarium La Rochelle, France. We recorded tri-axial acceleration at 50 Hz for each species for a full day while two fixed cameras recorded their behaviours. We identified behaviours from the acceleration data using two different supervised learning algorithms, Random Forest and Classification And Regression Tree (CART), treating the data from the adult animals as separate from the juvenile data. We achieved a global accuracy of 81.30% for the adult hawksbill and green turtle CART model and 71.63% for the juvenile loggerhead, identifying 10 and 12 different behaviours, respectively. Equivalent figures were 86.96% for the adult hawksbill and green turtle Random Forest model and 79.49% for the juvenile loggerhead, for the same behaviours. The use of Random Forest combined with CART algorithms allowed us to understand the decision rules implicated in behaviour discrimination, and thus remove or group together some 'confused' or under--represented behaviours in order to get the most accurate models. This study is the first to validate accelerometer data to identify turtle behaviours and the approach can now be tested on other captive sea turtle species. © 2018. Published by The Company of Biologists Ltd.

  19. Applications of inventory difference tool at Los Alamos Plutonium Facility

    International Nuclear Information System (INIS)

    Hench, K.W.; Longmire, V.; Yarbro, T.F.; Zardecki, A.

    1998-01-01

    A prototype computer program reads the inventory entries directly from the Microsoft Access database. Based on historical data, the program then displays temporal trends and constructs a library of rules that encapsulate the system behavior. The analysis of inventory data is illustrated using a combination of realistic and simulated facility examples. Potential payoffs of this methodology include a reduction in time and resources needed to perform statistical tests and a broad applicability to DOE needs such as treaty verification

  20. Strategic Inventories in Vertical Contracts

    OpenAIRE

    Krishnan Anand; Ravi Anupindi; Yehuda Bassok

    2008-01-01

    Classical reasons for carrying inventory include fixed (nonlinear) production or procurement costs, lead times, nonstationary or uncertain supply/demand, and capacity constraints. The last decade has seen active research in supply chain coordination focusing on the role of incentive contracts to achieve first-best levels of inventory. An extensive literature in industrial organization that studies incentives for vertical controls largely ignores the effect of inventories. Does the ability to ...

  1. Denmark's National Inventory Report 2013

    DEFF Research Database (Denmark)

    Nielsen, Ole-Kenneth; Plejdrup, Marlene Schmidt; Winther, Morten

    This report is Denmark’s National Inventory Report 2013. The report contains information on Denmark’s emission inventories for all years’ from 1990 to 2011 for CO2, CH4, N2O, HFCs, PFCs and SF6, NOx, CO, NMVOC, SO2.......This report is Denmark’s National Inventory Report 2013. The report contains information on Denmark’s emission inventories for all years’ from 1990 to 2011 for CO2, CH4, N2O, HFCs, PFCs and SF6, NOx, CO, NMVOC, SO2....

  2. Denmark's National Inventory Report 2017

    DEFF Research Database (Denmark)

    Nielsen, Ole-Kenneth; Plejdrup, Marlene Schmidt; Winther, Morten

    This report is Denmark’s National Inventory Report 2017. The report contains information on Denmark’s emission inventories for all years’ from 1990 to 2015 for CO2, CH4, N2O, HFCs, PFCs and SF6, NOx, CO, NMVOC, SO2......This report is Denmark’s National Inventory Report 2017. The report contains information on Denmark’s emission inventories for all years’ from 1990 to 2015 for CO2, CH4, N2O, HFCs, PFCs and SF6, NOx, CO, NMVOC, SO2...

  3. Denmark's National Inventory Report 2014

    DEFF Research Database (Denmark)

    Nielsen, Ole-Kenneth; Plejdrup, Marlene Schmidt; Winther, Morten

    This report is Denmark’s National Inventory Report 2014. The report contains information on Denmark’s emission inventories for all years’ from 1990 to 2012 for CO2, CH4, N2O, HFCs, PFCs and SF6, NOx, CO, NMVOC, SO2......This report is Denmark’s National Inventory Report 2014. The report contains information on Denmark’s emission inventories for all years’ from 1990 to 2012 for CO2, CH4, N2O, HFCs, PFCs and SF6, NOx, CO, NMVOC, SO2...

  4. Six ways to reduce inventory.

    Science.gov (United States)

    Lunn, T

    1996-05-01

    The purpose of this presentation is to help you reduce the inventory in your operation. We will accomplish that task by discussing six specific methods that companies have used successfully to reduce their inventory. One common attribute of these successes is that they also build teamwork among the people. Every business operation today is concerned with methods to improve customer service. The real trick is to accomplish that task without increasing inventory. We are all concerned with improving our skills at keeping inventory low.

  5. VTrans Small Culvert Inventory - Culverts

    Data.gov (United States)

    Vermont Center for Geographic Information — Vermont Agency of Transportation Small Culvert Inventory: Culverts. This data contains small culverts locations along VTrans maintained roadways. The data was...

  6. Hanford inventory program user's manual

    International Nuclear Information System (INIS)

    Hinkelman, K.C.

    1994-01-01

    Provides users with instructions and information about accessing and operating the Hanford Inventory Program (HIP) system. The Hanford Inventory Program is an integrated control system that provides a single source for the management and control of equipment, parts, and material warehoused by Westinghouse Hanford Company in various site-wide locations. The inventory is comprised of spare parts and equipment, shop stock, special tools, essential materials, and convenience storage items. The HIP replaced the following systems; ACA, ASP, PICS, FSP, WSR, STP, and RBO. In addition, HIP manages the catalog maintenance function for the General Supplies inventory stocked in the 1164 building and managed by WIMS

  7. Accelerated Best Basis Inventory Baselining Task

    International Nuclear Information System (INIS)

    SASAKI, L.M.

    2001-01-01

    The baselining effort was recently proposed to bring the Best-Basis Inventory (BBI) and Question No.8 of the Tank Interpretive Report (TIR) for all 177 tanks to the current standards and protocols and to prepare a TIR Question No.8 if one is not already available. This plan outlines the objectives and methodology of the accelerated BBI baselining task. BBI baselining meetings held during December 2000 resulted in a revised BBI methodology and an initial set of BBI creation rules to be used in the baselining effort. The objectives of the BBI baselining effort are to: (1) Provide inventories that are consistent with the revised BBI methodology and new BBI creation rules. (2) Split the total tank waste in each tank into six waste phases, as appropriate (Supernatant, saltcake solids, saltcake liquid, sludge solids, sludge liquid, and retained gas). In some tanks, the solids and liquid portions of the sludge and/or saltcake may be combined into a single sludge or saltcake phase. (3) Identify sampling events that are to be used for calculating the BBIs. (4) Update waste volumes for subsequent reconciliation with the Hanlon (2001) waste tank summary. (5) Implement new waste type templates. (6) Include any sample data that might have been unintentionally omitted in the previous BBI and remove any sample data that should not have been included. Sample data to be used in the BBI must be available on TWINS. (7) Ensure that an inventory value for each standard BBI analyte is provided for each waste component. Sample based inventories for supplemental BBI analytes will be included when available. (8) Provide new means and confidence interval reports if one is not already available and include uncertainties in reporting inventory values

  8. A Combination of Machine Learning and Cerebellar-like Neural Networks for the Motor Control and Motor Learning of the Fable Modular Robot

    DEFF Research Database (Denmark)

    Baira Ojeda, Ismael; Tolu, Silvia; Pacheco, Moises

    2017-01-01

    We scaled up a bio-inspired control architecture for the motor control and motor learning of a real modular robot. In our approach, the Locally Weighted Projection Regression algorithm (LWPR) and a cerebellar microcircuit coexist, in the form of a Unit Learning Machine. The LWPR algorithm optimizes...... the input space and learns the internal model of a single robot module to command the robot to follow a desired trajectory with its end-effector. The cerebellar-like microcircuit refines the LWPR output delivering corrective commands. We contrasted distinct cerebellar-like circuits including analytical...

  9. Combination of inquiry learning model and computer simulation to improve mastery concept and the correlation with critical thinking skills (CTS)

    Science.gov (United States)

    Nugraha, Muhamad Gina; Kaniawati, Ida; Rusdiana, Dadi; Kirana, Kartika Hajar

    2016-02-01

    Among the purposes of physics learning at high school is to master the physics concepts and cultivate scientific attitude (including critical attitude), develop inductive and deductive reasoning skills. According to Ennis et al., inductive and deductive reasoning skills are part of critical thinking. Based on preliminary studies, both of the competence are lack achieved, it is seen from student learning outcomes is low and learning processes that are not conducive to cultivate critical thinking (teacher-centered learning). One of learning model that predicted can increase mastery concepts and train CTS is inquiry learning model aided computer simulations. In this model, students were given the opportunity to be actively involved in the experiment and also get a good explanation with the computer simulations. From research with randomized control group pretest-posttest design, we found that the inquiry learning model aided computer simulations can significantly improve students' mastery concepts than the conventional (teacher-centered) method. With inquiry learning model aided computer simulations, 20% of students have high CTS, 63.3% were medium and 16.7% were low. CTS greatly contribute to the students' mastery concept with a correlation coefficient of 0.697 and quite contribute to the enhancement mastery concept with a correlation coefficient of 0.603.

  10. How Are Learning Strategies Reflected in the Eyes? Combining Results from Self-Reports and Eye-Tracking

    Science.gov (United States)

    Catrysse, Leen; Gijbels, David; Donche, Vincent; De Maeyer, Sven; Lesterhuis, Marije; Van den Bossche, Piet

    2018-01-01

    Background: Up until now, empirical studies in the Student Approaches to Learning field have mainly been focused on the use of self-report instruments, such as interviews and questionnaires, to uncover differences in students' general preferences towards learning strategies, but have focused less on the use of task-specific and online measures.…

  11. The Joint Influence of Intra- and Inter-Team Learning Processes on Team Performance : A Constructive or Destructive Combination?

    NARCIS (Netherlands)

    Bron, Rike; Endedijk, Maaike D.; van Veelen, Ruth; Veldkamp, Bernard P.

    2018-01-01

    In order for teams to build a shared conception of their task, team learning is crucial. Benefits of intra-team learning have been demonstrated in numerous studies. However, teams do not operate in a vacuum, and interact with their environment to execute their tasks. Our knowledge of the added value

  12. Applying inventory classification to a large inventory management system

    Directory of Open Access Journals (Sweden)

    Benjamin Isaac May

    2017-06-01

    Full Text Available Inventory classification aims to ensure that business-driving inventory items are efficiently managed in spite of constrained resources. There are numerous single- and multiple-criteria approaches to it. Our objective is to improve resource allocation to focus on items that can lead to high equipment availability. This concern is typical of many service industries such as military logistics, airlines, amusement parks and public works. Our study tests several inventory prioritization techniques and finds that a modified multi-criterion weighted non-linear optimization (WNO technique is a powerful approach for classifying inventory, outperforming traditional techniques of inventory prioritization such as ABC analysis in a variety of performance objectives.

  13. Inventory classification based on decoupling points

    Directory of Open Access Journals (Sweden)

    Joakim Wikner

    2015-01-01

    Full Text Available The ideal state of continuous one-piece flow may never be achieved. Still the logistics manager can improve the flow by carefully positioning inventory to buffer against variations. Strategies such as lean, postponement, mass customization, and outsourcing all rely on strategic positioning of decoupling points to separate forecast-driven from customer-order-driven flows. Planning and scheduling of the flow are also based on classification of decoupling points as master scheduled or not. A comprehensive classification scheme for these types of decoupling points is introduced. The approach rests on identification of flows as being either demand based or supply based. The demand or supply is then combined with exogenous factors, classified as independent, or endogenous factors, classified as dependent. As a result, eight types of strategic as well as tactical decoupling points are identified resulting in a process-based framework for inventory classification that can be used for flow design.

  14. The Marihuana Perception Inventory: The Effects of Substance Abuse Instruction.

    Science.gov (United States)

    Gabany, Steve G.; Plummer, Portia

    1990-01-01

    Studied 617 high school and college students prior to and after substance abuse instruction to determine relationship between perceptions and demographic characteristics, and to learn whether substance abuse instruction was related to changes in student's perception of relationships. Findings from Marihuana Perception Inventory showed five factors…

  15. 21 CFR 1304.11 - Inventory requirements.

    Science.gov (United States)

    2010-04-01

    ... the inventory of the registered location to which they are subject to control or to which the person... 21 Food and Drugs 9 2010-04-01 2010-04-01 false Inventory requirements. 1304.11 Section 1304.11... REGISTRANTS Inventory Requirements § 1304.11 Inventory requirements. (a) General requirements. Each inventory...

  16. Optimization of inventory management in furniture manufacturing

    OpenAIRE

    Karkauskas, Justinas

    2017-01-01

    Aim of research - to present inventory management optimization guidelines for furniture manufacturing company, based on analysis of scientific literature and empirical research. Tasks of the Issue: • Disclose problems of inventory management in furniture manufacturing sector; • To analyze theoretical inventory management decisions; • To develop theoretical inventory management optimization model; • Do empirical research of inventory management and present offers for optimizatio...

  17. Controlling Inventory: Real-World Mathematical Modeling

    Science.gov (United States)

    Edwards, Thomas G.; Özgün-Koca, S. Asli; Chelst, Kenneth R.

    2013-01-01

    Amazon, Walmart, and other large-scale retailers owe their success partly to efficient inventory management. For such firms, holding too little inventory risks losing sales, whereas holding idle inventory wastes money. Therefore profits hinge on the inventory level chosen. In this activity, students investigate a simplified inventory-control…

  18. Denmark's national inventory report 2006

    DEFF Research Database (Denmark)

    Illerup, Jytte Boll; Lyck, Erik; Nielsen, Ole-Kenneth

    This report is Denmark's National Inventory Report reported to the Conference of the Parties under the United Nations Framework Convention on Climate Change (UNFCCC) due by April 2006. The report contains information on Denmark's inventories for all years' from 1990 to 2004 for CO....

  19. Demand differentiation in inventory systems

    NARCIS (Netherlands)

    Kleijn, M.J.

    1998-01-01

    This book deals with inventory systems where customer demand is categorised into different classes. Most inventory systems do not take into account individual customer preferences for a given product, and therefore handle all demand in a similar way. Nowadays, market segmentation has become a

  20. Student-Life Stress Inventory.

    Science.gov (United States)

    Gadzella, Bernadette M.; And Others

    The reliability of the Student-Life Stress Inventory of B. M. Gadzella (1991) was studied. The inventory consists of 51 items listed in 9 sections indicating different types of stressors (frustrations, conflicts, pressures, changes, and self-imposed stressors) and reactions to the stressors (physiological, emotional, behavioral, and cognitive) as…

  1. Automation of Space Inventory Management

    Science.gov (United States)

    Fink, Patrick W.; Ngo, Phong; Wagner, Raymond; Barton, Richard; Gifford, Kevin

    2009-01-01

    This viewgraph presentation describes the utilization of automated space-based inventory management through handheld RFID readers and BioNet Middleware. The contents include: 1) Space-Based INventory Management; 2) Real-Time RFID Location and Tracking; 3) Surface Acoustic Wave (SAW) RFID; and 4) BioNet Middleware.

  2. ANALYSIS MODEL FOR INVENTORY MANAGEMENT

    Directory of Open Access Journals (Sweden)

    CAMELIA BURJA

    2010-01-01

    Full Text Available The inventory represents an essential component for the assets of the enterprise and the economic analysis gives them special importance because their accurate management determines the achievement of the activity object and the financial results. The efficient management of inventory requires ensuring an optimum level for them, which will guarantee the normal functioning of the activity with minimum inventory expenses and funds which are immobilised. The paper presents an analysis model for inventory management based on their rotation speed and the correlation with the sales volume illustrated in an adequate study. The highlighting of the influence factors on the efficient inventory management ensures the useful information needed to justify managerial decisions, which will lead to a balancedfinancial position and to increased company performance.

  3. Noise-aware dictionary-learning-based sparse representation framework for detection and removal of single and combined noises from ECG signal.

    Science.gov (United States)

    Satija, Udit; Ramkumar, Barathram; Sabarimalai Manikandan, M

    2017-02-01

    Automatic electrocardiogram (ECG) signal enhancement has become a crucial pre-processing step in most ECG signal analysis applications. In this Letter, the authors propose an automated noise-aware dictionary learning-based generalised ECG signal enhancement framework which can automatically learn the dictionaries based on the ECG noise type for effective representation of ECG signal and noises, and can reduce the computational load of sparse representation-based ECG enhancement system. The proposed framework consists of noise detection and identification, noise-aware dictionary learning, sparse signal decomposition and reconstruction. The noise detection and identification is performed based on the moving average filter, first-order difference, and temporal features such as number of turning points, maximum absolute amplitude, zerocrossings, and autocorrelation features. The representation dictionary is learned based on the type of noise identified in the previous stage. The proposed framework is evaluated using noise-free and noisy ECG signals. Results demonstrate that the proposed method can significantly reduce computational load as compared with conventional dictionary learning-based ECG denoising approaches. Further, comparative results show that the method outperforms existing methods in automatically removing noises such as baseline wanders, power-line interference, muscle artefacts and their combinations without distorting the morphological content of local waves of ECG signal.

  4. Quantitative Analysis of the Usage of a Pedagogical Tool Combining Questions Listed as Learning Objectives and Answers Provided as Online Videos

    Directory of Open Access Journals (Sweden)

    Odette Laneuville

    2015-05-01

    Full Text Available To improve the learning of basic concepts in molecular biology of an undergraduate science class, a pedagogical tool was developed, consisting of learning objectives listed at the end of each lecture and answers to those objectives made available as videos online. The aim of this study was to determine if the pedagogical tool was used by students as instructed, and to explore students’ perception of its usefulness. A combination of quantitative survey data and measures of online viewing was used to evaluate the usage of the pedagogical practice. A total of 77 short videos linked to 11 lectures were made available to 71 students, and 64 completed the survey. Using online tracking tools, a total of 7046 views were recorded. Survey data indicated that most students (73.4% accessed all videos, and the majority (98.4% found the videos to be useful in assisting their learning. Interestingly, approximately half of the students (53.1% always or most of the time used the pedagogical tool as recommended, and consistently answered the learning objectives before watching the videos. While the proposed pedagogical tool was used by the majority of students outside the classroom, only half used it as recommended limiting the impact on students’ involvement in the learning of the material presented in class.

  5. Recent evidence on the muted inventory cycle

    OpenAIRE

    Andrew J. Filardo

    1995-01-01

    Inventories play an important role in business cycles. Inventory build-ups add momentum to the economy during expansions, while inventory liquidations sap economic strength during recessions. In addition, because inventory fluctuations are notoriously difficult to predict, they present considerable uncertainty in assessing the economic outlook.> The role of inventories in shaping the current outlook for the U.S. economy is particularly uncertain. In the early 1990s, inventory swings appeared ...

  6. Effects of rolipram, a phosphodiesterase 4 inhibitor, in combination with imipramine on depressive behavior, CRE-binding activity and BDNF level in learned helplessness rats.

    Science.gov (United States)

    Itoh, Tetsuji; Tokumura, Miwa; Abe, Kohji

    2004-09-13

    The brain cAMP regulating system and its downstream elements play a pivotal role in the therapeutic effects of antidepressants. We previously reported the increase in activities of phosphodiesterase 4, a major phosphodiesterase isozyme hydrolyzing cAMP, in the frontal cortex and hippocampus of learned helplessness rats, an animal model for depression. The present study was undertaken to examine the combination of effects of rolipram, a phosphodiesterase 4 inhibitor, with imipramine, a typical tricyclic antidepressant, on depressive behavior in learned helplessness rats. Concurrently, cAMP-response element (CRE)-binding activity and brain-derived neurotrophic factor (BDNF) levels related to the therapeutic effects of antidepressants were determined. Repeated administration of imipramine (1.25-10 mg/kg, i.p.) or rolipram (1.25 mg/kg, i.p.) reduced the number of escape failures in learned helplessness rats. Imipramine could not completely ameliorate the escape behavior to a level similar to that of non-stressed rats even at 10 mg/kg. However, repeated coadministration of rolipram with imipramine (1.25 and 2.5 mg/kg, respectively) almost completely eliminated the escape failures in learned helplessness rats. The reduction of CRE-binding activities and BDNF levels in the frontal cortex or hippocampus in learned helplessness rats were ameliorated by treatment with imipramine or rolipram alone. CRE-binding activities and/or BDNF levels of the frontal cortex and hippocampus were significantly increased by treatment with a combination of rolipram and imipramine compared to those in imipramine-treated rats. These results indicated that coadministration of phosphodiesterase type 4 inhibitors with antidepressants may be more effective for depression therapy and suggest that elevation of the cAMP signal transduction pathway is involved in the antidepressive effects.

  7. INEEL Liquid Effluent Inventory

    Energy Technology Data Exchange (ETDEWEB)

    Major, C.A.

    1997-06-01

    The INEEL contractors and their associated facilities are required to identify all liquid effluent discharges that may impact the environment at the INEEL. This liquid effluent information is then placed in the Liquid Effluent Inventory (LEI) database, which is maintained by the INEEL prime contractor. The purpose of the LEI is to identify and maintain a current listing of all liquid effluent discharge points and to identify which discharges are subject to federal, state, or local permitting or reporting requirements and DOE order requirements. Initial characterization, which represents most of the INEEL liquid effluents, has been performed, and additional characterization may be required in the future to meet regulations. LEI information is made available to persons responsible for or concerned with INEEL compliance with liquid effluent permitting or reporting requirements, such as the National Pollutant Discharge Elimination System, Wastewater Land Application, Storm Water Pollution Prevention, Spill Prevention Control and Countermeasures, and Industrial Wastewater Pretreatment. The State of Idaho Environmental Oversight and Monitoring Program also needs the information for tracking liquid effluent discharges at the INEEL. The information provides a baseline from which future liquid discharges can be identified, characterized, and regulated, if appropriate. The review covered new and removed buildings/structures, buildings/structures which most likely had new, relocated, or removed LEI discharge points, and at least 10% of the remaining discharge points.

  8. Inventory of miscellaneous streams

    International Nuclear Information System (INIS)

    Lueck, K.J.

    1995-09-01

    On December 23, 1991, the US Department of Energy, Richland Operations Office (RL) and the Washington State Department of Ecology (Ecology) agreed to adhere to the provisions of the Department of Ecology Consent Order. The Consent Order lists the regulatory milestones for liquid effluent streams at the Hanford Site to comply with the permitting requirements of Washington Administrative Code. The RL provided the US Congress a Plan and Schedule to discontinue disposal of contaminated liquid effluent into the soil column on the Hanford Site. The plan and schedule document contained a strategy for the implementation of alternative treatment and disposal systems. This strategy included prioritizing the streams into two phases. The Phase 1 streams were considered to be higher priority than the Phase 2 streams. The actions recommended for the Phase 1 and 2 streams in the two reports were incorporated in the Hanford Federal Facility Agreement and Consent Order. Miscellaneous Streams are those liquid effluents streams identified within the Consent Order that are discharged to the ground but are not categorized as Phase 1 or Phase 2 Streams. This document consists of an inventory of the liquid effluent streams being discharged into the Hanford soil column

  9. Developing Professional Learning for Staff Working with Children with Speech, Language and Communication Needs Combined with Moderate-Severe Learning Difficulties

    Science.gov (United States)

    Anderson, Carolyn

    2011-01-01

    This article presents research undertaken as part of a PhD by Carolyn Anderson who is a senior lecturer on the BSc (Hons) in Speech and Language Pathology at the University of Strathclyde. The study explores the professional learning experiences of 49 teachers working in eight schools and units for children with additional support needs in…

  10. Software for Managing Inventory of Flight Hardware

    Science.gov (United States)

    Salisbury, John; Savage, Scott; Thomas, Shirman

    2003-01-01

    The Flight Hardware Support Request System (FHSRS) is a computer program that relieves engineers at Marshall Space Flight Center (MSFC) of most of the non-engineering administrative burden of managing an inventory of flight hardware. The FHSRS can also be adapted to perform similar functions for other organizations. The FHSRS affords a combination of capabilities, including those formerly provided by three separate programs in purchasing, inventorying, and inspecting hardware. The FHSRS provides a Web-based interface with a server computer that supports a relational database of inventory; electronic routing of requests and approvals; and electronic documentation from initial request through implementation of quality criteria, acquisition, receipt, inspection, storage, and final issue of flight materials and components. The database lists both hardware acquired for current projects and residual hardware from previous projects. The increased visibility of residual flight components provided by the FHSRS has dramatically improved the re-utilization of materials in lieu of new procurements, resulting in a cost savings of over $1.7 million. The FHSRS includes subprograms for manipulating the data in the database, informing of the status of a request or an item of hardware, and searching the database on any physical or other technical characteristic of a component or material. The software structure forces normalization of the data to facilitate inquiries and searches for which users have entered mixed or inconsistent values.

  11. Fusion program research materials inventory

    International Nuclear Information System (INIS)

    Roche, T.K.; Wiffen, F.W.; Davis, J.W.; Lechtenberg, T.A.

    1984-01-01

    Oak Ridge National Laboratory maintains a central inventory of research materials to provide a common supply of materials for the Fusion Reactor Materials Program. This will minimize unintended material variations and provide for economy in procurement and for centralized record keeping. Initially this inventory is to focus on materials related to first-wall and structural applications and related research, but various special purpose materials may be added in the future. The use of materials from this inventory for research that is coordinated with or otherwise related technically to the Fusion Reactor Materials Program of DOE is encouraged

  12. Forest inventory with LiDAR and stereo DSM on Washington department of natural resources lands

    Science.gov (United States)

    Jacob L. Strunk; Peter J. Gould

    2015-01-01

    DNR’s forest inventory group has completed its first version of a new remote-sensing based forest inventory system covering 1.4 million acres of DNR forest lands. We use a combination of field plots, lidar, NAIP, and a NAIP-derived canopy surface DSM. Given that height drives many key inventory variables (e.g. height, volume, biomass, carbon), remote-sensing derived...

  13. Anomaly detection for analysis of annual inventory data: a quality control approach

    Science.gov (United States)

    Francis A. Roesch; Paul C. Van Deusen

    2010-01-01

    Annual forest inventories present special challenges and opportunities for those analyzing the data arising from them. Here, we address one question currently being asked by analysts of the US Forest Service’s Forest Inventory and Analysis Program’s quickly accumulating annual inventory data. The question is simple but profound: When combining the next year’s data for...

  14. Biogenic Emission Inventory System (BEIS)

    Science.gov (United States)

    Biogenic Emission Inventory System (BEIS) estimates volatile organic compound (VOC) emissions from vegetation and nitric oxide (NO) emission from soils. Recent BEIS development has been restricted to the SMOKE system

  15. Severe Weather Data Inventory (SWDI)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The Severe Weather Data Inventory (SWDI) is an integrated database of severe weather records for the United States. SWDI enables a user to search through a variety...

  16. FEMA Flood Insurance Studies Inventory

    Data.gov (United States)

    Kansas Data Access and Support Center — This digital data set provides an inventory of Federal Emergency Management Agency (FEMA) Flood Insurance Studies (FIS) that have been conducted for communities and...

  17. Clinical Decision Support (CDS) Inventory

    Data.gov (United States)

    U.S. Department of Health & Human Services — The Clinical Decision Support (CDS) Inventory contains descriptions of past and present CDS projects across the Federal Government. It includes Federal projects,...

  18. COMPUTER ASSISTED INVENTORY CONTROL SYSTEM ...

    African Journals Online (AJOL)

    issue in supply chain inventory manugement is to coordinate .... A supply chain is a network of organizations that are involved in the ... make decisions, which result in sub-optimization. ... same time reduce the ultimate cost of finished goods.

  19. Allegheny County Toxics Release Inventory

    Data.gov (United States)

    Allegheny County / City of Pittsburgh / Western PA Regional Data Center — The Toxics Release Inventory (TRI) data provides information about toxic substances released into the environment or managed through recycling, energy recovery, and...

  20. National Greenhouse Gas Emission Inventory

    Data.gov (United States)

    U.S. Environmental Protection Agency — The National Greenhouse Gas Emission Inventory contains information on direct emissions of greenhouse gases as well as indirect or potential emissions of greenhouse...

  1. Title V Permitting Statistics Inventory

    Data.gov (United States)

    U.S. Environmental Protection Agency — The Title V Permitting Statistics Inventory contains measured and estimated nationwide statistical data, consisting of counts of permitted sources, types of permits...

  2. Travel reliability inventory for Chicago.

    Science.gov (United States)

    2013-04-01

    The overarching goal of this research project is to enable state DOTs to document and monitor the reliability performance : of their highway networks. To this end, a computer tool, TRIC, was developed to produce travel reliability inventories from : ...

  3. Predicting Teachers’ use of Digital Learning Materials: Combining Self-Determination Theory and the Integrative Model of Behavior Prediction

    NARCIS (Netherlands)

    Kreijns, Karel; Vermeulen, Marjan; Van Acker, Frederik; Van Buuren, Hans

    2018-01-01

    In this article, we report on a study that investigated the motivational (e.g., intrinsic motivation) and dispositional variables (e.g., attitudes) that determine teachers’ intention to use or not to use Digital Learning Materials (DLMs). To understand the direct and indirect relationships between

  4. A Neural Circuit for Acoustic Navigation combining Heterosynaptic and Non-synaptic Plasticity that learns Stable Trajectories

    DEFF Research Database (Denmark)

    Shaikh, Danish; Manoonpong, Poramate

    2017-01-01

    controllers be resolved in a manner that generates consistent and stable robot trajectories? We propose a neural circuit that minimises this conflict by learning sensorimotor mappings as neuronal transfer functions between the perceived sound direction and wheel velocities of a simulated non-holonomic mobile...

  5. Combining Vision with Voice: A Learning and Implementation Structure Promoting Teachers' Internalization of Practices Based on Self-Determination Theory

    Science.gov (United States)

    Assor, Avi; Kaplan, Haya; Feinberg, Ofra; Tal, Karen

    2009-01-01

    We propose that self-determination theory's conceptualization of internalization may help school reformers overcome the recurrent problem of "the predictable failure of educational reform" (Sarason, 1993). Accordingly, we present a detailed learning and implementation structure to promote teachers' internalization and application of ideas and…

  6. A Learning Log Analysis of an English-Reading e-Book System Combined with a Guidance Mechanism

    Science.gov (United States)

    Wu, Ting-Ting

    2016-01-01

    Learning English by reading articles on multimedia e-book devices can assist students in improving their vocabulary and in understanding the associations among vocabulary, textual meaning, and paragraph composition. Adaptive integration of reading technologies and strategies not only strengthens their language ability and reading comprehension,…

  7. Enhancing Learning Outcomes through New E-Textbooks: A Desirable Combination of Presentation Methods and Concept Maps

    Science.gov (United States)

    Huang, Kuo-Liang; Chen, Kuo-Hsiang; Ho, Chun-Heng

    2014-01-01

    It is possible that e-textbook readers and tablet PC's will become mainstream reading devices in the future. However, knowledge about instructional design in this field of learning sciences is inadequate. This study aimed to analyse how two factors, that is, presentation methods and concept maps, interact with cognitive load and learning…

  8. The Effect of Flipped Teaching Combined with Modified Team-Based Learning on Student Performance in Physiology

    Science.gov (United States)

    Gopalan, Chaya; Klann, Megan C.

    2017-01-01

    Flipped classroom is a hybrid educational format that shifts guided teaching out of class, thus allowing class time for student-centered learning. Although this innovative teaching format is gaining attention, there is limited evidence on the effectiveness of flipped teaching on student performance. We compared student performance and student…

  9. An investigation of Inventory Differences

    International Nuclear Information System (INIS)

    Harvel, C.

    1993-01-01

    The derivation of applicable Limits of Error for Inventory Differences (LEIDs) has been a long-term challenge for some material storage tanks at the Savannah River Site. Several investigations have been unsuccessful in producing usable estimates of the LEIDs. An investigation conducted in November of 1991 revealed some significant inventory characteristics. The corrective action involved the implementation of a multi-case LEID based on historical information and a correction in the use of the tank calibration charts for two storage tanks

  10. Denmark's National Inventory Report 2009

    DEFF Research Database (Denmark)

    Nielsen, Ole-Kenneth; Lyck, Erik; Mikkelsen, Mette Hjorth

    This report is Denmark's National Inventory Report 2009. The report contains information on Denmark's emission inventories for all years' from 1990 to 2007 for CO2, CH4, N2O, HFCs, PFCs and SF6, NOx, CO, NMVOC, SO2. The report documents the methodology as well as presents activity data and emissi...... factors for energy, industrial processes, sovent and other product use, agriculture, LULUCF (Land-Use, Land-Use Change and Forestry) and waste....

  11. A combination of traditional learning and e-learning can be more effective on radiological interpretation skills in medical students: a pre- and post-intervention study.

    Science.gov (United States)

    Salajegheh, Ali; Jahangiri, Alborz; Dolan-Evans, Elliot; Pakneshan, Sahar

    2016-02-03

    The ability to interpret an X-Ray is a vital skill for graduating medical students which guides clinicians towards accurate diagnosis and treatment of the patient. However, research has suggested that radiological interpretation skills are less than satisfactory in not only medical students, but also in residents and consultants. This study investigated the effectiveness of e-learning for the development of X-ray interpretation skills in pre-clinical medical students. Competencies in clinical X-Ray interpretation were assessed by comparison of pre- and post-intervention scores and one year follow up assessment, where the e-learning course was the 'intervention'. Our results demonstrate improved knowledge and skills in X-ray interpretation in students. Assessment of the post training students showed significantly higher scores than the scores of control group of students undertaking the same assessment at the same time. The development of the Internet and advances in multimedia technologies has paved the way for computer-assisted education. As more rural clinical schools are established the electronic delivery of radiology teaching through websites will become a necessity. The use of e-learning to deliver radiology tuition to medical students represents an exciting alternative and is an effective method of developing competency in radiological interpretation for medical students.

  12. Approximate ideal multi-objective solution Q(λ) learning for optimal carbon-energy combined-flow in multi-energy power systems

    International Nuclear Information System (INIS)

    Zhang, Xiaoshun; Yu, Tao; Yang, Bo; Zheng, Limin; Huang, Linni

    2015-01-01

    Highlights: • A novel optimal carbon-energy combined-flow (OCECF) model is firstly established. • A novel approximate ideal multi-objective solution Q(λ) learning is designed. • The proposed algorithm has a high convergence stability and reliability. • The proposed algorithm can be applied for OCECF in a large-scale power grid. - Abstract: This paper proposes a novel approximate ideal multi-objective solution Q(λ) learning for optimal carbon-energy combined-flow in multi-energy power systems. The carbon emissions, fuel cost, active power loss, voltage deviation and carbon emission loss are chosen as the optimization objectives, which are simultaneously optimized by five different Q-value matrices. The dynamic optimal weight of each objective is calculated online from the entire Q-value matrices such that the greedy action policy can be obtained. Case studies are carried out to evaluate the optimization performance for carbon-energy combined-flow in an IEEE 118-bus system and the regional power grid of southern China.

  13. Multi-Kernel Learning with Dartel Improves Combined MRI-PET Classification of Alzheimer’s Disease in AIBL Data: Group and Individual Analyses

    Directory of Open Access Journals (Sweden)

    Vahab Youssofzadeh

    2017-07-01

    Full Text Available Magnetic resonance imaging (MRI and positron emission tomography (PET are neuroimaging modalities typically used for evaluating brain changes in Alzheimer’s disease (AD. Due to their complementary nature, their combination can provide more accurate AD diagnosis or prognosis. In this work, we apply a multi-modal imaging machine-learning framework to enhance AD classification and prediction of diagnosis of subject-matched gray matter MRI and Pittsburgh compound B (PiB-PET data related to 58 AD, 108 mild cognitive impairment (MCI and 120 healthy elderly (HE subjects from the Australian imaging, biomarkers and lifestyle (AIBL dataset. Specifically, we combined a Dartel algorithm to enhance anatomical registration with multi-kernel learning (MKL technique, yielding an average of >95% accuracy for three binary classification problems: AD-vs.-HE, MCI-vs.-HE and AD-vs.-MCI, a considerable improvement from individual modality approach. Consistent with t-contrasts, the MKL weight maps revealed known brain regions associated with AD, i.e., (parahippocampus, posterior cingulate cortex and bilateral temporal gyrus. Importantly, MKL regression analysis provided excellent predictions of diagnosis of individuals by r2 = 0.86. In addition, we found significant correlations between the MKL classification and delayed memory recall scores with r2 = 0.62 (p < 0.01. Interestingly, outliers in the regression model for diagnosis were mainly converter samples with a higher likelihood of converting to the inclined diagnostic category. Overall, our work demonstrates the successful application of MKL with Dartel on combined neuromarkers from different neuroimaging modalities in the AIBL data. This lends further support in favor of machine learning approach in improving the diagnosis and risk prediction of AD.

  14. The combination of ethanol with mephedrone increases the signs of neurotoxicity and impairs neurogenesis and learning in adolescent CD-1 mice

    International Nuclear Information System (INIS)

    Ciudad-Roberts, Andrés; Duart-Castells, Leticia; Camarasa, Jorge; Pubill, David; Escubedo, Elena

    2016-01-01

    A new family of psychostimulants, under the name of cathinones, has broken into the market in the last decade. In light of the fact that around 95% of cathinone consumers have been reported to combine them with alcoholic drinks, we sought to study the consequences of the concomitant administration of ethanol on mephedrone -induced neurotoxicity. Adolescent male Swiss-CD1 mice were administered four times in one day, every 2 h, with saline, mephedrone (25 mg/kg), ethanol (2; 1.5; 1.5; 1 g/kg) and their combination at a room temperature of 26 ± 2 °C. The combination with ethanol impaired mephedrone-induced decreases in dopamine transporter and tyrosine hydroxylase in the frontal cortex; and in serotonin transporter and tryptophan hydroxylase in the hippocampus by approximately 2-fold, 7 days post-treatment. Furthermore, these decreases correlated with a 2-fold increase in lipid peroxidation, measured as concentration of malondialdehyde (MDA), 24 h post-treatment, and were accompanied by changes in oxidative stress-related enzymes. Ethanol also notably potentiated mephedrone-induced negative effects on learning and memory, as well as hippocampal neurogenesis, measured through the Morris water maze (MWM) and 5-bromo-2′-deoxyuridine staining, respectively. These results are of special significance, since alcohol is widely co-abused with amphetamine derivatives such as mephedrone, especially during adolescence, a crucial stage in brain maturation. Given that the hippocampus is greatly involved in learning and memory processes, normal brain development in young adults could be affected with permanent behavioral consequences after this type of drug co-abuse. - Highlights: • Mice were administered a binge regimen of mephedrone plus/minus ethanol. • Ethanol exacerbated mephedrone-induced changes in 5-HT and DA function markers. • Neurochemical alterations were accompanied by an increase in oxidative stress. • Ethanol potentiated mephedrone-induced learning

  15. The combination of ethanol with mephedrone increases the signs of neurotoxicity and impairs neurogenesis and learning in adolescent CD-1 mice

    Energy Technology Data Exchange (ETDEWEB)

    Ciudad-Roberts, Andrés; Duart-Castells, Leticia; Camarasa, Jorge; Pubill, David, E-mail: d.pubill@ub.edu; Escubedo, Elena

    2016-02-15

    A new family of psychostimulants, under the name of cathinones, has broken into the market in the last decade. In light of the fact that around 95% of cathinone consumers have been reported to combine them with alcoholic drinks, we sought to study the consequences of the concomitant administration of ethanol on mephedrone -induced neurotoxicity. Adolescent male Swiss-CD1 mice were administered four times in one day, every 2 h, with saline, mephedrone (25 mg/kg), ethanol (2; 1.5; 1.5; 1 g/kg) and their combination at a room temperature of 26 ± 2 °C. The combination with ethanol impaired mephedrone-induced decreases in dopamine transporter and tyrosine hydroxylase in the frontal cortex; and in serotonin transporter and tryptophan hydroxylase in the hippocampus by approximately 2-fold, 7 days post-treatment. Furthermore, these decreases correlated with a 2-fold increase in lipid peroxidation, measured as concentration of malondialdehyde (MDA), 24 h post-treatment, and were accompanied by changes in oxidative stress-related enzymes. Ethanol also notably potentiated mephedrone-induced negative effects on learning and memory, as well as hippocampal neurogenesis, measured through the Morris water maze (MWM) and 5-bromo-2′-deoxyuridine staining, respectively. These results are of special significance, since alcohol is widely co-abused with amphetamine derivatives such as mephedrone, especially during adolescence, a crucial stage in brain maturation. Given that the hippocampus is greatly involved in learning and memory processes, normal brain development in young adults could be affected with permanent behavioral consequences after this type of drug co-abuse. - Highlights: • Mice were administered a binge regimen of mephedrone plus/minus ethanol. • Ethanol exacerbated mephedrone-induced changes in 5-HT and DA function markers. • Neurochemical alterations were accompanied by an increase in oxidative stress. • Ethanol potentiated mephedrone-induced learning

  16. Combining deep learning and coherent anti-Stokes Raman scattering imaging for automated differential diagnosis of lung cancer

    Science.gov (United States)

    Weng, Sheng; Xu, Xiaoyun; Li, Jiasong; Wong, Stephen T. C.

    2017-10-01

    Lung cancer is the most prevalent type of cancer and the leading cause of cancer-related deaths worldwide. Coherent anti-Stokes Raman scattering (CARS) is capable of providing cellular-level images and resolving pathologically related features on human lung tissues. However, conventional means of analyzing CARS images requires extensive image processing, feature engineering, and human intervention. This study demonstrates the feasibility of applying a deep learning algorithm to automatically differentiate normal and cancerous lung tissue images acquired by CARS. We leverage the features learned by pretrained deep neural networks and retrain the model using CARS images as the input. We achieve 89.2% accuracy in classifying normal, small-cell carcinoma, adenocarcinoma, and squamous cell carcinoma lung images. This computational method is a step toward on-the-spot diagnosis of lung cancer and can be further strengthened by the efforts aimed at miniaturizing the CARS technique for fiber-based microendoscopic imaging.

  17. Development of e-module combining science process skills and dynamics motion material to increasing critical thinking skills and improve student learning motivation senior high school

    Directory of Open Access Journals (Sweden)

    Fengky Adie Perdana

    2017-02-01

    Full Text Available Learning media is one of the most components in the teaching and learning process. This research was conducted to design and develop the electronic modules combining science process skills and dynamics motion content for increasing critical thinking skills and improve student learning motivation for senior high school. The Methods used in this research is Research and Development (R&D. Model research and development using a research 4D Thiagarajan model. Physics module was developed using science process skills approach: observing, formulating the problem, formulating a hypothesis, identify variables, conduct experiments, analyse the data, summarise and communicate. The results showed that: 1 the electronics module has been developed by integrating the science process skills for enhancing critical thinking skills and student motivation. 2 Electronic Module Physics-based science process skills meet the criteria very well, judging from the results of validation content, validation media, validation of peer education and practitioners, with an average value of 3.80 is greater than the minimum eligibility 3.78. 3 effectiveness the modules of science process skills got N-gain value obtained from a large trial in grade samples of 0.67 and 0.59 in the control group were categorised as moderate. 4 Implementation of electronic modules Physics-based science process skills is considered an effective to enhance the students' motivation. Statistical analysis showed a significance value of 0.027 is lower than the significance level α = 0.05, this means that there are significant differences between learning motivation grade sample and the control class. As a result of analysis data obtained from the research, it was seen that the students' motivation that uses Physics module based science process skills better than conventional learning.

  18. Learning style versus time spent studying and career choice: Which is associated with success in a combined undergraduate anatomy and physiology course?

    Science.gov (United States)

    Farkas, Gary J; Mazurek, Ewa; Marone, Jane R

    2016-01-01

    The VARK learning style is a pedagogical focus in health care education. This study examines relationships of course performance vs. VARK learning preference, study time, and career plan among students enrolled in an undergraduate anatomy and physiology course at a large urban university. Students (n = 492) from the fall semester course completed a survey consisting of the VARK questionnaire, gender, academic year, career plans, and estimated hours spent per week in combined classroom and study time. Seventy-eight percent of students reported spending 15 or fewer hours per week studying. Study time and overall course score correlated significantly for the class as a whole (r = 0.111, P = 0.013), which was mainly due to lecture (r = 0.118, P = 0.009) performance. No significant differences were found among students grouped by learning styles. When corrected for academic year, overall course scores (mean ± SEM) for students planning to enter dentistry, medicine, optometry or pharmacy (79.89 ± 0.88%) were significantly higher than those of students planning to enter physical or occupational therapies (74.53 ± 1.15%; P = 0.033), as well as nurse/physician assistant programs (73.60 ± 1.3%; P = 0.040). Time spent studying was not significantly associated with either learning style or career choice. Our findings suggest that specific career goals and study time, not learning preferences, are associated with better performance among a diverse group of students in an undergraduate anatomy and physiology course. However, the extent to which prior academic preparation, cultural norms, and socioeconomic factors influenced these results requires further investigation. © 2015 American Association of Anatomists.

  19. The combining of multiple hemispheric resources in learning-disabled and skilled readers' recall of words: a test of three information-processing models.

    Science.gov (United States)

    Swanson, H L

    1987-01-01

    Three theoretical models (additive, independence, maximum rule) that characterize and predict the influence of independent hemispheric resources on learning-disabled and skilled readers' simultaneous processing were tested. Predictions related to word recall performance during simultaneous encoding conditions (dichotic listening task) were made from unilateral (dichotic listening task) presentations. The maximum rule model best characterized both ability groups in that simultaneous encoding produced no better recall than unilateral presentations. While the results support the hypothesis that both ability groups use similar processes in the combining of hemispheric resources (i.e., weak/dominant processing), ability group differences do occur in the coordination of such resources.

  20. Teaching for Different Learning Styles.

    Science.gov (United States)

    Cropper, Carolyn

    1994-01-01

    This study examined learning styles in 137 high ability fourth-grade students. All students were administered two learning styles inventories. Characteristics of students with the following learning styles are summarized: auditory language, visual language, auditory numerical, visual numerical, tactile concrete, individual learning, group…

  1. 10 CFR 39.37 - Physical inventory.

    Science.gov (United States)

    2010-01-01

    ... 10 Energy 1 2010-01-01 2010-01-01 false Physical inventory. 39.37 Section 39.37 Energy NUCLEAR... inventory. Each licensee shall conduct a semi-annual physical inventory to account for all licensed material received and possessed under the license. The licensee shall retain records of the inventory for 3 years...

  2. 27 CFR 20.170 - Physical inventory.

    Science.gov (United States)

    2010-04-01

    ... 27 Alcohol, Tobacco Products and Firearms 1 2010-04-01 2010-04-01 false Physical inventory. 20.170... Users of Specially Denatured Spirits Inventory and Records § 20.170 Physical inventory. Once in each... physical inventory of each formula of new and recovered specially denatured spirits. (Approved by the...

  3. Projecting Timber Inventory at the Product Level

    Science.gov (United States)

    Lawrence Teeter; Xiaoping Zhou

    1999-01-01

    Current timber inventory projections generally lack information on inventory by product classes. Most models available for inventory projection and linked to supply analyses are limited to projecting aggregate softwood and hardwood. The research presented describes a methodology for distributing the volume on each FIA (USDA Forest Service Forest Inventory and Analysis...

  4. Base-age invariance and inventory projections

    Science.gov (United States)

    C. J. Cieszewski; R. L. Bailey; B. E. Borders; G. H. Brister; B. D. Shiver

    2000-01-01

    One of the most important functions of forest inventory is to facilitate management decisions towards forest sustainability based on inventory projections into the future. Therefore, most forest inventories are used for predicting future states of the forests, in modern forestry the most common methods used in inventory projections are based on implicit functions...

  5. 27 CFR 40.201 - Inventories.

    Science.gov (United States)

    2010-04-01

    ... PROCESSED TOBACCO Operations by Manufacturers of Tobacco Products Inventories and Reports § 40.201 Inventories. Every manufacturer of tobacco products shall make true and accurate inventories on Form 5210.9... 27 Alcohol, Tobacco Products and Firearms 2 2010-04-01 2010-04-01 false Inventories. 40.201...

  6. Optimal ABC inventory classification using interval programming

    NARCIS (Netherlands)

    Rezaei, J.; Salimi, N.

    2015-01-01

    Inventory classification is one of the most important activities in inventory management, whereby inventories are classified into three or more classes. Several inventory classifications have been proposed in the literature, almost all of which have two main shortcomings in common. That is, the

  7. Annual Danish emissions inventory report to UNECE. Inventory 1990 - 2002

    Energy Technology Data Exchange (ETDEWEB)

    Illerup, J.B.; Nielsen, M.; Winther, M.; Hjort Mikkelsen, M.; Lyck, E.; Hoffmann, L.; Fauser, P.

    2004-05-01

    This report is a documentation report on the emission inventories for Denmark as reported to the UNECE Secretariat under the Convention on Long Range Transboundary Air Pollution due by 15 February 2004. The report contains information on Denmark's emission inventories regarding emissions of (1) SOx for the years 1980-2002, (2) NOx, CO, NMVOC and NH{sub 3} for the years 1985-2002; (3) Particulate matter: TSP, PM10, PM2.5 for the years 2000-2002, (4) Heavy Metals: Pb, Cd, Hg, As, Cr, Cu, Ni, Se and Zn for the years 1990-2002, and (5) Polyaromatic hydrocarbons (PAH): Benzo(a)pyrene, benzo(b)fluoranthene, benzo(k)fluoranthene and indeno(1,2,3-cd)pyrene for the years 1990-2002. Furthermore, the report contains information on background data for emissions inventory. (au)

  8. Annual Danish emissions inventory report to UNECE. Inventory 1990 - 2002

    Energy Technology Data Exchange (ETDEWEB)

    Illerup, J B; Nielsen, M; Winther, M; Hjort Mikkelsen, M; Lyck, E; Hoffmann, L; Fauser, P

    2004-05-01

    This report is a documentation report on the emission inventories for Denmark as reported to the UNECE Secretariat under the Convention on Long Range Transboundary Air Pollution due by 15 February 2004. The report contains information on Denmark's emission inventories regarding emissions of (1) SOx for the years 1980-2002, (2) NOx, CO, NMVOC and NH{sub 3} for the years 1985-2002; (3) Particulate matter: TSP, PM10, PM2.5 for the years 2000-2002, (4) Heavy Metals: Pb, Cd, Hg, As, Cr, Cu, Ni, Se and Zn for the years 1990-2002, and (5) Polyaromatic hydrocarbons (PAH): Benzo(a)pyrene, benzo(b)fluoranthene, benzo(k)fluoranthene and indeno(1,2,3-cd)pyrene for the years 1990-2002. Furthermore, the report contains information on background data for emissions inventory. (au)

  9. Making Theory Relevant: The Gender Attitude and Belief Inventory

    Science.gov (United States)

    McCabe, Janice

    2013-01-01

    This article describes and evaluates the Gender Attitude and Belief Inventory (GABI), a teaching tool designed to aid students in (a) realizing how sociological theory links to their personal beliefs and (b) exploring any combination of 11 frequently used theoretical perspectives on gender, including both conservative theories (physiological,…

  10. Learning

    Directory of Open Access Journals (Sweden)

    Mohsen Laabidi

    2014-01-01

    Full Text Available Nowadays learning technologies transformed educational systems with impressive progress of Information and Communication Technologies (ICT. Furthermore, when these technologies are available, affordable and accessible, they represent more than a transformation for people with disabilities. They represent real opportunities with access to an inclusive education and help to overcome the obstacles they met in classical educational systems. In this paper, we will cover basic concepts of e-accessibility, universal design and assistive technologies, with a special focus on accessible e-learning systems. Then, we will present recent research works conducted in our research Laboratory LaTICE toward the development of an accessible online learning environment for persons with disabilities from the design and specification step to the implementation. We will present, in particular, the accessible version “MoodleAcc+” of the well known e-learning platform Moodle as well as new elaborated generic models and a range of tools for authoring and evaluating accessible educational content.

  11. Combining macula clinical signs and patient characteristics for age-related macular degeneration diagnosis: a machine learning approach.

    Science.gov (United States)

    Fraccaro, Paolo; Nicolo, Massimo; Bonetto, Monica; Giacomini, Mauro; Weller, Peter; Traverso, Carlo Enrico; Prosperi, Mattia; OSullivan, Dympna

    2015-01-27

    To investigate machine learning methods, ranging from simpler interpretable techniques to complex (non-linear) "black-box" approaches, for automated diagnosis of Age-related Macular Degeneration (AMD). Data from healthy subjects and patients diagnosed with AMD or other retinal diseases were collected during routine visits via an Electronic Health Record (EHR) system. Patients' attributes included demographics and, for each eye, presence/absence of major AMD-related clinical signs (soft drusen, retinal pigment epitelium, defects/pigment mottling, depigmentation area, subretinal haemorrhage, subretinal fluid, macula thickness, macular scar, subretinal fibrosis). Interpretable techniques known as white box methods including logistic regression and decision trees as well as less interpreitable techniques known as black box methods, such as support vector machines (SVM), random forests and AdaBoost, were used to develop models (trained and validated on unseen data) to diagnose AMD. The gold standard was confirmed diagnosis of AMD by physicians. Sensitivity, specificity and area under the receiver operating characteristic (AUC) were used to assess performance. Study population included 487 patients (912 eyes). In terms of AUC, random forests, logistic regression and adaboost showed a mean performance of (0.92), followed by SVM and decision trees (0.90). All machine learning models identified soft drusen and age as the most discriminating variables in clinicians' decision pathways to diagnose AMD. Both black-box and white box methods performed well in identifying diagnoses of AMD and their decision pathways. Machine learning models developed through the proposed approach, relying on clinical signs identified by retinal specialists, could be embedded into EHR to provide physicians with real time (interpretable) support.

  12. A combined deep-learning and deformable-model approach to fully automatic segmentation of the left ventricle in cardiac MRI.

    Science.gov (United States)

    Avendi, M R; Kheradvar, Arash; Jafarkhani, Hamid

    2016-05-01

    Segmentation of the left ventricle (LV) from cardiac magnetic resonance imaging (MRI) datasets is an essential step for calculation of clinical indices such as ventricular volume and ejection fraction. In this work, we employ deep learning algorithms combined with deformable models to develop and evaluate a fully automatic LV segmentation tool from short-axis cardiac MRI datasets. The method employs deep learning algorithms to learn the segmentation task from the ground true data. Convolutional networks are employed to automatically detect the LV chamber in MRI dataset. Stacked autoencoders are used to infer the LV shape. The inferred shape is incorporated into deformable models to improve the accuracy and robustness of the segmentation. We validated our method using 45 cardiac MR datasets from the MICCAI 2009 LV segmentation challenge and showed that it outperforms the state-of-the art methods. Excellent agreement with the ground truth was achieved. Validation metrics, percentage of good contours, Dice metric, average perpendicular distance and conformity, were computed as 96.69%, 0.94, 1.81 mm and 0.86, versus those of 79.2-95.62%, 0.87-0.9, 1.76-2.97 mm and 0.67-0.78, obtained by other methods, respectively. Copyright © 2016 Elsevier B.V. All rights reserved.

  13. Effects of ginsenoside of stem and leaf combined with choline on learning and memory ability of rat models with Alzheimer diseases

    Institute of Scientific and Technical Information of China (English)

    Xiaomin Zhao; Xianglin Xie; Zuoli Xia; Yunsheng Gao; Yuyun Zhu; Hongxia Gu

    2006-01-01

    BACKGROUND: Central adrenergic nerve and 5-serotonergic nerve can influence central cholinergic nerve on learning and memory and make easy for study; however, ginsenoside of stem and leaf (GSL) can improve functions of central adrenergic nerve; moreover, 5-serotonergic nerve and the combination with choline can produce synergistic effect and enhance learning and memory ability so as to improve learning and memory disorder of patients with Alzheimer disease (AD).OBJECTIVE: To observe the effects of GSL combining with choline on learning and memory of AD model rats.DESIGN: Randomized grouping design and controlled animal study.SETTING: Department of Pharmacology, Taishan Medical College.MATERIALS: The experiment was carried out in the Pharmacological Department of Medical College of Jilin University from October 1996 to January 1997. Forty healthy male Wistar rats of clean grade were randomly divided into 5 groups, including sham-injury group, model group, GSL group, choline group and combination group, with 8 rats in each group. Main medications: GSL with the volume more than 92.8% was provided by Department of Chemistry, Norman Bethune Medical College of Jilin University. Panaxatriol, the main component, was detected with thin layer scanning technique and regarded as the index of GSL quality [(55±1)%, CV= 2%, n= 5]. Choline was provided by the Third Shanghai Laboratory Factory.METHODS: 150 nmol quinolinic acid was used to damage bilateral Meynert basal nuclei of adult rats so as to establish AD models. Rats in GSL, choline and combination groups were intragastric administrated with 400 mg/kg GSL, 200 mg/kg choline (20 mL/kg), and both respectively last for 17 days starting from two days 400 mg/kg GSL, 200 mg/kg choline (20 mL/kg), and both respectively last for 17 days starting from two days before operation. Rats in sham-injury group and model group were perfused with the same volume of distilled jumped up safe platform when they were shocked with 36 V

  14. The combined effects of developmental lead and ethanol exposure on hippocampus dependent spatial learning and memory in rats: Role of oxidative stress.

    Science.gov (United States)

    Soleimani, Elham; Goudarzi, Iran; Abrari, Kataneh; Lashkarbolouki, Taghi

    2016-10-01

    Either developmental lead or ethanol exposure can impair learning and memory via induction of oxidative stress, which results in neuronal damage. we examined the effect of combined exposure with lead and ethanol on spatial learning and memory in offspring and oxidative stress in hippocampus. Rats were exposed to lead (0.2% in drinking water) or ethanol (4 g/kg) either individually or in combination in 5th day gestation through weaning. On postnatal days (PD) 30, rats were trained with six trials per day for 6 consecutive days in the water maze. On day 37, a probe test was done. Also, oxidative stress markers in the hippocampus were also evaluated. Results demonstrated that lead + ethanol co-exposed rats exhibited higher escape latency during training trials and reduced time spent in target quadrant, higher escape location latency and average proximity in probe trial test. There was significant decrease in superoxide dismutase (SOD), catalase (CAT), glutathione peroxidase (GPx) activities and increase of malondialdehyde (MDA) levels in hippocampus of animals co-exposed to lead and ethanol compared with their individual exposures. We suggest that maternal consumption of ethanol during lead exposure has pronounced detrimental effects on memory, which may be mediated by oxidative stress. Copyright © 2016. Published by Elsevier Ltd.

  15. Effect of an EBM course in combination with case method learning sessions: an RCT on professional performance, job satisfaction, and self-efficacy of occupational physicians.

    Science.gov (United States)

    Hugenholtz, Nathalie I R; Schaafsma, Frederieke G; Nieuwenhuijsen, Karen; van Dijk, Frank J H

    2008-10-01

    An intervention existing of an evidence-based medicine (EBM) course in combination with case method learning sessions (CMLSs) was designed to enhance the professional performance, self-efficacy and job satisfaction of occupational physicians. A cluster randomized controlled trial was set up and data were collected through questionnaires at baseline (T0), directly after the intervention (T1) and 7 months after baseline (T2). The data of the intervention group [T0 (n = 49), T1 (n = 31), T2 (n = 29)] and control group [T0 (n = 49), T1 (n = 28), T2 (n = 28)] were analysed in mixed model analyses. Mean scores of the perceived value of the CMLS were calculated in the intervention group. The overall effect of the intervention over time comparing the intervention with the control group was statistically significant for professional performance (p Job satisfaction and self-efficacy changes were small and not statistically significant between the groups. The perceived value of the CMLS to gain new insights and to improve the quality of their performance increased with the number of sessions followed. An EBM course in combination with case method learning sessions is perceived as valuable and offers evidence to enhance the professional performance of occupational physicians. However, it does not seem to influence their self-efficacy and job satisfaction.

  16. Fuzzy Continuous Review Inventory Model using ABC Multi-Criteria Classification Approach: A Single Case Study

    Directory of Open Access Journals (Sweden)

    Meriastuti - Ginting

    2015-07-01

    Full Text Available Abstract. Inventory is considered as the most expensive, yet important,to any companies. It representsapproximately 50% of the total investment. Inventory cost has become one of the majorcontributorsto inefficiency, therefore it should be managed effectively. This study aims to propose an alternative inventory model,  by using ABC multi-criteria classification approach to minimize total cost. By combining FANP (Fuzzy Analytical Network Process and TOPSIS (Technique of Order Preferences by Similarity to the Ideal Solution, the ABC multi-criteria classification approach identified 12 items of 69 inventory items as “outstanding important class” that contributed to 80% total inventory cost. This finding  is then used as the basis to determine the proposed continuous review inventory model.This study found that by using fuzzy trapezoidal cost, the inventory  turnover ratio can be increased, and inventory cost can be decreased by 78% for each item in “class A” inventory.Keywords:ABC multi-criteria classification, FANP-TOPSIS, continuous review inventory model lead-time demand distribution, trapezoidal fuzzy number 

  17. Automatical and accurate segmentation of cerebral tissues in fMRI dataset with combination of image processing and deep learning

    Science.gov (United States)

    Kong, Zhenglun; Luo, Junyi; Xu, Shengpu; Li, Ting

    2018-02-01

    Image segmentation plays an important role in medical science. One application is multimodality imaging, especially the fusion of structural imaging with functional imaging, which includes CT, MRI and new types of imaging technology such as optical imaging to obtain functional images. The fusion process require precisely extracted structural information, in order to register the image to it. Here we used image enhancement, morphometry methods to extract the accurate contours of different tissues such as skull, cerebrospinal fluid (CSF), grey matter (GM) and white matter (WM) on 5 fMRI head image datasets. Then we utilized convolutional neural network to realize automatic segmentation of images in deep learning way. Such approach greatly reduced the processing time compared to manual and semi-automatic segmentation and is of great importance in improving speed and accuracy as more and more samples being learned. The contours of the borders of different tissues on all images were accurately extracted and 3D visualized. This can be used in low-level light therapy and optical simulation software such as MCVM. We obtained a precise three-dimensional distribution of brain, which offered doctors and researchers quantitative volume data and detailed morphological characterization for personal precise medicine of Cerebral atrophy/expansion. We hope this technique can bring convenience to visualization medical and personalized medicine.

  18. Application of Response Surface Methodology in Optimizing a Three Echelon Inventory System

    Directory of Open Access Journals (Sweden)

    Seyed Hossein Razavi Hajiagha

    2014-01-01

    Full Text Available Inventory control is an important subject in supply chain management. In this paper, a three echelon production, distribution, inventory system composed of one producer, two wholesalers and a set of retailers has been considered. Costumers' demands follow a compound Poisson process and the inventory policy is a kind of continuous review (R, Q. In this paper, regarding the standard cost structure in an inventory model, the cost function of system has been approximated using Response Surface Methodology as a combination of designed experiments, simulation, regression analysis and optimization. The proposed methodology in this paper can be applied as a novel method in optimization of inventory policy of supply chains. Also, the joint optimization of inventory parameters, including reorder point and batch order size, is another advantage of the proposed methodology.

  19. Inventory difference analysis at Los Alamos Plutonium Facility

    International Nuclear Information System (INIS)

    Zardecki, A.; Armstrong, J.M.; Longmire, V.; Strittmatter, R.B.

    1997-01-01

    The authors have developed a prototype computer program that reads directly the inventory entries from a Microsoft Access data base. Based on historical data, the program then displays temporal trends and constructs a library of rules that encapsulates the system behavior. The following analysis of inventory data is illustrated by using a combination of realistic and simulated facility examples. Potential payoffs of this methodology include a reduction in time and resources needed to perform statistical tests and broad applicability to Department of Energy needs--for example, treaty verification

  20. Classifying injury narratives of large administrative databases for surveillance-A practical approach combining machine learning ensembles and human review.

    Science.gov (United States)

    Marucci-Wellman, Helen R; Corns, Helen L; Lehto, Mark R

    2017-01-01

    Injury narratives are now available real time and include useful information for injury surveillance and prevention. However, manual classification of the cause or events leading to injury found in large batches of narratives, such as workers compensation claims databases, can be prohibitive. In this study we compare the utility of four machine learning algorithms (Naïve Bayes, Single word and Bi-gram models, Support Vector Machine and Logistic Regression) for classifying narratives into Bureau of Labor Statistics Occupational Injury and Illness event leading to injury classifications for a large workers compensation database. These algorithms are known to do well classifying narrative text and are fairly easy to implement with off-the-shelf software packages such as Python. We propose human-machine learning ensemble approaches which maximize the power and accuracy of the algorithms for machine-assigned codes and allow for strategic filtering of rare, emerging or ambiguous narratives for manual review. We compare human-machine approaches based on filtering on the prediction strength of the classifier vs. agreement between algorithms. Regularized Logistic Regression (LR) was the best performing algorithm alone. Using this algorithm and filtering out the bottom 30% of predictions for manual review resulted in high accuracy (overall sensitivity/positive predictive value of 0.89) of the final machine-human coded dataset. The best pairings of algorithms included Naïve Bayes with Support Vector Machine whereby the triple ensemble NB SW =NB BI-GRAM =SVM had very high performance (0.93 overall sensitivity/positive predictive value and high accuracy (i.e. high sensitivity and positive predictive values)) across both large and small categories leaving 41% of the narratives for manual review. Integrating LR into this ensemble mix improved performance only slightly. For large administrative datasets we propose incorporation of methods based on human-machine pairings such as

  1. Balancing flexibility and inventory in repair inventory systems

    NARCIS (Netherlands)

    Haas, de H.F.M.; Martin, H.H.

    1995-01-01

    In repair inventory systems, failed units are exchanged for serviceable units upon failure. The probability that serviceable units are available to support the exchange process can be used as a measure for the performance of the system. This measure is commonly called the expected fill rate. The

  2. Inventory of existing heat pump projects and the use of solar energy for heat pumps in the Dutch house construction sector

    International Nuclear Information System (INIS)

    1997-01-01

    The aim of the title inventory is to learn from the experiences with heat pump projects in the Netherlands. Descriptions are given of practical experiences with heat pump applications in the last 15 years in the housing sector. Possible and feasible heat pump system concepts are analyzed and energy balances and energy consumption are calculated. Special attention is paid to the use of solar energy in combination with electric (compression) heat pumps. One of the most important bottlenecks is the method and availability of heat extraction: the choice for the different options is determined by investment costs, permission, regulations, and local conditions. 14 refs., 4 appendices

  3. Evaluating Bay Area Methane Emission Inventory

    Energy Technology Data Exchange (ETDEWEB)

    Fischer, Marc [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Jeong, Seongeun [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)

    2016-03-01

    As a regulatory agency, evaluating and improving estimates of methane (CH4) emissions from the San Francisco Bay Area is an area of interest to the Bay Area Air Quality Management District (BAAQMD). Currently, regional, state, and federal agencies generally estimate methane emissions using bottom-up inventory methods that rely on a combination of activity data, emission factors, biogeochemical models and other information. Recent atmospheric top-down measurement estimates of methane emissions for the US as a whole (e.g., Miller et al., 2013) and in California (e.g., Jeong et al., 2013; Peischl et al., 2013) have shown inventories underestimate total methane emissions by ~ 50% in many areas of California, including the SF Bay Area (Fairley and Fischer, 2015). The goal of this research is to provide information to help improve methane emission estimates for the San Francisco Bay Area. The research effort builds upon our previous work that produced methane emission maps for each of the major source sectors as part of the California Greenhouse Gas Emissions Measurement (CALGEM) project (http://calgem.lbl.gov/prior_emission.html; Jeong et al., 2012; Jeong et al., 2013; Jeong et al., 2014). Working with BAAQMD, we evaluate the existing inventory in light of recently published literature and revise the CALGEM CH4 emission maps to provide better specificity for BAAQMD. We also suggest further research that will improve emission estimates. To accomplish the goals, we reviewed the current BAAQMD inventory, and compared its method with those from the state inventory from the California Air Resources Board (CARB), the CALGEM inventory, and recent published literature. We also updated activity data (e.g., livestock statistics) to reflect recent changes and to better represent spatial information. Then, we produced spatially explicit CH4 emission estimates on the 1-km modeling grid used by BAAQMD. We present the detailed activity data, methods and derived emission maps by sector

  4. Production planning of combined heat and power plants with regards to electricity price spikes : A machine learning approach

    OpenAIRE

    Fransson, Nathalie

    2017-01-01

    District heating systems could help manage the expected increase of volatility on the Nordic electricity market by starting a combined heat and power production plant (CHP) instead of a heat only production plant when electricity prices are expected to be high. Fortum Värme is interested in adjusting the production planning of their district heating system more towards high electricity prices and in their system there is a peak load CHP unit that could be utilised for this purpose. The econom...

  5. Insulin Combined with Glucose Improves Spatial Learning and Memory in Aluminum Chloride-Induced Dementia in Rats.

    Science.gov (United States)

    Nampoothiri, Madhavan; Ramalingayya, Grandhi Venkata; Kutty, Nampurath Gopalan; Krishnadas, Nandakumar; Rao, Chamallamudi Mallikarjuna

    2017-01-01

    Therapeutic intervention using drugs against Alzheimer disease is curative clinically. At present, there are no reports on the curative role of insulin in chronic models of dementia. We evaluated the curative role of insulin and its combination with glucose in dementia. We also investigated the impact of treatments on blood glucose to correlate with cognitive deficit. Further, we analyzed the interaction of treatments with the cholinergic system and oxidative stress in memory centers (i.e., hippocampus and frontal cortex). The antidementia activity of insulin was assessed against aluminum chloride (AlCl3)-induced dementia in rats. Behavioral parameters (Morris water maze test) along with biochemical parameters (Hippocampus and frontal cortex) such as acetylcholinesterase (AChE), catalase, and glutathione (GSH) levels were assessed to correlate cognitive function with cholinergic transmission and oxidative stress. Rats administered insulin and glucose showed improved cognitive function in the Morris water maze test. The combination corrected the diminished level of antioxidant enzymes such as catalase and GSH in the hippocampus and frontal cortex.Combined administration of insulin and glucose to aluminum-treated rats did not inhibit the aluminum action on the acetylcholinesterase enzyme. No significant changes were observed in blood glucose levels between the treatment groups.

  6. Cyberdiversity: improving the informatic value of diverse tropical arthropod inventories.

    Directory of Open Access Journals (Sweden)

    Jeremy A Miller

    Full Text Available In an era of biodiversity crisis, arthropods have great potential to inform conservation assessment and test hypotheses about community assembly. This is because their relatively narrow geographic distributions and high diversity offer high-resolution data on landscape-scale patterns of biodiversity. However, a major impediment to the more widespread application of arthropod data to a range of scientific and policy questions is the poor state of modern arthropod taxonomy, especially in the tropics. Inventories of spiders and other megadiverse arthropods from tropical forests are dominated by undescribed species. Such studies typically organize their data using morphospecies codes, which make it difficult for data from independent inventories to be compared and combined. To combat this shortcoming, we offer cyberdiversity, an online community-based approach for reconciling results of independent inventory studies where current taxonomic knowledge is incomplete. Participating scientists can upload images and DNA barcode sequences to dedicated databases and submit occurrence data and links to a web site (www.digitalSpiders.org. Taxonomic determinations can be shared with a crowdsourcing comments feature, and researchers can discover specimens of interest available for loan and request aliquots of genomic DNA extract. To demonstrate the value of the cyberdiversity framework, we reconcile data from three rapid structured inventories of spiders conducted in Vietnam with an independent inventory (Doi Inthanon, Thailand using online image libraries. Species richness and inventory completeness were assessed using non-parametric estimators. Community similarity was evaluated using a novel index based on the Jaccard replacing observed with estimated values to correct for unobserved species. We use a distance-decay framework to demonstrate a rudimentary model of landscape-scale changes in community composition that will become increasingly informative as

  7. A description of the reactor inventory module NECTAR-RICE

    International Nuclear Information System (INIS)

    Nair, S.

    1984-06-01

    This note describes the NECTAR-RICE module of the CEGB's NECTAR environmental code, which can be used to calculate the actinide and/or fission product inventories of irradiated nuclear fuel used as input to the calculation of the release source term to atmosphere for accidental releases. The range of actinide and fission product nuclides considered is large enough to permit studies to be made for virtually any irradiation history consisting of ad hoc combinations of irradiation and cooling periods. The actinide and fission product inventories are calculated for burnup periods using numerical methods best suited to this problem, while analytical solutions are used for cooling periods. The code can be used to perform a coupled actinide-fission product calculation, a solely actinide calculation or a solely fission product calculation. Output consists of inventories, activities, and γ spectra, among others. A brief description is also given of previous work in this field. (author)

  8. Diagnosis of major depressive disorder by combining multimodal information from heart rate dynamics and serum proteomics using machine-learning algorithm.

    Science.gov (United States)

    Kim, Eun Young; Lee, Min Young; Kim, Se Hyun; Ha, Kyooseob; Kim, Kwang Pyo; Ahn, Yong Min

    2017-06-02

    Major depressive disorder (MDD) is a systemic and multifactorial disorder that involves abnormalities in multiple biochemical pathways and the autonomic nervous system. This study applied a machine-learning method to classify MDD and control groups by incorporating data from serum proteomic analysis and heart rate variability (HRV) analysis for the identification of novel peripheral biomarkers. The study subjects consisted of 25 drug-free female MDD patients and 25 age- and sex-matched healthy controls. First, quantitative serum proteome profiles were analyzed by liquid chromatography-tandem mass spectrometry using pooled serum samples from 10 patients and 10 controls. Next, candidate proteins were quantified with multiple reaction monitoring (MRM) in 50 subjects. We also analyzed 22 linear and nonlinear HRV parameters in 50 subjects. Finally, we identified a combined biomarker panel consisting of proteins and HRV indexes using a support vector machine with recursive feature elimination. A separation between MDD and control groups was achieved using five parameters (apolipoprotein B, group-specific component, ceruloplasmin, RMSSD, and SampEn) at 80.1% classification accuracy. A combination of HRV and proteomic data achieved better classification accuracy. A high classification accuracy can be achieved by combining multimodal information from heart rate dynamics and serum proteomics in MDD. Our approach can be helpful for accurate clinical diagnosis of MDD. Further studies using larger, independent cohorts are needed to verify the role of these candidate biomarkers for MDD diagnosis. Copyright © 2017 Elsevier Inc. All rights reserved.

  9. Sourcing Life Cycle Inventory Data

    Science.gov (United States)

    The collection and validation of quality lifecycle inventory (LCI) data can be the most difficult and time-consuming aspect of developing a life cycle assessment (LCA). Large amounts of process and production data are needed to complete the LCI. For many studies, the LCA analyst ...

  10. Distribution method optimization : inventory flexibility

    NARCIS (Netherlands)

    Asipko, D.

    2010-01-01

    This report presents the outcome of the Logistics Design Project carried out for Nike Inc. This project has two goals: create a model to measure a flexibility aspect of the inventory usage in different Nike distribution channels, and analyze opportunities of changing the decision model of splitting

  11. Wisconsin's fourth forest inventory, 1983.

    Science.gov (United States)

    John S. Jr. Spencer; W. Brad Smith; Jerold T. Hahn; Gerhard K. Raile

    1988-01-01

    The fourth inventory of the timber resource of Wisconsin shows that growing-stock volume increased from 11.2 to 15.5 billion cubic feet between 1968 and 1983, and area of timberland increased from 14.5 to 14.8 million acres. Presented are analysis and statistics on forest area and timber volume, growth, mortality, removals, and projections.

  12. Stable isotope research pool inventory

    International Nuclear Information System (INIS)

    1980-12-01

    This report contains a listing of electromagnetically separated stable isotopes which are available for distribution within the United States for non-destructive research use from the Oak Ridge National Laboratory on a loan basis. This inventory includes all samples of stable isotopes in the Materials Research Collection and does not designate whether a sample is out on loan or in reprocessing

  13. Automated Interactive Storeroom Inventory System.

    Science.gov (United States)

    Sapp, Albert L.; Hess, Larry G.

    1989-01-01

    The inventory system designed for six storerooms in three buildings at the University of Illinois at Urbana-Champaign's School of Chemical Sciences replaced an issue-slip and transactions record system with barcode technology. Data collection error reductions have been significant, making it easier to determine stock levels and plan purchases.…

  14. The disposition to understand for oneself at university: integrating learning processes with motivation and metacognition.

    Science.gov (United States)

    Entwistle, Noel; McCune, Velda

    2013-06-01

    A re-analysis of several university-level interview studies has suggested that some students show evidence of a deep and stable approach to learning, along with other characteristics that support the approach. This combination, it was argued, could be seen to indicate a disposition to understand for oneself. To identify a group of students who showed high and consistent scores on deep approach, combined with equivalently high scores on effort and monitoring studying, and to explore these students' experiences of the teaching-learning environments they had experienced. Re-analysis of data from 1,896 students from 25 undergraduate courses taking four contrasting subject areas in eleven British universities. Inventories measuring approaches to studying were given at the beginning and the end of a semester, with the second inventory also exploring students' experiences of teaching. K-means cluster analysis was used to identify groups of students with differing patterns of response on the inventory scales, with a particular focus on students showing high, stable scores. One cluster clearly showed the characteristics expected of the disposition to understand and was also fairly stable over time. Other clusters also had deep approaches, but also showed either surface elements or lower scores on organized effort or monitoring their studying. Combining these findings with interview studies previously reported reinforces the idea of there being a disposition to understand for oneself that could be identified from an inventory scale or through further interviews. © 2013 The British Psychological Society.

  15. Combined biomass inventory in the scope of REDD (Reducing ...

    African Journals Online (AJOL)

    Daniel Plugge, Thomas Baldauf, Harifidy Rakoto Ratsimba, Gabrielle Rajoelison, Michael Köhl

    assumed to be approved at COP 16 in Mexico in December 2010. The proposed approach was developed and ... devant être approuvé à Mexico en décembre 2010 lors de la COP 16, d'autre part. Dans la mesure ...... Observations for Terrestrial Biodiversity and Ecosystems Special. Issue. Remote Sensing of Environment ...

  16. The Chandra Source Catalog 2.0: Combining Data for Processing (or How I learned 17 different words for "group")

    Science.gov (United States)

    Hain, Roger; Allen, Christopher E.; Anderson, Craig S.; Budynkiewicz, Jamie A.; Burke, Douglas; Chen, Judy C.; Civano, Francesca Maria; D'Abrusco, Raffaele; Doe, Stephen M.; Evans, Ian N.; Evans, Janet D.; Fabbiano, Giuseppina; Gibbs, Danny G., II; Glotfelty, Kenny J.; Graessle, Dale E.; Grier, John D.; Hall, Diane M.; Harbo, Peter N.; Houck, John C.; Lauer, Jennifer L.; Laurino, Omar; Lee, Nicholas P.; Martínez-Galarza, Juan Rafael; McCollough, Michael L.; McDowell, Jonathan C.; Miller, Joseph; McLaughlin, Warren; Morgan, Douglas L.; Mossman, Amy E.; Nguyen, Dan T.; Nichols, Joy S.; Nowak, Michael A.; Paxson, Charles; Plummer, David A.; Primini, Francis Anthony; Rots, Arnold H.; Siemiginowska, Aneta; Sundheim, Beth A.; Tibbetts, Michael; Van Stone, David W.; Zografou, Panagoula

    2018-01-01

    The Second Chandra Source Catalog (CSC2.0) combines data at multiple stages to improve detection efficiency, enhance source region identification, and match observations of the same celestial source taken with significantly different point spread functions on Chandra's detectors. The need to group data for different reasons at different times in processing results in a hierarchy of groups to which individual sources belong. Source data are initially identified as belonging to each Chandra observation ID and number (an "obsid"). Data from each obsid whose pointings are within sixty arcseconds of each other are reprojected to the same aspect reference coordinates and grouped into stacks. Detection is performed on all data in the same stack, and individual sources are identified. Finer source position and region data are determined by further processing sources whose photons may be commingled together, grouping such sources into bundles. Individual stacks which overlap to any extent are grouped into ensembles, and all stacks in the same ensemble are later processed together to identify master sources and determine their properties.We discuss the basis for the various methods of combining data for processing and precisely define how the groups are determined. We also investigate some of the issues related to grouping data and discuss what options exist and how groups have evolved from prior releases.This work has been supported by NASA under contract NAS 8-03060 to the Smithsonian Astrophysical Observatory for operation of the Chandra X-ray Center.

  17. Learning and instruction with computer simulations

    NARCIS (Netherlands)

    de Jong, Anthonius J.M.

    1991-01-01

    The present volume presents the results of an inventory of elements of such a computer learning environment. This inventory was conducted within a DELTA project called SIMULATE. In the project a learning environment that provides intelligent support to learners and that has a simulation as its

  18. Monitoring mangrove biomass change in Vietnam using SPOT images and an object-based approach combined with machine learning algorithms

    Science.gov (United States)

    Pham, Lien T. H.; Brabyn, Lars

    2017-06-01

    Mangrove forests are well-known for their provision of ecosystem services and capacity to reduce carbon dioxide concentrations in the atmosphere. Mapping and quantifying mangrove biomass is useful for the effective management of these forests and maximizing their ecosystem service performance. The objectives of this research were to model, map, and analyse the biomass change between 2000 and 2011 of mangrove forests in the Cangio region in Vietnam. SPOT 4 and 5 images were used in conjunction with object-based image analysis and machine learning algorithms. The study area included natural and planted mangroves of diverse species. After image preparation, three different mangrove associations were identified using two levels of image segmentation followed by a Support Vector Machine classifier and a range of spectral, texture and GIS information for classification. The overall classification accuracy for the 2000 and 2011 images were 77.1% and 82.9%, respectively. Random Forest regression algorithms were then used for modelling and mapping biomass. The model that integrated spectral, vegetation association type, texture, and vegetation indices obtained the highest accuracy (R2adj = 0.73). Among the different variables, vegetation association type was the most important variable identified by the Random Forest model. Based on the biomass maps generated from the Random Forest, total biomass in the Cangio mangrove forest increased by 820,136 tons over this period, although this change varied between the three different mangrove associations.

  19. Combining eco-efficiency and eco-effectiveness for continuous loop beverage packaging systems: learnings from the Carlsberg Circular Community

    DEFF Research Database (Denmark)

    Niero, Monia; Hauschild, Michael Zwicky; Hoffmeyer, Simon Boas

    2017-01-01

    Eco-efficiency (i.e., increasing value while reducing resource use and pollution) can with advantage be combined with eco-effectiveness (i.e., maximizing the benefits to ecological and economical systems) to address the challenges posed by the circular economy in the design of circular industrial......, the environmentally optimal beverage packaging life cycle scenario is identified, both in terms of defined use and reuse. Second, the limiting factors are identified for the continuous use of materials in multiple loops, meeting the two requirements in the C2C certification process that address the material level (i...... the most efficient and effective "upcycling" strategy for the beverage packaging, both from an environmental and an economic point of view. In the case of the aluminum cans, the main recommendation from both the LCA and C2C perspective is to ensure a system that enables can-to-can recycling....

  20. A call for a multifaceted approach to language learning motivation research: Combining complexity, humanistic, and critical perspectives

    Directory of Open Access Journals (Sweden)

    Julian Pigott

    2012-10-01

    Full Text Available In this paper I give an overview of recent developments in the L2 motivation field, in particular the movement away from quantitative, questionnaire-based methodologies toward smaller-scale qualitative studies incorporating concepts from complexity theory. While complexity theory provides useful concepts for exploring motivation in new ways, it has nothing to say about ethics, morality, ideology, politics, power or educational purpose. Furthermore, calls for its use come primarily from researchers from the quantitative tradition whose aim in importing this paradigm from the physical sciences appears to be to conceptualize and model motivation more accurately. The endeavor therefore remains a fundamentally positivist one. Rather than being embraced as a self-contained methodology, I argue that complexity theory should be used cautiously and prudently alongside methods grounded in other philosophical traditions. Possibilities abound, but here I suggest one possible multifaceted approach combining complexity theory, a humanisticconception of motivation, and a critical perspective.

  1. An Annotated Math Lab Inventory.

    Science.gov (United States)

    Schussheim, Joan Yares

    1980-01-01

    A listing of mathematics laboratory material is organized as follows: learning kits, tape programs, manipulative learning materials, publications, math games, math lab library, and an alphabetized listing of publishers and/or companies offering materials. (MP)

  2. Inventory on cleaner production education and training

    DEFF Research Database (Denmark)

    Jørgensen, Michael Søgaard; Pöyry, Sirkka; Huisingh, Donald

    Analysis and presentation of the data from an international inventory on cleaner production education and training......Analysis and presentation of the data from an international inventory on cleaner production education and training...

  3. Ottawa National Wildlife Refuge : Wildlife Inventory Plan

    Data.gov (United States)

    Department of the Interior — This Wildlife Inventory Plan for Ottawa NWR describes the inventory program’s relation to Refuge objectives and outlines the program’s policies and administration....

  4. CoC Housing Inventory Count Reports

    Data.gov (United States)

    Department of Housing and Urban Development — Continuum of Care (CoC) Homeless Assistance Programs Housing Inventory Count Reports are a snapshot of a CoC’s housing inventory, available at the national and state...

  5. Games for learning

    NARCIS (Netherlands)

    Slussareff, Michaela; Braad, Eelco; Wilkinson, Philip; Strååt, Björn; Dörner, Ralf; Göbel, Stefan; Kickmeier-Rust, Michael; Masuch, Maic; Zweig, Katharina

    This chapter discusses educational aspects and possibilities of serious games. For researchers as well as game designers we describe key learning theories to ground their work in theoretical framework. We draw on recent metareviews to offer an exhaustive inventory of known learning and affective

  6. Virtual screening approach to identifying influenza virus neuraminidase inhibitors using molecular docking combined with machine-learning-based scoring function.

    Science.gov (United States)

    Zhang, Li; Ai, Hai-Xin; Li, Shi-Meng; Qi, Meng-Yuan; Zhao, Jian; Zhao, Qi; Liu, Hong-Sheng

    2017-10-10

    In recent years, an epidemic of the highly pathogenic avian influenza H7N9 virus has persisted in China, with a high mortality rate. To develop novel anti-influenza therapies, we have constructed a machine-learning-based scoring function (RF-NA-Score) for the effective virtual screening of lead compounds targeting the viral neuraminidase (NA) protein. RF-NA-Score is more accurate than RF-Score, with a root-mean-square error of 1.46, Pearson's correlation coefficient of 0.707, and Spearman's rank correlation coefficient of 0.707 in a 5-fold cross-validation study. The performance of RF-NA-Score in a docking-based virtual screening of NA inhibitors was evaluated with a dataset containing 281 NA inhibitors and 322 noninhibitors. Compared with other docking-rescoring virtual screening strategies, rescoring with RF-NA-Score significantly improved the efficiency of virtual screening, and a strategy that averaged the scores given by RF-NA-Score, based on the binding conformations predicted with AutoDock, AutoDock Vina, and LeDock, was shown to be the best strategy. This strategy was then applied to the virtual screening of NA inhibitors in the SPECS database. The 100 selected compounds were tested in an in vitro H7N9 NA inhibition assay, and two compounds with novel scaffolds showed moderate inhibitory activities. These results indicate that RF-NA-Score improves the efficiency of virtual screening for NA inhibitors, and can be used successfully to identify new NA inhibitor scaffolds. Scoring functions specific for other drug targets could also be established with the same method.

  7. Combining deep residual neural network features with supervised machine learning algorithms to classify diverse food image datasets.

    Science.gov (United States)

    McAllister, Patrick; Zheng, Huiru; Bond, Raymond; Moorhead, Anne

    2018-04-01

    Obesity is increasing worldwide and can cause many chronic conditions such as type-2 diabetes, heart disease, sleep apnea, and some cancers. Monitoring dietary intake through food logging is a key method to maintain a healthy lifestyle to prevent and manage obesity. Computer vision methods have been applied to food logging to automate image classification for monitoring dietary intake. In this work we applied pretrained ResNet-152 and GoogleNet convolutional neural networks (CNNs), initially trained using ImageNet Large Scale Visual Recognition Challenge (ILSVRC) dataset with MatConvNet package, to extract features from food image datasets; Food 5K, Food-11, RawFooT-DB, and Food-101. Deep features were extracted from CNNs and used to train machine learning classifiers including artificial neural network (ANN), support vector machine (SVM), Random Forest, and Naive Bayes. Results show that using ResNet-152 deep features with SVM with RBF kernel can accurately detect food items with 99.4% accuracy using Food-5K validation food image dataset and 98.8% with Food-5K evaluation dataset using ANN, SVM-RBF, and Random Forest classifiers. Trained with ResNet-152 features, ANN can achieve 91.34%, 99.28% when applied to Food-11 and RawFooT-DB food image datasets respectively and SVM with RBF kernel can achieve 64.98% with Food-101 image dataset. From this research it is clear that using deep CNN features can be used efficiently for diverse food item image classification. The work presented in this research shows that pretrained ResNet-152 features provide sufficient generalisation power when applied to a range of food image classification tasks. Copyright © 2018 Elsevier Ltd. All rights reserved.

  8. Combining high-speed SVM learning with CNN feature encoding for real-time target recognition in high-definition video for ISR missions

    Science.gov (United States)

    Kroll, Christine; von der Werth, Monika; Leuck, Holger; Stahl, Christoph; Schertler, Klaus

    2017-05-01

    For Intelligence, Surveillance, Reconnaissance (ISR) missions of manned and unmanned air systems typical electrooptical payloads provide high-definition video data which has to be exploited with respect to relevant ground targets in real-time by automatic/assisted target recognition software. Airbus Defence and Space is developing required technologies for real-time sensor exploitation since years and has combined the latest advances of Deep Convolutional Neural Networks (CNN) with a proprietary high-speed Support Vector Machine (SVM) learning method into a powerful object recognition system with impressive results on relevant high-definition video scenes compared to conventional target recognition approaches. This paper describes the principal requirements for real-time target recognition in high-definition video for ISR missions and the Airbus approach of combining an invariant feature extraction using pre-trained CNNs and the high-speed training and classification ability of a novel frequency-domain SVM training method. The frequency-domain approach allows for a highly optimized implementation for General Purpose Computation on a Graphics Processing Unit (GPGPU) and also an efficient training of large training samples. The selected CNN which is pre-trained only once on domain-extrinsic data reveals a highly invariant feature extraction. This allows for a significantly reduced adaptation and training of the target recognition method for new target classes and mission scenarios. A comprehensive training and test dataset was defined and prepared using relevant high-definition airborne video sequences. The assessment concept is explained and performance results are given using the established precision-recall diagrams, average precision and runtime figures on representative test data. A comparison to legacy target recognition approaches shows the impressive performance increase by the proposed CNN+SVM machine-learning approach and the capability of real-time high

  9. Inventory Investment and the Real Interest Rate

    OpenAIRE

    Junayed, Sadaquat; Khan, Hashmat

    2009-01-01

    The relationship between inventory investment and the real interest rate has been difficult to assess empirically. Recent work has proposed a linear-quadratic inventory model with time-varying discount factor to identify the effects of the real interest rate on inventory investment. The authors show that this framework does not separately identify the effects of real interest rate on inventory investment from variables that determine the expected marginal cost of production. In other words, t...

  10. Accounting strategy of tritium inventory in the heavy water detritiation pilot plant from ICIT Rm. Valcea

    International Nuclear Information System (INIS)

    Bidica, N.; Stefanescu, I.; Cristescu, I.; Bornea, A.; Zamfirache, M.; Lazar, A.; Vasut, F.; Pearsica, C.; Stefan, I.; Prisecaru, I.; Sindilar, G.

    2008-01-01

    In this paper we present a methodology for determination of tritium inventory in a tritium removal facility. The method proposed is based on the developing of computing models for accountancy of the mobile tritium inventory in the separation processes, of the stored tritium and of the trapped tritium inventory in the structure of the process system components. The configuration of the detritiation process is a combination of isotope catalytic exchange between water and hydrogen (LPCE) and the cryogenic distillation of hydrogen isotopes (CD). The computing model for tritium inventory in the LPCE process and the CD process will be developed basing on mass transfer coefficients in catalytic isotope exchange reactions and in dual-phase system (liquid-vapour) of hydrogen isotopes distillation process. Accounting of tritium inventory stored in metallic hydride will be based on in-bed calorimetry. Estimation of the trapped tritium inventory can be made by subtraction of the mobile and stored tritium inventories from the global tritium inventory of the plant area. Determinations of the global tritium inventory of the plant area will be made on a regular basis by measuring any tritium quantity entering or leaving the plant area. This methodology is intended to be applied to the Heavy Water Detritiation Pilot Plant from ICIT Rm. Valcea (Romania) and to the Cernavoda Tritium Removal Facility (which will be built in the next 5-7 years). (authors)

  11. 42 CFR 35.41 - Inventory.

    Science.gov (United States)

    2010-10-01

    ... 42 Public Health 1 2010-10-01 2010-10-01 false Inventory. 35.41 Section 35.41 Public Health PUBLIC... STATION MANAGEMENT Disposal of Money and Effects of Deceased Patients § 35.41 Inventory. Promptly after the death of a patient in a station or hospital of the Service, an inventory of his money and effects...

  12. 7 CFR 984.21 - Handler inventory.

    Science.gov (United States)

    2010-01-01

    ... 7 Agriculture 8 2010-01-01 2010-01-01 false Handler inventory. 984.21 Section 984.21 Agriculture Regulations of the Department of Agriculture (Continued) AGRICULTURAL MARKETING SERVICE (Marketing Agreements... Regulating Handling Definitions § 984.21 Handler inventory. Handler inventory as of any date means all...

  13. 26 CFR 1.1374-7 - Inventory.

    Science.gov (United States)

    2010-04-01

    ... 26 Internal Revenue 11 2010-04-01 2010-04-01 true Inventory. 1.1374-7 Section 1.1374-7 Internal... TAXES Small Business Corporations and Their Shareholders § 1.1374-7 Inventory. (a) Valuation. The fair market value of the inventory of an S corporation on the first day of the recognition period equals the...

  14. 10 CFR 34.29 - Quarterly inventory.

    Science.gov (United States)

    2010-01-01

    ... 10 Energy 1 2010-01-01 2010-01-01 false Quarterly inventory. 34.29 Section 34.29 Energy NUCLEAR... RADIOGRAPHIC OPERATIONS Equipment § 34.29 Quarterly inventory. (a) Each licensee shall conduct a quarterly physical inventory to account for all sealed sources and for devices containing depleted uranium received...

  15. 77 FR 5280 - Service Contracts Inventory

    Science.gov (United States)

    2012-02-02

    ... NUCLEAR REGULATORY COMMISSION [NRC-2012-0023] Service Contracts Inventory AGENCY: Nuclear...) is providing for public information its Inventory of Contracts for Services for Fiscal Year (FY) 2011. The inventory includes service contract actions over $25,000 that were awarded in FY 2011. ADDRESSES...

  16. 75 FR 82095 - Service Contracts Inventory

    Science.gov (United States)

    2010-12-29

    ... NUCLEAR REGULATORY COMMISSION [NRC-2010-0394] Service Contracts Inventory AGENCY: U.S. Nuclear...) is providing for public information its Inventory of Contracts for Services for Fiscal Year (FY) 2010. The inventory includes service contract actions over $25,000 that were awarded in FY 2010. ADDRESSES...

  17. 78 FR 10642 - Service Contracts Inventory

    Science.gov (United States)

    2013-02-14

    ... NUCLEAR REGULATORY COMMISSION [NRC-2013-0029] Service Contracts Inventory AGENCY: Nuclear...) is providing for public information its Inventory of Contracts for Services for Fiscal Year (FY) 2012. The inventory includes service contract actions over $25,000 that were awarded in FY 2012. ADDRESSES...

  18. 27 CFR 24.266 - Inventory losses.

    Science.gov (United States)

    2010-04-01

    ... 27 Alcohol, Tobacco Products and Firearms 1 2010-04-01 2010-04-01 false Inventory losses. 24.266... OF THE TREASURY LIQUORS WINE Losses of Wine § 24.266 Inventory losses. (a) General. The proprietor... reported as required by § 24.313. (b) Bulk wine losses. The physical inventory of bulk wine will determine...

  19. 27 CFR 40.523 - Inventories.

    Science.gov (United States)

    2010-04-01

    ... 27 Alcohol, Tobacco Products and Firearms 2 2010-04-01 2010-04-01 false Inventories. 40.523... PROCESSED TOBACCO Manufacture of Processed Tobacco Operations by Manufacturers of Processed Tobacco § 40.523 Inventories. Every manufacturer of processed tobacco must provide a true and accurate inventory on TTB F 5210...

  20. 30 CFR 220.032 - Inventories.

    Science.gov (United States)

    2010-07-01

    ... operations. The accumulation of surplus stocks shall be avoided by proper materiel control, inventory and... physical inventory that has not been credited to NPSL operations under § 220.015(a)(2) shall be credited to... 30 Mineral Resources 2 2010-07-01 2010-07-01 false Inventories. 220.032 Section 220.032 Mineral...

  1. Teaching with technology: learning outcomes for a combined dental and dental hygiene online hybrid oral histology course.

    Science.gov (United States)

    Gadbury-Amyot, Cynthia C; Singh, Amul H; Overman, Pamela R

    2013-06-01

    Among the challenges leaders in dental and allied dental education have faced in recent years is a shortage of well-qualified faculty members, especially in some specialty areas of dentistry. One proposed solution has been the use of technology. At the University of Missouri-Kansas City School of Dentistry, the departure of a faculty member who taught the highly specialized content in oral histology and embryology provided the opportunity to implement distance delivery of that course. The course is taught once a year to a combined group of dental and dental hygiene students. Previous to spring semester of 2009, the course was taught using traditional face-to-face, in-class lectures and multiple-choice examinations. During the spring semesters of 2009, 2010, and 2011, the course was taught using synchronous and asynchronous distance delivery technology. Outcomes for these courses (including course grades and performance on the National Board Dental Examination Part I) were compared to those from the 2006, 2007, and 2008 courses. Students participating in the online hybrid course were also given an author-designed survey, and the perceptions of the faculty member who made the transition from teaching the course in a traditional face-to-face format to teaching in an online hybrid format were solicited. Overall, student and faculty perceptions and student outcomes and course reviews have been positive. The results of this study can provide guidance to those seeking to use technology as one method of curricular delivery.

  2. A new approach for peat inventory methods; Turvetutkimusten menetelmaekehitystarkastelu

    Energy Technology Data Exchange (ETDEWEB)

    Laatikainen, M.; Leino, J.; Lerssi, J.; Torppa, J.; Turunen, J. Email: jukka.turunen@gtk.fi

    2011-07-01

    Development of the new peatland inventory method started in 2009. There was a need to investigate whether new methods and tools could be developed cost-effectively so field inventory work would more completely cover the whole peatland area and the quality and liability of the final results would remain at a high level. The old inventory method in place at the Geological Survey of Finland (GTK) is based on the main transect and cross transect approach across a peatland area. The goal of this study was to find a practical grid-based method linked to the geographic information system suitable for field conditions. the triangle-grid method with even distance between the study points was found to be the most suitable approach. A new Ramac-ground penetrating radar was obtained by the GTK in 2009, and it was concluded in the study of new peatland inventory methods. This radar model is relatively light and very suitable, for example, to the forestry drained peatlands, which are often difficult to cross because of the intensive ditch network. the goal was to investigate the best working methods for the ground penetrating radar to optimize its use in the large-scale peatland inventory. Together with the new field inventory methods, a novel interpolation-based method (MITTI) for modelling peat depths was developed. MITTI makes it possible to take advantage of all the available peat-depth data including, at the moment, aerogeophysical and ground penetrating radar measurements, drilling data and the mire outline. The characteristic uncertainties of each data type are taken into account and, in addition to the depth model itself, an uncertainty map of the model is computed. Combined with the grid-based field inventory method, this multi-approach provides better tools to more accurately estimate the peat depths, peat amounts and peat type distributions. The development of the new peatland inventory method was divided into four separate sections: (1) Development of new field

  3. Development of a Coastal Inventory in Greece

    Science.gov (United States)

    Karditsa, Aikaterini; Poulos, Serafim; Velegrakis, Adonis; Ghionis, George; Petrakis, Stelios; Alexandrakis, George; Andreadis, Olympos; Monioudi, Isavella

    2015-04-01

    Greek coastline that accounts more than 16.000 km hosts hundreds of beaches, which constitute a great touristic destination. However, no gathered information exists relative to its qualitative and quantitative characteristics (e.g. physicogeographical characteristics, artificial structures, nearby land use). Therefore, the development of a coastal database that would successfully concentrate all relative data, in the form of a National Inventory, could be a valuable tool for the management and the sustainable use and exploitation of beaches and the coastal zone. This work presents an example of the development of a beach inventory in the case of the beach zones of Heraklion and Lassithi counties in the Island of Crete, which is one of the most touristic areas in Greece. Data were initially abstracted from satellite images and combined with in situ observations carried out along 98 beaches with shoreline length >100 m. The collected data included geomorphological, topographic and bathymetric mapping, sediment sampling from the subaerial and underwater part and recording of artificial structures. The initial mapping showed that beaches represent only the 18%, with 74% of the total coastline to be rocky while 8% of the coastline host some kind of artificial intervention. The combination of satellite and in situ mapping led to the development of a coastal geomorphological map. Beach widths were found to be limited with the majority of beaches (59%) to have maximum widths less than 25 m, 35% to range between 25 and 50m and about 6% with maximum widths >50m. Concerning beach length, the threshold of 1000 m is overcome only by the 46% of the beaches. Beaches with very smooth slopes (Entrepreneurship" co-funded by the European Regional Development Fund (ERDF) and the Ministry of Education and Relegious Affairs.

  4. TFTR tritium inventory accountability system

    International Nuclear Information System (INIS)

    Saville, C.; Ascione, G.; Elwood, S.; Nagy, A.; Raftopoulos, S.; Rossmassler, R.; Stencel, J.; Voorhees, D.; Tilson, C.

    1995-01-01

    This paper discusses the program, PPPL (Princeton Plasma Physics Laboratory) Material Control and Accountability Plan, that has been implemented to track US Department of Energy's tritium and all other accountable source material. Specifically, this paper details the methods used to measure tritium in various systems at the Tokamak Fusion Test Reactor; resolve inventory differences; perform inventory by difference inside the Tokamak; process and measure plasma exhaust and other effluent gas streams; process, measure and ship scrap or waste tritium on molecular sieve beds; and detail organizational structure of the Material Control and Accountability group. In addition, this paper describes a Unix-based computerized software system developed at PPPL to account for all tritium movements throughout the facility. 5 refs., 2 figs

  5. Role of Personality Traits, Learning Styles and Metacognition in Predicting Critical Thinking of Undergraduate Students

    Directory of Open Access Journals (Sweden)

    Soliemanifar O

    2015-04-01

    The aim of this study was to investigate the role of personality traits, learning styles and metacognition in predicting critical thinking. Instrument & Methods: In this descriptive correlative study, 240 students (130 girls and 110 boys of Ahvaz Shahid Chamran University were selected by multi-stage random sampling method. The instruments for collecting data were NEO Five-Factor Inventory, learning style inventory of Kolb (LSI, metacognitive assessment inventory (MAI of Schraw & Dennison (1994 and California Critical Thinking Skills Test (CCTST. The data were analyzed using Pearson correlation coefficient, stepwise regression analysis and Canonical correlation analysis.  Findings: Openness to experiment (b=0.41, conscientiousness (b=0.28, abstract conceptualization (b=0.39, active experimentation (b=0.22, reflective observation (b=0.12, knowledge of cognition (b=0.47 and regulation of cognition (b=0.29 were effective in predicting critical thinking. Openness to experiment and conscientiousness (r2=0.25, active experimentation, abstract conceptualization and reflective observation learning styles (r2=0.21 and knowledge and regulation of cognition metacognitions (r2=0.3 had an important role in explaining critical thinking. The linear combination of critical thinking skills (evaluation, analysis, inference was predictable by a linear combination of dispositional-cognitive factors (openness, conscientiousness, abstract conceptualization, active experimentation, knowledge of cognition and regulation of cognition. Conclusion: Personality traits, learning styles and metacognition, as dispositional-cognitive factors, play a significant role in students' critical thinking.

  6. Stable isotope research pool inventory

    International Nuclear Information System (INIS)

    1984-03-01

    This report contains a listing of electromagnetically separated stable isotopes which are available at the Oak Ridge National Laboratory for distribution for nondestructive research use on a loan basis. This inventory includes all samples of stable isotopes in the Research Materials Collection and does not designate whether a sample is out on loan or is in reprocessing. For some of the high abundance naturally occurring isotopes, larger amounts can be made available; for example, Ca-40 and Fe-56

  7. Waste management and chemical inventories

    Energy Technology Data Exchange (ETDEWEB)

    Gleckler, B.P.

    1995-06-01

    This section of the 1994 Hanford Site Environmental Report summarizes the classification and handling of waste at the Hanford Site. Waste produced at the Hanford Site is classified as either radioactive, nonradioactive, or mixed waste. Radioactive wastes are further categorized as transuranic, high-level, and low-level. Mixed waste may contain both radioactive and hazardous nonradioactive substances. This section describes waste management practices and chemical inventories at the site.

  8. Radioactive wastes - inventories and classification

    International Nuclear Information System (INIS)

    Brennecke, P.; Hollmann, A.

    1992-01-01

    A survey is given of the origins, types, conditioning, inventories, and expected abundance of radioactive wastes in the future in the Federal Republic of Germany. The Federal Government's radioactive waste disposal scheme provides that radioactive wastes be buried in deep geological formations which are expected to ensure a maintenance-free, unlimited and safe disposal without intentional excavation of the wastes at a later date. (orig./BBR) [de

  9. Waste management and chemical inventories

    International Nuclear Information System (INIS)

    Gleckler, B.P.

    1995-01-01

    This section of the 1994 Hanford Site Environmental Report summarizes the classification and handling of waste at the Hanford Site. Waste produced at the Hanford Site is classified as either radioactive, nonradioactive, or mixed waste. Radioactive wastes are further categorized as transuranic, high-level, and low-level. Mixed waste may contain both radioactive and hazardous nonradioactive substances. This section describes waste management practices and chemical inventories at the site

  10. Radioactive waste inventories and projections

    International Nuclear Information System (INIS)

    McLaren, L.H.

    1982-11-01

    This bibliography contains information on radioactive waste inventories and projections included in the Department of Energy's Energy Data Base from January 1981 through September 1982. The arrangement is by report number for reports, followed by nonreports in reverse chronological order. These citations are to research reports, journal articles, books, patents, theses, and conference papers from worldwide sources. Five indexes, each preceded by a brief description, are provided: Corporate Author, Personal Author, Subject, Contract Number, and Report Number. (25 abstracts)

  11. Stable isotope research pool inventory

    International Nuclear Information System (INIS)

    1982-01-01

    This report contains a listing of electromagnetically separated stable isotopes which are available for distribution within the United States for nondestructive research use from the Oak Ridge National Laboratory on a loan basis. This inventory includes all samples of stable isotopes in the Material Research Collection and does not designate whether a sample is out on loan or in reprocessing. For some of the high abundance naturally occurring isotopes, larger amounts can be made available; for example, Ca-40 and Fe-56

  12. National inventory of radioactive wastes

    International Nuclear Information System (INIS)

    1997-01-01

    There are in France 1064 sites corresponding to radioactive waste holders that appear in this radioactive waste inventory. We find the eighteen sites of E.D.F. nuclear power plants, The Cogema mine sites, the Cogema reprocessing plants, The Cea storages, the different factories and enterprises of nuclear industry, the sites of non nuclear industry, the Andra centers, decommissioned installations, disposals with low level radioactive wastes, sealed sources distributors, national defence. (N.C.)

  13. 78 FR 17205 - Notice of Availability of Service Contract Inventories

    Science.gov (United States)

    2013-03-20

    ... FEDERAL MARITIME COMMISSION Notice of Availability of Service Contract Inventories AGENCY: Federal Maritime Commission. ACTION: Notice of availability of service contract inventories. FOR FURTHER... Service Contract Inventory Analysis, the FY 2012 Service Contract Inventory, and the FY 2012 Service...

  14. Danish emission inventory for particular matter (PM)

    Energy Technology Data Exchange (ETDEWEB)

    Nielsen, M; Winther, M; Illerup, J B; Hjort Mikkelsen, M

    2003-11-01

    The first Danish emission inventory that was reported in 2002 was a provisional-estimate based on data presently available. This report documents methodology, emission factors and references used for an improved Danish emission inventory for particulate matter. Further results of the improved emission inventory for the year 2000 are shown. The particulate matter emission inventory includes TSP, PM,, and PM, The report covers emission inventories for transport and stationary combustion. An appendix covering emissions from agriculture is also included. For the transport sector, both exhaust and non-exhaust emission such as tyre and break wear and road abrasion are included. (au)

  15. An inventory of biomedical imaging physics elements-of-competence for diagnostic radiography education in Europe

    International Nuclear Information System (INIS)

    Caruana, Carmel J.; Plasek, Jaromir

    2006-01-01

    Purpose: To develop an inventory of biomedical physics elements-of-competence for diagnostic radiography education in Europe. Method: Research articles in the English literature and UK documentation pertinent to radiography education, competences and role development were subjected to a rigorous analysis of content from a functional and competence analysis perspective. Translations of radiography curricula from across Europe and relevant EU legislation were likewise analysed to ensure a pan-European perspective. Broad Subject Specific Competences for diagnostic radiography that included major biomedical physics components were singled out. These competences were in turn carefully deconstructed into specific elements-of-competence and those elements falling within the biomedical physics learning domain inventorised. A pilot version of the inventory was evaluated by participants during a meeting of the Higher Education Network for Radiography in Europe (HENRE), held in Marsascala, Malta, in November 2004. The inventory was further refined taking into consideration suggestions by HENRE members and scientific, professional and educational developments. Findings: The evaluation of the pilot inventory was very positive and indicated that the overall structure of the inventory was sensible, easily understood and acceptable - hence a good foundation for further development. Conclusions: Use of the inventory by radiography programme leaders and biomedical physics educators would guarantee that all necessary physics elements-of-competence underpinning the safe, effective and economical use of imaging devices are included within radiography curricula. It will also ensure the relevancy of physics content within radiography education. The inventory is designed to be a pragmatic tool for curriculum development across the entire range of radiography education up to doctorate level and irrespective of whether curriculum delivery is discipline-based or integrated, presentation

  16. An inventory of biomedical imaging physics elements-of-competence for diagnostic radiography education in Europe

    Energy Technology Data Exchange (ETDEWEB)

    Caruana, Carmel J. [University of Malta, Institute of Health Care, St Lukes Hospital, Gwardamangia (Malta)]. E-mail: carmel.j.caruana@um.edu.mt; Plasek, Jaromir [Charles University, Faculty of Mathematics and Physics, Institute of Physics, Division of Biophysics, Prague (Czech Republic)

    2006-08-15

    Purpose: To develop an inventory of biomedical physics elements-of-competence for diagnostic radiography education in Europe. Method: Research articles in the English literature and UK documentation pertinent to radiography education, competences and role development were subjected to a rigorous analysis of content from a functional and competence analysis perspective. Translations of radiography curricula from across Europe and relevant EU legislation were likewise analysed to ensure a pan-European perspective. Broad Subject Specific Competences for diagnostic radiography that included major biomedical physics components were singled out. These competences were in turn carefully deconstructed into specific elements-of-competence and those elements falling within the biomedical physics learning domain inventorised. A pilot version of the inventory was evaluated by participants during a meeting of the Higher Education Network for Radiography in Europe (HENRE), held in Marsascala, Malta, in November 2004. The inventory was further refined taking into consideration suggestions by HENRE members and scientific, professional and educational developments. Findings: The evaluation of the pilot inventory was very positive and indicated that the overall structure of the inventory was sensible, easily understood and acceptable - hence a good foundation for further development. Conclusions: Use of the inventory by radiography programme leaders and biomedical physics educators would guarantee that all necessary physics elements-of-competence underpinning the safe, effective and economical use of imaging devices are included within radiography curricula. It will also ensure the relevancy of physics content within radiography education. The inventory is designed to be a pragmatic tool for curriculum development across the entire range of radiography education up to doctorate level and irrespective of whether curriculum delivery is discipline-based or integrated, presentation

  17. 2009 National inventory of radioactive material and wastes. Geographical inventory

    International Nuclear Information System (INIS)

    2009-01-01

    A geographical inventory of the radioactive wastes present on the French territory (as recorded until the 31 of december, 2007) is presented, region by region. The various types of waste sites (production, processing, conditioning and storage sites, Uranium mines, ANDRA storage centers, historical storage sites and polluted sites where wastes are stored) are listed and located on maps. Details are given on the nature and origin of these wastes (nuclear industry, medical domain, scientific research, conventional industry, Defense...). A total of 1121 sites have been recorded, among which 163 are presented with details and charts

  18. Learning Styles: Do They Differ by Discipline?

    Science.gov (United States)

    Wolfe, Kara; Bates, Derald; Manikowske, Linda; Amundsen, Rebecca

    2005-01-01

    Kolb's Experiential Learning Theory describes how learners see and interpret information. Past studies have analyzed learning styles of certain professions and majors. This study evaluated whether student learning styles differ by major. The Marshall and Merritt Learning Style Inventory was completed by 531 students. Differences were found in…

  19. Joint inventory control and pricing in a service-inventory system

    DEFF Research Database (Denmark)

    Marand, Ata Jalili; Li, Hongyan Jenny; Thorstenson, Anders

    2017-01-01

    This study addresses joint inventory control and pricing decisions for a service-inventory system. In such a system both an on-hand inventory item and a positive service time are required to fulfill customer demands. The service-inventory system also captures main features of the classical...... inventory systems with a positive processing time, e.g., make-to-order systems. In this study, the service-inventory system is modeled as an M/M/1 queue in which the customer arrival rate is price dependent. The inventory of an individual item is continuously reviewed under an (r,Q) policy....... The replenishment lead times of the inventory are exponentially distributed. Furthermore, customers arriving during stock-out periods are lost. The stochastic customer inter-arrival times, service times, and inventory replenishment lead times cause the high complexity of the problem and the difficulty in solving it...

  20. Updating the New Zealand Glacier Inventory

    Science.gov (United States)

    Baumann, S. C.; Anderson, B.; Mackintosh, A.; Lorrey, A.; Chinn, T.; Collier, C.; Rack, W.; Purdie, H.

    2017-12-01

    The last complete glacier inventory of New Zealand dates from the year 1978 (North Island 1988) and was manually constructed from oblique aerial photographs and geodetic maps (Chinn 2001). The inventory has been partly updated by Gjermundsen et al. (2011) for the year 2002 (40% of total area) and by Sirguey & More (2010) for the year 2009 (32% of total area), both using ASTER satellite imagery. We used Landsat 8 OLI/TIRS satellite data from February/March 2016 to map the total glaciated area. Clean and debris-covered ice were mapped semi-automatically. The band ratio approach was used for clean ice (ratio: red/SWIR). We mapped debris-covered ice using a supervised classification (maximum likelihood). Manual post processing was necessary due to misclassifications (e.g. lakes, clouds) or mapping in shadowed areas. It was also necessary to manually combine the clean and debris-covered parts into single glaciers. Additional input data for the post processing were Sentinel 2 images from the same time period, orthophotos from Land Information New Zealand (resolution: 0.75 m, date: Nov 2014), and the 1978/88 outlines from the GLIMS database (http://www.glims.org/). As the Sentinel 2 data were more heavily cloud covered compared to the Landsat 8 images, they were only used for post processing and not for the classification itself. Initial results show that New Zealand glaciers covered an area of about 1050 km² in 2016, a reduction of 16% since 1978. Approximately 17% of glacier area was covered in surface debris. The glaciers in the central Southern Alps around Mt Cook reduced in area by 24%. Glaciers in the North Island of New Zealand reduced by 71% since 1988, and only 2 km² of ice cover remained in 2016. Chinn, TJH (2001). "Distribution of the glacial water resources of New Zealand." Journal of Hydrology (NZ) 40(2): 139-187 Gjermundsen, EF, Mathieu, R, Kääb, A, Chinn, TJH, Fitzharris, B & Hagen, JO (2011). "Assessment of multispectral glacier mapping methods and

  1. Slopeland utilizable limitation classification using landslide inventory

    Science.gov (United States)

    Tsai, Shu Fen; Lin, Chao Yuan

    2016-04-01

    In 1976, "Slopeland Conservation and Utilization Act" was promulgated as well as the criteria for slopeland utilization limitation classification (SULC) i.e., average slope, effective soil depth, degree of soil erosion, and parent rock became standardized. Due to the development areas on slope land steadily increased and the extreme rainfall events occurred frequently, the areas affected by landslides also increased year by year. According to the act, the land which damaged by disaster must be categorized to the conservation land and required rehabilitation. Nevertheless, the large-scale disaster on slope land and the limitation of SWCB officers are the constraint of field investigation. Therefore, how to establish the ongoing inspective procedure of post-disaster SULC using remote sensing was essential. A-Li-Shan, Ai-Liao, and Tai-Ma-Li Watershed were selected to be case studies in this project. The spatial data from big data i.e., Digital Elevation Model (DEM), soil map, and satellite images integrated with Geographic Information Systems (GIS) were applied to post-disaster SULC. The collapse and deposition area which delineated by vegetation recovery rate was established landslide inventory of cadastral unit combined with watershed unit. The results were verified with field survey and the accuracy was 97%. The landslide inventory could be an effective reference for sediment disaster investigation and a practical evidence for judgement to expropriation. Finally, the results showed that the ongoing inspective procedure of post-disaster SULC was practicable. From the four criteria, the average slope was the major factor. It was found that the non-uniform slopes, especially derived from cadastral units, often produce significant slope difference and lead to errors of average slope evaluation. Therefore, the Grid-based DEM slope derivation has been recommended as the standard method to calculate the average slope. Others criteria were previously required to classify

  2. Considering inventory distributions in a stochastic periodic inventory routing system

    Science.gov (United States)

    Yadollahi, Ehsan; Aghezzaf, El-Houssaine

    2017-07-01

    Dealing with the stochasticity of parameters is one of the critical issues in business and industry nowadays. Supply chain planners have difficulties in forecasting stochastic parameters of a distribution system. Demand rates of customers during their lead time are one of these parameters. In addition, holding a huge level of inventory at the retailers is costly and inefficient. To cover the uncertainty of forecasting demand rates, researchers have proposed the usage of safety stock to avoid stock-out. However, finding the precise level of safety stock depends on forecasting the statistical distribution of demand rates and their variations in different settings among the planning horizon. In this paper the demand rate distributions and its parameters are taken into account for each time period in a stochastic periodic IRP. An analysis of the achieved statistical distribution of the inventory and safety stock level is provided to measure the effects of input parameters on the output indicators. Different values for coefficient of variation are applied to the customers' demand rate in the optimization model. The outcome of the deterministic equivalent model of SPIRP is simulated in form of an illustrative case.

  3. Tritium inventory tracking and management

    International Nuclear Information System (INIS)

    Eichenberg, T.W.; Klein, A.C.

    1990-01-01

    This investigation has identified a number of useful applications of the analysis of the tracking and management of the tritium inventory in the various subsystems and components in a DT fusion reactor system. Due to the large amounts of tritium that will need to be circulated within such a plant, and the hazards of dealing with the tritium an electricity generating utility may not wish to also be in the tritium production and supply business on a full time basis. Possible scenarios for system operation have been presented, including options with zero net increase in tritium inventory, annual maintenance and blanket replacement, rapid increases in tritium creation for the production of additional tritium supplies for new plant startup, and failures in certain system components. It has been found that the value of the tritium breeding ratio required to stabilize the storage inventory depends strongly on the value and nature of other system characteristics. The real operation of a DT fusion reactor power plant will include maintenance and blanket replacement shutdowns which will affect the operation of the tritium handling system. It was also found that only modest increases in the tritium breeding ratio are needed in order to produce sufficient extra tritium for the startup of new reactors in less than two years. Thus, the continuous operation of a reactor system with a high tritium breeding ratio in order to have sufficient supplies for other plants is not necessary. Lastly, the overall operation and reliability of the power plant is greatly affected by failures in the fuel cleanup and plasma exhaust systems

  4. Radionuclide inventory and source terms for the surplus production reactors at Hanford

    International Nuclear Information System (INIS)

    Miller, R.L.; Steffes, J.M.

    1987-01-01

    Radionuclide inventories have been estimated for the eight surplus production reactors at Hanford. The inventories listed represent more than 95% of the total curie burden; the remaining 5% is distributed in piping, tunnels, and various other locations within the reactor building and unaccounted for inventories within the reactors or fuel storage basins. Estimates are conservative as the methodology was designed to overestimate the radionuclide inventories in the facilities. The estimated inventory per reactor facility ranges from 13,000 curies to 58,000 curies. The majority of the present inventory consists of tritium, carbon-14, cobalt-60, and nickel-63. The information in this document combines data from past characterization efforts and introduces adjustments for added information and refinement. The inventory of hazardous materials in the reactor facilities is also addressed. This document has been revised to include new reduced inventory figures for chlorine-36. The new figures were derived from recent analysis of irradiated graphite from the 105-kW reactor

  5. State-of-the-art techniques for inventory of Great Lakes aquatic habitats and resources

    Science.gov (United States)

    Edsall, Thomas A.; Brock, R.H.; Bukata, R.P.; Dawson, J.J.; Horvath, F.J.; Busch, W.-Dieter N.; Sly, Peter G.

    1992-01-01

    This section of the Classification and Inventory of Great Lakes Aquatic Habitat report was prepared as a series of individually authored contributions that describe, in various levels of detail, state-of-the-art techniques that can be used alone or in combination to inventory aquatic habitats and resources in the Laurentian Great Lakes system. No attempt was made to review and evaluate techniques that are used routinely in limnological and fisheries surveys and inventories because it was felt that users of this document would be familiar with them.

  6. Improved Prediction of Blood-Brain Barrier Permeability Through Machine Learning with Combined Use of Molecular Property-Based Descriptors and Fingerprints.

    Science.gov (United States)

    Yuan, Yaxia; Zheng, Fang; Zhan, Chang-Guo

    2018-03-21

    Blood-brain barrier (BBB) permeability of a compound determines whether the compound can effectively enter the brain. It is an essential property which must be accounted for in drug discovery with a target in the brain. Several computational methods have been used to predict the BBB permeability. In particular, support vector machine (SVM), which is a kernel-based machine learning method, has been used popularly in this field. For SVM training and prediction, the compounds are characterized by molecular descriptors. Some SVM models were based on the use of molecular property-based descriptors (including 1D, 2D, and 3D descriptors) or fragment-based descriptors (known as the fingerprints of a molecule). The selection of descriptors is critical for the performance of a SVM model. In this study, we aimed to develop a generally applicable new SVM model by combining all of the features of the molecular property-based descriptors and fingerprints to improve the accuracy for the BBB permeability prediction. The results indicate that our SVM model has improved accuracy compared to the currently available models of the BBB permeability prediction.

  7. Towards subsidized malaria rapid diagnostic tests. Lessons learned from programmes to subsidise artemisinin-based combination therapies in the private sector: a review.

    Science.gov (United States)

    Lussiana, Cristina

    2016-09-01

    The idea of a private sector subsidy programme of artemisinin-based combination therapies (ACTs) was first proposed in 2004. Since then, several countries around the world have hosted pilot projects or programmes on subsidized ACTs and/or the Affordable Medicines Facility-malaria programme (AMFm). Overall the private sector subsidy programmes of ACTs have been effective in increasing availability of ACTs in the private sector and driving down average prices but struggled to crowd out antimalarial monotherapies. The results obtained from this ambitious strategy should inform policy makers in the designing of future interventions aimed to control malaria morbidity and mortality. Among the interventions recently proposed, a subsidy of rapid diagnostic tests (RDTs) in the private sector has been recommended by governments and international donors to cope with over-treatment with ACTs and to delay the emergence of resistance to artemisinin. In order to improve the cost-effectiveness of co-paid RDTs, we should build on the lessons we learned from almost 10 years of private sector subsidy programmes of ACTs in malaria-endemic countries. © The Author 2015. Published by Oxford University Press in association with The London School of Hygiene and Tropical Medicine.

  8. An industrial perspective on bioreactor scale-down: what we can learn from combined large-scale bioprocess and model fluid studies.

    Science.gov (United States)

    Noorman, Henk

    2011-08-01

    For industrial bioreactor design, operation, control and optimization, the scale-down approach is often advocated to efficiently generate data on a small scale, and effectively apply suggested improvements to the industrial scale. In all cases it is important to ensure that the scale-down conditions are representative of the real large-scale bioprocess. Progress is hampered by limited detailed and local information from large-scale bioprocesses. Complementary to real fermentation studies, physical aspects of model fluids such as air-water in large bioreactors provide useful information with limited effort and cost. Still, in industrial practice, investments of time, capital and resources often prohibit systematic work, although, in the end, savings obtained in this way are trivial compared to the expenses that result from real process disturbances, batch failures, and non-flyers with loss of business opportunity. Here we try to highlight what can be learned from real large-scale bioprocess in combination with model fluid studies, and to provide suitable computation tools to overcome data restrictions. Focus is on a specific well-documented case for a 30-m(3) bioreactor. Areas for further research from an industrial perspective are also indicated. Copyright © 2011 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  9. A Genetic Algorithm on Inventory Routing Problem

    Directory of Open Access Journals (Sweden)

    Nevin Aydın

    2014-03-01

    Full Text Available Inventory routing problem can be defined as forming the routes to serve to the retailers from the manufacturer, deciding on the quantity of the shipment to the retailers and deciding on the timing of the replenishments. The difference of inventory routing problems from vehicle routing problems is the consideration of the inventory positions of retailers and supplier, and making the decision accordingly. Inventory routing problems are complex in nature and they can be solved either theoretically or using a heuristics method. Metaheuristics is an emerging class of heuristics that can be applied to combinatorial optimization problems. In this paper, we provide the relationship between vendor-managed inventory and inventory routing problem. The proposed genetic for solving vehicle routing problem is described in detail.

  10. Inventory Centralization Decision Framework for Spare Parts

    DEFF Research Database (Denmark)

    Gregersen, Nicklas; Herbert-Hansen, Zaza Nadja Lee

    2018-01-01

    Within the current literature, there is a lack of a holistic and multidisciplinary approach to managing spare parts and their inventory configuration. This paper addresses this research gap by examining the key contextual factors which influence the degree of inventory centralization and proposes...... a novel holistic theoretical framework, the Inventory Centralization Decision Framework (ICDF), useful for practitioners. Through an extensive review of inventory management literature, six contextual factors influencing the degree of inventory centralization have been identified. Using the ICDF...... practitioners can assess the most advantageous inventory configuration of spare parts. The framework is tested on a large global company which, as a result, today actively uses the ICDF; thus showing its practical applicability....

  11. Inventory estimation for nuclear fuel reprocessing systems

    International Nuclear Information System (INIS)

    Beyerlein, A.L.; Geldard, J.F.

    1987-01-01

    The accuracy of nuclear material accounting methods for nuclear fuel reprocessing facilities is limited by nuclear material inventory variations in the solvent extraction contactors, which affect the separation and purification of uranium and plutonium. Since in-line methods for measuring contactor inventory are not available, simple inventory estimation models are being developed for mixer-settler contactors operating at steady state with a view toward improving the accuracy of nuclear material accounting methods for reprocessing facilities. The authors investigated the following items: (1) improvements in the utility of the inventory estimation models, (2) extension of improvements to inventory estimation for transient nonsteady-state conditions during, for example, process upset or throughput variations, and (3) development of simple inventory estimation models for reprocessing systems using pulsed columns

  12. Hidden inventory and safety considerations

    International Nuclear Information System (INIS)

    Anderson, A.R.; James, R.H.; Morgan, F.

    1976-01-01

    Preliminary results are described of the evaluation of residual plutonium in a process line used for the production of experimental fast reactor fuel. Initial attention has been focussed on a selection of work boxes used for processing powders and solutions. Amounts of material measured as ''hidden inventory'' are generally less than 0.1 percent of throughput but in one box containing very complex equipment the amount was exceptionally about 0.5 percent. The total surface area of the box and the installed equipment appears to be the most significant factor in determining the amount of plutonium held-up as ''hidden inventory,'' representing an average of about 4 x 10 -4 g cm -2 . Present results are based on gamma spectrometer measurements but neutron techniques are being developed to overcome some of the inherent uncertainties in the gamma method. It is suggested that the routine use of sample plates of known surface area would be valuable in monitoring the deposition of plutonium in work boxes

  13. Item response theory analysis of Working Alliance Inventory, revised response format, and new Brief Alliance Inventory.

    Science.gov (United States)

    Mallinckrodt, Brent; Tekie, Yacob T

    2016-11-01

    The Working Alliance Inventory (WAI) has made great contributions to psychotherapy research. However, studies suggest the 7-point response format and 3-factor structure of the client version may have psychometric problems. This study used Rasch item response theory (IRT) to (a) improve WAI response format, (b) compare two brief 12-item versions (WAI-sr; WAI-s), and (c) develop a new 16-item Brief Alliance Inventory (BAI). Archival data from 1786 counseling center and community clients were analyzed. IRT findings suggested problems with crossed category thresholds. A rescoring scheme that combines neighboring responses to create 5- and 4-point scales sharply reduced these problems. Although subscale variance was reduced by 11-26%, rescoring yielded improved reliability and generally higher correlations with therapy process (session depth and smoothness) and outcome measures (residual gain symptom improvement). The 16-item BAI was designed to maximize "bandwidth" of item difficulty and preserve a broader range of WAI sensitivity than WAI-s or WAI-sr. Comparisons suggest the BAI performed better in several respects than the WAI-s or WAI-sr and equivalent to the full WAI on several performance indicators.

  14. Estimating dead wood during national forest inventories: a review of inventory methodologies and suggestions for harmonization.

    Science.gov (United States)

    Woodall, Christopher W; Rondeux, Jacques; Verkerk, Pieter J; Ståhl, Göran

    2009-10-01

    Efforts to assess forest ecosystem carbon stocks, biodiversity, and fire hazards have spurred the need for comprehensive assessments of forest ecosystem dead wood (DW) components around the world. Currently, information regarding the prevalence, status, and methods of DW inventories occurring in the world's forested landscapes is scattered. The goal of this study is to describe the status, DW components measured, sample methods employed, and DW component thresholds used by national forest inventories that currently inventory DW around the world. Study results indicate that most countries do not inventory forest DW. Globally, we estimate that about 13% of countries inventory DW using a diversity of sample methods and DW component definitions. A common feature among DW inventories was that most countries had only just begun DW inventories and employ very low sample intensities. There are major hurdles to harmonizing national forest inventories of DW: differences in population definitions, lack of clarity on sample protocols/estimation procedures, and sparse availability of inventory data/reports. Increasing database/estimation flexibility, developing common dimensional thresholds of DW components, publishing inventory procedures/protocols, releasing inventory data/reports to international peer review, and increasing communication (e.g., workshops) among countries inventorying DW are suggestions forwarded by this study to increase DW inventory harmonization.

  15. Inventories in the Australian business cycle

    OpenAIRE

    Chindamo, Phillip

    2010-01-01

    This Economics Research Note examines inventories in the business cycle for Australia covering the period since the mid 1980s. The Australian Bureau of Statistics (ABS) defines inventories as all materials etc., work in progress and finished goods owned by a business, whether held at locations of the business or elsewhere. These items are usually held by businesses in anticipation of a product’s sale. Inventory investment is counted as an additional contribution to gross domestic product (...

  16. Data Driven Tuning of Inventory Controllers

    DEFF Research Database (Denmark)

    Huusom, Jakob Kjøbsted; Santacoloma, Paloma Andrade; Poulsen, Niels Kjølstad

    2007-01-01

    A systematic method for criterion based tuning of inventory controllers based on data-driven iterative feedback tuning is presented. This tuning method circumvent problems with modeling bias. The process model used for the design of the inventory control is utilized in the tuning...... as an approximation to reduce time required on experiments. The method is illustrated in an application with a multivariable inventory control implementation on a four tank system....

  17. Annual Danish Informative Inventory Report to UNECE

    DEFF Research Database (Denmark)

    Nielsen, Ole-Kenneth; Winther, Morten; Mikkelsen, Mette Hjorth

    The report is a documentation report on the emission inventories for Denmark as reported to the UNECE Secretariat under the Convention on Long Range Transboundary Air Pollution due by 15 February 2013. The report contains information on Denmark’s emission inventories regarding emissions of (1) SOX......(k)fluoranthene and indeno(1,2,3-cd)pyrene, PCDD/F and HCB for the years 1990-2011. Further, the report contains information on background data for emissions inventory....

  18. Annual Danish Informative Inventory Report to UNECE

    DEFF Research Database (Denmark)

    Nielsen, Ole-Kenneth; Winther, Morten; Mikkelsen, Mette Hjorth

    2012-01-01

    This report is a documentation report on the emission inventories for Denmark as reported to the UNECE Secretariat under the Convention on Long Range Transboundary Air Pollution due by 15 February 2012. The report contains information on Denmark’s emission inventories regarding emissions of (1) SOX......(k)fluoranthene and indeno(1,2,3-cd)pyrene, PCDD/F and HCB for the years 1990-2010. Further, the report contains information on background data for emissions inventory....

  19. Inventories and sales uncertainty\\ud

    OpenAIRE

    Caglayan, M.; Maioli, S.; Mateut, S.

    2011-01-01

    We investigate the empirical linkages between sales uncertainty and firms´ inventory investment behavior while controlling for firms´ financial strength. Using large panels of manufacturing firms from several European countries we find that higher sales uncertainty leads to larger stocks of inventories. We also identify an indirect effect of sales uncertainty on inventory accumulation through the financial strength of firms. Our results provide evidence that financial strength mitigates the a...

  20. Deteriorating Inventory Model for Chilled Food

    OpenAIRE

    Yang, Ming-Feng; Tseng, Wei-Chung

    2015-01-01

    With many aspects that affect inventory policy, product perishability is a critical aspect of inventory policy. Most goods will deteriorate during storage and their original value will decline or be lost. Therefore, deterioration should be taken into account in inventory practice. Chilled food products are very common consumer goods that are, in fact, perishable. If the chilled food quality declines over time customers are less likely to buy it. The value the chilled food retains is, however,...