196,090 research outputs found
Kennedy and El-Sabaawi - Decay patterns of invasive plants and plastic trash in urban streams - R code and Data
No full textAppendix Supplement A2 - R Code and Data from: Kennedy KTM & El-Sabaawi RW. 2018 Decay patterns of invasive plants and plastic trash in urban streams -Urban Ecosystems. This data was collected in urban streams in Victoria, BC, Canada and analysed using R version 3.2.5 (2016-04-14) -- "Very, Very Secure Dishes". The following details the Excel workbook contents for each tab and heading descriptions for the data in each tab. Read Me tab - the description of the data. ### Section 1: Tabs for Leaf Decay Comparisons by Stream and Type data and R code. R Code for Leaf decay k kdd tab - The R code used to compare leaf decay k and kdd by stream and by lead type, and draw plots of Leaf toughness by type and Leaf LMA by type - (copy into a new R script for use).kkcalcdd tab - the kkcalcdd dataset (save as .csv for use with R code). kkcalcddnov042015GRAPH tab - the kkcalcddnov042015GRAPH dataset (save as .csv for use with R code). kkcalcddnov042015 tab - the kkcalcddnov042015 dataset (save as .csv for use with R code). kkcalcnov52015noT0notrash tab - the kkcalcnov52015noT0notrash dataset (save as .csv for use with R code). The kkcalcdd tab, kkcalcddnov042015GRAPH tab, kkcalcddnov042015 tab, and kkcalcnov52015noT0notrash tab all have the same column headings:entry - database entry number; stream - Stream site; subsite - subsite at stream; week - week code; timeelapsed - time elapsed in days; type - litter type; pack - pack number; inmass - initial mass in grams; finmass - final mass in grams; inif - (initial mass - final mass); neglnmr - the negative ln of inif; time - time elapsed in days; dd - degree days elapsed; k - the decay rate k; kdd - the decay rate in kdd.### Section 2: Tabs for Leaf Toughness and Leaf LMA Comparisons data and R code: R Code for Leaf Toughness LMA tab - The R code used to compare leaf toughness and leaf mass per area, and draw plots of Leaf toughness by type and Leaf LMA by type - (copy into a new R script for use). LeafToughKW tab - the LeafToughKW dataset (save as .csv for use with R code). The LeafToughKW tab column headings: id - the sample id number; type - the type of leaf; tough - the leaf samples' toughness in g/mm2 as measured with a penetrometer. LeafLMAKW tab - the LeafLMAKW dataset (save as .csv for use with R code). The LeafLMAKW tab column headings: id - the sample id number; type - the type of leaf; LMA - the leaf samples' Leaf Mass per Area (LMA) in mg/cm2. ### Section 3: Tabs for Invertebrate DCA Ordination, Bayesian Clustering, and Ordination Plot data and R code. R Code for Invert ordination tab - The R code used for the invertebrate DCA Ordination, Bayesian Clustering, and ordination plot and by litter type - (copy into a new R script for use). sy2 tab - the sy2 dataset (save as .csv for use with R code). sy2 tab - column headings: id - pack identifier; Chironomidae - Hellinger transformed counts of Chironomidae; Dugesiidae - Hellinger transformed counts of Dugesiidae; Hirudinea - Hellinger transformed counts of Hirudinea; Psychodidae - Hellinger transformed counts of Psychodidae; Crangonyx - Hellinger transformed counts of Crangonyx; Nemetoda - Hellinger transformed counts of Nemetoda; Lepidostomatidae - Hellinger transformed counts of Lepidostomatidae; Nemouridae - Hellinger transformed counts of Nemouridae; Chloroperlidae - Hellinger transformed counts of Chloroperlidae; Copepoda - Hellinger transformed counts of Copepoda; Dixidae - Hellinger transformed counts of Dixidae; Physidae - Hellinger transformed counts of Physidae. dcasy2scores tab - the dcasy2scores dataset (save as .csv for use with R code). dcasy2scores tab - column headings: pack - pack identifier; DCA1 - DCA 1st axis coordinate; DCA2 - DCA 2nd axis coordinate; marker - pack marker ( first letter = stream, second letter = type). dcasy2invertvectors tab - the dcasy2invert vectors dataset (save as .csv for use with R code). dcasy2invertvectors tab - column headings: species - invertebrate species; DCA1 - DCA 1st axis coordinate; DCA2 - DCA 2nd axis coordinate; DCA3 - DCA 3rd axis coordinate; DCA4 - DCA 4th axis coordinate; totals - DCA totals; marker - invertebrate species marker; ### Section 4: Tabs for invertebrate diversity Comparisons by Stream and Type data and R code. R Code for Invert alpha Shannon tab - The R code used to compare invertebrate alpha diversity and Shannon diversity by stream and by litter type, and draw plots of invertebrate alpha and Shannon diversity by stream and litter type - (copy into a new R script for use). Fall bug Diversity FINAL tab - the Fall bug Diversity FINAL dataset (save as .csv for use with R code). The Fall bug Diversity FINAL tab column headings: id - invertebrate sample ID number; pack - pack number; sdiv - Shannon diversity; fisha - Fisher's alpha; adiv - alpha diversity; indiv - number of individuals; stream – stream; type - litter type; lnindiv1 - ln(indiv +1); lnadiv1 - ln(adiv +1); lnsdiv1 - ln(sdiv +1). Fall bug Diversity tab - the Fall bug Diversity dataset (save as .csv for use with R code). The Fall bug Diversity tab column headings: id - invertebrate sample ID number; pack - pack number; sdiv - Shannon diversity; fisha - Fisher's alpha; adiv - alpha diversity; indiv - number of individuals; stream – stream; type - litter type; ### Section 5: Raw invertebrate count data tab - Our complete week 2 invertebrate count dataset prior to constraint for ordination. Raw invertebrate count data tab column headings: Entry #- data entry number; Pack – pack number; Id - pack identifier; stream – stream identifier, Type – pack type; fraction – fraction of pack identified; Counts of individuals: Chironomidae; Dugesiidae; Oligochaeta; Hirudinea; Psychodidae; Crangonyx; Nemetoda; Lepidostomatidae; Nemouridae; Chloroperlidae; Limnephilidae; Copepoda; Hydridae; Dixidae; Elmidae; Heptageniidae; Simuliidae; Physidae; Planorbidae; Ancylidae; Sphaeriidae; Hydrobiidae; Valvatidae; Lymnaeidae; Rhyacophilidae; Daphniidae; Athericidae; Ceratopogonidae; Astacidae; Tipulidae; Ptychopteridae; Dolichopodidae; Empididae; Stratiomyidae; Tabanidae; Phryganeidae; Coenagrionidae; Aeshnidae; Malacostraca; Sialidae; All individuals – sum of all individuals in the pack (sum formula); # of groups – sum of groups in the pack; All individuals - sum of all individuals in the pack (absolute value); individuals/groups (number of individuals divided by number of groups)
Dr. Duane M. Jackson, Morehouse College, July 2011
No full textThis video is a conversation with Dr. Duane M. Jackson. Dr. Jackson talks about his paper, "Recall and the Serial Position Effect: The Role of Primacy and Recency on Accounting Students' Performance." Jackie Daniel, AUC Woodruff Library, is the interviewer
"Reflections on the subject of Emigration from Europe with a view to Settlement in the United States" By M. Carey.
No full text"Reflections on the subject of Emigration from Europe with a view to Settlement in the United States: containing bried sketches of the moral and political character of those states.
By M. Carey, member of the American philosophical, and of the American Antiquarian Society, and author of The Olive Branch, Cindiciae Hibernicae, essays on banking, on political economy, and on internal improvement.
To which are now added the English editor's comments on the subject; together with Important Advice to Emigrants, and Cautions Against Impositions Practiced in the Outports
Dispelling the Myths Behind First-author Citation Counts
No full textWe conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued
use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation
counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more
sophisticated methods
Dr. Glendon Swarthout
No full textHosted by Roger M. Busfield, MSU Assistant Professor of Speech and Theater, Meet the Author is designed to introduce a general audience to a contemporary author and their work through in-depth interviews. This episode features a conversation between Dr. Glendon Swarthout, prolific author and English professor at MSU, and assistant professors Sam S. Baskett and Theodore B. Strandness
Simulation of thermal plant optimization and hydraulic aspects of thermal distribution loops for large campuses
No full textFollowing an introduction, the author describes Texas A&M University and its utilities system. After that, the author presents how to construct simulation models for chilled water and heating hot water distribution systems. The simulation model was used in a $2.3 million Ross Street chilled water pipe replacement project at Texas A&M University. A second project conducted at the University of Texas at San Antonio was used as an example to demonstrate how to identify and design an optimal distribution system by using a simulation model. The author found that the minor losses of these closed loop thermal distribution systems are significantly higher than potable water distribution systems. In the second part of the report, the author presents the latest development of software called the Plant Optimization Program, which can simulate cogeneration plant operation, estimate its operation cost and provide optimized operation suggestions. The author also developed detailed simulation models for a gas turbine and heat recovery steam generator and identified significant potential savings. Finally, the author also used a steam turbine as an example to present a multi-regression method on constructing simulation models by using basic statistics and optimization algorithms. This report presents a survey of the author??s working experience at the Energy Systems Laboratory (ESL) at Texas A&M University during the period of January 2002 through March 2004. The purpose of the above work was to allow the author to become familiar with the practice of engineering. The result is that the author knows how to complete a project from start to finish and understands how both technical and nontechnical aspects of a project need to be considered in order to ensure a quality deliverable and bring a project to successful completion. This report concludes that the objectives of the internship were successfully accomplished and that the requirements for the degree of Degree of Engineering have been satisfied
Two models based on social relations and SVD++ method for recommendation system
No full text*Al Sabaawi, Ali M. Ahmed (Aksaray, Yazar )
*Yenice, Yusuf Erkan (Aksaray, Yazar )Recently, Recommender Systems (RSs) have attracted many researchers whose goal is to improve the performance of the prediction accuracy of recommendation systems by alleviating RSs drawbacks. The most common limitations are sparsity and the cold-start user problems. This article proposes two models to mitigate the effects of these limitations. The proposed models exploit five sources of information: rating information, which involves two sources, namely explicit and implicit, which can be extracted via users’ ratings, and two types of social relations: explicit and implicit relations, the last source is confidence values that are included in the first model only. The whole sources are combined into the Singular Value Decomposition plus (SVD++) method. First, to extract implicit relations, each non-friend pair of users, the Multi-Steps Resource Allocation (MSRA) method is adopted to compute the probability of being friends. If the probability has accepted value which exceeds a threshold, an implicit relationship will be created. Second, the similarity of explicit and implicit social relationships for each pair of users is computed. Regarding the first model, a confidence value between each pair of users is computed by dividing the number of common items by the total number of items which have also rated by the first user of this pair. The confidence values are combined with the similarity values to produce the weight factor. Furthermore, the weight factor, explicit, and implicit feedback information are integrated into the SVD++ method to compute the missing prediction values. Additionally, three standard datasets are utilized in this study, namely Last. Fm, Ciao, and FilmTrust, to evaluate our models. The experimental results have revealed that the proposed models outperformed state-of-the-art approaches in terms of accuracy
Intern experience at CH���M Hill, Inc.: an internship report
No full textIncludes author's vita"Submitted to the College of Engineering of Texas A&M University in partial
fulfillment of the requirement for the degree of Doctor of Engineering."Includes bibliographical referencesA review of the author's internship experience with CH���M HILL, Inc.
during the period September 1975 through May 1976 is presented. During this nine month
internship the author worked as an Engineer II in the Industrial Processes discipline of this
large consulting engineering firm... The author's prime responsibility was as one of three
lead design engineers on the design of a large wastewater treatment facility for a pulp mill
in Hoquiam, Washington owned by ITT Rayonier Inc. The work generally consisted of the design
of individual treatment units and associated piping and pumping. The purpose of the project
was to provide wastewater treatment capabilities that would satisfy the effluent limitations
(standards) imposed upon the mill by the State of Washington Department of Ecology and the
U.S. Environmental Protection Agency. The author's assignment also entailed necessary
interaction with the project manager and other CH���M HILL design engineers and support staff
members, the client's representatives, and representatives of two other consulting engineering
firms working on the project. Thus, the internship position at CH���M HILL provided considerable
experience coordinating the author's work with the work of other engineers, guiding the design
and administrative efforts of a support staff, and interacting regularly with the client and
other consulting firms. This broad exposure to a variety of engineering and organizational
problems provided a valuable educational experience
Individuals with mental illness can control their aggressive behavior through mindfulness training
No full textTransition to turbulence in a qblique shock-wave/boundary-layer interaction at M=15
No full textDirect numerical simulations are carried out for different forcing techniques to trigger transition during the interaction between an oblique shock-wave and a laminar boundary-layer at M = 1.5. Three forcing methods are used: a) forcing of oblique unstable modes, whose shape and behaviour are determined by the local linear stability theory, b) broadband free-stream acoustic disturbances, and c) a cold plasma flow control device. While the oblique-mode breakdown is dominant for low-amplitude forcing, long streaky structures drive the transition process in a high-amplitude disturbance environment. LES are also performed on the experimental setup by the Institute of Theoretical and Applied Mechanics (ITAM) from Novosibirsk State University with cold plasma actuation. As well as the disturbance type, the effect of Reynolds number and forcing amplitude will be investigated
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