1,720,955 research outputs found
Hierarchical classification pathway for white maize, defect and foreign material classification using spectral imaging
Full text linkThis study aimed to present the South African maize industry with an accurate and affordable automated analytical technique for white maize grading using near infrared (NIR) spectral imaging. The 17 categories and sub-categories stipulated in South African maize grading legislation were simultaneously classified (1044 samples; 60 kernels of each class) using 25 partial least squares discriminant analysis (PLS-DA) models. The models were assembled in a hierarchical decision pathway that progressed from the most easily classified classes to the most difficult. The full NIR spectrum (288 wavebands) model performed with an overall accuracy of 93.3% for the main categories. Three waveband selection techniques were employed, namely waveband windows (48 wavebands), variable importance in projection (VIP) (21 wavebands) and covariance selection (CovSel) (13 wavebands). Overall, the VIP set based on only 7.3% of the original spectral variables was recommended as the best trade-off between performance and expected cost of a reduced waveband system. © 2020 Elsevier B.V
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Variations on the Author
Full text link“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
Full text linkWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
Dispelling the Myths Behind First-author Citation Counts
Full text linkWe 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
Characterisation of whole white maize kernels using spectral imaging
Full text linkMaize (Zea mays L.) is the most important cereal crop grown in South Africa. It is produced widely
across the country under diverse environments, and thus a variety of defects tend to occur. Grading
is an important quality and safety control step where these defective materials are identified and
quantified. This study considered the most important defective material classes, namely 6 types of
defective white maize kernels, 5 types of foreign matter, other colour kernels (yellow maize) and
pinked white maize kernels. Current maize grading is manual and tedious, and modern analytical
methods could improve this process. This study aimed to investigate the viability of using spectral
imaging with multivariate data analysis for maize grading by separating sound maize from the 13
defective materials classes.
NIR hyperspectral imaging with pixel-wise and object-wise data analysis were used for twoway
discrimination of the sound and defective material classes. The average spectra indicated
prominent bands at 1219 and 1476 (related to starch), 1941 (related to moisture), and 2117 nm
(related to protein). The loadings of principal component (PC) 1 exhibited similar bands. The objectwise
approach performed superiorly to the pixel-wise approach across all 13 analyses. Little
separation was observed in the principal component analysis (PCA) score plots in the pixel-wise
results due to a large similarity between classes. The object-wise approach utilised the average
spectrum for each maize kernel, and the overlap was reduced. Partial least squares discriminant
analysis (PLS-DA) models were calculated and used to classify an independent validation set of 30
sound kernels and 30 defective materials. The pixel-wise analyses achieved classification
accuracies ranging 75-99%. This approach was not able to accurately distinguish closely related
classes. The object-wise analyses performed well, with 8 of the 13 achieving 100% classification
accuracy, and the remaining 5 classes incurring only one error per analysis of 60 kernels.
Multispectral imaging followed to compare the two imaging techniques. Pixel-wise PCA was
applied to pre-process the spectral imaging data, followed by object-wise two-way PLS-DA
modelling using 17 sound kernels and 18 defective material objects. The PCA loadings revealed
that colour played a role in separating the classes, with a wide band appearing across 505, 525,
570 and 590 nm. Classification accuracies of 83-100% were achieved, and were generally slightly
lower than the results obtained for all classes using the NIR hyperspectral imaging instrument.
Spectral imaging was shown to be capable of separating white maize from 13 commonly
occurring defective materials. NIR hyperspectral imaging performed superiorly to multispectral
imaging, and the use of an object-wise data analysis approach further improved the accuracy of the
separations. These techniques have the potential to offer the maize industry a rapid, accurate and
objective alternative grading method.National Research Foundatio
Reduced wavelength spectral imaging for grading defect and asymptomatic Fusarium detection in white maize
Full text linkThesis (PhDFoodSc)--Stellenbosch University, 2020.ENGLISH ABSTRACT: The aim of this dissertation was to present the South African maize industry with an accurate and
affordable automated analytical technique for white maize grading and for identifying asymptomatic
Fusarium fungal contamination. This was achieved by using near infrared (NIR)
hyperspectral imaging, chemometric classification model development, optimal waveband selection
and hierarchical modelling.
White maize grade is assigned based on the content of 5 main categories in a maize
consignment, namely sound white maize, defective white maize, pinked white maize, yellow maize and
foreign materials. Defective white maize and foreign materials comprise further sub-categories,
giving a total of 17 classes. All of the categories stipulated in South African maize grading
legislation were simultaneously classified (1044 samples; 60 kernels of each class) using
NIR hyperspectral imaging and partial least squares discriminant analysis (PLS-DA) models
assembled in a hierarchical decision pathway. The hierarchical model divided the task into 25 small
steps (binary and ternary PLS-DA models), which progressed from the most easily classified classes
to the most difficult. The hierarchical model was based on the full NIR spectrum (288 wavebands)
and performed with an overall accuracy of 93.3% for the main categories. The classification of
sound white maize (88.3%), pinked white maize (83.3%) and yellow maize (75.0%) should ideally be
improved before the method is implemented for industry grading. Pinked white maize and
yellow maize are distinguishable due to the presence of anthocyanin and beta-carotene,
respectively, which both exhibit maximum absorption in the visible region and do not interact with
NIR radiation. The use of a spectral imaging system including the visible region is expected to
improve the classification of these classes.
Following the encouraging success of maize grading using the full NIR spectrum, waveband reduction
and optimisation was conducted to attempt simplified but accurate grading of white maize using a
recalculated hierarchical decision pathway. Three waveband selection techniques were
employed, namely waveband windows (48 wavebands), variable importance in projection (VIP) (21
wavebands) and covariance selection (CovSel) (13 wavebands). There was a loss of
performance in all three reduced waveband models. The waveband windows (87.1% main
category classification accuracy) and VIP waveband sets (84.5% main category
classification accuracy) performed with similar classification accuracies across the
numerous categories, but the VIP waveband set utilised less than half of the spectral variables.
The CovSel waveband set used the fewest wavebands but exhibited an unacceptable loss of
classification accuracy (81.9% main category classification accuracy). Overall, the VIP waveband
set (964, 1127, 1159, 1323, 1356, 1388, 1421, 1716, 1847,
1879, 1912, 1945, 2043, 2239, 2272, 2305, 2337, 2403, 2435, 2468 and 2501 nm), which was based on
only
7.3% of the 288 original spectral variables, was recommended as the best trade-off
between instrument performance and expected cost of the system.
A second issue in the South African maize industry was addressed, namely the detection of
single asymptomatically Fusarium infected kernels. NIR hyperspectral images of 224 visibly sound
(healthy) kernels were acquired prior to germination of the kernels in individual sterile
containers. Germination caused internal Fusarium infections to become visibly identifiable as external fungal growth, which was later
confirmed by conventional microbial testing. While only 3.3% of the kernels in the bulk samples
exhibited visible rotting symptoms (flagged during visual inspection), 32.1% of germinated kernels
were asymptomatically infected and capable of producing harmful fumonisin mycotoxins. Some of these
bulk samples contained fumonisin levels of 8 ppm (double the limit) but would have been
declared safe for human consumption based on manual inspection methods. This lack of
correlation between visible symptoms and safety emphasised the need for additional analytical
methods to determine Fusarium related risks. The pre-germination spectral images of the uninfected
and asymptomatically infected kernels were divided into two classes, and a PLS-DA model classified
the maize kernels with a classification accuracy of 67.0%. Considering the high food safety risk
associated with fumonisins, NIR hyperspectral imaging is not a viable method for detecting
asymptomatic Fusarium infections during South African white maize processing.
The results of this study demonstrated that NIR hyper- and multispectral imaging are
promising analytical techniques for automated maize grading, but not for the detection
of asymptomatic Fusarium infection. However, the results of the Fusarium germination study
provided insight into the status of Fusarium infection and fumonisins in the South African
maize industry that have not yet appeared in literature and emphasised the need for
industry-friendly mycotoxin testing methods.AFRIKAANSE OPSOMMING: Die doel van hierdie proefskrif was om die Suid-Afrikaanse mieliebedryf voor te stel
aan 'n akkurate en bekostigbare outomatiese analitiese tegniek vir witmielie-gradering en die
identifisering van asimptomatiese Fusarium-swambesmetting. Dit is bewerkstellig deur gebruik te
maak van naby-infrarooi (NIR) hiperspektrale beelding, chemometriese klassifikasies
modelontwikkeling, optimale golfband selektering en hiërargiese modellering.
Witmielie-graad word op grond van die inhoud van vyf hoofkategorieë in 'n mieliebesending, naamlik
gesonde witmielies, foutiewe witmielies, pienk witmielies, geelmielies en vreemde
materiale toegeken. Foutiewe witmielies en vreemde materiale bestaan uit verdere subkategorieë,
wat 'n totaal van 17 klasse gee. Al die kategorieë, soos uiteengesit in Suid-Afrikaanse
mielie-graderingswetgewing, is gelyktydig geklassifiseer (1044 monsters; 60 pitte van elke klas)
deur gebruik te maak van NIR-hiperspektrale beeldvorming en parsiële kleinste
kwadrate-diskriminantanalise (PLS-DA) modelle wat in 'n hiërargiese besluitweg saamgestel is. Die
hiërargiese model het die taak in 25 klein stappe (binêre en ternêre PLS-DA-modelle) verdeel, wat
van die maklikste klassifiseerbare klasse tot die moeilikste gevorder het. Die hiërargiese model
was op die volledige NIR-spektrum (288 golfbande) gebaseer en is vir die hoofkategorieë met 'n
algehele akkuraatheid van 93.3% uitgevoer. Die klassifikasie van gesonde witmielies (88.3%), pienk
witmielies (83.3%) en geelmielies (75.0%) moet verkieslik verbeter word voordat die metode
vir industrie-gradering geïmplementeer word. Pienk witmielies en geelmielies kan as
gevolg van die teenwoordigheid van antosianien en beta-karoteen, respektiewelik,
onderskei word wat beide 'n maksimum absorpsie in die sigbare gebied het en nie ‘n interaksie met
NIR-bestraling het nie. Die gebruik van 'n spektrale beeldstelsel, insluitend die
sigbare streek, sal na verwagting die klassifikasie van hierdie klasse verbeter.
Na die bemoedigende sukses van mielie-gradering deur die volledige NIR-spektrum te
gebruik, is golfbandvermindering en -optimalisering gedoen om 'n vereenvoudigde, maar
noukeurige gradering van witmielies te bewerkstellig met behulp van 'n
herberekende hiërargiese besluitneming. Drie golfbandseleksietegnieke is aangewend,
naamlik golfbandvensters (48 golfbande), veranderlike belang in projeksie (VIP) (21
golfbande) en seleksie van kovariansie (CovSel) (13 golfbande). Daar was in al drie die
golfbandmodelle 'n verlies aan prestasie. Die golfbandvensters (87.1% van die
hoofkategorie-klassifikasie- akkuraatheid) en VIP-golfbandstelle (84,5% van die
hoofkategorie-klassifikasie-akkuraatheid) is uitgevoer met soortgelyke klassifikasie-akkuraatheid
in die verskillende kategorieë, maar die VIP-golfbandstel het minder as die helfte van die
spektrale veranderlikes gebruik. Die CovSel-golfbandstel het die minste golfbande gebruik, maar
het 'n onaanvaarbare verlies aan klassifikasie-akkuraatheid getoon (81.9% in die
hoofkategorie- klassifikasie-akkuraatheid). In die algemeen is die VIP-golfbandstel (964, 1127,
1159, 1323, 1356, 1388, 1421,
1716, 1847, 1879, 1912, 1945, 2043, 2239, 2272, 2305, 2337, 2403, 2435, 2468 en 2501 nm), wat op
slegs
7,3% van die 288 oorspronklike spektrale veranderlikes gebaseer was, is aanbeveel as die beste
inruiling tussen instrumentprestasie en die verwagte koste van die stelsel. 'n Tweede kwessie in die Suid-Afrikaanse mieliebedryf is geadresseer, naamlik die
opsporing van
enkele asimptomaties Fusarium-besmette pitte. NIR hiperspektrale beelde van 224 sigbare (gesonde)
pitte is verkry voor die pitte, in individuele steriele houers, ontkieming ondergaan het.
Ontkieming het veroorsaak dat interne Fusarium-infeksies sigbaar identifiseerbaar word as eksterne
swamgroei, wat later deur konvensionele mikrobiese toetsing bevestig is. Alhoewel slegs
3.3% van die pitte in die massamonsters sigbare verrottingsimptome vertoon het (wat
tydens visuele inspeksie gemerk is), was 32.1% van die ontkiemde pitte asimptomaties besmet en is
in staat om skadelike fumonisien-mikotoksiene te produseer. Sommige van hierdie grootmaatmonsters
bevat fumonisienvlakke van 8 dpm (dubbel die wettige limiet), maar sou op grond van handmatige
inspeksiemetodes veilig vir menslike verbruik verklaar word. Hierdie gebrek aan korrelasie tussen
sigbare simptome en veiligheid beklemtoon die behoefte aan addisionele analitiese metodes
om Fusarium- verwante risiko's te bepaal. Die voor-ontkiemende spektrale beelde van die
onbesmette en asimptomaties besmette pitte is in twee klasse verdeel, en 'n PLS-DA-model
het die mieliepitte met 'n klassifikasie- akkuraatheid van 67.0% geklassifiseer. Met
inagneming van die hoë voedselveiligheidsrisiko verbonde aan fumonisiene, is NIR hiperspektrale
beelding nie 'n uitvoerbare metode om asimptomatiese Fusarium-infeksies tydens die verwerking van
Suid-Afrikaanse witmielies op te spoor nie.
Die resultate van hierdie studie het getoon dat NIR hiper- en multispektrale beelding
belowende analitiese tegnieke vir outomatiese mielie gradering is, maar nie vir die
opsporing van asimptomatiese Fusarium-infeksie nie. Die resultate van die
Fusarium-ontkiemingsstudie het egter insig gegee in die status van Fusarium-infeksie en fumonisiene
in die Suid-Afrikaanse mieliebedryf, wat nog nie in die literatuur verskyn het nie, en het die
behoefte aan industrie-vriendelike mikotoksien-toetsmetodes beklemtoon.Doctrora
koamabayili/VECTRON-author-checklist: VECTRON author checklist
No full textWe have done our best to complete the author checklist relating to the use of animals in the hut study. Note that the objective for the hut study was to evaluate the IRS treatment applications for residual efficacy against Anopheles mosquitoes, including the local An. coluzzii mosquito population. Cows were only used to attract mosquitoes into the huts and no tests were carried out directly on the cows. The author checklist is intended for use with studies where experiments are carried out on animals, which is why we have had such difficulty in completing this for the hut study, as many of the questions do not relate to how the cows were used
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