LC Class Research Articles

Machine learning based forest species susceptibility mapping using Sentinel 2A data and GIS: A case study of Ait Bouzid forest (Central High Atlas, Morocco)

In arid and semi-arid environments, producing accurate maps of forest tree cover using optical remote sensing data is essential to understand their spatial distributions and dynamics. In this respect, the current study aimed to explore the effectiveness of support vector machine (SVM), K nearest neighbors (KNN), and random forest (RF)machine learning (ML) models to map the forest tree species of Ait Bouzid region (Central High Atlas, Morocco) by using Sentinel-2A data. The results from all models showed that about 19-28%, 21-27%, 16-24%, 15-18%, and 0,3-0,32% of the area was covered by euphorbia, red juniper, cedar, holm oak, bare ground, and water body, respectively. According to the overall accuracy (OA) and kappa coefficient, the SVM classifier showed the highest OA (73%) and kappa (0.66) values, followed by KNN (OA=70%, kappa=0.62) and RF (OA=67%, kappa=0.59). Regarding LC classes, water, bare soil, and holm oak could be identified with the producer's accuracy attaining 100%, while red juniper and cedar were the most challenging classes to determine for all ML classifiers, with the producer's accuracy of 40-50% and 40-67%. This study revealed the potential of ML approaches coupled with multispectral Sentinel-2A data for forest species cartography in arid areas with high accuracy. Furthermore, it provides crucial information about forest tree species distribution for developing forest management plans.

Asymptotic convergence of the angular discretization error in the scalar flux computed from the particle transport equation with the method of discrete ordinates

The asymptotic convergence of the angular discretization error in the scalar flux solution of the particle transport equation computed with the Discrete Ordinates (SN) method with increasing quadrature order is examined. Five selected angular quadrature types are considered: Level Symmetric (LS), Legendre-Chebyshev Quadrangular (LCQ), Legendre-Chebyshev Triangular(LCT), Quadruple Range (QR) and Quadruple Range Spence-type (QRS) quadrature sets. We relate the SN angular discretization error to the quadrature error, and split the total flux into the uncollided flux and the fully collided flux, and then we verify the uncollided scalar flux error and the fully collided scalar flux error separately. After developing the theoretical basis for the relationship between true solution regularity and quadrature rule error, we employ a two-dimensional problem to verify the observed and theoretical convergence orders for the region-averaged uncollided and fully collided scalar flux errors. Numerical results show that the angular discretization errors in the region-averaged scalar flux obtained by different quadrature types converge with different rates, that are commensurate with the regularity order of the exact angular flux within the quadrature-designed integration interval. The angular discretization error in the uncollided region-averaged scalar flux obtained by LC class quadratures converges linearly, and the error obtained by QR class quadrature sets converges quadratically. The angular discretization error in the fully collided region-averaged scalar flux converges linearly for LC class quadratures, and faster-than-second order for QR class quadrature sets.

Mapping underrepresented land cover heterogeneity in arid regions: The Sahara-Sahel example

Arid and semi-arid regions comprise high levels of habitat heterogeneity that usually remain undetected in available global land cover (GLC) maps. The Sahara-Sahel is a critical example of how GLC maps continue to oversimplify the complex landscape structure of deserts and arid environments. In this work, we aimed to overcome a generalized knowledge gap concerning the LC heterogeneity of arid regions, using the largest warm desert in the world as a study case. We intended to generate a 30x30m land cover map for the Wet Sahara-Sahel and compare the results with currently available GLC maps (ESA GlobCover and GlobeLand30). To do this, we collected an extensive series of GPS field control points (n = 48,857) and associated descriptive traits. We included the control points in a Hierarchical Cluster Analyses (HCA), and the resulting groups were used as LC classes in Landsat 8 image classification. Independent control points (n = 10,082) suggested a robust regional classification (83.3% correctly classified) of land cover. The Sahara was the most representative ecoregion (around 70% of the study area) and exhibited the highest classification accuracy (91%). The final map is composed by a total of 18 classes, providing a higher number of classes for arid regions than currently available GLC maps. Differences were evident amongst the arid regions of the Sahara, in which the derived map presented a more complex land cover in comparison to the analysed GLC maps. The map derived in this study constitutes framework data for mapping local land cover information and for improving the effectiveness of the assessment and management of natural resources for both local human populations and biodiversity. These results highlight the prevalent need for improving local and regional land cover categorization of arid and semi-arid regions, areas whose land cover heterogeneity is still underrepresented by most of the available GLC maps.

Design of testing framework for code smell detection (OOPS) using BFO algorithm

Detection of bad smells refers to any indication in the program code of a execution that perhaps designate a issue, maintain the software and software evolution. Code Smell detection is a main challenging for software developers and their informal classification direct to the designing of various smell detection methods and software tools. It appraises 4 code smell detection tool in software like as a in Fusion, JDeodorant, PMD and Jspirit. In this research proposes a method for detection the bad code smells in software is called as code smell. Bad smell detection in software, OOSMs are used to identify the Source Code whereby Plug-in were implemented for code detection in which position of program initial code the bad smell appeared so that software refactoring can then acquire position. Classified the code smell, as a type of codes: long method, PIH, LPL, LC, SS and GOD class etc. Detection of the code smell and as a result applying the correct detection phases when require is significant to enhance the Quality of the code or program. The various tool has been proposed for detection of the code smell each one featured by particular properties. The main objective of this research work described our proposed method on using various tools for code smell detection. We find the major differences between them and dissimilar consequences we attained. The major drawback of current research work is that it focuses on one particular language which makes them restricted to one kind of programs only. These tools fail to detect the smelly code if any kind of change in environment is encountered. The base paper compares the most popular code smell detection tools on basis of various factors like accuracy, False Positive Rate etc. which gives a clear picture of functionality these tools possess. In this paper, a unique technique is designed to identify CSs. For this purpose, various object-oriented programming (OOPs)-based-metrics with their maintainability index are used. Further, code refactoring and optimization technique are applied to obtain low maintainability Index. Finally, the proposed scheme is evaluated to achieve satisfactory results. The results of the BFOA test defined that the lazy class caused framework defects in DLS, DR, and SE. However, the LPL caused no framework defects what so ever. The consequences of the connection rules test searched that the LCCS (Lazy Class Code Smell) caused structured defects in DE and DLS, which corresponded to the consequences of the BFOA test. In this research work, a proposed method is designed to verify the code smell. For this purpose, different OOPs based Software Metrics with their MI (Maintainability Index) are utilized. Further Code refactoring and optimization method id applied to attained the less maintainability index and evaluated to achieved satisfactory results.

The bond shear strength of methacrylate materials used to reduce dental and alveolar undercuts.

The reduction of dental and alveolar undercuts on plaster models is an important issue in the process of planning partial and complete prostheses. In recent years, new materials such as methacrylate resins that can be used to reduce undercuts have emerged. Their great advantage is high temperature insensitivity and relatively high ease of use. The study aimed at determining the factors that affect the shear bond strength, and which material can be better used at the laboratory stage of preparing the plaster model to facilitate the denture bearing area and reduce the traumatizing impact of the prosthesis. In the study, 2 composite materials Block-Out Gel LC (VOCO GmbH, Cuxhaven, Germany) and LC Block-Out Resin (Ultradent Products Inc., South Jordan, USA) were used for tests on the Tewerock and Stodent plaster. Specimens consisted of 20 mm × 10 mm × 10 mm plaster blocks as a base, and composite cylinders of 3 mm diameter and 5 mm height, attached to the blocks. The base of the sample was combined with a composite cylinder in the Individo Light Box halogen lamp (VOCO GmbH, Cuxhaven, Germany). A total of 120 samples were studied. The shear bond strength (SBS) test was performed using the Hounsfield H5KS model HTE S/N D83281 fitted with a 5.000-N head using a cutting knife speed of 5 mm/ min. LC Block-Out Resin and Block-Out Gel LC materials deposited on class III plaster and polymerized at temperatures of up to 100°C had the best SBS (5.59 MPa and 4.0 MPa, respectively). Samples made of LC Block-Out Resin and class IV plaster showed no statistically significant differences between all the groups. Additional polymerization under 2.4 bar was the most effective in improving SBS among Block-Out Gel LC and class IV plaster samples. The results of the studies show that both the plaster type and the polymerization process have a significant effect on the SBS of light-cured methacrylate material to plaster.

Using Logistic Regression to Examine Multiple Factors Related to E-book Use

Many studies have tried to identify factors that make electronic books (e-books) in academic libraries more likely to be used. For instance, are demand-driven acquisitions used more than titles in packages? Are e-books in the sciences used more than e-books on art? Most of these studies are limited to one or two variables. This study introduces logistic regression, which can incorporate multiple variables to determine which factors are the most useful in predicting e-book usage. The variables considered in this study are LC class, university press or other publisher, and platform. In the collection studied, the classes with the highest odds of being used were A (General Works), followed by F (History of the Americas), H (Social Sciences), and Q (Math and Science).

Compact complex manifolds bimeromorphic to locally conformally Kähler manifolds

We study compact complex manifolds bimeromorphic to locally conformally Kahler (LCK) manifolds. This is an analogy of studying a compact complex manifold bimeromorphic to a Kahler manifold. We give a negative answer for a question of Ornea, Verbitsky, Vuletescu by showing that there exists no LCK current on blow ups along a submanifold (dim $$\ge 1$$ ) of Vaisman manifolds. We show that a compact complex manifold with LCK currents satisfying a certain condition can be modified to an LCK manifold. Based on this fact, we define a compact complex manifold with a modification from an LCK manifold as a locally conformally class C (LC class C) manifold. We give examples of LC class C manifolds that are not LCK manifolds. Finally, we show that all LC class C manifolds are locally conformally balanced manifolds.

Humanities and Social Science Dissertations Published by University Presses: 2010–2014, Exploratory Observations

This study of humanities and social science dissertations published by university presses considers revised dissertations [RD’s] and their salient characteristics. Often dissertations in the humanities and social sciences become the sine qua non for advancement in academia; therefore, it is instructive to ascertain the ecology of dissertations published by university presses. Only revised dissertations [RD’s], and English language presses were surveyed from proprietary data provided by a North American book distributor [Yankee Book Peddler, Inc.] and were triaged for bibliographic aspects as well as for intellectual coverage. Disciplinary alignment, subject specializations, geographical distribution, as well degree of interdisciplinarity, and series publication highlight findings. Library of Congress Classification further articulated disciplinary orientation. Oxford and Cambridge University Presses, but presses are specialized by subject emphases. A significant number of RD’s are interdisciplinary, Eurocentric in subject and geographical coverage, historically oriented across LC Classes, and appear as titles in monographic series.

Employing crowdsourced geographic data and multi-temporal/multi-sensor satellite imagery to monitor land cover change: A case study in an urbanizing region of the Philippines

Land cover change (LCC) can have a significant impact on human and environmental well-being. LCC maps derived from historical remote sensing (RS) images are often used to evaluate the impacts of past LC changes and to construct models to predict future LC changes. Free moderate spatial resolution (~30m) optical and synthetic aperture radar (SAR) RS imagery is now becoming increasingly available for this LCC monitoring. However, the classification algorithms used to extract LC information from these images typically require “training data” for classification (i.e. points or polygons with LC class labels), and acquiring this labelled training data can be difficult and time-consuming. Alternatively, crowdsourced geographic data (CGD) has become widely available from online sources like OpenStreetMap (OSM), and it may provide a useful source of training data for LCC monitoring. A major challenge with utilizing CGD for LCC mapping, however, is the presence of class labelling errors, and these errors can vary spatially (e.g. due to differing levels of CGD contributor expertise) and temporally (e.g. due to time lag between CGD creation and RS imagery acquisition). In this study, we investigated a new LCC mapping method which utilizes free Landsat (optical) and PALSAR mosaic (SAR) satellite imagery in combination with labelled LC data extracted from CGD sources (the OSM “landuse” and “natural” polygon datasets). A semi-unsupervised classification approach was employed for the LCC mapping to reduce the effects of class label noise in the CGD. The main motivation and benefit of the proposed method is that it does not require training data to be manually collected, allowing for a faster and more automated assessment of LCC. As a case study, we applied the method to map LCC in the Laguna de Bay area of the Philippines over the 2007–2015 period. The LCC map produced using our proposed approach achieved an overall classification accuracy of 90.2%, providing evidence that CGD and multi-temporal/multi-sensor satellite imagery, when combined, have a great potential for LCC monitoring.

Fusing multiple existing space‐time land cover products

AbstractLand cover (LC) is a critical variable driving many environmental processes, so its assessment, monitoring, and characterization are essential. However, existing LC products, derived primarily from satellite spectral imagery, each have different temporal and spatial resolutions and different LC classes. Most effort is focused on either fusing a pair of LC products over a small space‐time region or on interpolating missing values in an individual LC product. Here, we review the complexities of LC identification and propose a method for fusing multiple existing LC products to produce a single LC record for a large spatial‐temporal grid, referred to as spatiotemporal categorical map fusion. We first reconcile the LC classes of different LC products and then present a probabilistic weighted nearest neighbor estimator of LC class. This estimator depends on three unknown parameters that are estimated using numerical optimization to maximize an agreement criterion that we define. We illustrate the method using six LC products over the Rocky Mountains and show the improvement gained by supplying the optimization with data‐driven information describing the spatial‐temporal behavior of each LC class. Given the massive size of the LC products, we show how the optimal parameters for a given year are often optimal for other years, leading to shorter computing times.

Land cover and land use changes in a Brazilian Cerrado landscape: drivers, processes, and patterns

ABSTRACTThe Cerrado is one of the most threatened biomes in South America. To create protection actions on any scale, understanding drivers and consequences of land cover and land use (LC and LU) is essential. This study defines the composition and configuration of a Cerrado landscape watershed from 1975 to 2011. Using Landsat images and socioeconomic census data, we determined the forces acting on LC and LU change processes and their consequences. LC classes differ from LU classes for landscape dominance and processes. Economic opportunities drove LU change and its spatial distribution was related to soil, streams, and roads. Deforestation was the main cause of forest loss but forest degradation was also important, with both presenting different patterns. The spatial distribution of bare soil was related to pasture in degradation and streams. Bare soil distribution was related to pasture in degradation and streams. We concluded that broad scale factors drove changes, but local features determined distribution, and that watershed conservation plans should act on different scales, with management being spatially explicit.

Taking a literature circles approach to teach Academic English

Abstract Literature circles (LC), an activity framework for classroom discussion, has been adapted for EFL classes to help students engage more deeply with reading texts. In this approach, students read texts outside of class, and discuss the texts in class, using a specified discussion framework. Originally developed for L1 classes as a tool for teaching literature, LC has been adapted for EFL classes, not only to help develop reading skills, but also to help students develop their discussion skills. However, to date, many adaptations of LC have relied on graded fiction as source material, which is not always appropriate for tertiary education. Feeling pressure to match course content with the labour market needs of our contemporary global society, English departments are increasingly being asked to include more academic content in their classes. This requires that non-fiction be used as source material. This preliminary study examines student perceptions of an LC class using non-fiction as source material. The subjects of this short, qualitative, pilot study were engineering students at a university in Japan. Procedures of the class and the issues that emerged are discussed.

Major forest changes and land cover transitions based on plant functional types derived from the ESA CCI Land Cover product

Land use and land cover change are of prime concern due to their impacts on CO2 emissions, climate change and ecological services. New global land cover products at 300m resolution from the European Space Agency (ESA) Climate Change Initiative Land Cover (CCI LC) project for epochs centered around 2000, 2005 and 2010 were analyzed to investigate forest area change and land cover transitions. Plant functional types (PFTs) fractions were derived from these land cover products according to a conversion table. The gross global forest loss between 2000 and 2010 is 172,171km2, accounting for 0.6% of the global forest area in year 2000. The forest changes are mainly distributed in tropical areas such as Brazil and Indonesia. Forest gains were only observed between 2005 and 2010 with a global area of 9844km2, mostly from crops in Southeast Asia and South America. The predominant PFT transition is deforestation from forest to crop, accounting for four-fifths of the total increase of cropland area between 2000 and 2010. The transitions from forest to bare soil, shrub, and grass also contributed strongly to the total areal change in PFTs. Different PFT transition matrices and composition patterns were found in different regions. The highest fractions of forest to bare soil transitions were found in the United States and Canada, reflecting forest management practices. Most of the degradation from grassland and shrubland to bare soil occurred in boreal regions. The areal percentage of forest loss and land cover transitions generally decreased from 2000–2005 to 2005–2010. Different data sources and uncertainty in the conversion factors (converting from original LC classes to PFTs) contribute to the discrepancy in the values of change in absolute forest area.

Use of Vegetation Index “Fingerprints” From Hyperion Data to Characterize Vegetation States Within Land Cover/Land Use Types in an Australian Tropical Savanna

Suites of spectral indices may be derived from hyperspectral sensors such as Hyperion on EO-1. Spectral indices linked to vegetation and landscape function that are scalable to multi-spectral global sensors, could provide “fingerprints” for vegetation states in tropical savannas. In this study, Hyperion images were acquired on three occasions throughout the dry season over each of two consecutive years in the tropical savanna near Darwin, Northern Territory, Australia (12°25 <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">'</sup> N,130°50 <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">'</sup> E) during 2005 and 2006. This paper examines the changes in fractional cover of photosynthetic and non-photosynthetic vegetation and bare soil and key diagnostic narrow band vegetation indices for major land cover/land use (LCLU) types over two contrasting post-monsoon seasons. The fractional cover proportions and vegetation indices responded strongly to the additional month of full monsoon rains in 2006 versus 2005. There were differences in vegetation indices sensitive to pigments, canopy water and cellulose between LU and LC classes, but within class variation was very high for large sized sample areas. When fine scale variation in vegetation indices and fractional cover were examined as “fingerprints” for small, more uniform areas of specific LC, distinct differences were evident. Vegetation indices and derived vegetation properties can be used to characterize vegetation states at the scale of natural and management-induced variation. The vegetation indices and fractional cover methods used here can be translated and scaled-up to current and new global sensors to improve description of vegetation structure and function in savannas.

Mutually Exclusive Cytoplasmic Dynein Regulation by NudE-Lis1 and Dynactin

Cytoplasmic dynein is responsible for a wide range of cellular roles. How this single motor protein performs so many functions has remained a major outstanding question for many years. Part of the answer is thought to lie in the diversity of dynein regulators, but how the effects of these factors are coordinated in vivo remains unexplored. We previously found NudE to bind dynein through its light chain 8 (LC8) and intermediate chain (IC) subunits (1), the latter of which also mediates the dynein-dynactin interaction (2). We report here that NudE and dynactin bind to a common region within the IC, and compete for this site. We find LC8 to bind to a novel sequence within NudE, without detectably affecting the dynein-NudE interaction. We further find that commonly used dynein inhibitory reagents have broad effects on the interaction of dynein with its regulatory factors. Together these results reveal an unanticipated mechanism for preventing dual regulation of individual dynein molecules, and identify the IC as a nexus for regulatory interactions within the dynein complex.

North American Approval Program coverage and cost study 1998/99

Blackwell’s Approval Program Coverage and Cost Study details subject areas and list prices of monographs covered by our New Titles program for academic library collections. The Study reports on titles treated, not on copies sold—each title is counted once, whether it was purchased by one library or by hundreds. The Study presents information on numbers of titles treated and average list price, arranged by Blackwell’s subjects and then by LC class, for all publishers and then for university presses exclusively. It also includes a detailed report of all treated titles by NLM class. Additionally, the report includes a breakdown of the non-subject characteristics (e.g., language and format) of treated titles. Since most of Blackwell’s Approval libraries are not profiled to receive books for titles coded with the Non-Subject Parameters (NSPs) Popular works and Lower undergraduate texts, we exclude titles with these NSPs from the Coverage and Cost Study.

Library of Congress Classification:· Does Organization of Knowledge Need a Shelf?

In the literature on cataloging and classification, the Library of Congress Classification (LoC) has been described as a generally acceptable library shelving device and shelfbrowsing mechanism for American libraries, based on LC literary warrant Indeed, from its inception, the various classifier never claimed that they developed LCC as a scientific system but rather as an utilitarian tool for reclassing and servicing large existing LC collections. Likewise, its critics rarely ever provided a discourse on the fact that it is a knowledge-based logical system, in which the records ofa literate culture are organized: the various manifestations of recognized knowledge fields, corresponding to their scientific framework at a given point in history. Since development of the last LC Class K (Law), classification has no longer been tied to the mandate of providing for retrospective conversion of existing LC holdings, and other classificatory techniques could be explored that advanced yet a more coherent concept classification. By freeing the electronic LCC from older policies and the constraints of providing for stable shelf arrangements for American libraries at large, its potential as a unique retrieval tool (browsing the virtual shelf) as well as a trans-class navigation tool for electronically-stored bibliographic information can be realized.

Optimally routing LC permutations on k-extra-stage cube-type networks

It is difficult to partition an arbitrary permutation into a minimum number of groups such that conflict-free paths for all source-destination pairs in each group can be established on an omega network. Based on linear algebra theory, this paper presents an optimal algorithm which solves this problem for the LC class of permutations on a large class of multi-stage networks. This algorithm extends the previous result which deals with the BPC class of permutations on the omega network.

Collection Assessment Using the RLG Conspectus

Collection development responsibilities can be difficult for newly hired librarians who lack an awareness of the existing collection and the needs and interests of the population to be served. To alleviate this problem at the University of Arizona Library, a collection assessment tool using the RLG Conspectus scheme is proposed. A model format is developed using General and Plant Ecology (QH540-549, QK901-938) LC Class collection as the evaluation area. Categories of information included in the conspectus format are curriculum, faculty research, identified emphasis areas, collection evaluation levels, and current collecting intensity in the sample study area. The developmental process involved is a good training methodology for newly hired librarians. The final product can be used as a source of current information for collection development judgments.

A use statistic for collection management: The 80/20 rule revisited

The statistical phenomenon known as the “80/20 rule” was introduced to the literature of libraries in 1969 by Richard Trueswell. This statistic has been cited in library use studies many times, but its application as an aid in allocating a library's acquisition's budget has never been explored. Utilizing data gathered from the automated circulation system of the University of Tennessee, Knoxville, the 80/20 statistic is computed for the collection as a whole and for selected LC classification ranges. Trueswell's findings are substantiated for the overall collection in that 20% of the most-circulated items account for about 80% of the circulations. Substantial deviation is found, however, when the statistic is computed for individual LC classes. This provides a valuable indicator of relative levels of use among the classification ranges, and offers a functional tool for allocating the acquisitions budget for optimum use.