Choosing Appropriate Taxonomic Units for Ecological Survey and Experimentation: the Response of Aristida to Management and Landscape Factors as an Example.

1997 ◽  
Vol 19 (1) ◽  
pp. 26 ◽  
Author(s):  
S Mcintyre ◽  
PG Filet

The use of appropriate taxonomic units to describe herbaceous vegetation is an issue of increasing importance due to developing interest in the effects of grazing and other management on plant diversity in pastures. We use data for the genus Aristida as an example to examine patterns of ecological response to grazing, pasture sowing and landscape position in different taxonomic units. Responses of Aristida at the level of genus, section and species were compared over the gradients. There was strong evidence of differential responses to these factors, both between sections within genus, and between species within sections. The planning and execution of botanical field descriptions involve striking a balance between taxonomic accuracy and precision that will best address the objectives of a particular project. The species of the genus Aristida have a range of ecological responses, the variety of which can not be captured in data sets which record Aristida as a single entity. As a result, management recommendations for the genus in its entirety are likely to be inaccurate. Although data collection might ideally record individual species, this is not always practicable. In any case, there may be many rare species in the data set, with occurrences too low to detect ecological pattern. Delineation of rare species may only be important if diversity issues are being examined. In other circumstances the use of an intermediate unit (e.g. section or species groups) may be appropriate. The latter approach may be required if there are practical limitations to the collection of data at specific level for all groups, or if the research objectives do not require a high level of precision.

Author(s):  
Agus Wibowo

Abstract: Implementation of guidance and counseling services should be based on the needs and problems of students, so the effectiveness of the service will be achieved to the fullest. But the reality is a lot of implementation of guidance and counseling services in schools, do not notice it. So that the completion of the problems experienced by students sama.Berangkat always use the services of this, the research level of effectiveness of guidance and counseling that implementation has been using the application activity instrumentation and data sets as the basis for an implementation of the service. The method used is a qualitative research subjects that teachers BK and Students at SMA Negeri 1 Metro. Data collection technique through interview, observation and documentation. Research results show that by utilizing activity instrumentation applications and data sets, the counseling services have a high level of effectiveness. In carrying out the service, BK teachers can identify problems and needs experienced by students, so that the efforts of the assistance provided to be more precise, and problem students can terentaskan optimally.Keyword: Guidance and Counseling, Instrumentation Applications, Data Association


2006 ◽  
Vol 38 ◽  
pp. 77-86 ◽  
Author(s):  
B. Peinado ◽  
J.L. Vega-Pla ◽  
M.A. Martínez ◽  
M. Galián ◽  
C. Barba ◽  
...  

SummaryThe Chato Murciano is the only surviving breed of pig of those historically farmed in the region of Murcia for their quality meat. At present, it is on the verge of extinction, having a population of only 260 reproductive animals. This paper describes the genetic studies made in the conservation and recovery programme of this breed of pig. A study of the morphological characterization of these animals was carried out first, measuring thirteen quantitative and six qualitative variables in a sample of 24 adult animals, 8 males and 16 females.Subsequently, investigation was made of the consanguinity of the individuals and of the population as well as the future influence of inbreeding in each generation. Finally, the accuracy and precision of the heterozygote-excess method was evaluated using two data sets from the Chato Murciano pig. One data set is an original population and the other is a F3+F4+F5 generation of a line created from mating a Chato Murciano female with a Large White boar as part of an absorption programme based on backcrosses with Chato Murciano boars.


2007 ◽  
Vol 73 ◽  
pp. 169-190 ◽  
Author(s):  
Mandy Jay ◽  
Michael P. Richards

This paper presents the results of new research into British Iron Age diet. Specifically, it summarises the existing evidence and compares this with new evidence obtained from stable isotope analysis. The isotope data come from both humans and animals from ten British middle Iron Age sites, from four locations in East Yorkshire, East Lothian, Hampshire, and Cornwall. These represent the only significant data-set of comparative humans (n = 138) and animals (n = 212) for this period currently available for the UK. They are discussed here alongside other evidence for diet during the middle Iron Age in Britain. In particular, the question of whether fish, or other aquatic foods, were a major dietary resource during this period is examined.The isotopic data suggest similar dietary protein consumption patterns across the groups, both within local populations and between them, although outliers do exist which may indicate mobile individuals moving into the sites. The diet generally includes a high level of animal protein, with little indication of the use of marine resources at any isotopically distinguishable level, even when the sites are situated directly on the coast. The nitrogen isotopic values also indicate absolute variation across these locations which is indicative of environmental background differences rather than differential consumption patterns and this is discussed in the context of the difficulty of interpreting isotopic data without a complete understanding of the ‘baseline’ values for any particular time and place. This reinforces the need for significant numbers of contemporaneous animals to be analysed from the same locations when interpreting human data-sets.


2011 ◽  
Vol 76 (3) ◽  
pp. 547-572 ◽  
Author(s):  
Charles Perreault

I examine how our capacity to produce accurate culture-historical reconstructions changes as more archaeological sites are discovered, dated, and added to a data set. More precisely, I describe, using simulated data sets, how increases in the number of known sites impact the accuracy and precision of our estimations of (1) the earliest and (2) latest date of a cultural tradition, (3) the date and (4) magnitude of its peak popularity, as well as (5) its rate of spread and (6) disappearance in a population. I show that the accuracy and precision of inferences about these six historical processes are not affected in the same fashion by changes in the number of known sites. I also consider the impact of two simple taphonomic site destruction scenarios on the results. Overall, the results presented in this paper indicate that unless we are in possession of near-total samples of sites, and can be certain that there are no taphonomic biases in the universe of sites to be sampled, we will make inferences of varying precision and accuracy depending on the aspect of a cultural trait’s history in question.


2021 ◽  
Vol 11 (5) ◽  
pp. 2232
Author(s):  
Francesca Noardo ◽  
Ken Arroyo Ohori ◽  
Thomas Krijnen ◽  
Jantien Stoter

Industry Foundation Classes (IFC) is a complete, wide and complex open standard data model to represent Building Information Models. Big efforts are being made by the standardization organization buildingSMART, to develop and maintain this standard in collaboration with researchers, companies and institutions. However, when trying to use IFC models from practice for automatic analysis, some issues emerge, as a consequence of a misalignment between what is prescribed by, or available in, the standard with the data sets that are produced in practice. In this study, a sample of models produced by practitioners for aims different from their explicit use within automatic processing tools is inspected and analyzed. The aim is to find common patterns in data set from practice and their possible discrepancies with the standard, in order to find ways to address such discrepancies in a next step. In particular, it is noticeable that the overall quality of the models requires specific additional care by the modellers before relying on them for automatic analysis, and a high level of variability is present concerning the storage of some relevant information (such as georeferencing).


2020 ◽  
Vol 221 (1) ◽  
pp. 586-602 ◽  
Author(s):  
Bin Liu ◽  
Yonghao Pang ◽  
Deqiang Mao ◽  
Jing Wang ◽  
Zhengyu Liu ◽  
...  

SUMMARY 4-D electrical resistivity tomography (ERT), an important geophysical method, is widely used to observe dynamic processes within static subsurface structures. However, because data acquisition and inversion consume large amounts of time, rapid changes that occur in the medium during a single acquisition cycle are difficult to detect in a timely manner via 4-D inversion. To address this issue, a scheme is proposed in this paper for restructuring continuously measured data sets and performing GPU-parallelized inversion. In this scheme, multiple reference time points are selected in an acquisition cycle, which allows all of the acquired data to be sequentially utilized in a 4-D inversion. In addition, the response of the 4-D inversion to changes in the medium has been enhanced by increasing the weight of new data being added dynamically to the inversion process. To improve the reliability of the inversion, our scheme uses actively varied time-regularization coefficients, which are adjusted according to the range of the changes in model resistivity; this range is predicted by taking the ratio between the independent inversion of the current data set and historical 4-D inversion model. Numerical simulations and experiments show that this new 4-D inversion method is able to locate and depict rapid changes in medium resistivity with a high level of accuracy.


Author(s):  
S. Palm ◽  
R. Sommer ◽  
A. Tessmann ◽  
U. Stilla

<p><strong>Abstract.</strong> In this paper we propose a strategy to focus ultra-high resolution single channel carborne SAR and airborne circular SAR (CSAR) data to image facades and vertical infrastructure. We illustrate the related theoretical background and the design of an optimal focusing geometry for carborne SAR applications while using backprojection focusing techniques. Of particular interest is thereby the determination of the minimum distance and orientation of the facade to the radar sensor. Potential image distortions due to a wrong choice of these parameters are illustrated. Effects on the final resolution of the data due to the rotation of the focusing geometry compared to typical airborne SAR are discussed. We validated the strategy by driving on conventional roads illuminating facades with an experimental mobile radar mapping (MRM) sensor operating at 300 GHz. We further present an adapted version of the proposed strategy to focus vertical infrastructure in CSAR data sets. By extracting the center coordinate and the principal orientation of an object from GiS data, the focusing plane is designed arbitrarily in the 3D space. For the CSAR data set, a radar sensor particularly designed for circular flight trajectories operating at 94 GHz was evaluated. An electrical pylon was chosen as potential target. In both applications, the final images show a high level of detail. The combination of proposed strategy and radar sensor with very high bandwidth is capable of subcentimeter imaging of facades. The height, shape and dimensions of objects can be extracted directly from the image geometry at very high accuracy.</p>


HortScience ◽  
2016 ◽  
Vol 51 (8) ◽  
pp. 972-979 ◽  
Author(s):  
Xinyi Zhang ◽  
Li Liao ◽  
Zhiyong Wang ◽  
Changjun Bai ◽  
Jianxiu Liu

Molecular genetic diversity and relationships among 86 Chrysopogon aciculatus (Retz.) Trin. accessions were assessed using intersimple sequence repeat (ISSR) and sequence-related amplified polymorphism (SRAP) markers. Twenty-five ISSR markers generated 283 amplification bands, of which 266 were polymorphic. In addition, 576 polymorphic bands were detected from 627 bands amplified using 30 SRAP primers. Both marker types revealed a high level of genetic diversity, with ISSR markers showing a higher proportion of polymorphic loci (PPL; 94%) than SRAP markers (91.87%). The ISSR and SRAP data were significantly correlated (r = 0.8023). Cluster analysis of the separate ISSR and SRAP data sets clustered the accessions into three groups, which generally were consistent with geographic provenance. Cluster analysis of the combined ISSR and SRAP data set revealed four major groups similar to those based solely on ISSR or SRAP markers. The findings demonstrate that ISSR and SRAP markers are reliable and effective tools for analysis of genetic diversity in C. aciculatus.


2020 ◽  
pp. 0887302X2093119 ◽  
Author(s):  
Rachel Rose Getman ◽  
Denise Nicole Green ◽  
Kavita Bala ◽  
Utkarsh Mall ◽  
Nehal Rawat ◽  
...  

With the proliferation of digital photographs and the increasing digitization of historical imagery, fashion studies scholars must consider new methods for interpreting large data sets. Computational methods to analyze visual forms of big data have been underway in the field of computer science through computer vision, where computers are trained to “read” images through a process called machine learning. In this study, fashion historians and computer scientists collaborated to explore the practical potential of this emergent method by examining a trend related to one particular fashion item—the baseball cap—across two big data sets—the Vogue Runway database (2000–2018) and the Matzen et al. Streetstyle-27K data set (2013–2016). We illustrate one implementation of high-level concept recognition to map a fashion trend. Tracking trend frequency helps visualize larger patterns and cultural shifts while creating sociohistorical records of aesthetics, which benefits fashion scholars and industry alike.


2018 ◽  
Vol 30 (12) ◽  
pp. 3309-3326 ◽  
Author(s):  
Yoichi Hayashi

We describe a simple method to transfer from weights in deep neural networks (NNs) trained by a deep belief network (DBN) to weights in a backpropagation NN (BPNN) in the recursive-rule eXtraction (Re-RX) algorithm with J48graft (Re-RX with J48graft) and propose a new method to extract accurate and interpretable classification rules for rating category data sets. We apply this method to the Wisconsin Breast Cancer Data Set (WBCD), the Mammographic Mass Data Set, and the Dermatology Dataset, which are small, high-abstraction data sets with prior knowledge. After training these three data sets, our proposed rule extraction method was able to extract accurate and concise rules for deep NNs trained by a DBN. These results suggest that our proposed method could help fill the gap between the very high learning capability of DBNs and the very high interpretability of rule extraction algorithms such as Re-RX with J48graft.


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