scholarly journals Components of a Digital Specimen Architecture for Biological Collections

2021 ◽  
Vol 5 ◽  
Author(s):  
Aimee Stewart
Keyword(s):  
High Performance ◽  
Application Programming Interface ◽  
Vital Role ◽  
Sources Of Information ◽  
Collections Management ◽  
Data Set ◽  
Data Infrastructure ◽  
Management Platform ◽  
Integration Architecture ◽  
Analytical Services

In 2020, we began developing software components for an Application Programming Interface (API)-based integration architecture (the “Specify Network”) to leverage the global footprint of the Specify 7 collections management platform (www.specifysoftware.org) and the analytical services of the Lifemapper (lifemapper.org) and Biotaphy (biotaphy.org) Projects. The University of Kansas Lifemapper Project is a community gateway for species distribution and macroecological modeling. The Biotaphy Project, an extension of Lifemapper, is the product of a six-year, U.S. National Science Foundation-funded collaboration among researchers at the Universities of Michigan, Florida, and Kansas. Biotaphy's primary scope is to use big data methods and high-performance computing to integrate species occurrence data with phylogenetic and biogeographic data sets for large taxonomic and spatial scale analyses. Our initial integrations between Biotaphy and the Specify Network enable Specify users to easily discover remote information related to the specimens in their collection. The widely-discussed, digital specimen architecture being championed by DiSSCo (Distributed System of Scientific Collections www.dissco.eu) and others (https://bit.ly/3jfsAgz) will change data communications between biodiversity collections and the broader biodiversity data community. Those network interactions will evolve from being predominantly one-way, batch-oriented transfers of information from museums to aggregators, to an n-way communications topology that will make specimen record discovery, updates and usage much easier to accomplish. But museum specimens and their catalogs will no longer be an intellectual endpoint of species documentation. Rather, records in collections management systems will increasingly serve as a point of departure for data synthesis, which takes place outside of institutional data domains, and which will overlay the legacy role of museums as authoritative sources of information about the diversity and distribution of life on Earth. Biological museum institutions will continue to play a vital role as the foundation of a global data infrastructure connecting aggregators, collaborative databases, analysis engines, journal publishers, and data set archives. In this presentation, we will provide an update on the components and capabilities that make up integrations in the Specify Network as an exemplar of the global architecture envisaged by the biodiversity research community.

scholarly journals The MRC IEU OpenGWAS data infrastructure

2020 ◽  
Author(s):  
Ben Elsworth ◽  
Matthew Lyon ◽  
Tessa Alexander ◽  
Yi Liu ◽  
Peter Matthews ◽  
...  
Keyword(s):  
High Performance ◽  
Association Studies ◽  
Application Programming Interface ◽  
Third Party ◽  
Reference Sequence ◽  
Genome Wide Association Studies ◽  
Genetic Associations ◽  
Data Infrastructure ◽  
Molecular Phenotypes ◽  
Analytical Tools

AbstractData generated by genome-wide association studies (GWAS) are growing fast with the linkage of biobank samples to health records, and expanding capture of high-dimensional molecular phenotypes. However the utility of these efforts can only be fully realised if their complete results are collected from their heterogeneous sources and formats, harmonised and made programmatically accessible.Here we present the OpenGWAS database, an open source, open access, scalable and high-performance cloud-based data infrastructure that imports and publishes complete GWAS summary datasets and metadata for the scientific community. Our import pipeline harmonises these datasets against dbSNP and the human genome reference sequence, generates summary reports and standardises the format of results and metadata. Users can access the data via a website, an application programming interface, R and Python packages, and also as downloadable files that can be rapidly queried in high performance computing environments.OpenGWAS currently contains 126 billion genetic associations from 14,582 complete GWAS datasets representing a range of different human phenotypes and disease outcomes across different populations. We developed R and Python packages to serve as conduits between these GWAS data sources and a range of available analytical tools, enabling Mendelian randomization, genetic colocalisation analysis, fine mapping, genetic correlation and locus visualisation.OpenGWAS is freely accessible at https://gwas.mrcieu.ac.uk, and has been designed to facilitate integration with third party analytical tools.

Machine Learning Verdict of EEG Signals in Brain Computer Interface

2018 ◽  
pp. 429-441
Author(s):  
M. Jeyanthi ◽  
C. Velayutham
Keyword(s):  
Nearest Neighbor ◽  
Technology Development ◽  
Vital Role ◽  
Svm Classifier ◽  
K Nearest Neighbor ◽  
Data Mining Technique ◽  
Data Set ◽  
Eeg Data ◽  
Irrelevant Attributes

In Science and Technology Development BCI plays a vital role in the field of Research. Classification is a data mining technique used to predict group membership for data instances. Analyses of BCI data are challenging because feature extraction and classification of these data are more difficult as compared with those applied to raw data. In this paper, We extracted features using statistical Haralick features from the raw EEG data . Then the features are Normalized, Binning is used to improve the accuracy of the predictive models by reducing noise and eliminate some irrelevant attributes and then the classification is performed using different classification techniques such as Naïve Bayes, k-nearest neighbor classifier, SVM classifier using BCI dataset. Finally we propose the SVM classification algorithm for the BCI data set.

Covid-19 – rumours and facts in media

2020 ◽  
Vol 11 (SPL1) ◽  
pp. 171-174
Author(s):  
Tarare Toshida ◽  
Chaple Jagruti
Keyword(s):  
Social Media ◽  
Preventive Measures ◽  
Vital Role ◽  
The Other ◽  
Sources Of Information ◽  
Other Hand ◽  
Corona Virus ◽  
The People ◽  
The World

The covid-19 resulted in broad range of spread throughout the world in which India has also became a prey of it and in this situation the means of media is extensively inϑluencing the mentality of the people. Media always played a role of loop between society and sources of information. In this epidemic also media is playing a vital role in shaping the reaction in ϑirst place for both good and ill by providing important facts regarding symptoms of Corona virus, preventive measures against the virus and also how to deal with any suspect of disease to overcome covid-19. On the other hand, there are endless people who spread endless rumours overs social media and are adversely affecting life of people but we always count on media because they provide us with valuable answers to our questions, facts and everything in need. Media always remains on top of the line when it comes to stop the out spread of rumours which are surely dangerous kind of information for society. So on our side we should react fairly and maturely to handle the situation to keep it in the favour of humanity and help government not only to ϑight this pandemic but also the info emic.

scholarly journals Hugoniot Data and Equation of State Parameters for an Ultra-High Performance Concrete

2021 ◽  
Author(s):  
C. Sauer ◽  
F. Bagusat ◽  
M.-L. Ruiz-Ripoll ◽  
C. Roller ◽  
M. Sauer ◽  
...  
Keyword(s):  
Equation Of State ◽  
High Performance ◽  
High Performance Concrete ◽  
Applied Pressure ◽  
High Strength ◽  
Parameter Study ◽  
Ultra High Performance Concrete ◽  
Data Set ◽  
Shock Response ◽  
Particle Velocities

AbstractThis work aims at the characterization of a modern concrete material. For this purpose, we perform two experimental series of inverse planar plate impact (PPI) tests with the ultra-high performance concrete B4Q, using two different witness plate materials. Hugoniot data in the range of particle velocities from 180 to 840 m/s and stresses from 1.1 to 7.5 GPa is derived from both series. Within the experimental accuracy, they can be seen as one consistent data set. Moreover, we conduct corresponding numerical simulations and find a reasonably good agreement between simulated and experimentally obtained curves. From the simulated curves, we derive numerical Hugoniot results that serve as a homogenized, mean shock response of B4Q and add further consistency to the data set. Additionally, the comparison of simulated and experimentally determined results allows us to identify experimental outliers. Furthermore, we perform a parameter study which shows that a significant influence of the applied pressure dependent strength model on the derived equation of state (EOS) parameters is unlikely. In order to compare the current results to our own partially reevaluated previous work and selected recent results from literature, we use simulations to numerically extrapolate the Hugoniot results. Considering their inhomogeneous nature, a consistent picture emerges for the shock response of the discussed concrete and high-strength mortar materials. Hugoniot results from this and earlier work are presented for further comparisons. In addition, a full parameter set for B4Q, including validated EOS parameters, is provided for the application in simulations of impact and blast scenarios.

An approach for document retrieval using cluster-based inverted indexing

2021 ◽  
pp. 016555152110184
Author(s):  
Gunjan Chandwani ◽  
Anil Ahlawat ◽  
Gaurav Dubey
Keyword(s):  
High Performance ◽  
Clustering Algorithm ◽  
Pearson Correlation ◽  
Relevant Information ◽  
Document Retrieval ◽  
Bhattacharyya Distance ◽  
Data Set ◽  
Query Matching ◽  
Inverted Indexing ◽  
Query Optimisation

Document retrieval plays an important role in knowledge management as it facilitates us to discover the relevant information from the existing data. This article proposes a cluster-based inverted indexing algorithm for document retrieval. First, the pre-processing is done to remove the unnecessary and redundant words from the documents. Then, the indexing of documents is done by the cluster-based inverted indexing algorithm, which is developed by integrating the piecewise fuzzy C-means (piFCM) clustering algorithm and inverted indexing. After providing the index to the documents, the query matching is performed for the user queries using the Bhattacharyya distance. Finally, the query optimisation is done by the Pearson correlation coefficient, and the relevant documents are retrieved. The performance of the proposed algorithm is analysed by the WebKB data set and Twenty Newsgroups data set. The analysis exposes that the proposed algorithm offers high performance with a precision of 1, recall of 0.70 and F-measure of 0.8235. The proposed document retrieval system retrieves the most relevant documents and speeds up the storing and retrieval of information.

scholarly journals Effects of Molecular Weight of Functionalized Liquid Butadiene Rubber as a Processing Aid on the Properties of SSBR/Silica Compounds

Polymers ◽  
2021 ◽  
Vol 13 (6) ◽  
pp. 850
Author(s):  
Donghyuk Kim ◽  
Byungkyu Ahn ◽  
Kihyun Kim ◽  
JongYeop Lee ◽  
Il Jin Kim ◽  
...  
Keyword(s):  
Molecular Weight ◽  
Anionic Polymerization ◽  
High Performance ◽  
Crosslink Density ◽  
Functional Group ◽  
Vital Role ◽  
Butadiene Rubber ◽  
Molecular Weights ◽  
Mooney Viscosity ◽  
Silica Dispersion

Liquid butadiene rubber (LqBR) which used as a processing aid play a vital role in the manufacturing of high-performance tire tread compounds. However, the studies on the effect of molecular weight, microstructure, and functionalization of LqBR on the properties of compounds are still insufficient. In this study, non-functionalized and center-functionalized liquid butadiene rubbers (N-LqBR and C-LqBR modified with ethoxysilyl group, respectively) were synthesized with low vinyl content and different molecular weights using anionic polymerization. In addition, LqBR was added to the silica-filled SSBR compounds as an alternative to treated distillate aromatic extract (TDAE) oil, and the effect of molecular weight and functionalization on the properties of the silica-filled SSBR compound was examined. C-LqBR showed a low Payne effect and Mooney viscosity because of improved silica dispersion due to the ethoxysilyl functional group. Furthermore, C-LqBR showed an increased crosslink density, improved mechanical properties, and reduced organic matter extraction compared to the N-LqBR compound. LqBR reduced the glass transition temperature (Tg) of the compound significantly, thereby improving snow traction and abrasion resistance compared to TDAE oil. Furthermore, the energy loss characteristics revealed that the hysteresis loss attributable to the free chain ends of LqBR was dominant.

scholarly journals A Fast and Lightweight Method with Feature Fusion and Multi-Context for Face Detection

2018 ◽  
Vol 10 (8) ◽  
pp. 80
Author(s):  
Lei Zhang ◽  
Xiaoli Zhi
Keyword(s):  
Face Detection ◽  
Graphics Processing Units ◽  
High Performance ◽  
Feature Fusion ◽  
Local Context ◽  
Data Set ◽  
Global Context ◽  
Detection Algorithms ◽  
Multi Scale ◽  
Benchmark Datasets

Convolutional neural networks (CNN for short) have made great progress in face detection. They mostly take computation intensive networks as the backbone in order to obtain high precision, and they cannot get a good detection speed without the support of high-performance GPUs (Graphics Processing Units). This limits CNN-based face detection algorithms in real applications, especially in some speed dependent ones. To alleviate this problem, we propose a lightweight face detector in this paper, which takes a fast residual network as backbone. Our method can run fast even on cheap and ordinary GPUs. To guarantee its detection precision, multi-scale features and multi-context are fully exploited in efficient ways. Specifically, feature fusion is used to obtain semantic strongly multi-scale features firstly. Then multi-context including both local and global context is added to these multi-scale features without extra computational burden. The local context is added through a depthwise separable convolution based approach, and the global context by a simple global average pooling way. Experimental results show that our method can run at about 110 fps on VGA (Video Graphics Array)-resolution images, while still maintaining competitive precision on WIDER FACE and FDDB (Face Detection Data Set and Benchmark) datasets as compared with its state-of-the-art counterparts.

Error identification in orbital laser altimeter data by machine learning

2021 ◽  
Author(s):  
Oliver Stenzel ◽  
Robin Thor ◽  
Martin Hilchenbach
Keyword(s):  
Machine Learning ◽  
High Performance ◽  
Space Science ◽  
Altimeter Data ◽  
Laser Altimetry ◽  
Error Identification ◽  
Laser Altimeter ◽  
Data Set ◽  
Baseline Design ◽  
Solar System Bodies

<p>Orbital Laser altimeters deliver a plethora of data that is used to map planetary surfaces [1] and to understand interiors of solar system bodies [2]. Accuracy and precision of laser altimetry measurements depend on the knowledge of spacecraft position and pointing and on the instrument. Both are important for the retrieval of tidal parameters. In order to assess the quality of the altimeter retrievals, we are training and implementing an artificial neural network (ANN) to identify and exclude scans from analysis which yield erroneous data. The implementation is based on the PyTorch framework [3]. We are presenting our results for the MESSENGER Mercury Laser Altimeter (MLA) data set [4], but also in view of future analysis of the BepiColombo Laser Altimeter (BELA) data, which will arrive in orbit around Mercury in 2025 on board the Mercury Planetary Orbiter [5,6]. We further explore conventional methods of error identification and compare these with the machine learning results. Short periods of large residuals or large variation of residuals are identified and used to detect erroneous measurements. Furthermore, long-period systematics, such as those caused by slow variations in instrument pointing, can be modelled by including additional parameters.<br>[1] Zuber, Maria T., David E. Smith, Roger J. Phillips, Sean C. Solomon, Gregory A. Neumann, Steven A. Hauck, Stanton J. Peale, et al. ‘Topography of the Northern Hemisphere of Mercury from MESSENGER Laser Altimetry’. Science 336, no. 6078 (13 April 2012): 217–20. https://doi.org/10.1126/science.1218805.<br>[2] Thor, Robin N., Reinald Kallenbach, Ulrich R. Christensen, Philipp Gläser, Alexander Stark, Gregor Steinbrügge, and Jürgen Oberst. ‘Determination of the Lunar Body Tide from Global Laser Altimetry Data’. Journal of Geodesy 95, no. 1 (23 December 2020): 4. https://doi.org/10.1007/s00190-020-01455-8.<br>[3] Paszke, Adam, Sam Gross, Francisco Massa, Adam Lerer, James Bradbury, Gregory Chanan, Trevor Killeen, et al. ‘PyTorch: An Imperative Style, High-Performance Deep Learning Library’. Advances in Neural Information Processing Systems 32 (2019): 8026–37.<br>[4] Cavanaugh, John F., James C. Smith, Xiaoli Sun, Arlin E. Bartels, Luis Ramos-Izquierdo, Danny J. Krebs, Jan F. McGarry, et al. ‘The Mercury Laser Altimeter Instrument for the MESSENGER Mission’. Space Science Reviews 131, no. 1 (1 August 2007): 451–79. https://doi.org/10.1007/s11214-007-9273-4.<br>[5] Thomas, N., T. Spohn, J. -P. Barriot, W. Benz, G. Beutler, U. Christensen, V. Dehant, et al. ‘The BepiColombo Laser Altimeter (BELA): Concept and Baseline Design’. Planetary and Space Science 55, no. 10 (1 July 2007): 1398–1413. https://doi.org/10.1016/j.pss.2007.03.003.<br>[6] Benkhoff, Johannes, Jan van Casteren, Hajime Hayakawa, Masaki Fujimoto, Harri Laakso, Mauro Novara, Paolo Ferri, Helen R. Middleton, and Ruth Ziethe. ‘BepiColombo—Comprehensive Exploration of Mercury: Mission Overview and Science Goals’. Planetary and Space Science, Comprehensive Science Investigations of Mercury: The scientific goals of the joint ESA/JAXA mission BepiColombo, 58, no. 1 (1 January 2010): 2–20. https://doi.org/10.1016/j.pss.2009.09.020.</p>

scholarly journals Pengaruh Etos Kerja Terhadap Kinerja Karyawan PT. AE

2017 ◽  
Vol 3 (2) ◽  
pp. 150
Author(s):  
Andri Hadiansyah ◽  
Rini Purnamasari Yanwar
Keyword(s):  
High Performance ◽  
Work Ethic ◽  
Employee Performance ◽  
Linear Regression Analysis ◽  
Multiple Linear Regression Analysis ◽  
Positive Influence ◽  
Vital Role ◽  
Theoretical Test ◽  
High Work ◽  
Synergistic Relationship

<p><em>Abstrak -<strong> </strong></em><strong>U</strong><strong>ntuk dapat mencapai hubungan yang sinergis, perusahaan harus dapat memperhatikan pola kinerja karyawannya.</strong><strong> </strong><strong>K</strong><strong>aryawan yang bermutu dan dapat menghasilkan kinerja yang tinggi adalah karyawan yang dibutuhkan oleh suatu organisasi. Peran yang sangat vital dalam mewujudkan prestasi kinerja seorang karyawan adalah dirinya sendiri. Bagaimana dia memiliki semangat dan etos kerja yang tinggi untuk dapat memberikan pengaruh positif pada lingkungannya. Karyawan yang memiliki pemikiran yang luhur mengenai pekerjaannya dapat bekerja dengan tulus. Suatu pandangan dan sikap terhadap kerja dikenal dengan istilah etos kerja. Penelitian ini bertujuan untuk melakukan uji teoritik mengenai pengaruh etos kerja terhadap kinerja karyawan PT. AE. Untuk menguji pengaruh variabel etos kerja terhadap kinerja karyawan digunakan analisis regresi linear berganda dengan menyebar 132 kuesioner pada karyawan PT. AE. Setelah dianalisis didapat hasil R square 0.724 dengan signifikansi</strong><strong> </strong><strong>(p&lt;0.05), yang berarti etos kerja memberikan pengaruh secara signifikan</strong><strong> </strong><strong>terhadap kinerja karyawan sebesar 72.4%.</strong><strong></strong></p><p><strong><em> </em></strong></p><p><strong><em>Kata Kunci</em></strong><em>: Etika Kerja, Performa Kerja </em></p><p> </p><p><em>Abstract - </em><strong>T</strong><strong>o be able to achieve a synergistic relationship, the company should be able to notice employee performance. Employees who are qualified and able to produce high performance is needed by the organization. A very vital role in realizing the achievement of the performance of an employee is himself. How does he have the spirit and high work ethic to be a positive influence on the environment. Employees who have lofty thoughts about the job can work sincerely. An outlook and attitude towards work is known as the work ethic. This study aims to perform a theoretical test on the effect of the work ethic on the performance of employees of PT. AE. To test the effect of variables on the</strong> <strong>performance of the employee's work ethic multiple linear regression analysis was used, by spread 132 questionnaires to employees of PT. AE. Having analyzed the results obtained R square 0.724 with 0.000 significance (p &lt;0.05), which means the work ethic significant influence on employee performance amounted to 72.4%. The dominant aspect of the work ethic that effect the performance is the view of work is trustworthy.</strong></p><p> </p><p><em><strong>Keywords:</strong> Work ethic, Employee performance</em></p>

scholarly journals Optimization Aspects of an Ejector Type Hypersonic Thrust Nozzle

1992 ◽  
Author(s):  
G. Trittler ◽  
E. Eckert ◽  
M. Göing
Keyword(s):  
High Performance ◽  
Exhaust System ◽  
Vital Role ◽  
Calculation Model ◽  
Nozzle Geometry ◽  
Design Parameters ◽  
Axial Thrust ◽  
Thrust Coefficient ◽  
Wide Range ◽  
Low Performance

Hypersonic aircraft projects are highly dependant on efficient propulsion systems. High performance and integration within the airframe play a vital role in the overall concept. Particular attention must be paid to the exhaust system that is submitted to a wide range of operational requirements. An optimization of the nozzle geometry for high flight Mach numbers will lead to a low performance at the transonic flight regime. The additional use of secondary ejector air flow at transonic speeds is one option to improve the thrust behaviour of the nozzle. In the presented paper performance data of single expansion ramp ejector type nozzles are predicted using a calculation model based on a method-of-characteristics algorithm. For optimization purposes the effects of various design parameters on axial thrust coefficient and thrust vector angle are discussed. The geometric parameters investigated are the length of the lower nozzle wall and its deflection angle as well as the ejector slot location and its cross-section.

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