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The Evaluation of Child Capacity by Machine Learning According to the region

Journal of Computer and Communications 2022年第6期10卷 90-98页

作者： Jamyandorj Narantuya Tsend Ganbat Department of Science and Engineering University of Mandakh Ulaanbaatar Mongolia School of Information and Communication Technology Mongolian University of Science and Technology Ulaanbaatar Mongolia

Mongolian territory is 1.5 million square kilometers, there are 1.439 kindergartens that include 263.333 children. Mongolia has 5 regional zones. The research was made on selected provinces such as Sukhbaatar district from Ulaanbaatar region, Huvsgul aimag from Khangai region, Umnugobi from Central region, Dornod aimag from Eastern region and Bayan-Ulgii from Western region. Total 450 preschool children at age of 3 - 5 years old (30 children at every 3, 4 and 5 years old) were selected randomly, they performed 5 tasks of Math according to the curriculum. The classification of age, sex and region was made under cluster analyses of children’s mathematical ability using research method. The purpose of the research is classification of province zone, determination of inequality and difference between rural and urban areas. It is made support for developer’s policy and decision makers of education under the base of financing and sharing kindergarten budget, specialization, retraining of teachers and children, developing, elaboration and planning curriculum.

关键词： Data Mining Machine Learning Clustering HCPC r programming

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One hundred years of neurosciences in the arts and humanities, a bibliometric review

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PHILOSOPHY ETHICS AND HUMANITIES IN MEDICINE 2023年第1期18卷 17-17页

作者： Cebral-Loureda, Manuel Sanabria-Z, Jorge ramirez-Moreno, Mauricio A. Kaminsky-Castillo, Irina Tecnol Monterrey Sch Humanities & Educ Humanist Studies Dept Monterrey Mexico Tecnol Monterrey Inst Future Educ Monterrey Mexico Tecnol Monterrey Sch Engn & Sci Mechatron Dept Monterrey Mexico

BackgroundNeuroscientific approaches have historically triggered changes in the conception of creativity and artistic experience, which can be revealed by noting the intersection of these fields of study in terms of variables such as global trends, methodologies, objects of study, or application of new technologies;however, these neuroscientific approaches are still often considered as disciplines detached from the arts and humanities. In this light, the question arises as to what evidence the history of neurotechnologies provides at the intersection of creativity and aesthetic *** conducted a century-long bibliometric analysis of key parameters in multidisciplinary studies published in the Scopus database. Screening techniques based on the PrISMA method and advanced data analysis techniques were applied to 3612 documents metadata from the years 1922 to 2022. We made graphical representations of the results applying algorithmic and clusterization processes to keywords and authors *** the analyses, we found a) a shift from a personality-focus quantitative analysis to a field-focus qualitative approach, considering topics such as art, perception, aesthetics and beauty;b) The locus of interest in fMrI-supported neuroanatomy has been shifting toward EEG technologies and models based on machine learning and deep learning in recent years;c) four main clusters were identified in the study approaches: humanistic, creative, neuroaesthetic and medical;d) the neuroaesthetics cluster is the most central and relevant, mediating between creativity and neuroscience;e) neuroaesthetics and neuroethics are two of the neologism that better characterizes the challenges that this convergence of studies will have in the next *** a longitudinal analysis, we evidenced the great influence that neuroscience is having on the thematic direction of the arts and humanities. The perspective presented shows how this field is being consoli

关键词： Neuro-Arts Neurosciences Humanities Scopus r programming Neuroaesthetics Higher Education Educational innovation

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palaeoverse: A community-driven r package to support palaeobiological analysis

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METHODS IN ECOLOGY AND EVOLUTION 2023年第9期14卷 2205-2215页

作者： Jones, Lewis A. Gearty, William Allen, Bethany J. Eichenseer, Kilian Dean, Christopher D. Galvan, Sofia Kouvari, Miranta Godoy, Pedro L. Nicholl, Cecily S. C. Buffan, Lucas Dillon, Erin M. Flannery-Sutherland, Joseph T. Chiarenza, Alfio Alessandro Univ Vigo Dept Ecol & Biol Anim Grp Ecol Anim Vigo Spain Amer Museum Nat Hist Div Paleontol New York NY 10024 USA Swiss Fed Inst Technol Dept Biosyst Sci & Engn Basel Switzerland Swiss Inst Bioinformat Computat Evolut Grp Lausanne Switzerland Univ Durham Dept Earth Sci Durham England UCL Dept Earth Sci London England Nat Hist Museum Life Sci Dept London England Univ Sao Paulo Fac Filosofia Ciencias & Letras Ribeirao Preto Lab Paleontol Ribeirao Preto SP Brazil SUNY Stony Brook Dept Anat Sci Stony Brook NY 11794 USA Univ Claude Bernard Lyon 1 Ecole Normale Super Lyon Dept Biol Lyon 07 France Smithsonian Trop Res Inst Balboa Panama Univ Calif Santa Barbara Dept Ecol Evolut & Marine Biol Santa Barbara CA 93106 USA Univ Bristol Sch Earth Sci Bristol Avon England

1. The open-source programming language 'r' has become a standard tool in the palaeobiologist's toolkit. Its popularity within the palaeobiological community continues to grow, with published articles increasingly citing the usage of r and r packages. However, there are currently a lack of agreed standards for data preparation and available frameworks to support the implementation of such standards. Consequently, data preparation workflows are often unclear and not reproducible, even when code is provided. Moreover, due to a lack of code accessibility and documentation, palaeobiologists are often forced to 'reinvent the wheel' to find solutions to issues already solved by other members of the community. 2. Here, we introduce palaeoverse, a community-driven r package to aid data preparation and exploration for quantitative palaeobiological research. The package is freely available and has three core principles: (1) streamline data preparation and analyses;(2) enhance code readability;and (3) improve reproducibility of results. To develop these aims, we assessed the analytical needs of the broader palaeobiological community using an online survey, in addition to incorporating our own experiences. 3. In this work, we first report the findings of the survey, which shaped the development of the package. Subsequently, we describe and demonstrate the functionality available in palaeoverse and provide usage examples. Finally, we discuss the resources we have made available for the community and our future plans for the broader Palaeoverse project. 4. palaeoverse is a community-driven r package for palaeobiology, developed with the intention of bringing palaeobiologists together to establish agreed standards for high-quality quantitative research. The package provides a user-friendly platform for preparing data for analysis with well-documented open-source code to enhance transparency. The functionality available in palaeoverse improves code reproducibility and accessibility

关键词： analytical palaeobiology computational palaeobiology r programming readable reproducible reusable

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Leveraging Open-Source Geographic Databases to Enhance the representation of Landscape Heterogeneity in Ecological Models

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ECOLOGY AND EVOLUTION 2024年第10期14卷 e70402页

作者： Gelmi-Candusso, Tiziana A. rodriguez, Peter Fidino, Mason rivera, Kim Lehrer, Elizabeth W. Magle, Seth Fortin, Marie-Josee Univ Toronto Ecol & Evolutionary Biol Dept Toronto ON Canada Lincoln Pk Zoo Dept Conservat & Sci Chicago IL USA

Wildlife abundance and movement are strongly impacted by landscape heterogeneity, especially in cities which are among the world's most heterogeneous landscapes. Nonetheless, current global land cover maps, which are used as a basis for large-scale spatial ecological modeling, represent urban areas as a single, homogeneous, class. This often requires urban ecologists to rely on geographic resources from local governments, which are not comparable between cities and are not available in underserved countries, limiting the spatial scale at which urban conservation issues can be tackled. The recent expansion of community-based geographic databases, for example, OpenStreetMap (OSM), represents an opportunity for ecologists to generate large-scale maps geared toward their specific research needs. However, computational differences in language and format, and the high diversity of information within, limit the access to these data. We provide a framework, using r, to extract geographic features from the OSM database, classify, and integrate them into global land cover maps. The framework includes an exhaustive list of OSM features describing urban and peri-urban landscapes and is validated by quantifying the completeness of the OSM features characterized, and the accuracy of its final output in 34 cities in North America. We portray its application as the basis for generating landscape variables for ecological analysis by using the OSM-enhanced map to generate an urbanization index, and subsequently analyze the spatial occupancy of six mammals throughout Chicago, Illinois, USA. The OSM features characterized had high completeness values for impervious land cover classes (50%-100%). The final output, the OSM-enhance map, provided an 89% accurate representation of the landscape at 30m resolution. The OSM-derived urbanization index outperformed other global spatial data layers in the spatial occupancy analysis and concurred with previously seen local response trends, whereby

关键词： animal movement confusion matrix human disturbance landscape configuration mammal occupancy analysis r programming spatial ecology urban wildlife ecology

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abmr: An r package for agent-based model analysis of large-scale movements across taxa

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METHODS IN ECOLOGY AND EVOLUTION 2023年第1期14卷 218-230页

作者： Gochanour, Benjamin Fernandez-Lopez, Javier Contina, Andrea Univ Oklahoma Corix Plains Inst Norman OK 73019 USA Univ Oklahoma Oklahoma Biol Survey Norman OK 73019 USA Univ Massachusetts Dept Biol Boston MA 02125 USA Univ Colorado Dept Integrat Biol Denver CO USA Univ Oklahoma Ctr Earth Observat & Modeling Dept Microbiol & Plant Biol Norman OK USA Univ Texas Austin Dept Integrat Biol Austin TX USA

Agent-based modelling (ABM) shows promise for animal movement studies. However, a robust, open-source and spatially explicit ABM coding platform is currently lacking. We present abmr, an r package for conducting continental-scale ABM simulations across animal taxa. The package features two movement functions, each of which relies on the Ornstein-Uhlenbeck (OU) process. The theoretical background for abmr is discussed and the main functionalities are illustrated using example populations. Potential future additions to this open-source package may include the ability to specify multiple environmental variables or to model interactions between agents. Additionally, updates may offer opportunities for disease ecology and integration with other r movement modelling packages.

关键词： animal migration ecology open-source r programming simulations

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Potential inhibitors of VEGFr1, VEGFr2, and VEGFr3 developed through Deep Learning for the treatment of Cervical Cancer

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SCIENTIFIC rEPOrTS 2024年第1期14卷 1-21页

作者： Nayarisseri, Anuraj Abdalla, Mohnad Joshi, Isha Yadav, Manasi Bhrdwaj, Anushka Chopra, Ishita Khan, Arshiya Saxena, Arshiya Sharma, Khushboo Panicker, Aravind Panwar, Umesh Mendonca Junior, Francisco Jaime Bezerra Singh, Sanjeev Kumar Sil Res Lab Eminent Biosci Sect A Indore 452010 Madhya Pradesh India LeGene Biosci Pvt Ltd Bioinformat Res Lab Sect A Indore 452010 Madhya Pradesh India Shandong Univ Cheeloo Coll Med Sch Pharmaceut Sci Dept PharmaceutMinist EducKey Lab Chem Biol 44 Cultural West Rd Jinan 250012 Shandong Peoples R China George Washington Univ Sch Med & Hlth Sci Ross Hall2300 Eye St Washington DC 20037 USA Alagappa Univ Dept Bioinformat Comp Aided Drug Designing & Mol Modeling Lab Karaikkudi 630003 Tamil Nadu India State Univ Paraiba Dept Biol Sci Lab Synth & Drug Delivery BR-58429500 Joao Pessoa Brazil

Cervical cancer stands as a prevalent gynaecologic malignancy affecting women globally, often linked to persistent human papillomavirus infection. Biomarkers associated with cervical cancer, including VEGF-A, VEGF-B, VEGF-C, VEGF-D, and VEGF-E, show upregulation and are linked to angiogenesis and lymphangiogenesis. This research aims to employ in-silico methods to target tyrosine kinase receptor proteins-VEGFr-1, VEGFr-2, and VEGFr-3, and identify novel inhibitors for Vascular Endothelial Growth Factors receptors (VEGFrs). A comprehensive literary study was conducted which identified 26 established inhibitors for VEGFr-1, VEGFr-2, and VEGFr-3 receptor proteins. Compounds with high-affinity scores, including PubChem ID-25102847, 369976, and 208908 were chosen from pre-existing compounds for creating Deep Learning-based models. rD-Kit, a Deep learning algorithm, was used to generate 43 million compounds for VEGFr-1, VEGFr-2, and VEGFr-3 targets. Molecular docking studies were conducted on the top 10 molecules for each target to validate the receptor-ligand binding affinity. The results of Molecular Docking indicated that PubChem IDs-71465,645 and 11152946 exhibited strong affinity, designating them as the most efficient molecules. To further investigate their potential, a Molecular Dynamics Simulation was performed to assess conformational stability, and a pharmacophore analysis was also conducted for indoctrinating interactions.

关键词： VEGFr inhibitors Machine-learning Deep learning Molecular docking Molecular dynamics simulation r programming Python ADMET studies

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Association rule Mining for Selecting Proper Students to Take Part in Proper Discipline Competition: A Case Study of Zhejiang University of Finance and Economics

INTERNATIONAL JOURNAL OF EMERGING TECHNOLOGIES IN LEARNING

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INTErNATIONAL JOUrNAL OF EMErGING TECHNOLOGIES IN LEArNING 2018年第3期13卷 100-113页

作者： Huang, Xiaoling Xu, Yangbing Zhang, Shuai Zhang, Wenyu Zhejiang Univ Finance & Econ Hangzhou Zhejiang Peoples R China

In recent years, the educational issues have attracted more and more researchers' and teachers' attention. On the other hand, the development of data mining technology, provides a new method to extract the useful information from the complex educational data. In order to increase the chance of students to be awarded in discipline competition, it is better to select the proper students to take part in the proper discipline competition. Therefore, in this study, we collect the information of 164 undergraduate students as a case study. All students majored in Software Engineering in Zhejiang University of Finance and Economics. The Apriori algorithm with group strategy is used to find the relationship between the students' courses scores and competition awards. According to the results of association rule mining, we find that the students with higher scores of C# Development, Object-Oriented, Internet Web Design, Data Structure(C#), and Basic programming will have a higher probability to be awarded in the competition.

关键词： association rule mining Apriori algorithm r programming discipline competition

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Text mining methodologies with r: An application to central bank texts

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MACHINE LEArNING WITH APPLICATIONS 2022年 8卷

作者： Benchimol, Jonathan Kazinnik, Sophia Saadon, Yossi Bank Israel Res Dept Jerusalem Israel Fed Reserve Bank Richmond Quantitat Supervis & Res Charlotte NC USA

We review several existing text analysis methodologies and explain their formal application processes using the open -source software r and relevant packages. Several text mining applications to analyze central bank t... 详细信息

关键词： Text mining r programming Sentiment analysis Topic modeling Natural language processing Central bank communication Bank of Israel

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Big Data Analysis in a Social Learning Platform

Big Data Analysis in a Social Learning Platform

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2015 4th International Conference on Computer, Mechatronics, Control and Electronic Engineering (ICCMCEE 2015)

作者： Lan Huang Yunfeng Wei Alessio Zamboni Jing Zhang Hao Xu School of Computer Science and Technology Jilin University School of Software Jilin University School of information engineering and computer science DISI University of Trento

ISBN: (纸本)9781510813465

As the amount of networking information production keeps growing, big data analysis has been widely used in the field of education. In recent years, teacher-student interactions on the Web are increasing, this will generate a lot of data. The use of big data analysis methods to analyze these data has become a popular research lately. In this paper, we use Hadoop big data analytic platform to analyze the log data of Jilin University Website, which is used to analyze these data to find out during when students surf the Internet most so that teachers can better communicate with students during these periods. By doing so, these data has not only been put to good use, but can also make teacher-student interactions more effective.

关键词： Big Data Analysis Social Learning Platform Hadoop Map reduce r programming

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r for Genome-Wide Association Studies

R for Genome-Wide Association Studies

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作者： Cedric Gondro Laercio r. Porto-Neto Seung Hwan Lee

In recent years r has become de facto statistical programming language of choice for statisticians and it is also arguably the most widely used generic environment for analysis of high-throughput genomic data. In this... 详细信息

关键词： programming Language Genome-wide association studies High-throughput analysis r programming Parallel computation

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