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Neutrosophic approach for patient health monitoring using r programming

DISCOVEr APPLIED SCIENCES 2025年第4期7卷 1-15页

作者： Sebastian, Liji rita, S. Al-Absy, Mujeeb Saif Mohsen Vennila, J. Mukthar, K. P. Jaheer Periyar Univ Dept Stat Salem Tamil Nadu India Periyar Univ Stat Dept Salem Tamil Nadu India Gulf Univ Coll Adm & Financial Sci Accounting & Financial Sci Dept Sanad Bahrain Manipal Acad Higher Educ Manipal Coll Hlth Profess Manipal Karnataka India Kristu Jayanti Coll Autonomous Bengaluru India

Although reliability Block Diagrams (rBDs), are frequently employed for reliability analysis, their efficacy in healthcare applications is limited because they frequently fail to address the imprecision and uncertainty present in clinical data. By adding Neutrosophic Logic to rBDs, this work creates a novel method for improving reliability evaluations in ambiguous clinical settings. In contrast to conventional approaches, the Neutrosophic rBD model better represents the complexity of healthcare systems by integrating truth, indeterminacy, and falsity components. r programming is used to develop the model, and simulations are used to gauge how well it performs in various clinical settings. According to the simulations, the Neutrosophic rBD model outperforms conventional rBDs in managing uncertainty and enhancing decision-making, offering more flexibility and more precise reliability evaluations. This research establishes a foundation for future research that could broaden the application of this method to other decision-support systems, both within and beyond the healthcare sector. Article highlights center dot By incorporating Truth, Indeterminacy, and Falsity components, Neutrosophic logic enhances evaluation of complex health metrics such as blood pressure, cholesterol, etc, of a patient's health state by providing nuanced insights into variations, than the binary classifications as given by fuzzy logic. center dot reliability Block Diagrams (rBDs) and Neutrosophic logic can be combined to enhance the ability to handle ambiguous and partial clinical data and thus provides more accurate reliability evaluations in situations where device reliability or health statistics are unknown. center dot Learners gain insights into analyzing complex health data with precision, while researchers can develop advanced models integrating neutrosophic logic and machine learning to improve healthcare prognosis. Case studies further establish its practical applications and open avenu

关键词： reliability block diagram (rBD) Neutrosophic logic Truth Indeterminacy Falsehood Health care Efficiency r programming

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Geoheritage research Trends: A Comparative Bibliometric Analysis of Global and Türkiye Perspectives Using r programming

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GEOHErITAGE 2025年第2期17卷 1-19页

作者： Goktas, Yaren Boyraz, Zeki Inonu Univ Fac Sci & Letters Dept Geog Malatya Turkiye

Geoheritage refers to the scientific, aesthetic and cultural value of geological formations and is closely related to the concepts of geotourism, geosite, geopark, geodiversity and geoconservation. All these concepts work together to protect the scientific, educational and economic value of geoheritage and to use it sustainably. In this study, the findings of a bibliometric analysis that comparatively examines geoheritage literature in the international and Turkish context are presented. The analysis was carried out using the Biblioshiny package of the r program. The methodology of the study is as follows: determining the boundaries of the research, collecting data, analyzing data, creating and interpreting bibliometric maps. In the first stage of the research, studies conducted between 1994-2024 were determined using the databases Web of Science, Scopus, Google Scholar, researcgate, Dergipark Academic, Y & ouml;kTez. The studies were analyzed within certain limitations and the results were visualized with bibliometric maps. The results indicate that the topic of geoheritage is explored through an interdisciplinary approach in the international literature, while the literature in T & uuml;rkiye remains underdeveloped in this field at the global level. Despite the geological and geomorphological advantages provided by its geographical location, T & uuml;rkiye has not been able to fully utilize its existing geoheritage potential. Establishing stronger connections between studies conducted in T & uuml;rkiye and the international literature is of great importance.

关键词： Geoheritage Geotourism T & uuml rkiye's Geoheritage r programming Bibliometric Analysis Biblioshiny Package

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r programming for Social Network Analysis - A review 3

R programming for Social Network Analysis - A Review

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3rd International Conference on Information Technology research (ICITr)

作者： Maddumage, Chamila Dhanushika, M. P. TIQRI Corp Pvt Ltd 201 Sir James Peiris Mawatha Colombo 2 Sri Lanka Univ Moratuwa Dept Computat Math Katubedda Sri Lanka

ISBN: (纸本)9781728114705

Social network data have become richer and easier to collect, but that has pushed the borders of the prior art of advanced networks. Therefore, capability of scaling social network is not simply in terms of these advanced networks. However, with the advent of social network, network analysis has always been committed to the development and interaction with social network analysis (SNA). Because of the emergence of continuous SNA in the current state of technological progress, analyzing social network is more conducive to individuals and organizations to make a better future. Even though there are various programming languages which can be used for SNA, this article focuses on use of r programming language due to its huge library of packages. With this background, this article presents a review on r programming in various types of SNA and related issues for best practices.

关键词： Network r programming r Packages Social Network Analysis

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An Inquiry-Based Activity for Investigating the Effect of Climate Change on Phenology Using the r programming Language

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AMErICAN BIOLOGY TEACHEr 2024年第4期86卷 233-241页

作者： Austin, Matthew W. Miller-Struttmann, Nicole E. Missouri Bot Garden Biodivers Data St Louis MO 63110 USA Washington Univ Living Earth Collaborat St Louis MO 14263 USA Webster Univ Biol Sci Webster Groves MO USA

Engaging students in research is increasingly recognized as a valuable pedagogical tool that can augment student learning outcomes. Here, we present an original activity that utilizes research as pedagogy to teach upper-division college students about phenological responses to climate change. By studying phenological responses in multiple species, this activity emphasizes interspecific variability in responses to a changing climate (i.e., that not all species respond in the same way), while demonstrating the relationship between environmental and phenotypic variability. In this activity, students collect data from herbarium specimens of spring ephemerals native to North America and are tasked with formulating and testing hypotheses about how the day of year that a species' flowering occurs (i.e., flowering phenology) has been affected by climate change. To accomplish this, students perform linear regressions using the r programming language-including data exploration and ensuring the dependent variable follows a normal distribution-and subsequently present their results via oral presentation. We taught this activity as a three-unit lab in an upper-division ecology course and observed quantifiable improvement in student learning outcomes. While designed as a three-unit, upper-division lab, this activity can be modified for other educational levels, blocks of time, and/or as a flipped classroom activity. Through this activity, students are provided with the opportunity to learn about the scientific method, biological collections, linear regressions, the r programming language, and scientific communication. Changes to flowering time are one of the most conspicuous effects of climate change, thus presenting an ideal topic for engaging students in biological inquiry.

关键词： climate change flowering time herbaria inquiry investigation linear regression phenology plant ecology r programming scientific method upper-division biology laboratory

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Spatial data analysis with r programming for environment

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HUMAN AND ECOLOGICAL rISK ASSESSMENT 2019年第6期25卷 1521-1530页

作者： Kaya, Efdal Agca, Muge Adiguzel, Fatih Cetin, Mehmet Kocaeli Univ Dept Geomat Engn Nat & Appl Sci Kocaeli Turkey Izmir Katip Celebi Univ Dept Geomat Engn Izmir Turkey Nevsehir Haci Bektas Veli Univ Urgup Sebahat & Erol Toksoz Vocat Sch Programs Cultural Heritage & Tourism Nevsehir Nevsehir Turkey Kastamonu Univ Fac Engn & Architecture Dept Landscape Architecture TR-37150 Kastamonu Turkey

The use of open source software, which has been constantly evolving since the mid-2000s, has affected every research discipline. Disciplines using geographic information systems (GIS) and remote sensing (rS) data have been heavily affected owing to this evolution of technology. researchers working on these data sets have begun to use open source software intensively. The analysis and visualization of spatial data with the help of open source software has caused the emergence of new different features, which are cost effective and editable by other users. In this study, eight sample points have been used for the analysis of water quality in the Mamasin dam in the 2209/A group project of "Assessment and Modeling with GIS and rS Data of the Land Use Effects on Water Quality of Mamasin Dam" supported by the Scientific and Technological research Council of Turkey (TUBITAK) under its program to support graduate students. While visualizing spatial features of the points, QGIS Desktop 2.18.0 and Studio programs with open source code have been used. The rStudio program is an open source software that allows the use of the functions of the r programming language. This study is an ideal application for spatial analysis studies with the r programming language. The sample points used in the study were analyzed in the laboratories of Department of Environmental Engineering, Aksaray University. Spatial properties of the analyzed data were examined by coding in the Studio program that is free open source software. In the analysis process, first, the libraries, Leaflet(), ***(), rgdal(), sp(), raster(), and magrittr(), which are used in the study, have been uploaded. With the help of these libraries, the locations of the sample points are transferred to the OpenStreetMap using latitudes and longitudes of the geographic coordinate system as base map. The pH, conductivity, PO4-P, PO4, dissolved oxygen, and temperature information of each sample points are assigned to the va

关键词： spatial data visualization QGIS rStudio r programming open source software

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Integrating Data Science and r programming at an Early Stage 4

Integrating Data Science and R Programming at an Early Stage

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4th IEEE International Conference on Soft Computing & Machine Intelligence (ISCMI)

作者： Datta, Soma Nagabandi, Veneela Univ Houston Clear Lake Software Engn Houston TX 77058 USA

ISBN: (纸本)9781538613146

The use of data has become an integral part of everyday life. Hence, introducing data science with games would generate an interest and prepare students for the rapidly changing world of technology. This study is especially intended to teach data science (DS) and r programming using games for cognitive learning. Tangible learning with real-life examples were used to teach Data Science. A correlation between the typical toys that are played are tied to concepts of DS. The three variables of social cognitive learning are integrated in this study. The data collected from the workshops are different from other studies because of broadly two reasons. First, the games used to teach data science were measured with the elements of cognitive learning. The other, was that the learning data collected from the students that participated in the study had a modified environment. The data that was collected during the experimental study for thirty hours for about 100 students. Students at the end of each session were able to identify the data science terms with respect to the games. They were able to write a small r program that they self-taught themselves due to the environmental factor of cognitive learning.

关键词： r programming Data Science Game based learning cognitive learning sixth grade features creation data integration clustering lifelong learning

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Goal programming Advanced Yield Model by Artificial Intelligence and r programming

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SN Computer Science 2024年第7期5卷 899页

作者： Shalini, K. Polasi, Sridevi Kuntal, ravinder Singh Vishwanatha, S. Patil, Vishal Department of Mathematics REVA University Karnataka Bangalore India Department of Mathematics Nitte Meenakshi Institute of Technology Karnataka Bangalore India Department of Mathematics FET Jain (Deemed to-be University) Karnataka Bangalore India

A nation’s economic and social progress is strongly influenced by its agricultural sector. Crop distribution, crop combination, and operational activities for crop production are critical decisions that must be made in order to get the best farm outputs. The goal of this work is to develop an optimal crop design using goal programming formulation aimed at achieving higher returns for farmers compared to their current net returns. In this work, LINGO 19.0 and r programming were employed to analyze the data. The same result is shown by both programming models. The result shows that allocating 103.3 acres of land to paddy and wheat gives an income of rs. 44,79,860 which increases the net profit by 32.8% more than the current farmers’ plan. Similarly, other optimal plan increases the net profit from 5.49 to 20.18%. © The Author(s), under exclusive licence to Springer Nature Singapore Pte Ltd. 2024.

关键词： Crop plan Crop production Goal programming NetProfit r programming

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A Comprehensive Analysis for Crime Prediction in Smart City Using r programming 8

A Comprehensive Analysis for Crime Prediction in Smart City ...

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8th IEEE International Conference on Cloud Computing, Data Science and Engineering (Confluence) / Global Technology, Innovation and Enterpreneurship Summit

作者： Garg, rahul Malik, Arun raj, Gaurav Lovely Profess Univ Dept Comp Sci & Engn Phagwara India Amity Univ Uttar Pradesh Dept Comp Sci & Engn Noida Uttar Pradesh India

ISBN: (纸本)9781538617199

With the advancements in the technology, we are stepping forward to the future of Smart Cities. But sill we have a large number of hurdles to achieve that vision. One such problem faced by our society is the large number of crimes happening across cities. So, it is very cardinal that we find solutions to this problem. The aim of this paper is to scrutinize the crimes history in a city and derive insights which would lead to better public safety decisions. In this paper, the crime data of City of Baltimore is used. Firstly, the data collection phase of data analysis followed by a brief introduction to data cleaning is explained in this paper. Then an exploratory analysis is carried out in this paper based on r programming. Tableau is used to generate visualizations from this data. This paper will briefly discuss the process of data analysis and conclude the important insights based on this analysis.

关键词： Tableau Crime data Analysis r programming

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Identification of Association rules in Buying Patterns of Customers based on Modified Apriori and Eclat Algorithms by using r programming Language 2

Identification of Association Rules in Buying Patterns of Cu...

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2017 International Conference on Computer Science and Engineering (UBMK)

作者： Huseyinov, Ilham Aytac, Utku Can Istanbul Aydin Univ Yazilim Muhendisligi Bolumu Istanbul Turkey Istanbul Aydin Univ Bilgisayar Muhendisligi Bolumu Istanbul Turkey

ISBN: (纸本)9781538609309

The identificat on of association relationships in buying patterns of customers is an important problem to make proper decision by business companies. Current most research works utilizes commonly traditional Apriori algorithm to solve this problem. In this paper, a modified version of Apriori algorithm, and its combination with Eclat algorithm is suggested. Applying this approach to a case study demonsrates efficiency of the approach versus traditional Apriori algorithm in terms of performance. Implementation of algorithms are done by using r programming language. Some recommendations based on the results of the paper are presented for supermarket companies.

关键词： Buying Patterns Association rule Mining Improved Apriori Algorithm Eclat Algorithm r programming Machine Learning

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A Comparison of Data Mining Techniques in Evaluating retail Credit Scoring Using r programming

A Comparison of Data Mining Techniques in Evaluating Retail ...

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International Conference on Disaster recovery and Business Continuity

作者： Dilmurat Zakirov Aleksey Bondarev Nodar Momtselidze Information Technologies Department Demir Kyrgyz International Bank Computer Science Department International Ataturk Alatoo University Faculty of Computer Technologies and Engineering International Black Sea University

ISBN: (纸本)9781509002016

retail credit scoring has become more efficient in recent years because of the use of data mining techniques that allow marketing officers and top managers to better estimate their customers credibility. In recent years, many complicated models have been developed;however there are few of them which continues to be used because of its efficiency and simplicity. This study investigates k-Nearest Neighbourhood (kNN), support vector machines (SVMs), gradient boosted model (GBM), Naive Bayes classification, Classification and regression Tree (CArT) and random Forest (rF) as analytical methods for customer credit scoring estimation and evaluation, using real dataset. At the end of the study it is found that random Forest model with down-sampling (rF_US) has better accuracy rate when compared to other models.

关键词： Data mining Credit scoring Support vector machines random forest KNN r programming

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