1,720,994 research outputs found
Machine Learning Algorithm-Based Prediction of Diabetes Among Female Population Using PIMA Dataset
Get PDFBackground: Diabetes is a metabolic disorder characterized by increased blood sugar levels. Early detection of diabetes could help individuals to manage and delay the progression of this disorder effectively. Machine learning (ML) methods are important in forecasting the progression and diagnosis of different medical problems with better accuracy. Although they cannot substitute the work of physicians in the prediction and diagnosis of disease, they can be of great help in identifying hidden patterns based on the results and outcome of disease. Methods: In this research, we retrieved the PIMA dataset from the Kaggle repository, the retrieved dataset was further processed for applied PCA, heatmap, and scatter plot for exploratory data analysis (EDA), which helps to find out the relationship between various features in the dataset using visual representation. Four different ML algorithms Random Forest (RF), Decision Tree (DT), Naïve Bayes (NB), and Logistic regression (LR) were implemented on Rattle using Python for the prediction of diabetes among the female population. Results: Results of our study showed that RF performs better in terms of accuracy of 80%, precision of 82%, error rate of 20%, and sensitivity of 88% as compared to other developed models DT, NB, and LR. Conclusions: Diabetes is a common problem prevailing across the globe, ML-based prediction models can help in the prediction of diabetes much earlier before the worsening of the condition
An Ontology of Megaprojects
Get PDFMegaprojects are symbolic milestones of human history. From the Great Pyramid of Giza and the Great Wall of China to the Hoover Dam and the Manhattan Project, history is marked by an array of megaprojects. Some megaprojects are born out of necessity while others showcase power and status of individuals, groups, or countries. Most megaprojects are one-of-a-kind endeavors to which traditional project management principles are neither applicable nor suitable, rendering the holistic study of megaprojects especially difficult. Regardless of the recent uptick in research on megaprojects there is no systemic framework that can help systematically assess and guide megaprojects and megaproject research. In the absence of such a framework there is a significant risk of bias in planning the projects and the topics researched. In this paper, we present an ontology of megaprojects and discuss how it can help analyze individual megaprojects and synthesize the corpus of megaproject research
Ontological Meta-Analysis and Synthesis
Get PDFWe present ontological meta-analysis and synthesis as a method for reviewing, mapping, and visualizing the research literature in a domain cumulatively, logically, systematically, and systemically. The method highlights a domain’s bright spots that have been heavily studied, the light spots that have been lightly studied, the blind spots that have been overlooked, and the blank spots that have not been studied. It highlights the biases in a domain’s research; the research can then be realigned to make it stronger and more effective. We illustrate the method using the emerging domain of public health informatics (PHI). We present an ontological framework for the domain, map the literature onto the framework, and highlight its bright, light, and blind/blank spots. We also present detailed analyses using the ontological maps of dyads and triads. We conclude by discussing how (a) the results can be used to realign PHI research, and (b) the method can be used in other information systems domains
Ontological Meta-Analysis and Synthesis
Get PDFWe present ontological meta-analysis and synthesis as a method for reviewing, mapping, and visualizing the research literature in a domain cumulatively, logically, systematically, and systemically. The method will highlight the domain’s bright spots which are heavily emphasized, the light spots which are lightly emphasized, the blank spots which are not emphasized, and the blind spots which have been overlooked. It will highlight the biases and asymmetries in the domain’s research; the research can then be realigned to make it stronger and more effective. We illustrate the method using the emerging domain of Public Health Informatics (PHI). We present an ontological framework for the domain, map the literature onto the framework, and highlight its bright, light, and blank/blind spots. We conclude with a discussion of how (a) the results can be used to realign PHI research, and (b) the method can be used in other information systems domains
Reframing the Problem of Statelessness: Quest for a Supra-Legal Perspective
Get PDF34 pagesAny democratic state must internalize and be sensitive to the human rights of susceptible groups. Most successful democracies seem to have realized this paramount goal, though reality presents a contradictory proposition where a considerable amount of people are still deprived of the mainstream protective umbrella of legal and social regimes. One such group that can often be excluded from the ideological basis of human rights discourse is stateless persons
Probing two chief executives' schematic knowledge of the US steel industry using cognitive maps
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Going Beyond Counting First Authors in Author Co-citation Analysis
Get PDFThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Variations on the Author
Get PDF“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
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