scholarly journals SURVEY SURFER: A WEB BASED DATA GATHERING AND ANALYSIS APPLICATION

2016 ◽  
Vol 3 (3) ◽  
pp. 09-15
Author(s):  
Dhanamma Jagli ◽  
Krutika Tawde ◽  
Pratima Musale ◽  
Swathi Muthukumar
Keyword(s):  
Data Gathering ◽  
Web Based ◽  
Analysis Application ◽  
Data Gathering And Analysis

The Authenticity and Ethics of Phenomenological Research: How to Overcome the Researcher's Own Views

1999 ◽  
Vol 6 (1) ◽  
pp. 12-22 ◽  
Author(s):  
Arja Häggman-Laitila
Keyword(s):  
Data Gathering ◽  
Phenomenological Research ◽  
Ethical Standards ◽  
Crucial Importance ◽  
Data Gathering And Analysis

This article is based on the assumption that the researcher cannot detach from his or her own view in phenomenological research. The researcher is assumed to be able to understand the experiences of an individual only through the points of departure created by the researcher's own view. The goal of this article is to describe practical aspects and their theoretical grounds that are of crucial importance in overcoming a researcher's views in data gathering and analysis. Its purpose is to clarify the authenticity and ethical standards concerning the views of the researcher in phenomenological research.

The Organization of Life before Death in Two Québec Cultural Configurations

1993 ◽  
Vol 27 (1) ◽  
pp. 35-50
Author(s):  
Luce Des Aulniers
Keyword(s):  
Basic Concept ◽  
Data Gathering ◽  
Doctoral Thesis ◽  
Historical Factors ◽  
Personal Experiences ◽  
Life Threatening ◽  
New Type ◽  
The Subject ◽  
Fatal Illness ◽  
Data Gathering And Analysis

This article is based on data from a doctoral thesis about the “anthropology of life-threatening, death and time.” [1] The interpretation is made from twelve life reviews set at homes of people who suffered a serious, but not necessarily fatal illness. Two-cultural configurations are chosen along the axis of rural-urban polarity. It focuses on three types of solidarity, facing the awareness of death: 1) the ethnographic position, in data gathering and analysis. Specific propositions are given concerning the subject and intersubjectivity, cultural generalization of personal experiences, and scientific criteria; 2) what helps cope with illness. Pre-death practices are structured on the basic concept of resistance to illness and preparation for death practices rely on a coherence “test.” The genealogy of practices emerge in six situational and seven historical factors; 3) the conditions of a new type of rite before death and its functions, beside the institutionalization of illness and death.

Toward a Phenomenology of the Material

2019 ◽  
Vol 26 (5) ◽  
pp. 507-513
Author(s):  
Kristidel McGregor
Keyword(s):  
Data Gathering ◽  
Human Experience ◽  
The World ◽  
Data Gathering And Analysis

Can phenomenological approaches to experience allow me to attend to not just the human experience but also the material discursive forces that are a part of the shifting, moving network of agents at work in a phenomenon? Focusing on the material structures of experience means not asking what materiality is, but rather asking what it is doing in the context of an intra-active phenomena. In this article, I consider what possibilities for data gathering and analysis are opened if I think the Husserlian concept of encounters with the world within a feminist new materialist framework, and find the tensions provocative.

Data gathering and analysis for needs assessment: A case study

2010 ◽  
Vol 49 (8) ◽  
pp. 27-34 ◽  
Author(s):  
Christin Lundberg ◽  
Jennifer L. Elderman ◽  
Patricia Ferrell ◽  
Leslie Harper
Keyword(s):  
Needs Assessment ◽  
Data Gathering ◽  
Data Gathering And Analysis

scholarly journals Web-based Application for Classification Using Naïve Bayes and K-means Clustering (Case Study: Tic-tac-toe Game)

2020 ◽  
Vol 5 (1) ◽  
pp. 8
Author(s):  
Indriyani Indriyani ◽  
M. Ihsan Alfani Putera
Keyword(s):  
Naive Bayes ◽  
Naïve Bayes ◽  
Quality Data ◽  
Clustering Methods ◽  
Web Based ◽  
Numerical Attributes ◽  
Analysis Application ◽  
Categorical Attributes ◽  
Data Generalization

A database can consist of numerical and non-numerical attributes. However, several data processing algorithms, such as K-means clustering, can be used only in a dataset with numerical attributes. Data generalization by using Naïve Bayes and K-means clustering methods is usually employed WEKA (Waikato environment for knowledge analysis) application. Although the strength of WEKA lies in increasingly complete and sophisticated algorithms, the success of data mining still lies in the knowledge factor of the human implementer. The task of collecting high-quality data and knowledge of modeling and the use of appropriate algorithms is needed to guarantee the accuracy of the expected formulations. In this paper, we propose a simple web-based application that can be used like WEKA. The methodology used in this study includes several stages. The first stage is the preparation of data, which is the tic-tac-toe game dataset that is converted to CSV (comma-separated values) format. The next stage is the process of modifying data from non-numeric to numeric, specifically for clustering with the K-means algorithm. Afterward, the calculation of the distance between data is conducted and followed by data clustering. The final stage is the summary of these processes and results. From the experimental results, it was found that clustering can be done on categorical attributes that are transformed first into the numerical form using web-based applications.

scholarly journals Scientists Denounce Pending Australian Climate Science Cuts

Eos ◽  
2016 ◽  
Vol 97 ◽  
Author(s):  
Puneet Kollipara
Keyword(s):  
Data Gathering ◽  
Climate Science ◽  
Climate Research ◽  
Australian Climate ◽  
Climate Studies ◽  
Data Gathering And Analysis

The recently unveiled planned shift from basic climate research toward responses to a transformed climate could cost research jobs, hamper climate studies, and limit data gathering and analysis.

Data Gathering and Analysis

2017 ◽  
pp. 159-180
Author(s):  
Peter O’Donoghue ◽  
Lucy Holmes ◽  
Gemma Robinson
Keyword(s):  
Data Gathering ◽  
Data Gathering And Analysis
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