scholarly journals A Rational Framework for Production Decision Making in Blood Establishments

2012 ◽  
Vol 9 (3) ◽  
pp. 69-79 ◽  
Author(s):  
Augusto Ramoa ◽  
Salomé Maia ◽  
Anália Lourenço
Keyword(s):  
Data Mining ◽  
Decision Making ◽  
Quality Management System ◽  
Analysis Software ◽  
Production Chain ◽  
Use Of Data ◽  
Production Strategies ◽  
Definition Of ◽  
General Operation ◽  
Production Decision

Summary SAD_BaSe is a blood bank data analysis software, created to assist in the management of blood donations and the blood production chain in blood establishments. In particular, the system keeps track of several collection and production indicators, enables the definition of collection and production strategies, and the measurement of quality indicators required by the Quality Management System regulating the general operation of blood establishments.This paper describes the general scenario of blood establishments and its main requirements in terms of data management and analysis. It presents the architecture of SAD_BaSe and identifies its main contributions. Specifically, it brings forward the generation of customized reports driven by decision making needs and the use of data mining techniques in the analysis of donor suspensions and donation discards.

Embracing School Counselors’ Situatedness: Data-Based Decision Making as Fulfillment of a Complex Identity

2021 ◽  
Vol 24 (1_part_3) ◽  
pp. 2156759X2110119
Author(s):  
Brett Zyromski ◽  
Catherine Griffith ◽  
Jihyeon Choi
Keyword(s):  
Decision Making ◽  
School Counselors ◽  
School Counselor ◽  
Use Of Data ◽  
Counselor Identity ◽  
Using Data ◽  
Definition Of ◽  
Support Students ◽  
Students Success ◽  
Data Based Decision Making

Since at least the 1930s, school counselors have used data to inform school counseling programming. However, the evolving complexity of school counselors’ identity calls for an updated understanding of the use of data. We offer an expanded definition of data-based decision making that reflects the purpose of using data in educational settings and an appreciation of the complexity of the school counselor identity. We discuss implications for applying the data-based decision-making process using a multifaceted school counselor identity lens to support students’ success.

Knowledge Discovery for Large Databases in Education Institutes

2017 ◽  
pp. 27-110
Author(s):  
Robab Saadatdoost ◽  
Alex Tze Hiang Sim ◽  
Hosein Jafarkarimi ◽  
Jee Mei Hee
Keyword(s):  
Higher Education ◽  
Data Mining ◽  
Decision Making ◽  
Knowledge Discovery ◽  
Learning Style ◽  
Science Research ◽  
Data Set ◽  
Use Of Data ◽  
Education Data ◽  
Decision Making System

This project presents the patterns and relations between attributes of Iran Higher Education data gained from the use of data mining techniques to discover knowledge and use them in decision making system of IHE. Large dataset of IHE is difficult to analysis and display, since they are significant for decision making in IHE. This study utilized the famous data mining software, Weka and SOM to mine and visualize IHE data. In order to discover worthwhile patterns, we used clustering techniques and visualized the results. The selected dataset includes data of five medical university of Tehran as a small data set and Ministry of Science - Research and Technology's universities as a larger data set. Knowledge discovery and visualization are necessary for analyzing of these datasets. Our analysis reveals some knowledge in higher education aspect related to program of study, degree in each program, learning style, study mode and other IHE attributes. This study helps to IHE to discover knowledge in a visualize way; our results can be focused more by experts in higher education field to assess and evaluate more.

The Safety Monitoring of Colliery Equipments Based on Data Mining Technology

2011 ◽  
Vol 128-129 ◽  
pp. 731-734
Author(s):  
Shu Fang Zhao ◽  
Li Chao Chen
Keyword(s):  
Data Mining ◽  
Decision Making ◽  
Essential Role ◽  
Scientific Information ◽  
Safety Monitoring ◽  
Monitoring Data ◽  
Mining Technology ◽  
Use Of Data ◽  
Stochastic Data

Data mining is the process of abstracting unaware, potential and useful information and knowledge from plentiful, incomplete, noisy, fuzzy and stochastic data. The reliability of colliery equipments takes an essential role in the safety of production. Not only since their continuance of operation, had the accumulation of historical error data of colliery equipments resulted in a mass of surplus data, but also because their lacks of helpful information, which as a result makes colliery managers as well as equipment operators hard to make decisions. Seeing that, we introduced ways here that makes use of data mining technology by processing and analyzing historical monitoring data, recognizing and extracting meaningful patterns so as to provide scientific information for decision-making on the safety of colliery operations, which would help for the forecasting of potential threatens of colliery equipments’ operation, thus, make great contributions to prevent disasters from happening.

scholarly journals DATA MINING TECHNIQUES FOR EDUCATIONAL DATA: A REVIEW

2020 ◽  
Vol 5 (2) ◽  
pp. 166-177 ◽  
Author(s):  
Pragati Sharma ◽  
Dr. Sanjiv Sharma
Keyword(s):  
Higher Education ◽  
Data Mining ◽  
Decision Making ◽  
Educational Institutions ◽  
Data Set ◽  
Data Mining Techniques ◽  
Use Of Data ◽  
New Knowledge ◽  
Hidden Patterns ◽  
Educational Field

Recently, data mining is gaining more popularity among researcher. Data mining provides various techniques and methods for analysing data produced by various applications of different domain. Similarly, Educational mining is providing a way for analyzing educational data set. Educational mining concerns with developing methods for discovering knowledge from data that come from educational field and it helps to extract the hidden patterns and to discover new knowledge from large educational databases with the use of data mining techniques and tools. Extracted knowledge from educational mining can be used for decision making in higher educational institutions. This paper is based on literature review of different data mining techniques along with certain algorithms like classification, clustering etc. This paper represents the effectiveness of mining techniques with educational data set for higher education institutions.

scholarly journals Data warehousing and data mining: A case study

2005 ◽  
Vol 15 (1) ◽  
pp. 125-145 ◽  
Author(s):  
Milija Suknovic ◽  
Milutin Cupic ◽  
Milan Martic ◽  
Darko Krulj
Keyword(s):  
Data Mining ◽  
Decision Making ◽  
Data Warehouse ◽  
Business Decision ◽  
Serbia And Montenegro ◽  
Data Mining Algorithms ◽  
Use Of Data ◽  
Business System ◽  
Time Period ◽  
Mining Algorithms

This paper shows design and implementation of data warehouse as well as the use of data mining algorithms for the purpose of knowledge discovery as the basic resource of adequate business decision making process. The project is realized for the needs of Student's Service Department of the Faculty of Organizational Sciences (FOS), University of Belgrade, Serbia and Montenegro. This system represents a good base for analysis and predictions in the following time period for the purpose of quality business decision-making by top management. Thus, the first part of the paper shows the steps in designing and development of data warehouse of the mentioned business system. The second part of the paper shows the implementation of data mining algorithms for the purpose of deducting rules, patterns and knowledge as a resource for support in the process of decision making.

Data Mining Approach to Decision Support in Social Welfare

2018 ◽  
pp. 1783-1802
Author(s):  
Ricardo Anderson ◽  
Gunjan Mansingh
Keyword(s):  
Data Mining ◽  
Decision Making ◽  
Decision Support ◽  
Social Welfare ◽  
Knowledge Discovery ◽  
Support System ◽  
Process Model ◽  
Data Mining Techniques ◽  
Use Of Data ◽  
Data Mining Approach

Knowledge discovery and data-mining techniques have the potential to provide insights into data that can improve decision making. This paper explores the use of data mining to extract patterns from data in the domain of social welfare. It discusses the application of the Integrated Knowledge Discovery and Data Mining process model (IKDDM) a social welfare programme in Jamaica. Further, it demonstrates how the knowledge acquired from the data is used to develop a knowledge driven decision support system (DSS) in the PATH CCT programme. This system was successfully tested in the domain showing over 94% accuracy in the comparative decisions produced.

scholarly journals Use of Data Mining Techniques in Human Resource Management

2017 ◽  
Vol 1 (1) ◽  
pp. 41-46
Author(s):  
Okaile R. Marumo ◽  
Tumisang Angela Mmopelwa
Keyword(s):  
Data Mining ◽  
Decision Making ◽  
Resource Management ◽  
Human Resource Management ◽  
Human Resource ◽  
Transformational Change ◽  
Decision Making Process ◽  
Data Mining Techniques ◽  
The Past ◽  
Use Of Data

In the past few years, Analytics has rapidly risen in among organizations within the field of human resource management. To the present date, however, Human Resource Analytics has not been subject to a lot of scrutiny from educational researchers. The aim of this paper is so to look at Different Mining Techniques could be implemented in the HR Department to enhance or support their decision making process. This will improve existing practices of HR analytics and will deliver transformational change indeed

Data Mining Approach to Decision Support in Social Welfare

2014 ◽  
Vol 5 (2) ◽  
pp. 39-61 ◽  
Author(s):  
Ricardo Anderson ◽  
Gunjan Mansingh
Keyword(s):  
Data Mining ◽  
Decision Making ◽  
Decision Support ◽  
Decision Support System ◽  
Social Welfare ◽  
Knowledge Discovery ◽  
Support System ◽  
Process Model ◽  
Use Of Data ◽  
Data Mining Approach

Knowledge discovery and data-mining techniques have the potential to provide insights into data that can improve decision making. This paper explores the use of data mining to extract patterns from data in the domain of social welfare. It discusses the application of the Integrated Knowledge Discovery and Data Mining process model (IKDDM) a social welfare programme in Jamaica. Further, it demonstrates how the knowledge acquired from the data is used to develop a knowledge driven decision support system (DSS) in the PATH CCT programme. This system was successfully tested in the domain showing over 94% accuracy in the comparative decisions produced.

scholarly journals Data mining for marine data analysis

2021 ◽  
Vol 8 (1) ◽  
Author(s):  
Valery Maximov ◽  
Kseniya Reznikova ◽  
Dmitry Popov
Keyword(s):  
Data Mining ◽  
Data Analysis ◽  
Information Technologies ◽  
Software Tool ◽  
Production Costs ◽  
Highly Qualified ◽  
Use Of Data ◽  
Marine Data ◽  
Definition Of ◽  
Effective Use

There is practically no industry left where modern information technologies would not be used. Data mining approaches are very popular today. Using this technology allows to transform huge amounts of data into useful information. In the article, the authors present the definition of data mining technology and frequently used methods. Some of the popular data mining techniques include classification, clustering, machine learning, and prediction. The authors paid special attention to such a clustering method as the k-means. The algorithm’s essence is to distribute the dataset into clusters. The finished results can be visualized and detect the scatter by naked eye, which implies heterogeneity in the data. By further investigating these variations, the analyst can find errors and weaknesses in the study area according to the task at hand. Accurate and complete data is essential in maritime activities. In the field of shipbuilding data analysis and well-made operational decisions can affect the speed and quality of ship construction or even reduce production costs. In shipping and logistics, they can be used to optimize routes and improve the safety of seafarers. Effective use of data mining usually requires highly qualified database specialists and programmers. In this work, the authors have demonstrated a variant of using the Orange Data Mining software tool. This program does not require programming skills from the user, which makes it a useful tool for people far from writing program code. The article explores the application of the Orange Data Mining program for automated mining of marine data. The results obtained show that the program can be effectively used in maritime activities.

Knowledge Discovery for Large Databases in Education Institutes

2018 ◽  
pp. 158-245
Author(s):  
Robab Saadatdoost ◽  
Alex Tze Hiang Sim ◽  
Hosein Jafarkarimi ◽  
Jee Mei Hee
Keyword(s):  
Higher Education ◽  
Data Mining ◽  
Decision Making ◽  
Knowledge Discovery ◽  
Learning Style ◽  
Science Research ◽  
Data Set ◽  
Use Of Data ◽  
Education Data ◽  
Decision Making System

This project presents the patterns and relations between attributes of Iran Higher Education data gained from the use of data mining techniques to discover knowledge and use them in decision making system of IHE. Large dataset of IHE is difficult to analysis and display, since they are significant for decision making in IHE. This study utilized the famous data mining software, Weka and SOM to mine and visualize IHE data. In order to discover worthwhile patterns, we used clustering techniques and visualized the results. The selected dataset includes data of five medical university of Tehran as a small data set and Ministry of Science - Research and Technology's universities as a larger data set. Knowledge discovery and visualization are necessary for analyzing of these datasets. Our analysis reveals some knowledge in higher education aspect related to program of study, degree in each program, learning style, study mode and other IHE attributes. This study helps to IHE to discover knowledge in a visualize way; our results can be focused more by experts in higher education field to assess and evaluate more.

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