A Real-world Case Study of Process and Data Driven Predictive Analytics for Manufacturing Workflows

A predictive analytics approach to understanding process mass intensity (PMI) is described. This method leverages real-world data to predict probable PMI outcomes for a potential synthetic route and to compare PMI outcomes to the summation of prior experience.

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A data-driven hierarchical MILP approach for scheduling clinical pathways: a real-world case study from a German university hospital

BuR - Business Research ◽

10.1007/s40685-019-00102-z ◽

2019 ◽

Vol 12 (2) ◽

pp. 597-636

Author(s):

Karsten Schwarz ◽

Michael Römer ◽

Taïeb Mellouli

Keyword(s):

Real World ◽

Clinical Pathways ◽

University Hospital ◽

Data Driven

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Determining Potential Failures and Challenges in Data Driven Endeavors: A Real World Case Study Analysis

Proceedings of the 5th International Conference on Internet of Things, Big Data and Security ◽

10.5220/0009792504530460 ◽

2020 ◽

Author(s):

Daniel Staegemann ◽

Matthias Volk ◽

Tuan Vu ◽

Sascha Bosse ◽

Robert Häusler ◽

...

Keyword(s):

Real World ◽

Data Driven ◽

Study Analysis ◽

Case Study Analysis

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The Use of Predictive Analyzes for University Dropout Cases

Iraqi Journal of Science ◽

10.24996/ijs.2021.si.1.7 ◽

2021 ◽

pp. 44-51

Author(s):

Iraqi Journal Of Science ◽

Hachem Harouni Alaoui ◽

Elkaber Hachem ◽

Cherif Ziti ◽

Mustapha Bassiri

Keyword(s):

Real World ◽

Predictive Analytics ◽

Dropping Out ◽

University Dropout ◽

The University

We will also derive practical solutions using predictive analytics. And this would include application making predictions with real world example from University of Faculty of Chariaa of Fez. As soon as student enrolled to the university, they will certainly encounter many difficulties and problems which discourage their motivation towards their courses and which pushes them to leave their university.The aim of our article is to manage an investigation of the issue of dropping out their studies. This investigation actively integrates the benefits ofmachine learning. Hence, we will concentrate on two fundamental strategies which are KNN, which depends on the idea of likeness among data; and the famous strategy SVM, which can break the issues of classification.Thanks to predictive analytics, we can come up concrete solutions to decrease this issue. Therefore, our case study was specifically limited to University of Chariaa-Fez, Morocco.

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Operating Data-driven Predictive Analytics for Tele-diagnosis of Refrigeration Systems: A Case Study

2018 IEEE International Conference on Industrial Engineering and Engineering Management (IEEM) ◽

10.1109/ieem.2018.8607436 ◽

2018 ◽

Author(s):

Tianyi Lu ◽

Jun Du ◽

Roger J. Jiao

Keyword(s):

Predictive Analytics ◽

Data Driven ◽

Operating Data

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Qualitative Case Study Research Design

Perspectives on Fluency and Fluency Disorders ◽

10.1044/ffd25.1.39 ◽

2015 ◽

Vol 25 (1) ◽

pp. 39-45 ◽

Cited By ~ 5

Author(s):

Jennifer Tetnowski

Keyword(s):

Research Design ◽

Real World ◽

Qualitative Case Study ◽

Case Study Research ◽

Study Research

Qualitative case study research can be a valuable tool for answering complex, real-world questions. This method is often misunderstood or neglected due to a lack of understanding by researchers and reviewers. This tutorial defines the characteristics of qualitative case study research and its application to a broader understanding of stuttering that cannot be defined through other methodologies. This article will describe ways that data can be collected and analyzed.

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Big Data-driven Algorithmic Decision-Making in Selecting and Managing Employees: Advanced Predictive Analytics, Workforce Metrics, and Digital Innovations for Enhancing Organizational Human Capital Social Sciences, Sociology, Management and complex organi

Psychosociological Issues in Human Resource Management ◽

10.22381/pihrm7220198 ◽

2019 ◽

Vol 7 (2) ◽

pp. 49 ◽

Cited By ~ 2

Keyword(s):

Social Sciences ◽

Decision Making ◽

Human Capital ◽

Big Data ◽

Predictive Analytics ◽

Data Driven ◽

Capital Social

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Digital Storytelling in Cultural Heritage: Audience Engagement in the Interactive Documentary New Life

Sustainability ◽

10.3390/su13031193 ◽

2021 ◽

Vol 13 (3) ◽

pp. 1193

Author(s):

Anna Podara ◽

Dimitrios Giomelakis ◽

Constantinos Nicolaou ◽

Maria Matsiola ◽

Rigas Kotsakis

Keyword(s):

Cultural Heritage ◽

Full Range ◽

Social Dimension ◽

Data Driven ◽

Specific Interest ◽

Key Factors ◽

Audience Engagement ◽

Main Research ◽

The Social

This paper casts light on cultural heritage storytelling in the context of interactive documentary, a hybrid media genre that employs a full range of multimedia tools to document reality, provide sustainability of the production and successful engagement of the audience. The main research hypotheses are enclosed in the statements: (a) the interactive documentary is considered a valuable tool for the sustainability of cultural heritage and (b) digital approaches to documentary storytelling can provide a sustainable form of viewing during the years. Using the Greek interactive documentary (i-doc) NEW LIFE (2013) as a case study, the users’ engagement is evaluated by analyzing items from a seven-year database of web metrics. Specifically, we explore the adopted ways of the interactive documentary users to engage with the storytelling, the depth to which they were involved along with the most popular sections/traffic sources and finally, the differences between the first launch period and latest years were investigated. We concluded that interactivity affordances of this genre enhance the social dimension of cultural, while the key factors for sustainability are mainly (a) constant promotion with transmedia approach; (b) data-driven evaluation and reform; and (c) a good story that gathers relevant niches, with specific interest to the story.

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