A tool for visualization of risk information: the Risk Box

Karakoçak, Elif
Visualization is an effective way to represent data that mainly aims to make the data easier to be understood, analyzed, and processed by the users. In literature, there exist many studies focusing on the necessity and effectiveness of visualization in decision-making processes. Risk, on the other hand, is an important topic that needs to be considered for decision-makers in the project to decide on the further pathways to follow and need to be visualized in such a way to aid the decision-makers in these procedures. Hence, this thesis aims to understand the performance of the existing risk visualization techniques and form new ways to visualize the risk analysis outputs and risk information. In this manner, an initial needs assessment study has been conducted using the traditional outputs of Monte Carlo Simulation and found out that the visuals are not easy to understand by decision-makers. Hence, a “Risk Box” idea has been proposed and tested with decision-makers via semi-structured interviews using a case project. The proposed concept of Risk Box aimed to be designed as in the shape of a box having different faces while acquiring different and complementary risk information. At the end of the study, it has been found out that Risk Box is a useful and promising tool to be used in practice. Therefore, this study has shown that construction professionals can use Risk Box during risk assessment for a more effective communication of probabilistic information.


Recent Trends in the Use of Graph Neural Network Models for Natural Language Processing
Yılmaz, Burcu; Genç, Hilal; Ağrıman, Mustafa; Demirdöver, Buğra Kaan; Erdemir, Mert; Şimşek, Gökhan; Karagöz, Pınar (IGI Global, 2020-01-01)
Graphs are powerful data structures that allow us to represent varying relationships within data. In the past, due to the difficulties related to the time complexities of processing graph models, graphs rarely involved machine learning tasks. In recent years, especially with the new advances in deep learning techniques, increasing number of graph models related to the feature engineering and machine learning are proposed. Recently, there has been an increase in approaches that automatically learn to encode ...
A risk management approach for acquisition of software intensive systems in the Turkish Army.
Saylan, Necip; Demirös, Elif; Demirös, Onur; Department of Information Systems (2002)
The current techniques of risk assessment rely on checklists and human expertise. This constitutes a rigorous approach only when the people are experts on risk assessment. This thesis introduces a formal method and addresses the necessity of the identification and analysis of the risk. During implementation of risk management process, risk assessment will be discussed within an acquisition of software intensive systems in the Turkish Army. This thesis includes a survey and comparison of other software risk ...
A systematic review of eye-tracking-based research on animated multimedia learning
Coskun, Atakan; Çağıltay, Kürşat (2021-12-01)
Background The most challenging task in eye-tracking-based multimedia research is to establish a relationship between eye-tracking metrics (or cognitive processes) and learners' performance scores. Additionally, there are current debates about the effectiveness of animations (or simulations) in promoting learning in multimedia settings. Objectives As a result, the current study aimed to review eye tracking-based research on learners' cognitive processes in the animated/simulated multimedia learning domain. ...
A new approach to multivariate adaptive regression splines by using Tikhonov regularization and continuous optimization
TAYLAN, PAKİZE; Weber, Gerhard Wilhelm; Ozkurt, Fatma Yerlikaya (2010-12-01)
This paper introduces a model-based approach to the important data mining tool Multivariate adaptive regression splines (MARS), which has originally been organized in a more model-free way. Indeed, MARS denotes a modern methodology from statistical learning which is important in both classification and regression, with an increasing number of applications in many areas of science, economy and technology. It is very useful for high-dimensional problems and shows a great promise for fitting nonlinear multivar...
Collective classification of user emotions in twitter
İleri, İbrahim; Karagöz, Pınar; Department of Computer Engineering (2015)
The recent explosion of social networks has generated a big amount of data including user opinions about varied subjects. For classifying the sentiment of user postings, many text-based techniques have been proposed in the literature. As a continuation of sentiment analysis, there are also studies on the emotion analysis. Because of the fact that many different emotions are needed to be dealt with at this point, the problem becomes much more complicated. In this thesis, a different user-centric approach is ...
Citation Formats
E. Karakoçak, “A tool for visualization of risk information: the Risk Box,” M.S. - Master of Science, Middle East Technical University, 2021.