Searched for: subject%3A%22Data%255C+mining%22
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Budel, G.J.A. (author), Frasincar, Flavius (author), Boekestijn, David (author)
Sequence data mining has become an increasingly popular research topic as the availability of data has grown rapidly over the past decades. Sequence clustering is a type of method within this field that is in high demand in the industry, but the sequence clustering problem is non-trivial and, as opposed to static cluster analysis,...
journal article 2024
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Özmetin, Doruk (author)
In this study, we try to understand what kind of topics and frameworks are covered by the popular software testing books, and see whether these topics satisfy the industry needs and address the rising trends. To define "popular" software testing books, we formulated three heuristics. The topics of the books are analyzed through LDA topic...
bachelor thesis 2023
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Yang, Fuqiang (author), Huang, Yujie (author), Tao, Jing (author), Reniers, G.L.L.M.E. (author), Chen, Chao (author)
It is well known that safety climate (SC) has paramount significance in safety science and accident prevention. In this paper, a bibliometric data mining is conducted to systematically review the research domain of SC. Overall, 1624 documents on SC are obtained, covering 4830 authors, 473 journals, 89 countries/regions, and 1766 institutions...
review 2023
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Pannunzio, V. (author), Kleinsmann, M.S. (author), Snelders, H.M.J.J. (author), Raijmakers, J.H.M. (author)
Digital health technologies, powered by digital data, provide an opportunity to improve the efficacy and efficiency of health systems at large. However, little is known about different approaches to the use of data for digital health design, or about their possible relations to system-level dynamics. In this contribution, we identify four...
journal article 2023
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Shome, A. (author), Cruz, Luis (author), van Deursen, A. (author)
Visualisations drive all aspects of the Machine Learning (ML) Development Cycle but remain a vastly untapped resource by the research community. ML testing is a highly interactive and cognitive process which demands a human-in-the-loop approach. Besides writing tests for the code base, bulk of the evaluation requires application of domain...
conference paper 2023
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Ding, Chuanwei (author), Zhang, Li (author), Chen, Haoyu (author), Hong, Hong (author), Zhu, Xiaohua (author), Fioranelli, F. (author)
Radar-based solutions have attracted great attention in human activity recognition (HAR) for their advantages in accuracy, robustness, and privacy protection. The conventional approaches transform radar signals into feature maps and then directly process them as visual images. While effective, these image-based methods may not be the best...
journal article 2023
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Piadeh, Farzad (author), Behzadian, Kourosh (author), Chen, Albert S. (author), Kapelan, Z. (author), Rizzuto, Joseph P. (author), Campos, Luiza C. (author)
This study presents a novel approach for urban flood forecasting in drainage systems using a dynamic ensemble-based data mining model which has yet to be utilised properly in this context. The proposed method incorporates an event identification technique and rainfall feature extraction to develop weak learner data mining models. These models...
journal article 2023
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Kunneman, Youetta (author), Alves da Motta-Filho, Mauricy (author), van der Waa, J.S. (author)
To support effective and successful projects, Service Design practitioners rely on insights that mainly build on qualitative research methodology. The literature on data science promises to help transform how design research is done, adding sophisticated quantitative analyses, complementing existing methods with the power of machines. Due to...
journal article 2022
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Smirnova, Alisa (author), Yang, J. (author), Yang, Dingqi (author), Cudre-Mauroux, Philippe (author)
Noisy labels represent one of the key issues in supervised machine learning. Existing work for label noise reduction mainly takes a probabilistic approach that infers true labels from data distributions in low-level feature spaces. Such an approach is not only limited by its capability to learn high-quality data representations, but also by...
journal article 2022
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Herrera-Semenets, Vitali (author), Hernández-León, Raudel (author), van den Berg, Jan (author)
We live in a world that is being driven by data. This leads to challenges of extracting and analyzing knowledge from large volumes of data. An example of such a challenge is intrusion detection. Intrusion detection data sets are characterized by huge volumes, which affects the learning of the classifier. So there is a need to reduce the size...
journal article 2022
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Schulze Balhorn, L. (author), Gao, Q. (author), Goldstein, Dominik (author), Schweidtmann, A.M. (author)
Flowsheets are the most important building blocks to define and communicate the structure of chemical processes. Gaining access to large data sets of machine-readable chemical flowsheets could significantly enhance process synthesis through artificial intelligence. A large number of these flowsheets are publicly available in the scientific...
book chapter 2022
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Coraddu, A. (author), Kalikatzarakis, Miltiadis (author), Walker, J.M. (author), Ilardi, Davide (author), Oneto, Luca (author)
The purpose of this chapter is to provide an overview of the state-of-the-art and future perspectives of Data Science and Advanced Analytics for Shipping Energy Systems. Specifically, we will start by listing the different static and dynamic data sources and knowledge base available in this particular context. Then we will review the Data...
book chapter 2022
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Lee, Sujin (author), Lee, Jinwoo (author), Hiemstra-van Mastrigt, S. (author), Kim, E.Y. (author)
As city-level modal splits are outcomes of city functions, it is essential to understand whether and how city attributes affect modal splits to derive a modal shift toward low-emission travel modes and sustainable mobility in cities. This study elucidates this relationship between modal splits and city attributes in 46 cities worldwide,...
journal article 2022
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Chang, Haoliang (author), Huang, Jianxiang (author), Yao, Weiran (author), Zhao, Weizun (author), Li, L. (author)
Urban rail development can increase land value, reduce commute time, and increase accessibility, as reported in the literature. However, little is known about the impact of opening urban rail transit stations on people's sentiment, particularly in the context of large metropolises where population density is significantly high. This paper...
journal article 2022
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Faber, Robin (author)
Agent-based simulation models are rising in popularity recently due to their ability to model real-world problems in a wide range of domains. Inherent to these types of simulations is the fact that an enormous amount of data can be generated, which needs to be analysed in order to make the simulation useful. At the moment, the available tools to...
master thesis 2021
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Bonifazi, A. (author), Sun, Junzi (author), van Baren, Gerben (author), Hoekstra, J.M. (author)
Not all flight data anomalies correspond to operational safety concerns. But anomalous safety events can be linked to anomalies in flight data. During the final phases of a flight, two significant safety events are unstable approach and goaround. In this paper, using Automatic Dependent Surveillance- Broadcast (ADS-B) data, we develop several...
conference paper 2021
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Liu, Y. (author), Semertzis, I. (author), Stefanov, Alexandru (author), Palensky, P. (author)
The security issues of Cyber-Physical power Systems (CPS) have attracted widespread attention from scholars. Vulnerability assessment emerges as an effective method to identify the critical components and thus increase the system resilience. While efforts have been made to study the vulnerability features of power systems under the occurrence...
conference paper 2021
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Athanasiou, Panagiotis (author), Van Dongeren, Ap (author), Giardino, Alessio (author), Vousdoukas, Michalis (author), Antolínez, José A. Á. (author), Ranasinghe, Roshanka (author)
Dune erosion driven by extreme marine storms can damage local infrastructure or ecosystems and affect the long-term flood safety of the hinterland. These storms typically affect long stretches (∼100 km) of sandy coastlines with variable topo-bathymetries. The large spatial scale makes it computationally challenging for process-based...
journal article 2021
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Bonifazi, Alberto (author)
This thesis shows that it is possible to produce safety knowledge by mining Automatic Dependent Surveillance-Broadcast (ADS-B) data. The methodology combines exceedance detection and anomaly detection techniques to identify anomalous safety events in approach flights. One of these events is unstable approaches, which are identified with a rule...
master thesis 2020
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ZHENG, Qianqian (author)
Emo:on-driven design inspects people’s emotional experiences in a targeted context and study the concerns behind these emo:ons. The is connected to an understanding to people’s personal experiences. Social media is playing an increasingly important role in daily life, as the technologies to do social media mining is developing, it is becoming a...
master thesis 2020
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