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Mashail Shaeel Althabiti,Manal Abdullah
Pág. pp. 90 - 106
Data stream is the huge amount of data generated in various fields, including financial processes, social media activities, Internet of Things applications, and many others. Such data cannot be processed through traditional data mining algorithms due to ...
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Reenu Mohandas, Mark Southern, Eoin O?Connell and Martin Hayes
Deep learning based visual cognition has greatly improved the accuracy of defect detection, reducing processing times and increasing product throughput across a variety of manufacturing use cases. There is however a continuing need for rigorous procedure...
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Yu Yao and Quan Qian
We develop the online process parameter design (OPPD) framework for efficiently handling streaming data collected from industrial automation equipment. This framework integrates online machine learning, concept drift detection and Bayesian optimization t...
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Guilherme Yukio Sakurai, Jessica Fernandes Lopes, Bruno Bogaz Zarpelão and Sylvio Barbon Junior
The stream mining paradigm has become increasingly popular due to the vast number of algorithms and methodologies it provides to address the current challenges of Internet of Things (IoT) and modern machine learning systems. Change detection algorithms, ...
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Sijia Jia, Zhenkai Zhang, Qi Dang, Chen Song and Chao Yang
Compared with traditional wings equipped with conventional control surfaces, variable-camber morphing wings have become a hot research topic in the field of aviation due to their ability to maintain a smooth and continuous overall shape while ensuring ex...
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Zhehu Yuan, Yinqi Sun and Dennis Shasha
Database and data structure research can improve machine learning performance in many ways. One way is to design better algorithms on data structures. This paper combines the use of incremental computation as well as sequential and probabilistic filterin...
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Lingkai Yang, Sally McClean, Mark Donnelly, Kevin Burke and Kashaf Khan
Concept drift, which refers to changes in the underlying process structure or customer behaviour over time, is inevitable in business processes, causing challenges in ensuring that the learned model is a proper representation of the new data. Due to fact...
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Frederic Stahl, Thien Le, Atta Badii and Mohamed Medhat Gaber
This paper introduces a new and expressive algorithm for inducing descriptive rule-sets from streaming data in real-time in order to describe frequent patterns explicitly encoded in the stream. Data Stream Mining (DSM) is concerned with the automatic ana...
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Juncal Alonso, Leire Orue-Echevarria, Eneko Osaba, Jesús López Lobo, Iñigo Martinez, Josu Diaz de Arcaya and Iñaki Etxaniz
The current IT market is more and more dominated by the ?cloud continuum?. In the ?traditional? cloud, computing resources are typically homogeneous in order to facilitate economies of scale. In contrast, in edge computing, computational resources are wi...
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Alessio Ferone and Antonio Maratea
Data streams are ubiquitous and related to the proliferation of low-cost mobile devices, sensors, wireless networks and the Internet of Things. While it is well known that complex phenomena are not stationary and exhibit a concept drift when observed for...
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Arvind Kumar Gangwar, Sandeep Kumar and Alok Mishra
The early and accurate prediction of defects helps in testing software and therefore leads to an overall higher-quality product. Due to drift in software defect data, prediction model performances may degrade over time. Very few earlier works have invest...
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Osama A. Mahdi, Eric Pardede, Nawfal Ali and Jinli Cao
The proposed drift detector can be applied in areas such as intrusion detection, fraud detectors or monitoring and forecasting traffic.
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Ghada Elkhawaga, Mervat Abuelkheir, Sherif I. Barakat, Alaa M. Riad and Manfred Reichert
Business processes evolve over time to adapt to changing business environments. This requires continuous monitoring of business processes to gain insights into whether they conform to the intended design or deviate from it. The situation when a business ...
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Dionisis Margaris and Costas Vassilakis
One of the major problems that social networks face is the continuous production of successful, user-targeted information in the form of recommendations, which are produced exploiting technology from the field of recommender systems. Recommender systems ...
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Viacheslav Moskalenko, Vyacheslav Kharchenko, Alona Moskalenko and Sergey Petrov
Modern trainable image recognition models are vulnerable to different types of perturbations; hence, the development of resilient intelligent algorithms for safety-critical applications remains a relevant concern to reduce the impact of perturbation on m...
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Ewa Osekowska, Henric Johnson, Bengt Carlsson
Pág. 1457 - 1476
Maritime traffic modeling serves the purpose of extracting human-readable information and discovering knowledge in the otherwise illegible mass of traffic data. The goal of this study is to examine the presence and character of fluctuations in maritime t...
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Abishek Manikandaraja, Peter Aaby and Nikolaos Pitropakis
Artificial intelligence and machine learning have become a necessary part of modern living along with the increased adoption of new computational devices. Because machine learning and artificial intelligence can detect malware better than traditional sig...
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Alberto Verdecia Cabrera, Isvani Frías Blanco, Luis Quintero Domínguez, Yanet Rodríguez Sarabia
Pág. 145 - 158
Nowadays many sources generate massive data continuously, without control of the arrival order and at high speed. Internet, cell-phones, cars, and security sensors are examples of such sources. Because of the temporal dimension of the data (they are cons...
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Viacheslav Moskalenko, Vyacheslav Kharchenko, Alona Moskalenko and Borys Kuzikov
Artificial intelligence systems are increasingly being used in industrial applications, security and military contexts, disaster response complexes, policing and justice practices, finance, and healthcare systems. However, disruptions to these systems ca...
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Takim Andriono,Abraham Abraham,L. David A.T.,Wong Foek Tjong
Pág. pp. 51 - 59
Recently, displacement-based seismic design concept is being developed. According to this concept, structures are designed based on a certain displacement target. This paper presents the application of the displacement-based design concept to reinforce...
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