Article
Engineering, Electrical & Electronic
Yichen Duan, Xiaohong Shen, Haiyan Wang, Yongsheng Yan
Summary: This paper proposes a module-level soft fault detection method for the core module of a typical underwater acoustic sensing system. Simulation data obtained from multiple measurement points using Simulink are used, and the Short-Time Fourier Transform (STFT) is employed to represent different fault modes for effective learning by a convolutional neural network. The deep learning model is designed with an expansion bottleneck layer and an attention mechanism to enhance the learning ability, and it is pre-trained with simulation data. Experimental data from actual engineering practice are collected to fine-tune the model with a small amount of data. The experimental results demonstrate the feasibility of the proposed method for soft fault detection of the core module of typical underwater acoustic sensing systems.
SENSORS AND ACTUATORS A-PHYSICAL
(2023)
Article
Computer Science, Artificial Intelligence
Muhammad Irfan Ali, Mostafa K. El-Bably, El-Sayed A. Abo-Tabl
Summary: Approximation space is crucial for the accuracy of approximations on a subset of the universal set. This paper aims to develop new soft rough sets models using near open sets, enhancing the accuracy of approximations significantly. The concepts of near soft rough approximations and their properties are proposed, and comparisons with previous methods are made. An algorithm is provided for decision-making problems, and tested on hypothetical data for comparison with existing methods.
Article
Mathematics, Applied
Mostafa K. El-Bably, Radwan Abu-Gdairi, Mostafa A. El-Gayar
Summary: One of the challenges in medical diagnosis is accurately determining the nature of an injury due to similar symptoms of different diseases. This study focuses on proposing new mathematical methodologies using soft rough sets to improve precise decision-making in diagnosing Chikungunya virus disease. The proposed approach utilizes soft sets to approximate any set and demonstrates its superiority over previous works. The study also provides important medical applications using soft delta-rough sets and presents algorithms for diagnosis.
Article
Computer Science, Artificial Intelligence
Shuyin Xia, Hao Zhang, Wenhua Li, Guoyin Wang, Elisabeth Giem, Zizhong Chen
Summary: Feature reduction is crucial in Big Data analytics, and rough sets are commonly used for attribute reduction. However, existing rough set algorithms have limitations in terms of efficiency and effectiveness. To address these issues, a novel method called granular ball neighborhood rough sets (GBNRS) is proposed, which outperforms the current state-of-the-art method in terms of performance and classification accuracy.
IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING
(2022)
Article
Computer Science, Artificial Intelligence
Adem Yolcu, Aysun Benek, Taha Yasin Ozturk
Summary: This paper aims to expand the application scope of rough set theory, soft set theory, and neutrosophic set theory by introducing the concept of neutrosophic soft rough sets and developing the concept of neutrosophic soft rough topology. Definitions, properties, and examples of neutrosophic soft rough sets are established, and characteristics of neutrosophic soft rough topology such as open sets, closed sets, interior, and closure are defined.
KNOWLEDGE AND INFORMATION SYSTEMS
(2023)
Review
Energy & Fuels
Zhelun Chen, Zheng O'Neill, Jin Wen, Ojas Pradhan, Tao Yang, Xing Lu, Guanjing Lin, Shohei Miyata, Seungjae Lee, Chou Shen, Roberto Chiosa, Marco Savino Piscitelli, Alfonso Capozzoli, Franz Hengel, Alexander Kuehrer, Marco Pritoni, Wei Liu, John Clauss, Yimin Chen, Terry Herr
Summary: This paper reviews and summarizes the literature on data-driven fault detection and diagnostics (FDD) for building HVAC systems, focusing on the process, systems studied, and evaluation metrics. It identifies challenges such as real-building deployment, performance evaluation, scalability, interpretability, cyber security, data privacy, and user experience that data-driven FDD methods still face despite promising performance reported in the literature.
Article
Computer Science, Artificial Intelligence
Di Zhang, Pi-Yu Li, Shuang An
Summary: This paper introduces a new hybrid model called N-soft rough sets for handling problems involving multi-criteria decision-making, by introducing approximation operators and decision-making procedures, aiming to address limitations of extended rough sets models and illustrate its application in a real life example.
JOURNAL OF INTELLIGENT & FUZZY SYSTEMS
(2021)
Article
Computer Science, Artificial Intelligence
Ivenio Teixeira de Souza, Ana Carolina Rosa, Riccardo Patriarca, Assed Haddad
Summary: This study develops an integrated soft computing approach for nonlinear risk assessment in STS, combining FRAM with fuzzy sets to overcome the subjectivity of qualitative analysis.
EXPERT SYSTEMS WITH APPLICATIONS
(2022)
Article
Mathematics
Mohammed Atef, Shokry Nada, Abdu Gumaei, Ashraf S. Nawar
Summary: This study defines and discusses various types of soft rough fuzzy covering models and their derived measures, such as soft neighborhoods and soft measure degrees, aiming to increase lower approximation and decrease upper approximation. The relationships among these models and traditional models are also explored, providing insights into improving approximation accuracy.
JOURNAL OF MATHEMATICS
(2021)
Article
Computer Science, Information Systems
Frederico Cerveira, Raul Barbosa, Henrique Madeira, Filipe Araujo
Summary: Virtualized servers are widely used in cloud computing environments to host online applications and provide elastic computing resources. However, the presence of soft errors in large-scale servers can lead to various failure modes, with hang failures being the most common. A recovery mechanism using online testing is developed to address these hang failures and ensure server uptime.
IEEE TRANSACTIONS ON CLOUD COMPUTING
(2022)
Article
Automation & Control Systems
Haoyuan Gu, Hesheng Wang, Fan Xu, Zhe Liu, Weidong Chen
Summary: This article introduces an improved method for active fault detection to eliminate negative influences from additional signals. By generating fault detection signals with the controller and merging them with control signals, the system stability is rigorously proven, successfully applied in detecting locked-motor faults and visual servoing tasks.
IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS
(2021)
Article
Mathematics, Applied
Jose Sanabria, Katherine Rojo, Fernando Abad
Summary: Rough set and soft set theories provide mathematical foundations for studying decision making problems. This study rigorously analyzed two approaches, soft pre-rough approximation and soft beta-rough approximation, and concluded that they are the same. Additionally, proposed modifications to soft rough approximations were presented, with one method showing improved accuracy. The implemented approaches were used for diagnosing COVID-19 in Colombia, yielding the highest accuracy, and an algorithm was designed to handle larger datasets.
Review
Thermodynamics
Vijay Singh, Jyotirmay Mathur, Aviruch Bhatia
Summary: This review study focuses on the latest research and developments in fault detection and diagnostics (FDD) of Heating Ventilation and Air Conditioning (HVAC) systems. The basics of FDD and the methods developed for it are discussed, with emphasis on the use of machine learning techniques. The paper also covers fault prognosis, fault modeling, and provides a comparative study of different FDD methods. Future challenges and the importance of more efficient FDD systems in reducing energy consumption are also discussed.
INTERNATIONAL JOURNAL OF REFRIGERATION
(2022)
Article
Computer Science, Artificial Intelligence
Debarati B. Chakraborty, JingTao Yao
Summary: This article proposes a new methodology for unsupervised event prediction from videos, using the motion information in the video to detect events. By using rough sets and fuzzy sets, this method can accurately predict the occurrence of events.
PATTERN ANALYSIS AND APPLICATIONS
(2023)
Article
Computer Science, Information Systems
Saba Ayub, Waqas Mahmood, Muhammad Shabir, Ali N. A. Koam, Rizwan Gul
Summary: This paper introduces a soft multi-granulation RS (SMGRS) model based on two soft binary relations for dealing with uncertainty in data analysis. The model is applied to commutative algebra, group theory to investigate its structural properties. Numerical examples show the influence of SMGRS in decision-making.
Article
Engineering, Multidisciplinary
Piotr Bilski
Article
Engineering, Multidisciplinary
Piotr Bilski
Article
Engineering, Multidisciplinary
Piotr Bilski
Article
Engineering, Multidisciplinary
Piotr Bilski
Article
Engineering, Multidisciplinary
Piotr Bilski
Article
Energy & Fuels
Augustyn Wojcik, Piotr Bilski, Robert Lukaszewski, Krzysztof Dowalla, Ryszard Kowalik
Summary: The paper introduces a novel method for determining the characteristics of Electrical Appliances (EA) in the end-user environment, which evaluates the operational state of EAs through improved measurement systems and feature extraction. Experimental results demonstrate the practicality and usefulness of this approach for identifying different states of EAs accurately.
Article
Energy & Fuels
Krzysztof Dowalla, Piotr Bilski, Robert Lukaszewski, Augustyn Wojcik, Ryszard Kowalik
Summary: The paper presents a novel non-intrusive method for identifying appliances by analyzing changes in the common supply current signal. The method achieves high accuracy by processing the signal in the time domain, preserving the information in the original signal. Experimental results demonstrate the effectiveness of the approach in real-world scenarios.
Article
Telecommunications
Karol Kuczynski, Adrian Bilski, Piotr Bilski, Jerzy Szymanski
INTERNATIONAL JOURNAL OF ELECTRONICS AND TELECOMMUNICATIONS
(2020)
Proceedings Paper
Acoustics
Piotr Bilski, Adam Krajewski, Piotr Witomski, Piotr Bobinski, Marcin Lewandowski
2018 JOINT CONFERENCE - ACOUSTICS
(2018)
Proceedings Paper
Computer Science, Artificial Intelligence
Piotr Bilski, Jozef Modelski, Bartosz Kosciug, Jacek Olejnik, Iwona Badaczewska, Anna Malamou, Rodoula Makri
2017 IEEE INTERNATIONAL CONFERENCE ON RFID TECHNOLOGY & APPLICATION (RFID-TA)
(2017)
Proceedings Paper
Computer Science, Hardware & Architecture
Piotr Bilski, Wieslaw Winiecki
PROCEEDINGS OF THE 2017 9TH IEEE INTERNATIONAL CONFERENCE ON INTELLIGENT DATA ACQUISITION AND ADVANCED COMPUTING SYSTEMS: TECHNOLOGY AND APPLICATIONS (IDAACS), VOL 2
(2017)
Article
Acoustics
Piotr Bilski, Piotr Bobinski, Adam Krajewski, Piotr Witomski
ARCHIVES OF ACOUSTICS
(2017)
Proceedings Paper
Computer Science, Artificial Intelligence
Piotr Bilski, Wieslaw Winiecki
2015 IEEE 8TH INTERNATIONAL CONFERENCE ON INTELLIGENT DATA ACQUISITION AND ADVANCED COMPUTING SYSTEMS: TECHNOLOGY AND APPLICATIONS (IDAACS), VOLS 1-2
(2015)
Proceedings Paper
Computer Science, Artificial Intelligence
Piotr Bilski, Pawel Mazurek, Jakub Wagner
2015 IEEE 8TH INTERNATIONAL CONFERENCE ON INTELLIGENT DATA ACQUISITION AND ADVANCED COMPUTING SYSTEMS: TECHNOLOGY AND APPLICATIONS (IDAACS), VOLS 1-2
(2015)
Article
Automation & Control Systems
Piotr Bilski, Jacek Wojciechowski
INTERNATIONAL JOURNAL OF APPLIED MATHEMATICS AND COMPUTER SCIENCE
(2014)
