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- Aslam, Muhammad Shamrooz, et al.
(author)
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Observer–Based Control for a New Stochastic Maximum Power Point tracking for Photovoltaic Systems With Networked Control System
- 2023
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In: IEEE transactions on fuzzy systems. - Piscataway, NJ : IEEE. - 1063-6706 .- 1941-0034. ; 31:6, s. 1870-1884
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Journal article (peer-reviewed)abstract
- This study discusses the new stochastic maximum power point tracking (MPPT) control approach towards the photovoltaic cells (PCs). PC generator is isolated from the grid, resulting in a direct current (DC) microgrid that can provide changing loads. In the course of the nonlinear systems through the time-varying delays, we proposed a Networked Control Systems (NCSs) beneath an event-triggered approach basically in the fuzzy system. In this scenario, we look at how random, variable loads impact the PC generator's stability and efficiency. The basic premise of this article is to load changes and the value matching to a Markov chain. PC generators are complicated nonlinear systems that pose a modeling problem. Transforming this nonlinear PC generator model into the Takagi–Sugeno (T–S) fuzzy model is another option. Takagi–Sugeno (T–S) fuzzy model is presented in a unified framework, for which 1) the fuzzy observer–based on this premise variables can be used for approximately in the infinite states to the present system, 2) the fuzzy observer–based controller can be created using this same premises be the observer, and 3) to reduce the impact of transmission burden, an event-triggered method can be investigated. Simulating in the PC generator model for the realtime climate data obtained in China demonstrates the importance of our method. In addition, by using a new Lyapunov–Krasovskii functional (LKF) for combining to the allowed weighting matrices incorporating mode-dependent integral terms, the developed model can be stochastically stable and achieves the required performances. Based on the T-P transformation, a new depiction of the nonlinear system is derived in two separate steps in which an adequate controller input is guaranteed in the first step and an adequate vertex polytope is ensured in the second step. To present the potential of our proposed method, we simulate it for PC generators. © 2022 IEEE.
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| 3. |
- Aslam, Muhammad Shamrooz, et al.
(author)
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Robust stability analysis for class of Takagi-Sugeno (T-S) fuzzy with stochastic process for sustainable hypersonic vehicles
- 2023
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In: Information Sciences. - Amsterdam : Elsevier. - 0020-0255 .- 1872-6291. ; 641
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Journal article (peer-reviewed)abstract
- Recently, the rapid development of Unmanned Aerial Vehicles (UAVs) enables ecological conservation, such as low-carbon and “green” transport, which helps environmental sustainability. In order to address control issues in a given region, UAV charging infrastructure is urgently needed. To better achieve this task, an investigation into the T–S fuzzy modeling for Sustainable Hypersonic Vehicles (SHVs) with Markovian jump parameters and H∞ attitude control in three channels was conducted. Initially, the reentry dynamics were transformed into a control–oriented affine nonlinear model. Then, the original T–S local modeling method for SHV was projected by primarily referring to Taylor's expansion and fuzzy linearization methodologies. After the estimation of precision and controller complexity was assumed, the fuzzy model for jump nonlinear systems mainly consisted of two levels: a crisp level and a fuzzy level. The former illustrates the jumps, and the latter a fuzzy level that represents the nonlinearities of the system. Then, a systematic method built in a new coupled Lyapunov function for a stochastic fuzzy controller was used to guarantee the closed–loop system for H∞ gain in the presence of a predefined performance index. Ultimately, numerical simulations were conducted to show how the suggested controller can be successfully applied and functioned in controlling the original attitude dynamics. © 2023 Elsevier Inc.
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- Khan, Hameed Ullah, et al.
(author)
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SMDetector : Small mitotic detector in histopathology images using faster R-CNN with dilated convolutions in backbone model
- 2023
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In: Biomedical Signal Processing and Control. - Amsterdam : Elsevier. - 1746-8094 .- 1746-8108. ; 81
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Journal article (peer-reviewed)abstract
- Breast cancer is one of the most common cancer types among women, and it is a deadly disease caused by the uncontrolled proliferation of cells. Pathologists face a challenging issue of mitotic cell identification and counting during manual detection and identification of cancer. Artificial intelligence can help the medical professional with early, quick, and accurate diagnosis of breast cancer. Consequently, the survival rate will be improved and mortality rate will be decreased. Different deep learning techniques are used in computational pathology for cancer diagnosis. In this study, the SMDetector is proposed which is a deep learning model for detecting small objects such as mitotic and non-mitotic nuclei. This model employs dilated layers in the backbone to prevent small objects from disappearing in the deep layers. The purpose of the dilated layers in this model is to reduce the size gap between the image and the objects it contains. Region proposal network is optimized to accurately identify small objects. The proposed model yielded overall average precision (AP) of 50.31% and average recall (AR) of 55.90% that outperforms the existing standard object detection models on ICPR 2014 (Mitos-Atypia-14) dataset. To best of our knowledge the proposed model is state-of-the-art model for precision and recall of mitotic object detection on ICPR 2014 (Mitos-Atypia-14) dataset. The proposed model has achieved average precision for mitotic nuclei 68.49%, average recall for mitotic nuclei 59.86% and f-measure 63.88%. © 2022 The Authors
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| 5. |
- Mumtaz, Nadia, et al.
(author)
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An overview of violence detection techniques : current challenges and future directions
- 2023
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In: Artificial Intelligence Review. - Dordrecht : Springer Nature. - 0269-2821 .- 1573-7462. ; 56, s. 4641-4666
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Journal article (peer-reviewed)abstract
- The Big Video Data generated in today’s smart cities has raised concerns from its purposeful usage perspective, where surveillance cameras, among many others are the most prominent resources to contribute to the huge volumes of data, making its automated analysis adifcult task in terms of computation and preciseness. Violence detection (VD), broadly plunging under action and activity recognition domain, is used to analyze Big Video data for anomalous actions incurred due to humans. The VD literature is traditionally basedon manually engineered features, though advancements to deep learning based standalone models are developed for real-time VD analysis. This paper focuses on overview of deepsequence learning approaches along with localization strategies of the detected violence.This overview also dives into the initial image processing and machine learning-based VD literature and their possible advantages such as efciency against the current complex models. Furthermore,the datasets are discussed, to provide an analysis of the current models, explaining their pros and cons with future directions in VD domain derived from anin-depth analysis of the previous methods. © The Author(s), under exclusive licence to Springer Nature B.V. 2022.
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| 6. |
- Prayag, Girish, et al.
(author)
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Is Gen Z really that different? : Environmental attitudes, travel behaviours and sustainability practices of international tourists to Canterbury, New Zealand
- 2023
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In: Journal of Sustainable Tourism. - : Taylor & Francis Group. - 0966-9582 .- 1747-7646.
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Journal article (peer-reviewed)abstract
- Age has a significant influence on environmental attitudes and behaviour but there is no consensus on the effect that generational cohort has on these attitudes and behaviour. Using the New Environmental Paradigm (NEP) as the theoretical lens, this study evaluates whether Gen Z is similar or different to three other generations (Gen X, Y and Baby Boomers) on their environmental attitudes toward travel. The sustainability practices that these generational cohorts undertake during their travel are also evaluated. Based on 615 useable surveys of international visitors to the Canterbury region of New Zealand, we identify segments of visitors based on environmental attitudes and behaviour toward travel and generational cohort using a two-step clustering procedure. The results confirm inter-generational differences in environmental attitudes and travel behaviours but also highlight intra-generational differences. Gen Z tourists are more likely to belong to "Environmental" or "Mixed-Bag Environmental" segments that are more likely engage in sustainable practices related to resource saving and buying local food compared to other generations. The findings have implications for destination marketing and management.
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| 7. |
- Saberi-Movahed, Farid, et al.
(author)
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Dual Regularized Unsupervised Feature Selection Based on Matrix Factorization and Minimum Redundancy with application in gene selection
- 2022
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In: Knowledge-Based Systems. - Amsterdam : Elsevier. - 0950-7051 .- 1872-7409. ; 256
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Journal article (peer-reviewed)abstract
- Gene expression data have become increasingly important in machine learning and computational biology over the past few years. In the field of gene expression analysis, several matrix factorization-based dimensionality reduction methods have been developed. However, such methods can still be improved in terms of efficiency and reliability. In this paper, an innovative approach to feature selection, called Dual Regularized Unsupervised Feature Selection Based on Matrix Factorization and Minimum Redundancy (DR-FS-MFMR), is introduced. The major focus of DR-FS-MFMR is to discard redundant features from the set of original features. In order to reach this target, the primary feature selection problem is defined in terms of two aspects: (1) the matrix factorization of data matrix in terms of the feature weight matrix and the representation matrix, and (2) the correlation information related to the selected features set. Then, the objective function is enriched by employing two data representation characteristics along with an inner product regularization criterion to perform both the redundancy minimization process and the sparsity task more precisely. To demonstrate the proficiency of the DR-FS-MFMR method, a large number of experimental studies are conducted on nine gene expression datasets. The obtained computational results indicate the efficiency and productivity of DR-FS-MFMR for the gene selection task. © 2022 The Author(s)
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| 8. |
- Shamrooz Aslam, Muhammad, et al.
(author)
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A delayed Takagi–Sugeno fuzzy control approach with uncertain measurements using an extended sliding mode observer
- 2023
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In: Information Sciences. - Philadelphia, PA : Elsevier. - 0020-0255 .- 1872-6291. ; 643
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Journal article (peer-reviewed)abstract
- In this study, a sliding mode observer (SMO) is implemented on a T–S fuzzy system with multiple time–varying delays over continuous time. Because state data may not be fully available in practice, state observers are used to estimate state information. A system based on observers is implemented with non–parallel distribution compensation (N-PDC). Moreover, the concept of dissipative control provides a framework for analyzing the performance of H∞, L2−L∞, and dissipativeness. In order to design two sliding surfaces using the SMO gain matrix, first two integral–type sliding surfaces must be constructed. Then, we define a few additional parameters using fuzzy Lyapunov stability and SMO theory, resulting in asymptotically stable closed–loop performances. On the basis of the new error system, convex optimization is used to generate the sliding mode controller and the gained weight matrices. Following is an example of the power system (ship electric propulsion) to demonstrate the potential scheme. © 2023 Elsevier Inc.
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| 9. |
- Singh, Ram, et al.
(author)
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Impact of quarantine on fractional order dynamical model of Covid-19
- 2022
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In: Computers in Biology and Medicine. - Oxford : Elsevier. - 0010-4825 .- 1879-0534. ; 151, Part A
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Journal article (peer-reviewed)abstract
- In this paper, a Covid-19 dynamical transmission model of a coupled non-linear fractional differential equation in the Atangana-Baleanu Caputo sense is proposed. The basic dynamical transmission features of the proposed system are briefly discussed. The qualitative as well as quantitative results on the existence and uniqueness of the solutions are evaluated through the fixed point theorem. The Ulam-Hyers stability analysis of the suggested system is established. The two-step Adams-Bashforth-Moulton (ABM) numerical method is employed to find its numerical solution. The numerical simulation is performed to accesses the impact of various biological parameters on the dynamics of Covid-19 disease. © 2022 The Author(s). Published by Elsevier Ltd. All rights reserved.
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