Category: 7. Maths
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Heat-vision based drone surveillance augmented by deep learning for critical industrial monitoring
Power plant experiment To collect data on both normal and abnormal states in power plants, the experiments were conducted using the scaled-down nuclear power plant experimental facility named URI-LO32 as shown in Fig. 1a. This facility was meticulously designed to replicate the APR-1400 which is the modern pressurized water nuclear power reactor operational in Korea, featured…
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Consolidation of LVFRT capabilities of microgrids using energy storage devices
Tarafdar Hagh, M. & Khalili, T. A review of fault ride through of PV and wind renewable energies in grid codes. Int. J. Energy Res. 43(4), 1342–1356 (2019). Article Google Scholar Chandak, S. & Rout, P. K. The implementation framework of a microgrid: A review. Int. J. Energy Res. 45(3), 3523–3547 (2021). Article Google Scholar …
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Uncertainties in critical slowing down indicators of observation-based fingerprints of the Atlantic Overturning Circulation
HadISST The HadISST dataset is based on the Met Office Marine Data Bank as well as the Comprehensive Ocean-Atmosphere Data Set (COADS)46, and has been bias adjusted and then temporally and spatially homogenized using reduced-space optimal interpolation (RSOI). RSOI uses a set of global empirical orthogonal functions (EOFs), and includes regularizing terms when fitting the…
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Oblivious network intrusion detection systems
In this section, we present two application algorithms that utilize the hybrid gates: 1. Hybrid Direct Matching (HDM): Matching of plaintext stream against a homomorphically encrypted ciphertext rule. The algorithm describes how an oblivious NIDS at the Cloud Side can use the hybrid gates to search within the payload for an exact match against an…
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Scale-dependent power law properties in hashtag usage time series of Weibo
Time series of hashtag numbers We analyze the posting behavior of hashtags from Weibo, a mainstream micro-blog social media in China. We collect Weibo data through the publicly available API. Due to the huge volume of users and the limitation of the API, it is impossible to collect all the data for analysis, so we…
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A universal variational quantum eigensolver for non-Hermitian systems
Mathematical foundation The critical aspect of enabling variational quantum algorithms to calculate the eigenvalues of a general matrix involves identifying a unitary transformation matrix that can distinctly expose the eigenvalues in a similar manner to the eigenvector matrix. In our devised variational quantum universal eigensolver (VQUE), we utilize the mathematical foundation of Schur’s decomposition theory…
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Geometric trust-based secure localization technique for resiliency of GPS outage and location error in vehicular cyber-physical systems (VCPS)
This section comprises two phases. First, is the Geometric Localization technique for handling GPS outages, and the next is the location prediction and correction mechanism using an Extended Kalman filter for reducing location errors. Geometric localization technique for handling GPS outage In this phase, the overall design of the proposed GPS-assisted geometric localization is discussed.…
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Altitude measurement method of VHF radar based on spatial smoothing of correlation matrix
Figure 3 shows the schematic diagram of the forward and backward spatial smoothing (FBSS) algorithm. The principle of the forward smoothing algorithm is as follows. Divide the \(N\) uniform linear arrays into the \(P\) subarrays, where the adjacent subarrays are misaligned by one element. If the number of the elements of each subarray is \(M\), then…
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An ensemble-based deep learning model for detection of mutation causing cutaneous melanoma
This section includes all the step-by-step process of getting material (datasets) and processing it using different machine learning algorithms to identify melanomas. In the following sections testing methods of algorithms are explained thoroughly. Benchmark dataset collection The datasets are the most critical part of the research. These datasets are used for training the model, testing,…
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Optimum rescheduling of water networks for batch processes using a goal programming technique
To get the best rescheduling scheme by goal programming, a multi-objective function model is introduced. This model aims to achieve multiple objectives, including minimizing freshwater requirements, minimizing wastewater discharge, optimizing the number of tanks, and minimizing the degree of stream shifting, through goal programming to obtain the best rescheduling scheme. The proposed approach comprises three…