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Investigating the potential associations between long non-coding RNAs (lncRNAs) and diseases is crucial for advancing disease research and the development of therapeutic approaches. Nevertheless, the current lncRNA-disease association (LDA) data ...

Thanks to the broad application fields, learning neural networks is still a more significant problem nowadays. Any attempt in the construction of faster learning algorithms is highly well come. This article presents a new way of learning neural ...

This paper considers technical systems described by nonlinear dynamic models. The fault tolerance property of such systems is ensured by introducing feedback with full or partial fault decoupling. The solution is based on separating a subsystem ...

The Dynamic Mode Decomposition (DMD) is a versatile and increasingly popular method for data driven analysis of dynamical systems that arise in a variety of applications in, e.g., computational fluid dynamics, robotics or machine learning. In the ...

The Dynamic Mode Decomposition (DMD) is a method for computational analysis of nonlinear dynamical systems in data driven scenarios. Based on high fidelity numerical simulations or experimental data, the DMD can be used to reveal the latent structures in ...

The development of a secure battery management system (BMS) for electric vehicles depends heavily on the correct assessment of the online state-of-charge (SOC) of Li-ion batteries. The ternary lithium battery is used as the research object in this paper, ...

Major problems in time-of-arrival (TOA)-based ultra-wide band (UWB) indoor localisation and tracking of multi-targets reside in the noise induced by the multipath effect in line-of-sight (LOS) and non-line-of-sight (NLOS) conditions and the interference ...

In the present scenario, the security of medical images is an important aspect in the field of image processing. Support vector machines (SVMs) are a supervised machine learning technique used in image classification. The roots of SVM are from ...

A significant security and protection concern in telemedicine at the moment is how to secure the confidentiality of sensitive data delivered over the Internet and limit access to designated information. In this paper, we propose medical ECG data privacy ...

Owing to the low accuracy and efficiency of extracting abnormal signals in traditional methods, a power grid abnormal frequency signal extraction method based on spectrum analysis is proposed. Secondly, for the denoised power grid signal, the bispectral ...

This study proposes a lifelong deep learning control scheme for robotic manipulators with bounded disturbances. This scheme involves the use of an online tunable deep neural network (DNN) to approximate the unknown nonlinear dynamics of the robot. ...

We introduce a new singular value decomposition (SVD) solver based on the QR-based Dynamically Weighted Halley (QDWH) algorithm for computing the partial spectrum SVD (QDWHpartial-SVD) problems. By optimizing the rational function underlying the ...

This paper is a brief note on the natural implementation of singular value decomposition (SVD) and polar decomposition of an arbitrary multivector in nondegenerate real (Clifford) geometric algebras of arbitrary dimension and signature. We ...

In dynamic interaction graphs, user-item interactions usually follow heterogeneous patterns, represented by different structural information, such as user-item co-occurrence, sequential information of user interactions and the transition probabilities of ...

This article applies multiple machine learning methods to strongly suggest that Chief Justice John Marshall behaved unethically in an important 19th Century case of American constitutional law: Martin v. Hunter's Lessee. He wrote large swathes of the ...

This paper is concerned with the issue of hybrid‐triggered scheme H∞ asynchronous control for networked Markov jump systems (MJSs) with probabilistic cyber attacks. First, in view of the subsistent phenomenon that the controller cannot capture the ...

The purpose of this study is to develop a text clustering–based analysis of COVID-19 research articles. Owing to the proliferation of published COVID-19 research articles, researchers need a method for reducing the number of articles they have to search ...

Symmetric eigenvalue decomposition (EVD) is a fundamental analytic and numerical tool used in many scientific areas. The state-of-the-art algorithm in terms of performance is typically the two-stage tridiagonalization method. The first stage in the two-...

Forecasting of fuzzy time series is considered by presenting a standard fuzzy set in the form of a tensor obtained as a result of the tensor product of components, as well as by forming a tensor sequence whose last element (the predicted fuzzy set)...

Electronic healthcare records (EHR) provide a rich resource for healthcare research. An important problem for the efficient utilization of the EHR data is the representation of the EHR features, which include the unstructured clinical narratives and the ...