In this study, Fourier-transform near infrared (FT-NIR) spectroscopy in combination with chemometrics was utilized to determine the antioxidant capacity and γaminobutyric acid (GABA) content of Chinese rice wine (CRW). Interval partial least-squares (iPLS) and extreme learning machine (ELM) were used to improve the performances of partial least-squares (PLS) models. In total, four different cal...

Memory encryption (ME) with authentication is becoming a key security feature of modern processors, as evident by the adoption ME Intel’s SGX. Recently actively studied from viewpoint system architecture. This paper studies symmetric-key cryptographic designs, primal focus on latency. A significant progress in such direction can be observed SGX Integrity Tree (SIT). Using variant AES-GCM...

The Joint European Torus (JET) high resolution Thomson scattering (HRTS) system measures radial electron temperature and density profiles. One of the key capabilities of this diagnostic is measuring the steep pressure gradient, termed the pedestal, at the edge of JET plasmas. The pedestal is susceptible to limiting instabilities, such as Edge Localised Modes (ELMs), characterised by a periodic ...

In this paper, a new hidden layer construction method for Extreme Learning Machines (ELMs) is investigated, aimed at generating a diverse set of weights. The paper proposes two new ELM variants: Binary ELM, with a weight initialization scheme based on f0;1g–weights; and Ternary ELM, with a weight initialization scheme based on f 1;0;1g–weights. The motivation behind this approach is that these ...

The deformation of landslides is a non-linear dynamic and complex process due to the impacts both inherent external factors. Understanding basis landslide essential prevent damage properties losses life. To forecast displacement, hybrid machine learning model proposed, in which Variational Modal Decomposition (VMD) implemented decompose measured total surface displacement into trend periodic co...

Discriminative clustering is an unsupervised learning framework which introduces the discriminative learning rule of supervised classification into clustering. The underlying assumption is that a good partition (clustering) of the data should yield high discrimination, namely, the partitioned data can be easily classified by some classification algorithms. In this paper, we propose three discri...

This paper proposes the online sequential extreme learning machine algorithm based on the recursive partial leastsquares method (OS-ELM-RPLS). It is an improvement to the online sequential extreme learning machine based on recursive least-squares (OS-ELM-RLS) introduced in [1]. Like in the batch extreme learning machine (ELM), in OSELM-RLS the input weights of a single-hidden layer feedforward ...

respectively. There are many iterative methods such as GMRES [7] and Bi-CGSTAB [9] algorithms for solving Eq. (1.1) which are more efficient than the Jacobi and Gauss-Seidel methods. However, when these methods are combined with the more efficient methods, for example as a preconditioner, can be quite successful. For example see [4, 6]. It has been proved that if A is a strictly diagonally domi...

BACKGROUND Effective and accurate diagnosis of attention-deficit/hyperactivity disorder (ADHD) is currently of significant interest. ADHD has been associated with multiple cortical features from structural MRI data. However, most existing learning algorithms for ADHD identification contain obvious defects, such as time-consuming training, parameters selection, etc. The aims of this study were a...