In this paper, we will focus to one of the recent applications of PU-algebras in the coding theory, namely the construction of codes by soft sets PU-valued functions. First, we shall introduce the notion of soft sets PU-valued functions on PU-algebra and investigate some of its related properties.Moreover, the codes generated by a soft sets PU-valued function are constructed and several examples are given. Furthermore, example with graphs of binary block code constructed from a soft sets PU-valued function is constructed.
Ischemic stroke is a significant cause of morbidity and mortality worldwide. Autophagy, a process of intracellular degradation, has been shown to play a crucial role in the pathogenesis of ischemic stroke. Long non-coding RNAs (lncRNAs) have emerged as essential regulators of autophagy in various diseases, including ischemic stroke. Recent studies have identified several lncRNAs that modulate autophagy in ischemic stroke, including MALAT1, MIAT, SNHG12, H19, AC136007. 2, C2dat2, MEG3, KCNQ1OT1, SNHG3, and RMRP. These lncRNAs regulate autophagy by interacting with key proteins involved in the autophagic process, such as Beclin-1, ATG7, and LC3. Understanding the role of lncRNAs in regulating auto
Image compression is very important in reducing the costs of data storage transmission in relatively slow channels. Wavelet transform has received significant attention because their multiresolution decomposition that allows efficient image analysis. This paper attempts to give an understanding of the wavelet transform using two more popular examples for wavelet transform, Haar and Daubechies techniques, and make compression between their effects on the image compression.
This paper presents the application of a framework of fast and efficient compressive sampling based on the concept of random sampling of sparse Audio signal. It provides four important features. (i) It is universal with a variety of sparse signals. (ii) The number of measurements required for exact reconstruction is nearly optimal and much less then the sampling frequency and below the Nyquist frequency. (iii) It has very low complexity and fast computation. (iv) It is developed on the provable mathematical model from which we are able to quantify trade-offs among streaming capability, computation/memory requirement and quality of reconstruction of the audio signal. Compressed sensing CS is an attractive compression scheme due to its uni
... Show MoreIn this paper a nonlinear adaptive control method is presented for a pH process, which is difficult to control due to the nonlinear and uncertainties. A theoretical and experimental investigation was conducted of the dynamic behavior of neutralization process in a continuous stirred tank reactor (CSTR). The process control was implemented using different control strategies, velocity form of PI control and nonlinear adaptive control. Through simulation studies it has been shown that the estimated parameters are in good agreement with the actual values and that the proposed adaptive controller has excellent tracking and regulation performance.
Text based-image clustering (TBIC) is an insufficient approach for clustering related web images. It is a challenging task to abstract the visual features of images with the support of textual information in a database. In content-based image clustering (CBIC), image data are clustered on the foundation of specific features like texture, colors, boundaries, shapes. In this paper, an effective CBIC) technique is presented, which uses texture and statistical features of the images. The statistical features or moments of colors (mean, skewness, standard deviation, kurtosis, and variance) are extracted from the images. These features are collected in a one dimension array, and then genetic algorithm (GA) is applied for image clustering.
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