Nitin Mittal¹, Rohit Salgotra^2,3, Abhishek Sharma⁴, Sandeep Kaur⁵, S. S. Askar⁶, Mohamed Abouhawwash^7,8,*

Intelligent Automation & Soft Computing, Vol.37, No.3, pp. 3159-3177, 2023, DOI:10.32604/iasc.2023.041059

Abstract The optimization of cognitive radio (CR) system using an enhanced firefly algorithm (EFA) is presented in this work. The Firefly algorithm (FA) is a nature-inspired algorithm based on the unique light-flashing behavior of fireflies. It has already proved its competence in various optimization problems, but it suffers from slow convergence issues. To improve the convergence performance of FA, a new variant named EFA is proposed. The effectiveness of EFA as a good optimizer is demonstrated by optimizing benchmark functions, and simulation results show its superior performance compared to biogeography-based optimization (BBO), bat algorithm, artificial bee colony, and FA. As an… More >

Xiukai Ruan¹, Shahid Iqbal Awan^2,*

Journal on Internet of Things, Vol.4, No.4, pp. 215-225, 2022, DOI:10.32604/jiot.2022.038270

Abstract A SCMA ACO-OFDM downlink visible light communication (VLC) system is proposed. Six users share four spectrum resources, four of which are 4 primary color LED lights. ACO-OFDM technology is used to convert the user’s sparse codebook mapped signal into a positive real value signal that can be carried on the light wave, which can realize high-speed parallel communication. Simulation verifies the feasibility of the system. At the same time, the channel model of visible light communication is constructed, and the signal-to-noise ratio(SNR) and channel gain of the visible light channel are systematically analyzed. Finally, the theoretical bit error rate formula… More >

WENQI CHEN^1,#, XIAOYANG CHU^2,#, YANG ZENG^3,#, YOUSHENG YAN⁴, YIPENG WANG⁴, DONGLAN SUN¹, DONGLIANG ZHANG⁵, JING ZHANG^1,*, KAI YANG^4,*

BIOCELL, Vol.47, No.7, pp. 1561-1569, 2023, DOI:10.32604/biocell.2023.028851

Abstract Background: Receptor tyrosine kinase-like orphan receptor 2 (ROR2) has a vital role in osteogenesis. However, the mechanism underlying the regulation of ROR2 in osteogenic differentiation is still poorly comprehended. A previous study by our research group showed that a novel compound heterozygous ROR2 variation accounted for the autosomal recessive Robinow syndrome (ARRS). This study attempted to explore the impact of the ROR2: c.904C>T variant specifically on the osteogenic differentiation of BMSCs. Methods: Coimmunoprecipitation (CoIP)-western blotting was carried out to identify the interaction between ROR2 and Wnt5a. Double-immunofluorescence staining was used for determining the expressions and co-localization of ROR2 and Wnt5a… More > Graphic Abstract

Rongge Xiao^a , Yue Zhu^b,*, Wenbo Jin^a , Zheng Dai^a , Shifang Li^a , Fan Zhang^c

Frontiers in Heat and Mass Transfer, Vol.12, pp. 1-6, 2019, DOI:10.5098/hmt.12.28

Abstract In order to accurately obtain the wax deposition rate model, according to the kinetic principle of wax deposition, several factors affecting the wax deposition rate were selected, and by a optimization software of First Optimization(1stOpt), The parameters of two typical wax deposition rate models are solved respectively based on optimization algorithm combined by Levenberg-Marquardt (L-M) algorithm and global optimization and the calculated data were compared. The results show that: compared with the model parameters obtained by least squares method, the model parameters obtained by this optimization algorithm can describe the variation of wax deposition rate more accurately. The maximum error… More >

Jingang Kim, Suengbum Lim, Taejin Lee^*

Computer Systems Science and Engineering, Vol.47, No.1, pp. 471-490, 2023, DOI:10.32604/csse.2023.038413

Abstract AI-related research is conducted in various ways, but the reliability of AI prediction results is currently insufficient, so expert decisions are indispensable for tasks that require essential decision-making. XAI (eXplainable AI) is studied to improve the reliability of AI. However, each XAI methodology shows different results in the same data set and exact model. This means that XAI results must be given meaning, and a lot of noise value emerges. This paper proposes the HFD (Hybrid Feature Dropout)-based XAI and evaluation methodology. The proposed XAI methodology can mitigate shortcomings, such as incorrect feature weights and impractical feature selection. There are… More >

V. W. Bhatkar^a, Anirban Sur^b,*, Anindita Roy^b

Frontiers in Heat and Mass Transfer, Vol.19, pp. 1-8, 2022, DOI:10.5098/hmt.19.3

Abstract In heating, Wet-bulb temperature in HVAC (heating, ventilation, and air conditioning) applications is crucial for building the equipment. But radiation from the surrounding surfaces caused the errors during the thermodynamic wet-bulb temperature measurement. The wet-bulb temperature of moist air is measured in the current work utilising an aspiration psychrometer designed, developed, and built to reduce the error term caused by radiation and convection heat transfer. Wet-bulb temperature is calculated in the experiments using an aspiration psychrometer at various locations throughout the year, both with and without a shield. It has been found that the error term depends on several factors,… More >

Feezan Ahmad¹, Xiaowei Tang¹, Jilei Hu^2,*, Mahmood Ahmad^3,4, Behrouz Gordan⁵

CMES-Computer Modeling in Engineering & Sciences, Vol.137, No.1, pp. 455-487, 2023, DOI:10.32604/cmes.2023.025993

Abstract Slope stability prediction plays a significant role in landslide disaster prevention and mitigation. This paper’s reduced error pruning (REP) tree and random tree (RT) models are developed for slope stability evaluation and meeting the high precision and rapidity requirements in slope engineering. The data set of this study includes five parameters, namely slope height, slope angle, cohesion, internal friction angle, and peak ground acceleration. The available data is split into two categories: training (75%) and test (25%) sets. The output of the RT and REP tree models is evaluated using performance measures including accuracy (Acc), Matthews correlation coefficient (Mcc), precision… More >

QIAOLING WU^1,2, ZHAOLEI CUI³, HONGMEI XIA¹, SHAN JIANG¹, JING BAI⁴, ZHUO SHAO⁴, YANG SUN^1,*

BIOCELL, Vol.47, No.5, pp. 1039-1050, 2023, DOI:10.32604/biocell.2023.027494

Abstract Background: Ovarian cancer (OC) is a leading cause of gynecological cancer-linked deaths worldwide. Exosomal miR-1825 and its target gene C-type lectin domain family 5 member A (CLEC5A) are associated with tumorigenesis in cancers that was further probed. Methods: Exosomal miR-1825 expression in exosomes and its impact on overall survival (OS) prediction were determined using Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA) data. Target genes of miR-1825 were searched in five prediction databases and prognostically significant differentially expressed genes were identified. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were carried out. The… More >

S. Vijayashaarathi^1,*, S. NithyaKalyani²

Computer Systems Science and Engineering, Vol.46, No.3, pp. 2881-2897, 2023, DOI:10.32604/csse.2023.036864

Abstract In recent years, real-time video streaming has grown in popularity. The growing popularity of the Internet of Things (IoT) and other wireless heterogeneous networks mandates that network resources be carefully apportioned among versatile users in order to achieve the best Quality of Experience (QoE) and performance objectives. Most researchers focused on Forward Error Correction (FEC) techniques when attempting to strike a balance between QoE and performance. However, as network capacity increases, the performance degrades, impacting the live visual experience. Recently, Deep Learning (DL) algorithms have been successfully integrated with FEC to stream videos across multiple heterogeneous networks. But these algorithms… More >

Salah-ud-din Khokhar^1,2,*, QinKe Peng¹, Muhammad Yasir Noor³

CMC-Computers, Materials & Continua, Vol.75, No.2, pp. 2413-2427, 2023, DOI:10.32604/cmc.2023.036148

Abstract For fuzzy systems to be implemented effectively, the fuzzy membership function (MF) is essential. A fuzzy system (FS) that implements precise input and output MFs is presented to enhance the performance and accuracy of single-input single-output (SISO) FSs and introduce the most applicable input and output MFs protocol to linearize the fuzzy system’s output. Utilizing a variety of non-linear techniques, a SISO FS is simulated. The results of FS experiments conducted in comparable conditions are then compared. The simulated results and the results of the experimental setup agree fairly well. The findings of the suggested model demonstrate that the relative… More >