Zhelong He^1,*

The International Conference on Computational & Experimental Engineering and Sciences, Vol.26, No.1, pp. 1-1, 2023, DOI:10.32604/icces.2023.010452

Abstract This presentation introduces a concurrent topology and fiber-path optimization for continuous fiber composite under thermos-mechanical loadings. The optimization goal is to minimize the structural compliance of composite with thermos-mechanical coupling while satisfying volume fraction constraint, and ensuring the manufacturability by using continuous fibers and avoiding the appearance of over thin members. Level-set function is utilized to represent both shape boundary and fiber path. The zero isocontour of level-set function is updated using a shape sensitivity analysis for anisotropic composite, and fiber paths in shape are given by level-set functions determined from shape boundary. A level-set-based… More >

Zhixian Qi^1,2,*, Shuohe Wang^1,2, Qiang Xue^1,2, Haiting Mi³, Jian Wang^1,2

Energy Engineering, Vol.120, No.9, pp. 2059-2077, 2023, DOI:10.32604/ee.2023.028595 - 03 August 2023

Abstract A current identification method based on optimized variational mode decomposition (VMD) and sample entropy (SampEn) is proposed in order to solve the problem that the main protection of the urban rail transit DC feeder cannot distinguish between train charging current and remote short circuit current. This method uses the principle of energy difference to optimize the optimal mode decomposition number k of VMD; the optimal VMD for DC feeder current is decomposed into the intrinsic modal function (IMF) of different frequency bands. The sample entropy algorithm is used to perform feature extraction of each IMF, and More >

Zhaoting Liu¹, Jianbo Wu^1,*, Sha He², Xin Rao³, Shiqiang Wang², Shen Wang¹, Wei Wei⁴

Structural Durability & Health Monitoring, Vol.17, No.4, pp. 299-314, 2023, DOI:10.32604/sdhm.2023.022554 - 02 August 2023

Abstract It is known that eddy current effect has a great influence on magnetic flux leakage testing (MFL). Usually, contact-type encoder wheels are used to measure MFL testing speed to evaluate the effect and further compensate testing signals. This speed measurement method is complicated, and inevitable abrasion and occasional slippage will reduce the measurement accuracy. In order to solve this problem, based on eddy current effect due to the relative movement, a speed measurement method is proposed, which is contactless and simple. In the high-speed MFL testing, eddy current induced in the specimen will cause an More > Graphic Abstract

Manar Ahmed Hamza^1,*, Hala J. Alshahrani², Khaled Tarmissi³, Ayman Yafoz⁴, Amira Sayed A. Aziz⁵, Mohammad Mahzari⁶, Abu Sarwar Zamani¹, Ishfaq Yaseen¹

Computer Systems Science and Engineering, Vol.47, No.2, pp. 1691-1707, 2023, DOI:10.32604/csse.2023.034798 - 28 July 2023

Abstract Applied linguistics is one of the fields in the linguistics domain and deals with the practical applications of the language studies such as speech processing, language teaching, translation and speech therapy. The ever-growing Online Social Networks (OSNs) experience a vital issue to confront, i.e., hate speech. Amongst the OSN-oriented security problems, the usage of offensive language is the most important threat that is prevalently found across the Internet. Based on the group targeted, the offensive language varies in terms of adult content, hate speech, racism, cyberbullying, abuse, trolling and profanity. Amongst these, hate speech is… More >

Loc Vu-Quoc^1,*, Alexander Humer²

CMES-Computer Modeling in Engineering & Sciences, Vol.137, No.2, pp. 1069-1343, 2023, DOI:10.32604/cmes.2023.028130 - 26 June 2023

Abstract Three recent breakthroughs due to AI in arts and science serve as motivation: An award winning digital image, protein folding, fast matrix multiplication. Many recent developments in artificial neural networks, particularly deep learning (DL), applied and relevant to computational mechanics (solid, fluids, finite-element technology) are reviewed in detail. Both hybrid and pure machine learning (ML) methods are discussed. Hybrid methods combine traditional PDE discretizations with ML methods either (1) to help model complex nonlinear constitutive relations, (2) to nonlinearly reduce the model order for efficient simulation (turbulence), or (3) to accelerate the simulation by predicting… More >

Jayashree Shetty¹, Nisha P. Shetty^1,*, Hrushikesh Kothikar¹, Saleh Mowla¹, Aiswarya Anand¹, Veeraj Hegde²

Intelligent Automation & Soft Computing, Vol.37, No.2, pp. 1345-1362, 2023, DOI:10.32604/iasc.2023.039206 - 21 June 2023

Abstract Alzheimer’s disease (AD) is an intensifying disorder that causes brain cells to degenerate early and destruct. Mild cognitive impairment (MCI) is one of the early signs of AD that interferes with people’s regular functioning and daily activities. The proposed work includes a deep learning approach with a multimodal recurrent neural network (RNN) to predict whether MCI leads to Alzheimer’s or not. The gated recurrent unit (GRU) RNN classifier is trained using individual and correlated features. Feature vectors are concatenated based on their correlation strength to improve prediction results. The feature vectors generated are given as… More >

Nur Fairuz Mohamed Yusof¹, Dahaman Ishak², Muhammad Ammirrul Atiqi Mohd Zainuri^3,*, Muhammad Najwan Hamidi², Zuhair Muhammed Alaas⁴, Mohamed Mostafa Ramadan Ahmed⁵

Intelligent Automation & Soft Computing, Vol.37, No.2, pp. 2441-2457, 2023, DOI:10.32604/iasc.2023.037778 - 21 June 2023

Abstract Grid-connected reactive-load compensation and harmonic control are becoming a central topic as photovoltaic (PV) grid-connected systems diversified. This research aims to produce a high-performance inverter with a fast dynamic response for accurate reference tracking and a low total harmonic distortion (THD) even under nonlinear load applications by improving its control scheme. The proposed system is expected to operate in both stand-alone mode and grid-connected mode. In stand-alone mode, the proposed controller supplies power to critical loads, alternatively during grid-connected mode provide excess energy to the utility. A modified variable step incremental conductance (VS-InCond) algorithm is… More >

T. Karthikeyan^1,*, M. Govindarajan¹, V. Vijayakumar²

Intelligent Automation & Soft Computing, Vol.37, No.2, pp. 1483-1498, 2023, DOI:10.32604/iasc.2023.037606 - 21 June 2023

Abstract Frauds don’t follow any recurring patterns. They require the use of unsupervised learning since their behaviour is continually changing. Fraudsters have access to the most recent technology, which gives them the ability to defraud people through online transactions. Fraudsters make assumptions about consumers’ routine behaviour, and fraud develops swiftly. Unsupervised learning must be used by fraud detection systems to recognize online payments since some fraudsters start out using online channels before moving on to other techniques. Building a deep convolutional neural network model to identify anomalies from conventional competitive swarm optimization patterns with a focus… More >

Tiankui Sun^1,*, Mingming Shi¹, Xiaolong Xiao¹, Ping He¹, Yu Ji¹, Zhiyuan Yuan²

Energy Engineering, Vol.120, No.7, pp. 1621-1636, 2023, DOI:10.32604/ee.2023.026948 - 04 May 2023

Abstract To reduce current harmonics caused by switching frequency, T-type grid-connected inverter topology with LCL filter is adopted. In view of the disadvantages of the slow response speed of the traditional current control and the failure to eliminate the influence of the LCL filter on the grid-connected current by using current PI control alone, a current double closed loop PI current tracking control is proposed. Through the theoretical analysis of the grid-connected inverter control principle, the grid-connected inverter control model is designed, and the transfer function model of each control link is deduced, and the current More >

S. Balaji^*, S. Karthik

Intelligent Automation & Soft Computing, Vol.37, No.1, pp. 727-743, 2023, DOI:10.32604/iasc.2023.037409 - 29 April 2023

Abstract The creation of national energy strategy cannot proceed without accurate projections of future electricity consumption; this is because EC is intimately tied to other forms of energy, such as oil and natural gas. For the purpose of determining and bettering overall energy consumption, there is an urgent requirement for accurate monitoring and calculation of EC at the building level using cutting-edge technology such as data analytics and the internet of things (IoT). Soft computing is a subset of AI that tries to design procedures that are more accurate and reliable, and it has proven to… More >