Qiang Li^1,2,*, Pan Chen¹, Lihong Gao¹, Dan Meng¹, Jinjie Zou¹

CMES-Computer Modeling in Engineering & Sciences, Vol.135, No.1, pp. 465-481, 2023, DOI:10.32604/cmes.2022.020300

Abstract Monopiles are the most common foundation form of offshore wind turbines, which bear the vertical load, lateral load and bending moment. It remains uncertain whether the applied vertical load increases the lateral deflection of the pile. This paper investigated the influence of vertical load on the behaviour of monopiles installed in the sand under combined load using three-dimensional numerical methods. The commercial software PLAXIS was used for simulations in this paper. Monopiles were modelled as a structure incorporating linear elastic material behaviour and soil was modelled using the Hardening-Soil (HS) constitutive model. The monopiles under vertical load, lateral load and… More >

KHANDAKAR ABU MD MOSTAFIZAR RAHMAN^1,2, ABDUL SHUKOR JURAIMI^2,*, MD. REZWAN MOLLA³, MUHAMMAD ASYRAF MD HATTA⁴, ZULKEFLY BIN SULAIMAN⁵, SHAMIMA SULTANA⁶, AHMED GABER⁷, BENUKAR BISWAS⁸, AKBAR HOSSAIN^9,*

BIOCELL, Vol.47, No.1, pp. 227-237, 2023, DOI:10.32604/biocell.2023.025135

Abstract Every breeding program that aims to create new and improved cultivars with desired traits mostly relies on information related to genetic diversity. Therefore, molecular characterization of germplasms is important to obtain target cultivars with desirable traits. Sweet potato [Ipomoea batatas (L.) Lam] is widely considered the world’s most important crop, with great diversity in morphological and phenotypic traits. The genetic diversity of 20 sweet potato germplasms originating from Bangladesh, CIP, Philippines, Taiwan, and Malaysia were compared, which was accomplished by genetic diversity analysis by exploring 20 microsatellite DNA markers for germplasm characterization and utilization. This information was effective in differentiating… More >

Yongqiang Guo^1,2,*, Zhiyuan Lv³

CMES-Computer Modeling in Engineering & Sciences, Vol.134, No.3, pp. 1855-1870, 2023, DOI:10.32604/cmes.2022.022211

Abstract In uncertainty analysis and reliability-based multidisciplinary design and optimization (RBMDO) of engineering structures, the saddlepoint approximation (SA) method can be utilized to enhance the accuracy and efficiency of reliability evaluation. However, the random variables involved in SA should be easy to handle. Additionally, the corresponding saddlepoint equation should not be complicated. Both of them limit the application of SA for engineering problems. The moment method can construct an approximate cumulative distribution function of the performance function based on the first few statistical moments. However, the traditional moment matching method is not very accurate generally. In order to take advantage of… More >

Samuel Bimenyimana¹, Chen Wang^1,*, Godwin Norense Osarumwense Asemota², Aphrodis Nduwamungu², Francis Mulolani⁶, Jean De Dieu Niyonteze⁸, Shilpi Bora^1,7, Chun-Ling Ho¹, Noel Hagumimana³, Theobald Habineza⁴, Waqar Bashir⁵, Yiyi Mo¹

Energy Engineering, Vol.119, No.6, pp. 2369-2406, 2022, DOI:10.32604/ee.2022.019257

Abstract The world’s energy consumption and power generation demand will continue to rise. Furthermore, the bulk of the energy resources needed to satisfy the rising demand is far from the load centers. The aforementioned requires long-distance transmission systems and one way to accomplish this is to use high voltage direct current (HVDC) transmission systems. The main technical issues for HVDC transmission systems are loss of synchronism, variation of quadrature currents, amplitude, the inability of station 1 (rectifier), and station 2 (inverter) to either inject, or absorb active, or reactive power in the network in any circumstances (before a fault occurs, during… More >

Shin Jin Kang¹, Soo Kyun Kim^2,*

Intelligent Automation & Soft Computing, Vol.35, No.3, pp. 2573-2588, 2023, DOI:10.32604/iasc.2023.029893

Abstract In this paper, we propose an authentication method that use mouse and keystroke dynamics to enhance online privacy and security. The proposed method identifies personalized repeated user interface (UI) sequences by analyzing mouse and keyboard data. To this end, an Apriori algorithm based on the keystroke-level model (KLM) of the human–computer interface domain was used. The proposed system can detect repeated UI sequences based on KLM for authentication in the software. The effectiveness of the proposed method is verified through access testing using commercial applications that require intensive UI interactions. The results show using our cognitive mouse-and-keystroke dynamics system can… More >

Suma Sekhar^1,*, Sakuntala S. Pillai², S. Santhosh Kumar³

Intelligent Automation & Soft Computing, Vol.35, No.3, pp. 3187-3197, 2023, DOI:10.32604/iasc.2023.028702

Abstract Worldwide Interoperability for Microwave Access (WiMAX) trusts Multiple Input Multiple Output-Orthogonal Frequency Division Multiplexing (MIMO-OFDM) combination for the deployment of physical layer functions and for connecting the medium access control to the wireless media. Even though Orthogonal Frequency Division Multiplexing (OFDM) facilitates reliable digital broadband transmission in the fading wireless channels, the presence of synchronization errors in the form of Carrier Frequency Offset (CFO) and Time Offset (TO) adversely affect the performance of OFDM based physical layers. The objective of this work is to improve the accuracy of the frequency and the time offset estimation in the WiMAX physical layer.… More >

P. Sharmila^1,*, C. Deisy¹, S. Parthasarathy²

Computer Systems Science and Engineering, Vol.45, No.1, pp. 377-393, 2023, DOI:10.32604/csse.2023.027481

Abstract With the continuous growth of online news articles, there arises the necessity for an efficient abstractive summarization technique for the problem of information overloading. Abstractive summarization is highly complex and requires a deeper understanding and proper reasoning to come up with its own summary outline. Abstractive summarization task is framed as seq2seq modeling. Existing seq2seq methods perform better on short sequences; however, for long sequences, the performance degrades due to high computation and hence a two-phase self-normalized deep neural document summarization model consisting of improvised extractive cosine normalization and seq2seq abstractive phases has been proposed in this paper. The novelty… More >

T. S. Kanchana^*, B. Smitha Evelin Zoraida

Intelligent Automation & Soft Computing, Vol.35, No.2, pp. 2003-2013, 2023, DOI:10.32604/iasc.2023.029412

Abstract Human Facial expressions exhibits the inner personality. Evaluating the inner personality is performed through questionnaires during recruitment process. However, the evaluation through questionnaires performs less due to anxiety, and stress during interview and prediction of leadership quality becomes a challenging problem. To the above problem, Temporal sequence based SENet architecture (TSSA) is proposed for accurate evaluation of personality trait for employing the correct person for leadership position. Moreover, SENet is integration with modern architectures for performance evaluation. In Proposed TSSA, face book facial images of a particular person for a period of one month and face images collect from different… More >

Haikuo Peng¹, Yun Tan^1,*, Hao Tang², Ling Tan², Xuyu Xiang¹, Yongjun Wang², Neal N. Xiong³

CMC-Computers, Materials & Continua, Vol.73, No.2, pp. 2757-2771, 2022, DOI:10.32604/cmc.2022.029727

Abstract Aortic dissection (AD) is one of the most serious diseases with high mortality, and its diagnosis mainly depends on computed tomography (CT) results. Most existing automatic diagnosis methods of AD are only suitable for AD recognition, which usually require preselection of CT images and cannot be further classified to different types. In this work, we constructed a dataset of 105 cases with a total of 49021 slices, including 31043 slices expert-level annotation and proposed a two-stage AD diagnosis structure based on sequence information and deep learning. The proposed region of interest (RoI) extraction algorithm based on sequence information (RESI) can… More >

S. Hariprasad^1,*, T. Deepa¹, N. Bharathiraja²

Intelligent Automation & Soft Computing, Vol.34, No.3, pp. 1425-1440, 2022, DOI:10.32604/iasc.2022.022856

Abstract The Internet of Things (IoT) is a global information and communication technology which aims to connect any type of device to the internet at any time and in any location. Nowadays billions of IoT devices are connected to the world, this leads to easily cause vulnerability to IoT devices. The increasing of users in different IoT-related applications leads to more data attacks is happening in the IoT networks after the fog layer. To detect and reduce the attacks the deep learning model is used. In this article, a hybrid sample selected recurrent neural network-extreme learning machine (hybrid SSRNN-ELM) algorithm that… More >