Meng Zhang¹, Lijuan Zhang², Jie Zhang¹, Shiliang Miao², Jiangong Yang², Yajun Zhao^1,*, Feifei Bu¹

Energy Engineering, Vol.123, No.7, 2026, DOI:10.32604/ee.2025.074465 - 18 June 2026

Abstract Conventional electric servo drive systems suffer from high common-mode voltage (CMV) due to the use of zero vectors in Space Vector Pulse Width Modulation (SVPWM). To mitigate this issue, this paper proposes an inverted SVPWM (I-SVPWM) strategy. By simply inverting the switching actions of a specific phase, this strategy avoids the use of zero vectors and achieves an effect similar to Active Zero-State PWM (AZSPWM), thereby effectively suppressing common-mode voltage. Compared with AZSPWM, the proposed method eliminates the need to recalculate vector action times or design new switching sequences. It can be seamlessly implemented by… More > Graphic Abstract

Vinh Truong Hoang^*, Nghia Dinh, Luu Quang Phuong, Kiet Tran-Trung, Ha Duong Thi Hong, Bay Nguyen Van, Hau Nguyen Trung, Thien Ho Huong

CMC-Computers, Materials & Continua, Vol.88, No.2, 2026, DOI:10.32604/cmc.2026.078743 - 15 June 2026

Abstract Visual speech recognition is a central problem in computer vision, encompassing both lip reading (visual speech recognition) and sign language recognition. Although substantial progress has been achieved independently on each task, their complementary characteristics have rarely been explored jointly. In this work we propose UniModal-LSR (Unified Multimodal Lip and Sign Recognition), a novel deep learning framework that jointly addresses lip reading and sign language recognition within a single multimodal architecture. By exploiting shared properties of visual communication channels, namely temporal dynamics, spatial articulation structure, and contextual dependencies, the proposed model enables bidirectional transfer of knowledge… More >

Yan Ge¹, Zhenzhou Zhang², Chien-Ming Chen^3,*

CMC-Computers, Materials & Continua, Vol.88, No.2, 2026, DOI:10.32604/cmc.2026.077790 - 15 June 2026

Abstract Periodic pattern mining plays an important role in revealing recurring behavioral regularities from temporal sequence data. Most existing approaches, however, are developed for single-sequence settings and rarely account for quantitative information or sequence-level constraints when patterns recur across multiple sequences. This limits their usefulness in practical scenarios, where a pattern is expected to be not only periodic but also quantitatively significant in a sufficiently large portion of sequences. In this work, we formulate the problem of mining High-Quantitative Periodic Frequent Patterns (HQPFPS) from multi-sequence databases and propose an efficient algorithm, termed MHQPFPS. The proposed method… More >

Jinhuo Liang, Jinan Shen^*, Pengfei Wang, Fang Liang, Xuejian Deng

CMC-Computers, Materials & Continua, Vol.87, No.1, 2026, DOI:10.32604/cmc.2025.073076 - 10 February 2026

Abstract The method for malware detection based on Application Programming Interface (API) call sequences, as a primary research focus within dynamic detection technologies, currently lacks attention to subsequences of API calls, the variety of API call types, and the length of sequences. This oversight leads to overly complex call sequences. To address this issue, a dynamic malware detection approach based on multiple subsequences is proposed. Initially, APIs are remapped and encoded, with the introduction of percentile lengths to process sequences. Subsequently, a combination of One-Dimensional Convolutional Neural Network (1D-CNN) and Bidirectional Long Short-Term Memory (Bi-LSTM) networks, More >

Yali Si^1,2, Feng Li^1,*, Shan Zhong^1,2, Chenghang Huo³, Jing Chen⁴, Jinglian Liu^1,2

CMC-Computers, Materials & Continua, Vol.81, No.1, pp. 685-706, 2024, DOI:10.32604/cmc.2024.055141 - 15 October 2024

Abstract Point-of-interest (POI) recommendations in location-based social networks (LBSNs) have developed rapidly by incorporating feature information and deep learning methods. However, most studies have failed to accurately reflect different users’ preferences, in particular, the short-term preferences of inactive users. To better learn user preferences, in this study, we propose a long-short-term-preference-based adaptive successive POI recommendation (LSTP-ASR) method by combining trajectory sequence processing, long short-term preference learning, and spatiotemporal context. First, the check-in trajectory sequences are adaptively divided into recent and historical sequences according to a dynamic time window. Subsequently, an adaptive filling strategy is used to… More >

Haoxue Wu^#, Xiaohan Zhang^§,#, Xiaoyu Chen, Kang Li, Aixia Xu, Zhen Huang, Jungang Dong, Chengyu Yu^*

Phyton-International Journal of Experimental Botany, Vol.93, No.3, pp. 627-640, 2024, DOI:10.32604/phyton.2024.050321 - 28 March 2024

Abstract Genetic manipulation (either restraint or enhancement) of the biosynthesis pathway of α-linolenic acid (ALA) in seed oil is an important goal in Brassica napus breeding. B. napus is a tetraploid plant whose genome often harbors four and six homologous copies, respectively, of the two fatty acid desaturases FAD2 and FAD3, which control the last two steps of ALA biosynthesis during seed oil accumulation. In this study, we compared their promoters, coding sequences, and expression levels in three high-ALA inbred lines 2006L, R8Q10, and YH25005, a low-ALA line A28, a low-ALA/high-oleic-acid accession SW, and the wildtype ZS11. The expression… More >

Rafi Ullah^1,*, Mohd Hilmi bin Hasan¹, Sultan Daud Khan², Mussadiq Abdul Rahim³

CMC-Computers, Materials & Continua, Vol.78, No.3, pp. 3283-3301, 2024, DOI:10.32604/cmc.2024.046305 - 26 March 2024

Abstract Medical imaging plays a key role within modern hospital management systems for diagnostic purposes. Compression methodologies are extensively employed to mitigate storage demands and enhance transmission speed, all while upholding image quality. Moreover, an increasing number of hospitals are embracing cloud computing for patient data storage, necessitating meticulous scrutiny of server security and privacy protocols. Nevertheless, considering the widespread availability of multimedia tools, the preservation of digital data integrity surpasses the significance of compression alone. In response to this concern, we propose a secure storage and transmission solution for compressed medical image sequences, such as… More >

Zhenhua Yu, Liangxue Bai, Ou Ye^*, Xuya Cong

CMC-Computers, Materials & Continua, Vol.78, No.2, pp. 1773-1795, 2024, DOI:10.32604/cmc.2023.047130 - 27 February 2024

Abstract Social robot accounts controlled by artificial intelligence or humans are active in social networks, bringing negative impacts to network security and social life. Existing social robot detection methods based on graph neural networks suffer from the problem of many social network nodes and complex relationships, which makes it difficult to accurately describe the difference between the topological relations of nodes, resulting in low detection accuracy of social robots. This paper proposes a social robot detection method with the use of an improved neural network. First, social relationship subgraphs are constructed by leveraging the user’s social… More >

Muhammad Naeem Akbar^1,*, Seemab Khan², Muhammad Umar Farooq¹, Majed Alhaisoni³, Usman Tariq⁴, Muhammad Usman Akram¹

CMC-Computers, Materials & Continua, Vol.76, No.3, pp. 3275-3295, 2023, DOI:10.32604/cmc.2023.039289 - 08 October 2023

Abstract The combination of spatiotemporal videos and essential features can improve the performance of human action recognition (HAR); however, the individual type of features usually degrades the performance due to similar actions and complex backgrounds. The deep convolutional neural network has improved performance in recent years for several computer vision applications due to its spatial information. This article proposes a new framework called for video surveillance human action recognition dubbed HybridHR-Net. On a few selected datasets, deep transfer learning is used to pre-trained the EfficientNet-b0 deep learning model. Bayesian optimization is employed for the tuning of… More >

Siti Julia Rosli^1,2, Hasliza A Rahim^1,2,*, Khairul Najmy Abdul Rani^1,2, Ruzelita Ngadiran^2,3, Wan Azani Mustafa^3,4, Muzammil Jusoh^1,2, Mohd Najib Mohd Yasin^1,2, Thennarasan Sabapathy^1,2, Mohamedfareq Abdulmalek⁵, Wan Suryani Firuz Wan Ariffin², Ahmed Alkhayyat⁶

CMC-Computers, Materials & Continua, Vol.76, No.2, pp. 2571-2571, 2023, DOI:10.32604/cmc.2023.045533 - 30 August 2023

Abstract This article has no abstract. More >