Lujuan Deng, Boyi Liu^*, Zuhe Li

CMC-Computers, Materials & Continua, Vol.78, No.1, pp. 1157-1170, 2024, DOI:10.32604/cmc.2023.042150

Abstract Multimodal sentiment analysis aims to understand people’s emotions and opinions from diverse data. Concatenating or multiplying various modalities is a traditional multi-modal sentiment analysis fusion method. This fusion method does not utilize the correlation information between modalities. To solve this problem, this paper proposes a model based on a multi-head attention mechanism. First, after preprocessing the original data. Then, the feature representation is converted into a sequence of word vectors and positional encoding is introduced to better understand the semantic and sequential information in the input sequence. Next, the input coding sequence is fed into the transformer model for further… More >

Xinzong Wang¹, Xiaofang Kang^1,2,*, Qingguan Lei¹

CMES-Computer Modeling in Engineering & Sciences, Vol.137, No.2, pp. 1749-1771, 2023, DOI:10.32604/cmes.2023.027745

Abstract The chaotic motion behavior of the rectangular conductive thin plate that is simply supported on four sides by airflow and mechanical external excitation in a magnetic field is studied. According to Kirchhoff ’s thin plate theory, considering geometric nonlinearity and using the principle of virtual work, the nonlinear motion partial differential equation of the rectangular conductive thin plate is deduced. Using the separate variable method and Galerkin’s method, the system motion partial differential equation is converted into the general equation of the Duffing equation; the Hamilton system is introduced, and the Melnikov function is used to analyze the Hamilton system,… More > Graphic Abstract

H. Varun Chand^*, J. Karthikeyan

Intelligent Automation & Soft Computing, Vol.31, No.2, pp. 717-728, 2022, DOI:10.32604/iasc.2022.020008

Abstract

The drowsiness of the driver and rash driving are the major causes of road accidents, which result in loss of valuable life, and deteriorate the safety in the road traffic. Reliable and precise driver drowsiness systems are required to prevent road accidents and to improve road traffic safety. Various driver drowsiness detection systems have been designed with different technologies which have an affinity towards the unique parameter of detecting the drowsiness of the driver. This paper proposes a novel model of multi-level distribution of detecting the driver drowsiness using the Convolution Neural Networks (CNN) followed by the emotion analysis. The… More >

Abeer A. AlFutamani, Heyam H. Al-Baity^*

Intelligent Automation & Soft Computing, Vol.29, No.1, pp. 89-109, 2021, DOI:10.32604/iasc.2021.016555

Abstract Social media sites produce a large amount of data and offer a highly competitive advantage for companies when they can benefit from and address data, as data provides a deeper understanding of clients and their needs. This understanding of clients helps in effectively making the correct decisions within the company, based on data obtained from social media websites. Thus, sentiment analysis has become a key tool for understanding that data. Sentiment analysis is a research area that focuses on analyzing people’s emotions and opinions to identify the polarity (e.g., positive or negative) of a given text. Since we need to… More >

Huiping Jiang^1,*, Rui Jiao¹, Demeng Wu¹, Wenbo Wu²

CMC-Computers, Materials & Continua, Vol.68, No.2, pp. 2315-2327, 2021, DOI:10.32604/cmc.2021.016832

Abstract With the rapid development of deep learning and artificial intelligence, affective computing, as a branch field, has attracted increasing research attention. Human emotions are diverse and are directly expressed via non-physiological indicators, such as electroencephalogram (EEG) signals. However, whether emotion-based or EEG-based, these remain single-modes of emotion recognition. Multi-mode fusion emotion recognition can improve accuracy by utilizing feature diversity and correlation. Therefore, three different models have been established: the single-mode-based EEG-long and short-term memory (LSTM) model, the Facial-LSTM model based on facial expressions processing EEG data, and the multi-mode LSTM-convolutional neural network (CNN) model that combines expressions and EEG. Their… More >

Xinxin Lu^1,*, Hong Zhang²

CMES-Computer Modeling in Engineering & Sciences, Vol.125, No.1, pp. 281-297, 2020, DOI:10.32604/cmes.2020.010948

Abstract As an interdisciplinary comprehensive subject involving multidisciplinary knowledge, emotional analysis has become a hot topic in psychology, health medicine and computer science. It has a high comprehensive and practical application value. Emotion research based on the social network is a relatively new topic in the field of psychology and medical health research. The text emotion analysis of college students also has an important research significance for the emotional state of students at a certain time or a certain period, so as to understand their normal state, abnormal state and the reason of state change from the information they wrote. In… More >

Jiqiang Zhang¹, Ziru Niu^1,2, Tianhua Li^1,2, Yanqiang Wu¹, Rui Xi¹, Yuhua Li¹, Guanghua Li³, Jialin Hou^1,2,*

Phyton-International Journal of Experimental Botany, Vol.89, No.1, pp. 147-166, 2020, DOI:10.32604/phyton.2020.08479

Abstract Considering the current low level of mechanization for domestic green onion planting and the high labor intensity of artificial planting, a 2ZYX-2 green onion ditching and transplanting machine, which can complete ditching, ridging, transplanting, repression, soil covering and other operations, is designed in this study. The Central Composite test design method was carried out with the speed of the transplanting machine, the depth of the opener and the horizontal position of the opener as the experimental factors and with the qualification ratio of perpendicularity, the variation coefficient of the plant spacing and the qualification ratio of the planting depth as… More >

Maria João M. Vasconcelos¹, João Manuel R. S. Tavares¹

The International Conference on Computational & Experimental Engineering and Sciences, Vol.10, No.1, pp. 3-4, 2009, DOI:10.3970/icces.2009.010.003

Abstract In the last years, researchers from the Computational Vision working field have been developing new methods to perform image segmentation for human motion analysis. The development of computational techniques suitable to automatically identify the structures involved is necessary to obtain more representative and robust features to be further used in the analysis of human motion from image sequences.
The first step of human motion analysis from image sequences is strongly related with image segmentation. In fact, the first goal of any system designed for this aim is the identification of the structures’ features to be analysed in the image frames.… More >

Mingxu Sun^1,#,*, Yinghang Jiang^2,3,#, Qi Liu^3,4,*, Xiaodong Liu⁴

CMC-Computers, Materials & Continua, Vol.60, No.1, pp. 67-83, 2019, DOI:10.32604/cmc.2019.06079

Abstract A Functional Electrical stimulation (FES) therapy is a common rehabilitation intervention after stroke, and finite state machine (FSM) has proven to be an effective and intuitive FES control method. The FSM uses the data information generated by the accelerometer to robustly trigger state transitions. In the medical field, it is necessary to obtain highly safe and accurate acceleration data. In order to ensure the accuracy of the acceleration sensor data without affecting the accuracy of the motion analysis, we need to perform acceleration big data calibration. In this context, we propose a method for robustly calculating the auto-calibration gain using… More >