Emotion recognition is of great significance to computational intelligence systems. In order to improve the accuracy of emotion recognition, electroencephalogram (EEG) signals and external physiological (EP) signals are adopted due to their perfect performance in reflecting the slight variations of emotions, wherein EEG signals consist of multiple channels signals and EP signals consist of multiple types of signals. In this paper, a multimodal emotion recognition method based on convolutional auto-encoder (CAE) is proposed. Firstly, a CAE is designed to obtain the fusion features of multichannel EEG signals and multitype EP signals. Secondly, a fully connected neural network classifier is constructed to achieve emotion recognition. Finally, experiment results show that the proposed method can improve the accuracy of emotion recognition obviously compared with other similar methods.
Highway landscape and its regional elements think that it has the essential characteristics of various cultural phenomena, the functions of reproduction, dissemination and evolution, and the cultural diversity. Like all things in nature, it evolves with the changes of the times and the erosion of the historical river. Aiming at the historical changes of the region along the highway and the important activity space of continuing the local context, this paper studies the expression forms and recognition methods of the regional elements in the landscape by excavating the historical context of the region. The research results of this paper can be used in highway construction to better identify regional landscape elements and inherit historical and cultural factors.
Highway regional landscape elements are an important part of highway landscape, which can play an attractive exploration of the unique landscape effect. The infiltration of regional landscape elements of expressway can make drivers and tourists experience the local conditions and customs in the region through which they pass, and also enable the staff of the Department to understand the local economic characteristics and bring business opportunities to the economic development of the region. This paper uses analytic hierarchy process to rank the importance of five regional factors. The results show that representativeness and influence are the two most important factors.
Background and aims Alfalfa (Medicago sativa. L) growth is largely restricted by abiotic stress such as drought and nutrient deficiency. Identifying root architectural and anatomical characteristics is of great significance for breeding alfalfa genotypes with improved adaptation to adverse environments. Methods Using nutrient solution sand culture method and visual rhizobox cultivation system, we explored the variability in root system architecture (RSA) and anatomy of 53 alfalfa genotypes at the seedling stage. Results Among 44 measured traits, 23 root traits, nitrogen (N) and phosphorus (P) uptake exhibited larger coefficients of variation (CVs ≥ 0.25) across tested genotypes. The variation degrees of local root traits and root anatomical traits were larger than global root traits. Twenty-five traits with CVs ≥ 0.25 constituted 6 principal components (eigenvalues > 1) accounting for 88.9% of the total genotypic variation. Total root length, root length in diameter thin, root tips number, maximal root depth, root length and root tips number in different soil layers were positively correlated with shoot dry mass and root dry mass (P ≤ 0.05). Total stele area (P ≤ 0.05) and xylem vessel area (P ≤ 0.001) were positively correlated with N and P uptake. Conclusion The tested alfalfa genotypes showed larger variation in local root morphological and anatomical traits at the seedling stage. Some important root traits, including root length, root length in diameter thin, root tips number, maximal root depth, total stele area and xylem vessel area have potential function on breeding alfalfa genotypes with improved adaption to abiotic stress.
Environmental supervision plays an important role during highway construction. There are a lot of key components involved in environmental supervision, such as how to improve the work effectively and efficiently. Based on remote sensing and Geographic Information System (GIS), this paper presents a design for environmental supervision system in terms of environmental monitoring technology, integrated management and public involvement. The main components in the system include unmanned aerial vehicle (UAV)-based environment monitor and environment management database and environment monitoring subsystem
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