The widespread use of artificial intelligence in the field of design teaching has become a development trend, and for the art design profession, we should conform to and actively adapt to this ...development trend, change the original teaching mode, innovate their own teaching methods, constantly enrich the teaching methods, so as to improve the quality of teaching, and constantly cultivate high-quality art design talents in the new era. For the subject students, they grow up under the Internet. They are more affectionate to many new technologies, and the traditional teaching methods have some problems to meet their learning needs, so it is very necessary to introduce artificial intelligence in teaching. In this paper, we will discuss the optimization of the curriculum system of art design in higher education institutions in the context of artificial intelligence. The purpose of guiding the innovation of environmental art design thinking is to stimulate students’ learning ability and innovation ability and learn to use design ideas in practice. Integrating design thinking with artificial intelligence gets four innovative ways of culture, form, function, and emotion in terms of innovation at the design thinking level; in terms of thinking innovation guidance, it gets the guidance of role transformation and model practice, integrating artificial intelligence with environmental art design thinking, designing interactive spaces more in line with the times, and promoting the harmonious development of human and nature.
Temperature monitoring plays an important role in ensuring product quality, saving energy, promoting the development of national economy and providing basic diagnostic criteria in the field of ...biomedicine. Due to the importance and universality of temperature measurement, the study of temperature sensing property and the pursuit of high sensitivity have become an important research field of rare-earth luminescent materials in recent years, and have received extensive attention. In this paper, different optical temperature sensing methods and principles, the application of rare-earth luminescent materials in optical temperature sensing, and the types of up-conversion luminescent thermometry materials are reviewed. First, we introduce that optical thermometry can realize non-contact temperature measurement, large-scale imaging, wide dynamic range and rapid response in biological fluorescent tag, accurate measurement of local temperature in medical treatment, and direct temperature measurement of an inaccessible object, which has a very broad application prospect. Meanwhile, we emphasize that the fluorescence intensity ratio technique based on the thermally coupled levels of rare-earth ions has been considered as a reliable and promising non-contact optical temperature sensing method due to its high accuracy and reliability. In the later sections, we review the fundamentals and research progress of rare-earth luminescent materials in optical temperature sensing. Double-doped up-conversion thermometry materials with diverse activators and Yb3+ as sensitizers are mainly introduced, as well as tri-doped multi-color optical thermometry materials. Finally, we summarize the current research results and discuss further research directions on the basis of their current developments. It is hoped that this review could provide new inspiration for the subsequent novel temperature sensors in the future.
•Optical thermometry of up-conversion luminescent material is reviewed emphatically.•Optical thermometry focuses on the fluorescence intensity ratio method.•The main challenges that we need to overcome are discussed.
In the age of information technology, the teacher is no longer the only source of information, and a single lecture mode can trigger a range of messages for learning emotions. For this reason, this ...paper designs a cs-structured computer-aided translation system composed of machine translation in a neural network. After solving the exposure bias problem, the model regularization method combined with the bi-directional decoding consistency is used to optimize the assisted translation system. Then, aspects of the effectiveness of students’ use of the system on their English proficiency improvement were studied. The test scores of the test and comparison classes showed that the mean values of the scores before and after the test of the test class were 13.58 and 15.94, with a mean difference of 2.36 points. The mean values of the scores before and after the test of the comparison class were 14.58 and 14.94, respectively, with a mean difference of 0.4. Comparing the absolute values of the mean differences between the scores before and after the test of the two classes, it is clear that the test class improved their English proficiency level significantly more than the comparison class.
Furthermore, the overall satisfaction of the teachers using the system reached 85.62%. Therefore, in terms of traditional teaching methods, the assisted translation system is more capable of improving students’ English proficiency. It enables teachers to improve English teaching efficiency in the classroom and promotes the modernization and intelligence of English teaching.
Multi-modality medical image fusion technology can integrate the complementary information of different modality medical images, obtain more precise, reliable and better description of lesions. ...Dictionary learning based image fusion draws a great attention in researchers and scientists, for its high performance. The standard learning scheme uses entire image for dictionary learning. However, in medical images, the informative region takes a small proportion of the whole image. Most of the image patches have limited and redundant information. Taking all the image patches for dictionary learning brings lots of unvalued and redundant information, which can influence the medical image fusion quality. In this paper, a novel dictionary learning approach is proposed for image fusion. The proposed approach consists of three steps. Firstly, a novel image patches sampling scheme is proposed to obtain the informative patches. Secondly, a local density peaks based clustering algorithm is conducted to classify the image patches with similar image structure information into several patch groups. Each patch group is trained to a compact sub-dictionary by K-SVD. Finally the sub-dictionaries are combined to a complete, informative and compact dictionary. In this dictionary,only important and useful information which can effectively describe the medical image are selected. To show the efficiency of the proposed dictionary learning approach, the sparse coefficient vectors are estimated by a simultaneous orthogonal matching pursuit (SOMP) algorithm with the trained dictionary, and fused by max-L1 rules. The comparative experimental results and analyses reveal that the proposed method achieves better image fusion quality than existing state-of-the-art methods.
•A novel dimension reduction and dictionary learning framework is proposed.•At dimension reduction stage, it learns a nonlinear mapping via an autoencoder.•At dictionary learning stage, it preserves ...local structure and enhances class discrimination.•The nonlinear mapping and dictionary are optimized jointly.•It preserves nonlinear structure within data and results in enhanced classification performance.
High-dimensional problem poses significant challenges for dictionary learning based classification architecture. Joint Dimension Reduction and Dictionary Learning (JDRDL) framework shows great potential for overcoming the challenges caused by high dimensionality. However, most of the existing JDRDL approaches do not consider the complex nonlinear relationships within high-dimensional data, which limits their classification performance. To overcome this problem, a novel joint dimension reduction and dictionary learning framework is proposed in this paper for high-dimensional data classification. Firstly, at dimension reduction stage, an autoencoder is employed to learn a nonlinear mapping that reduces dimensionality and preserves nonlinear structure of the high-dimensional data. Then, at dictionary learning stage, the locality constraint with label embedding, which takes the locality and label information into account together, is incorporated into the learning process to preserve desirable nonlinear local structure and enhance class discrimination. Moreover, the mapping function and dictionary are optimized simultaneously to enhance the performance. Encouraging experimental results on multiple benchmark datasets confirm that the proposed framework is effective and efficient for high-dimensional data classification.
An aqueous suspension deposition method was used to coat the sized carbon fibers T700SC and T300B with commercially carboxylic acid-functionalized and hydroxyl-functionalized carbon nanotubes (CNTs). ...The CNTs on the fiber surfaces were expected to improve the interfacial strength between the fibers and the epoxy. The factors affecting the deposition, especially the fiber sizing, were studied. According to single fiber-composite fragmentation tests, the deposition process results in improved fiber/matrix interfacial adhesion. Using carboxylic acid-functionalized CNTs, the interfacial shear strength was increased 43% for the T700SC composite and 12% for the T300B composite. The relationship between surface functional groups of the CNTs and the interfacial improvement was discussed. The interfacial reinforcing mechanism was explored by analyzing the surface morphology of the carbon fibers, the wettability between the carbon fibers and the epoxy resin, the chemical bonding between the fiber sizing and the CNTs, and fractographic observation of cross-sections of the composites. Results indicate that interfacial friction, chemical bonding and resin toughening are responsible for the interfacial improvement of nanostructured carbon fiber/epoxy composites. The mechanical properties of the CNT-deposited composite laminate were further measured to confirm the effectiveness of this strategy.
The present study investigated the interactions of trait emotional intelligence (trait EI), foreign language anxiety (FLA), and foreign language enjoyment (FLE) in the foreign language speaking ...classroom. Data collected from 274 Chinese postgraduate EFL learners showed that the subjects generally had medium to high scores on global trait EI; in terms of the four trait EI factors, they scored relatively high on emotionality and well-being, followed in turn by self-control and sociability. They had high mean levels of FLE and moderate to high mean levels of FLA. Significant small to medium correlations were found between trait EI, FLE, and FLA. Regressions revealed that trait EI was a stronger predictor of FLA than of FLE. Trait EI played a fundamental role in its significant interactions with FLA and FLE. In addition, well-being and emotionality figured significantly to both FLE and FLA, while sociability only significantly predicted FLA. High levels of self-control hindered the effect of other significant factors. It is implied that fostering learners' trait EI can potentially boost FLE and alleviate FLA. The findings also offer suggestions for the development of EI-based intervention programmes.
In recent years, there has been a notable increase in the consumption of fossil energy, leading to a significant rise in environmental pollution, particularly in China due to its rapid development. ...This has resulted in the frequent occurrence of large‐scale fog and haze weather, highlighting the urgent need for environmental protection measures. To gain insights into the atmospheric conditions in China, an analysis was conducted on the wet deposition of polycyclic aromatic hydrocarbons (PAHs) in a remote region of Central South China from 2014 to 2017. The study revealed that the average concentrations and peak values of Ʃ16PAHs in 2014 and 2015 were considerably higher than those observed in 2016 and 2017. Furthermore, it was found that five‐ring PAH species were the predominant components during 2014 and 2015, indicating a shift in the main sources of PAHs. The peaks of Ʃ16PAHs were predominantly detected in samples collected during light rain in the winter, specifically on days without heavy rainfall. This can be attributed to the absence of heavy rain, which would otherwise reduce the concentration of air pollutants. Consequently, contaminants accumulated in the air are easily enriched in rainwater. The concentrations of Ʃ15Alkyl‐PAHs also exhibited a significant correlation with the number of rainfall days. Notably, a much higher annual average concentration of Ʃ15Alkyl‐PAHs was observed in 2017, which experienced fewer rainfall days. Coal combustion, petroleum sources, and vehicular emissions accounted for 58%, 12%, and 30% of the PAHs in the air, respectively. Despite improvements in air quality in China since 2016, it is crucial to address the elevated concentrations of PAHs in the atmosphere, particularly under adverse meteorological conditions characterized by reduced rainfall.
Wet deposition of PAHs in a remote area of central south China from 2014 to 2017
In this study, a group of submicro BaTiO3 ceramics ranging from 330 nm to 1.05 μm was successfully prepared by a two-step sintering process and the dependence of electric and mechanical properties on ...grain size was investigated. By dynamic mechanical analysis (DMA), phase transitions and grain size effects on modulus and internal friction were clearly detected. A clear low-frequency relaxation behavior induced by Debye relaxation was characterized in orthorhombic phase for fine BT ceramics. Furthermore, Arrhenius relationship was applied to theoretically analyze the relaxation peak, for which 90° domain wall motion was considered to be responsible. Another anomaly peak around 70 °C became more obvious after annealing in oxygen atmosphere, which was caused by the surface charge release, the interaction between domain walls and stress, and size effect.
•An experimental system of frost deposition on cryogenic-temperature surfaces was set up.•Liquid air was first formed on cryogenic-temperature surface before frost crystals appeared.•Frost crystal ...clusters deposited on liquid air droplets are not static, they keep moving.•Under very low surface temperature, as surface temperature drops, the frost layer thickness decreases.
An experimental system of frost deposition on cryogenic-temperature surfaces under natural convection conditions was set up and a series of frost formation experiments were conducted under various conditions, focusing on the frosting phenomena on horizontally- and vertically-placed cryogenic-temperature surfaces under natural convection conditions especially the early stage frost formation phenomena. The influences of surface temperature, air temperature and air relative humidity were also carefully studied of frost formation on vertical cryogenic surfaces. A very peculiar and important phenomenon for frost formation on cryogenic-temperature surfaces observed is that liquid air droplets were first formed on cryogenic-temperature surface if surface temperature is lower than −165°C before frost crystals appeared. The liquid droplets on horizontally-placed surfaces may exist for a quite long time and even form a continuous film, and have significant influences on frost deposition. It was found that frost crystal clusters deposited on liquid air droplets are not static, they moves both as and relatively to the droplets. The frost layer growth on the vertical surfaces of cryogenic-temperature is highly non-uniform and exists a downward growth period during which the frost layer grows mainly along the downward direction of the vertical surfaces. It was also found that under very low surface temperature and natural convection conditions, as the surface temperature drops, the frost layer thickness decreases. This is completely different to the phenomenon observed on ordinary low-temperature cold surfaces.
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