International development is a challenge that each university must face.The educational mechanism of private undergraduate universities is flexible,and has certain advantages in expanding international education progr...International development is a challenge that each university must face.The educational mechanism of private undergraduate universities is flexible,and has certain advantages in expanding international education programs.Sino-foreign credit mutual recognition programs are more common in private undergraduate universities.With the continuous development of resources and models on international education cooperation,the forms of Sino-foreign credits mutual recognition cooperation are becoming more diversified.The rapid development of Chinese and foreign credit recognition education programs in private undergraduate universities requires scientific and advanced management concepts and support.Young private universities have short international development time and lack of experience.Therefore,relevant issues should be more researched.This paper analyzes the problems and challenges in the education mode and management of Sino-foreign credit mutual recognition projects in private undergraduate universities,and puts forward relevant countermeasures.展开更多
To ensure revulsive driving of intelligent vehicles at intersections, a method is presented to detect and recognize the traffic lights. First, the stabling siding at intersections is detected by applying Hough transfo...To ensure revulsive driving of intelligent vehicles at intersections, a method is presented to detect and recognize the traffic lights. First, the stabling siding at intersections is detected by applying Hough transformation. Then, the colors of traffic lights are detected with color space transformation. Finally, self-associative memory is used to recognize the countdown characters of the traffic lights. Test results at 20 real intersections show that the ratio of correct stabling siding recognition reaches up to 90%;and the ratios of recognition of traffic lights and divided characters are 85% and 97%, respectively. The research proves that the method is efficient for the detection of stabling siding and is robust enough to recognize the characters from images with noise and broken edges.展开更多
In order to solve the poor performance in text classification when using traditional formula of mutual information （MI） , a feature selection algorithm were proposed based on improved mutual information. The improve...In order to solve the poor performance in text classification when using traditional formula of mutual information （MI） , a feature selection algorithm were proposed based on improved mutual information. The improved mutual information algorithm, which is on the basis of traditional improved mutual information methods that enbance the MI value of negative characteristics and feature＇ s frequency, supports the concept of concentration degree and dispersion degree. In accordance with the concept of concentration degree and dispersion degree, formulas which embody concentration degree and dispersion degree were constructed and the improved mutual information was implemented based on these. In this paper, the feature selection algorithm was applied based on improved mutual information to a text classifier based on Biomimetic Pattern Recognition and it was compared with several other feature selection methods. The experimental results showed that the improved mutu- al information feature selection method greatly enhances the performance compared with traditional mutual information feature selection methods and the performance is better than that of information gain. Through the introduction of the concept of concentration degree and dispersion degree, the improved mutual information feature selection method greatly improves the performance of text classification system.展开更多
Classifier learning methods commonly assume that the training data and the testing data are drawn from the same underlying distribution. However, in many practical situations, this assumption is violated. One examp...Classifier learning methods commonly assume that the training data and the testing data are drawn from the same underlying distribution. However, in many practical situations, this assumption is violated. One example is the practical action videos with complex background and the universal human action databases of Kangliga Tekniska Hogskolan （KTH）. When training data are very scarce, supervised learning is difficult. However, it will cost lots of human and material resources to establish a labeled video set which includes a large amount of videos with complex backgrounds. In this paper, we propose an action recognition framework which uses transfer boosting learning algorithm. By using this algorithm, we can train an action recognition model fitting for most practical situations just relaying on the universal action video dataset and a tiny set of action videos with complex background. And the experiment results show that the performance is improved.展开更多
Age-related memory impairments show a progressive decline across lifespan. Studies have demonstrated equivocal results in biological and behavioral outcomes of aging. Thus, in the present study we examined the novel o...Age-related memory impairments show a progressive decline across lifespan. Studies have demonstrated equivocal results in biological and behavioral outcomes of aging. Thus, in the present study we examined the novel object recognition task at a delay period that has been shown to be impaired in aged rats of two different strains. Moreover, we used a strain of rats, Fisher 344XBrown Norway, which have published age-related biological changes in the brain. Young (10 month old) and aged (28 month old) rats were tested on a standard novel object recognition task with a 50-minute delay period. The data showed that young and aged rats in the strain we used performed equally well on the novel object recognition task and that both young and old rats demonstrated a righthanded side preference for the novel object. Our data suggested that novel object recognition is not impaired in aged rats although both young and old rats have a demonstrated side preference. Thus, it may be that genetic differences across strains contribute to the equivocal results in behavior, and genetic variance likely influences the course of cognitive aging.展开更多
多模态的对话情绪识别(Emotion Recognition in Conversation,ERC)是构建情感对话系统的关键。近年来,基于图的融合方法在会话中动态聚合多模态上下文特征,提高了模型在多模态对话情绪识别方面的性能。然而,这些方法都没有充分保留和利...多模态的对话情绪识别(Emotion Recognition in Conversation,ERC)是构建情感对话系统的关键。近年来,基于图的融合方法在会话中动态聚合多模态上下文特征,提高了模型在多模态对话情绪识别方面的性能。然而,这些方法都没有充分保留和利用输入数据中的有价值的信息。具体地说,它们都没有保留从输入到融合结果的任务相关信息,并且忽略了标签本身蕴含的信息。为了解决上述问题,该文提出了一种基于互信息最大化和对比损失的多模态对话情绪识别模型(Multimodal ERC with Mutual Information Maximization and Contrastive Loss,MMIC)。模型通过在输入级和融合级上分级最大化模态之间的互信息(Mutual Information),使任务相关信息在融合过程中得以保存,从而生成更丰富的多模态表示。该文还在基于图的动态融合网络中引入了监督对比学习(Supervised Contrastive Learning),通过充分利用标签蕴含的信息,使不同情绪相互排斥,增强了模型识别相似情绪的能力。在两个英文和一个中文的公共数据集上的大量实验证明了该文所提出模型的有效性和优越性。此外,在所提出模型上进行的案例探究有效地证实了模型可以有效保留任务相关信息,更好地区分出相似的情绪。消融实验和可视化结果证明了模型中每个模块的有效性。展开更多
文摘International development is a challenge that each university must face.The educational mechanism of private undergraduate universities is flexible,and has certain advantages in expanding international education programs.Sino-foreign credit mutual recognition programs are more common in private undergraduate universities.With the continuous development of resources and models on international education cooperation,the forms of Sino-foreign credits mutual recognition cooperation are becoming more diversified.The rapid development of Chinese and foreign credit recognition education programs in private undergraduate universities requires scientific and advanced management concepts and support.Young private universities have short international development time and lack of experience.Therefore,relevant issues should be more researched.This paper analyzes the problems and challenges in the education mode and management of Sino-foreign credit mutual recognition projects in private undergraduate universities,and puts forward relevant countermeasures.
基金The Cultivation Fund of the Key Scientific and Technical Innovation Project of Higher Education of Ministry of Education (No.705020)
文摘To ensure revulsive driving of intelligent vehicles at intersections, a method is presented to detect and recognize the traffic lights. First, the stabling siding at intersections is detected by applying Hough transformation. Then, the colors of traffic lights are detected with color space transformation. Finally, self-associative memory is used to recognize the countdown characters of the traffic lights. Test results at 20 real intersections show that the ratio of correct stabling siding recognition reaches up to 90%;and the ratios of recognition of traffic lights and divided characters are 85% and 97%, respectively. The research proves that the method is efficient for the detection of stabling siding and is robust enough to recognize the characters from images with noise and broken edges.
基金Sponsored by the National Nature Science Foundation Projects (Grant No. 60773070,60736044)
文摘In order to solve the poor performance in text classification when using traditional formula of mutual information （MI） , a feature selection algorithm were proposed based on improved mutual information. The improved mutual information algorithm, which is on the basis of traditional improved mutual information methods that enbance the MI value of negative characteristics and feature＇ s frequency, supports the concept of concentration degree and dispersion degree. In accordance with the concept of concentration degree and dispersion degree, formulas which embody concentration degree and dispersion degree were constructed and the improved mutual information was implemented based on these. In this paper, the feature selection algorithm was applied based on improved mutual information to a text classifier based on Biomimetic Pattern Recognition and it was compared with several other feature selection methods. The experimental results showed that the improved mutu- al information feature selection method greatly enhances the performance compared with traditional mutual information feature selection methods and the performance is better than that of information gain. Through the introduction of the concept of concentration degree and dispersion degree, the improved mutual information feature selection method greatly improves the performance of text classification system.
基金National Natural Science Foundation of China ( No.60873179)Shenzhen Municipal Science and Technology Planning Program for Basic Research, China ( No. JC200903180630A)Research Fund for the Doctoral Program of Higher Education of China (No.20090121110032)
文摘Classifier learning methods commonly assume that the training data and the testing data are drawn from the same underlying distribution. However, in many practical situations, this assumption is violated. One example is the practical action videos with complex background and the universal human action databases of Kangliga Tekniska Hogskolan （KTH）. When training data are very scarce, supervised learning is difficult. However, it will cost lots of human and material resources to establish a labeled video set which includes a large amount of videos with complex backgrounds. In this paper, we propose an action recognition framework which uses transfer boosting learning algorithm. By using this algorithm, we can train an action recognition model fitting for most practical situations just relaying on the universal action video dataset and a tiny set of action videos with complex background. And the experiment results show that the performance is improved.
文摘Age-related memory impairments show a progressive decline across lifespan. Studies have demonstrated equivocal results in biological and behavioral outcomes of aging. Thus, in the present study we examined the novel object recognition task at a delay period that has been shown to be impaired in aged rats of two different strains. Moreover, we used a strain of rats, Fisher 344XBrown Norway, which have published age-related biological changes in the brain. Young (10 month old) and aged (28 month old) rats were tested on a standard novel object recognition task with a 50-minute delay period. The data showed that young and aged rats in the strain we used performed equally well on the novel object recognition task and that both young and old rats demonstrated a righthanded side preference for the novel object. Our data suggested that novel object recognition is not impaired in aged rats although both young and old rats have a demonstrated side preference. Thus, it may be that genetic differences across strains contribute to the equivocal results in behavior, and genetic variance likely influences the course of cognitive aging.
文摘多模态的对话情绪识别(Emotion Recognition in Conversation,ERC)是构建情感对话系统的关键。近年来,基于图的融合方法在会话中动态聚合多模态上下文特征,提高了模型在多模态对话情绪识别方面的性能。然而,这些方法都没有充分保留和利用输入数据中的有价值的信息。具体地说,它们都没有保留从输入到融合结果的任务相关信息,并且忽略了标签本身蕴含的信息。为了解决上述问题,该文提出了一种基于互信息最大化和对比损失的多模态对话情绪识别模型(Multimodal ERC with Mutual Information Maximization and Contrastive Loss,MMIC)。模型通过在输入级和融合级上分级最大化模态之间的互信息(Mutual Information),使任务相关信息在融合过程中得以保存,从而生成更丰富的多模态表示。该文还在基于图的动态融合网络中引入了监督对比学习(Supervised Contrastive Learning),通过充分利用标签蕴含的信息,使不同情绪相互排斥,增强了模型识别相似情绪的能力。在两个英文和一个中文的公共数据集上的大量实验证明了该文所提出模型的有效性和优越性。此外,在所提出模型上进行的案例探究有效地证实了模型可以有效保留任务相关信息,更好地区分出相似的情绪。消融实验和可视化结果证明了模型中每个模块的有效性。
