张竞生美学观辨析

在中国现代美学的初创时期,张竞生的美学观可谓独树一帜,他主张美"以用力少而收效大"为大纲,标举"关的人生现",力倡"美的社会组织法".坚信爱与美的信仰,宣称美与人的生命创造力密不可分,力图把日常生活提升到美的境界,使爱与美的主张贯穿于人生社会中.     

基于数据挖掘方法的皮肤病诊断建模

临床特征和组织病理学特征在皮肤科疾病分类问题中起着非常关键的作用。本文的主要目的是使用这些特征建立皮肤科疾病分类模型。本文首先使用最大相关最小冗余方法选择相关特征,然后使用支持向量机构造分类模型。文中所使用的数据集包含358皮肤病患者病例样本和35属性。通过实验比较使用特征选择方法前后的模型分类精度可知,使用特征选择方法能明显提升模型分类性能。同时,本文通过实验研究对不同年龄段的皮肤科疾病患者分类的差异性,并选择出了对于35岁以下皮肤科疾病患者分类重要的13个特征以及35岁以上患者分类重要的9个特征。     

基于改进神经网络的图像生物特征识别方法

在图像的固定生物特征识别过程中,传统的识别方法针对像素质量不高的问题,很难建立完整的寻优计算过程,识别效果不好。提出基于改进神经网络算法的图像特征识别方法。通过量子计算对神经网络进行优化,优化神经网络在特征识别中的阀值确定过程,完成图像识别。实验结果表明,利用改进的算法进行图像特征识别,能够极大的提高生物特征识别的准确性,扩展了应用的范围。     

基于平方法的雷达信号脉内调制粗识别

为了能够简单快速识别出雷达信号脉内调制类型,提出了一种简单高效的调制类型粗识别方法。首先对输入信号进行平方处理,经FFT变换得到其频谱并计算出平方后的信号3d B带宽,最后将平方后的信号3d B带宽与阈值比较,粗识别出调相信号和调频信号。仿真结果表明,该方法使输入信号的频谱特征更加明显,验证了该方法的有效性和实用性。     

浅论“说新闻”节目的类型与特征

近年来,“说新闻”成为电视新闻节目播报的一种主要形式。文章以此为对象,归纳出“说新闻”的三种类型,并进一步分析了“说新闻”的特征及原则,提出主持人在“说新闻”要注意拉近与观众之间的心理距离,注重外在形象、巧用态势语,提升新闻品位。同时指出,“播新闻”“说新闻”各有特色,要相辅相成,相互结合。     

从“三美”角度看《红楼梦》中《好了歌》的两个译本

“三美论”是著名翻译家许渊冲先生提出的翻译标准,主要用于诗歌翻译。《红楼梦》是中国古典小说艺术的集大成者,是中国小说的巅峰。其中文采斐然的诗词韵文集中体现了这部作品的艺术性与文学性,但也给《红楼梦》的翻译增加了很多难度。该文将结合“三美论”来分析杨宪益、戴乃迭夫妇和霍克思和闵福德译本中关于《好了歌》的翻译。     

Identification of Chinese dark jargons in Telegram underground markets using context-oriented and linguistic features

When cybercriminals communicate with their customers in underground markets, they tend to use secure and customizable instant messaging (IM) software, i.e. Telegram. It is a popular IM software with over 700 million monthly active users (MAU) up to June 2022. In recent years, more and more dark jargons (i.e. an innocent-looking replacement of sensitive terms) appear frequently on Telegram. Therefore, jargons identification is one of the most significant research perspectives to track online underground markets and cybercrimes. This paper proposes a novel Chinese Jargons Identification Framework (CJI-Framework) to identify dark jargons. Firstly, we collect chat history from Telegram groups that are related to the underground market and construct the corpus TUMCC (Telegram Underground Market Chinese Corpus), which is the first Chinese corpus in jargons identification research field. Secondly, we extract seven brand-new features which can be classified into three categories: Vectors-based Features (VF), Lexical analysis-based Features (LF), and Dictionary analysis-based Features (DF), to identify Chinese dark jargons from commonly-used words. Based on these features, we then run a statistical outlier detection to decide whether a word is a jargon. Furthermore, we employ a word vector projection method and a transfer learning method to improve the effect of the framework. Experimental results show that CJI-Framework achieves a remarkable performance with an F1-score of 89.66%. After adaptation for English, it performs better than state-of-the-art English jargons identification method as well. Our built corpus and code have been publicly released to facilitate the reproduction and extension of our work.     

Demand forecasting model using hotel clustering findings for hospitality industry

Tourism has become a growing industry day by day with the developing economic conditions and the increasing communication and social interaction ability of the people. Forecasting tourism demand is not only important for tourism operators to maximize their revenues but also important for the formation of economic plans of the countries on a global scale. Based on the predictions countries are able to regulate the sectors that benefit economically from tourism locally. Therefore, it is crucial to accurately predict the demand in many weeks advance. In this study, we propose a new demand forecasting model for the hospitality industry that forecasts weekly hotel demand four weeks in advance through Attention-Long Short Term Memory (Attention-LSTM). Unlike most of the existing methods, the proposed method utilizes the time series demand data together with additional features obtained from K-Means Clustering findings such as Top 10 Hotel Features or Hotel Embeddings obtained using Neural Networks (NN). While creating our model, the clustering part was influenced by the fact that travelers choose their accommodation according to certain criteria, and the hotels meeting similar criteria may have similar demands. Therefore, before the clustering part, we also applied methods that would enable us to represent the features of the hotels more properly and we observed that 10-D Embedded Hotel Data representation with NN Embeddings came to the fore. In order to observe the performance of the proposed hotel demand forecasting model we used a real-world dataset provided by a tourism agency in Turkey and the results show that the proposed model achieves less mean absolute error and mean absolute percentage error (at worst % 3 and at most % 29 improvements) compared to the currently used machine learning and deep learning models.     

创办体育管理专业的探索与实践──武汉体育学院体育管理专业教学成果报告

武汉体育学院体育管理专业经过１０余年的艰苦探索与实践，已发展成为本院的一个特色专业，本文初步总结和提炼出创办体育新专业的一整套成功经验，以期填补我国体育人才培养目标的空白，促进我国体育事业的发展。     

Fault diagnosis for analog circuits based on chaotic signal excitation

A fault diagnosis method for analog circuit is proposed in this paper. An all-purpose amplifier is taken as the typical circuit under test (CUT). The chaotic signal, which is generated by an improved Chua's circuit, is employed as the excitation signal of CUT. The algorithm for phase-space reconstruction of chaotic time series is a combination algorithm of multiple autocorrelation and Γ-test. The circuit state is estimated based on detecting the geometric change of Chua's attractor with a data-mining approach. For the purpose of information fusion, another eight features are extracted from the testing data to comprehensively determine the CUT states. A discussion is made for comparing the effectiveness of each feature according to the testing results.