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关键词： “稍微”   “多少”   量范畴   不定量   有界   无界  

摘要： 文章描写了"稍微"和"多少"结构中量范畴的表现形式,并分析了两个高频使用结构"稍微……(一)点儿/些"和"多少有点儿/有些……"的语义特点,认为"稍微/多少"与量范畴共现时两部分的语义并不重复。从"稍微"结构中谓词的语义特点、所在句的语体类型和篇章句际间的语义关联等角度揭示了"稍微"可以不与量范畴共现的可能原因,而"多少"使用的一般条件是其后修饰的成分需是复杂结构。最后从"有界"和"无界"的对立分析了两个副词与量范畴的互动。

关键词： 指导性案例   司法解释   范畴   法律解释   法院审理   中国特色   成文法   示范性  

摘要： 指导性案例在我国被称为法律解释之一种方式，规范性为指导性案例的立命之本。因为成文法制度的限制，指导性案例总体上不构成我国私法的法源，但对各级法院审理类似案件具有参照效用，为中国特色的释法工具。指导性案例的体例、目的，示范性以及参照均围绕其规范性而展开。为指导性案例的目的和本旨的全面落实，有必要将指导性案例的规范性转型为司法解释的一种形式，并继续发挥指导性案例的参照效用，以切实推进指导性案例制度在我国的成长。

关键词： 惯常   语义地图   汉语方言   助动词   句末助词  

摘要： 本文旨在探讨惯常范畴的语义类型和标记方式,聚焦于汉语表达惯常义的特点。我们首先分出惯常义的四种类型,然后简析汉语方言的几个惯常标记(南方方言的助动词"要、会、有"、句末助词"的"及北方方言的句末助词"呢、着"),以此为基础探讨了惯常义的标记度及汉语惯常标记的类型,并构建了惯常范畴的语义地图,从而整理出时体态三大范畴的交接状况。这种惯常标记的跨方言比较不仅推进了对特定语法词的认识,亦窥见到南北汉语在语序结构及时体态范畴上的类型差异。本研究仅是该课题的初步探索,有待更多方言/语言来验证和改进。

关键词： 沉默   文化模式   符号学文化   范畴   哲学   文化传播  

摘要： 本文是对"沉默"在中国文化模式非语言符号下的特点进行分析解读。要理解中国文化,就有必要研究"沉默"在非语言符号中起到的重要作用。本文按照符号学方法根据功能对沉默在中国文化符号中的作用进行了分类解读,将其分为宗教沉默、审美沉默、日常生活沉默及政治沉默几类。

关键词： Individual differences   Eye-movements   Face recognition   Face perception   Pattern similarity measure   Idiosyncratic  

摘要： The spatial pattern of eye-movements to faces considered typical for neurologically healthy individuals is a roughly T-shaped distribution over the internal facial features with peak fixation density tending toward the left eye (observer's perspective). However, recent studies indicate that striking deviations from this classic pattern are common within the population and are highly stable over time. The classic pattern actually reflects the average of these various idiosyncratic eye-movement patterns across individuals. The natural categories and respective frequencies of different types of idiosyncratic eye-movement patterns have not been specifically investigated before, so here we analyzed the spatial patterns of eye- movements for 48 participants to estimate the frequency of different kinds of individual eye-movement patterns to faces in the normal healthy population. Four natural clusters were discovered such that approximately 25% of our participants' fixation density peaks clustered over the left eye region (observer's perspective), 23% over the right eye-region, 31% over the nasion/bridge region of the nose, and 20% over the region spanning the nose, philthrum, and upper lips. We did not find any relationship between particular idiosyncratic eye-movement patterns and recognition performance. Individuals' eye-movement patterns early in a trial were more stereotyped than later ones and idiosyncratic fixation patterns evolved with time into a trial. Finally, while face inversion strongly modulated eye-movement patterns, individual patterns did not become less distinct for inverted compared to upright faces. Group-averaged fixation patterns do not represent individual patterns well, so exploration of such individual patterns is of value for future studies of visual cognition. (C) 2016 Elsevier Ltd. All rights reserved.

关键词： Artificial neural network   Environmental impact categories   Life cycle assessment   Tea  

摘要： In this study, an artificial neural network (ANN) model was developed for predicting the yield and life cycle environmental impacts based on energy inputs required in processing of black tea, green tea, and oolong tea in Guilan province of Iran. A life cycle assessment (LCA) approach was used to investigate the environmental impact categories of processed tea based on the cradle to gate approach, i.e., from production of input materials using raw materials to the gate of tea processing units, i.e., packaged tea. Thus, all the tea processing operations such as withering, rolling, fermentation, drying, and packaging were considered in the analysis. The initial data were obtained from tea processing units while the required data about the background system was extracted from the EcoInvent 2.2 database. LCA results indicated that diesel fuel and corrugated paper box used in drying and packaging operations, respectively, were the main hotspots. Black tea processing unit caused the highest pollution among the three processing units. Three feed-forward back-propagation ANN models based on Levenberg-Marquardt training algorithm with two hidden layers accompanied by sigmoid activation functions and a linear transfer function in output layer, were applied for three types of processed tea. The neural networks were developed based on energy equivalents of eight different input parameters (energy equivalents of fresh tea leaves, human labor, diesel fuel, electricity, adhesive, carton, corrugated paper box, and transportation) and 11 output parameters (yield, global warming, abiotic depletion, acidification, eutrophication, ozone layer depletion, human toxicity, freshwater aquatic ecotoxicity, marine aquatic ecotoxicity, terrestrial ecotoxicity, and photochemical oxidation). The results showed that the developed ANN models with R-2 values in the range of 0.878 to 0.990 had excellent performance in predicting all the output variables based on inputs. Energy consumption for process

关键词： Progressive   Visual analytics   Categorical data analysis  

摘要： When using data-mining tools to analyze big data, users often need tools to support the understanding of individual data attributes and control the analysis progress. This requires the integration of data-mining algorithms with interactive tools to manipulate data and analytical process. This is where visual analytics can help. More than simple visualization of a dataset or some computation results, visual analytics provides users an environment to iteratively explore different inputs or parameters and see the corresponding results. In this research, we explore a design of progressive visual analytics to support the analysis of categorical data with a data-mining algorithm, Apriori. Our study focuses on executing data mining techniques step-by-step and showing intermediate result at every stage to facilitate sense-making. Our design, called Pattern Discovery Tool, targets for a medical dataset. Starting with visualization of data properties and immediate feedback of users' inputs or adjustments, Pattern Discovery Tool could help users detect interesting patterns and factors effectively and efficiently. Afterward, further analyses such as statistical methods could be conducted to test those possible theories. (C) 2017 Elsevier Ltd. All rights reserved.

摘要： We study the indecomposability and isomorphism of objects from the category of monomial matrices Mmat(K) over a commutative local principal ideal ring K (whose objects are square monomial matrices and the morphisms from X to Y are matrices C such that XC = CY). We also study the subcategory Mmat(0)(K) of the category Mmat(K) with the same objects and solely with morphisms that are monomial matrices.

关键词： hierarchical Bayesian model   bidding strategy   competing-brand keywords   generic keywords   focal-brand keywords   keyword auctions   purchase funnel   sponsored search advertising  

摘要： Although keyword auctions are often studied in the context of a single keyword in the literature, firms generally have to participate in multiple keyword auctions at the same time. Advertisers purchase a variety of keywords that can be categorized as generic-relevant, focal-brand, and competing-brand keywords. At the same time, firms also have to choose how the keywords can be matched to search queries: exact, phrase, or broad. This study empirically examines how keyword categories and match types influence the performance of advertising campaigns. We build a hierarchical Bayesian model to address the endogeneity problem contained in the simultaneous equations of the click-through rate, the conversion rate, cost per click, and rank, and we use the Markov Chain Monte Carlo method to identify the parameters. Our results suggest that it is important to differentiate among the various bidding strategies for various keyword categories and match types. We also report results related to financial performance such as number of sales, profit, and return on investment for different keywords. These findings shed light on the practice of sponsored search advertising by offering insights into how to manage ad campaigns when advertisers have to bid on multiple keywords.

关键词： Categorical sequences   cluster validation   cluster validity index (CVI)   data clustering   model selection   robust clustering  

摘要： Cluster validation, which is the process of evaluating the quality of clustering results, plays an important role for practical machine learning systems. Categorical sequences, such as biological sequences in computational biology, have become common in real-world applications. Different from previous studies, which mainly focused on attribute-value data, in this paper, we work on the cluster validation problem for categorical sequences. The evaluation of sequences clustering is currently difficult due to the lack of an internal validation criterion defined with regard to the structural features hidden in sequences. To solve this problem, in this paper, a novel cluster validity index (CVI) is proposed as a function of clustering, with the intracluster structural compactness and intercluster structural separation linearly combined to measure the quality of sequence clusters. A partition-based algorithm for robust clustering of categorical sequences is also proposed, which provides the new measure with high-quality clustering results by the deterministic initialization and the elimination of noise clusters using an information theoretic method. The new clustering algorithm and the CVI are then assembled within the common model selection procedure to determine the number of clusters in categorical sequence sets. A case study on commonly used protein sequences and the experimental results on some real-world sequence sets from different domains are given to demonstrate the performance of the proposed method.