representation

摘要： This work shows, after a brief introduction to Riemann zeta function , the demonstration that all non-trivial zeros of this function lies on the so-called “critical line”,, the one Hardy demonstrated in his famous work that infinite countable zeros of the above function can be found on it. Thus, out of this strip, the only remaining zeros of this function are the so-called “trivial ones” . After an analytical introduction reminding the existence of a germ from a generic zero lying in , we show through a Weierstrass-Hadamard representation approach of the above germ that non-trivial zeros out of cannot be found.

摘要： Symbolic Aggregate approXimation (SAX) is an efficient symbolic representation method that has been widely used in time series data mining. Its major limitation is that it relies exclusively on the mean values of segmented time series to derive the symbols. So, many important features of time series are not considered, such as extreme value, trend, fluctuation and so on. To solve this issue, we propose in this paper an improved Symbolic Aggregate approXimation based on multiple features and Vector Frequency Difference (SAX_VFD). SAX_VFD discriminates between time series by adopting an adaptive feature selection method. Furthermore, SAX_VFD is endowed with a new distance that takes into account the vector frequency difference between the symbolic sequence. We demonstrate the utility of the SAX_VFD on the time series classification task. The experimental results show that the proposed method has a better performance in terms of accuracy and dimensionality reduction compared to the so far published SAX based reduction techniques.

摘要： The knowledge graph(KG) that represents structural relations among entities has become an increasingly important research field for knowledge-driven artificial intelligence. In this survey, a comprehensive review of KG and KG reasoning is provided. It introduces an overview of KGs, including representation, storage, and essential technologies. Specifically, it summarizes several types of knowledge reasoning approaches, including logic rules-based, representation-based, and neural network-based methods. Moreover, this paper analyzes the representation methods of knowledge hypergraphs. To effectively model hyper-relational data and improve the performance of knowledge reasoning, a three-layer knowledge hypergraph model is proposed. Finally, it analyzes the advantages of three-layer knowledge hypergraphs through reasoning and update algorithms which could facilitate future research.

摘要： Dear editor,Neural networks (NNs) and fuzzy systems are commonly used computational intelligence techniques, each with their own merits in terms of applications. The integration of NNs and fuzzy systems, which leads to a hybrid framework known as neuro-fuzzy systems, inherits the useful properties of its constituents:the learning power of an NN and the knowledge representation of a fuzzy inference system。

摘要： SOOAs refer to the phenomenon that the state adjective in the adverbial position is semantically associated with the object.In this paper this fact will be accounted for by invoking the properties of a pre-syntactic level of semantic representation and its interplay with syntax proper.It will be argued that the object-oriented adverbial is not derived from the attributive;in effect,it is base-generated in the complement position.A model of projection of arguments that allows for this will be proposed.It will be shown that the other special properties of SOOAs follow from the way the verb’s object and complement are represented at the pre-syntactic level.In particular,it will be shown that the underlying structure must satisfy both the requirement of the syntactic system and the requirement of the semantic system.The presence of any symbol in a representation is conditional.The theta-roles of internal arguments are assigned by the predicate,which is locally constrained,whereas the theta-roles of external arguments are assigned by the maximal projection of the predicate,viz.VP.When an external argument occurs,there is an empty predicate position in the representation,for there is an asymmetry between the conceptual system and the syntactic system.Derivation involves Move-αand Generalized Transformation.Different use of derivation methods gives rise to various forms of constructions in Chinese.Similarly,different semantic orientations result from different distributions.The state adjective is base-generated in the position behind the object because its nature is to serve the function of the complement of the object.It co-occurs with the object in the embedded VP because they are closely related to each other in terms of semantics.There is no overt predicate between the object and the state adjective.The state adjective occurs in other positions,which is the result of movement.Movement falls into two types,viz.object movement and state adjective movement.Object movement is prior to state adjective movement.In order to satisfy the requirement of feature checking,the object moves to the position NP.Then the state adjective moves to the major predicate and merges with it so as to maintain its semantic association with the state adjective and to serve the function of the complement.It follows that the difference between Chinese SOOAs and English as well as German SOOAs lies in the distance of movement of state adjectives.In Chinese,there are causative markers,resultative markers,and manner markers that can license the state adjective in the landing sites and help to maintain its semantic association with the object while in English and German there are no such markers.As a consequence,the object in Chinese-type SOOAs does not move while the state adjective moves out of the embedded VP to the empty verb position where the manner marker is inserted.The major predicate moves to the same position and merges with the newly-formed syntactic object ADJ-MANN.Furthermore,Chinese-type SOOAs allow the state adjective to precede the major predicate as the manner marker can license the state adjective.In contrast,in English-type SOOAs,neither the state adjective nor the object moves.Moreover,English-type SOOAs do not allow the state adjective to come before the major predicate because there is no manner marker to license it.

摘要： Dear editor,Time series anomaly detection,aiming for identifying unexpected observations within the given time series,has been considered as one of the most challenging studies in time series data mining[1,2].In this study,we present a novel set-based piecewise aggregate representation(SPAR)for anomaly detection,dubbed as SPAR-AD.

摘要： representation原是一个美学概念,近年来越来越频繁地出现在史学作品当中.一般而言,representation有两种用法:一是指根据相似性的标准,对某物进行的描绘和刻画;二是指某种符号或图案,它象征着已不在场的事物替代原事物出场.柏拉图是相似论的忠实支持者,后世哲学家则多从事于对相似论的批判,史学理论家安克斯密特即可被视为其中的一员.在替代论的基础上,安克斯密特将representation一词引入历史领域,构成"historical representation"(历史再现).史学理论对历史再现的探讨,很大程度地揭示了历史书写中蕴含的"诗性"成分.海登·怀特和安克斯密特这两位重要的叙事主义史学理论家皆认为,正是被史家归于艺术层面的"形式"给予了历史以融贯性和条理性."再现"观念于史学领域的接受在一定程度上改变了20世纪七八十年代之后西方历史意识的一些传统层面.

摘要： Associated data,which refer to sets of entities with specific relations and relational weights that can usually be expressed in a relational matrix,are found in many fields.Two typical examples are the pesticide residue dataset in food-safety,in which pesticides are associated with agricultural products[1],and E-transaction dataset,in which there is special relation between buyer and seller[2].

摘要： 亚里士多德并不在本质上把模仿(再现)理解为对现实的复制。胡塞尔的认识论现象学区分了Vorstellung与representation,前者指广义的表象,后者指实存对象的当下化“再造”或“再现”。在康德的先验主体哲学视野中,Vorstellung主要意指各种“表象”,其知性表象也表现出对感性表象“再造”的含义。霍尔对representation的通俗理解,综合了索绪尔的符号学与福柯的话语理论,其基本含义也是“再现”。因此,本文主张根据具体语境把representation汉译为“再现”或“表象”。