Formalizing Synthetic Domain Theory

Synthetic Domain Theory (SDT) is a constructive variant of Domain Theory where all functions are continuous following Dana Scotts idea of domains as sets. Recently there have been suggested more abstract axiomatizations encompassing alternative notions of domain theory as, for example, stable domain theory.In this article a logical and axiomatic version of SDT capturing the essence of Domain Theory à la Scott is presented. It is based on a sufficiently expressive version of constructive type theory and fully implemented in the proof checker Lego. On top of this core SDT denotational semantics and program verification can be – and in fact has been – developed in a purely formal machine-checked way.The version of SDT we have chosen for this purpose is based on work by Reus and Streicher and can be regarded as an axiomatization of complete extensional PERs. This approach is a modification of Phoas complete -spaces and uses axioms introduced by Taylor.     

How to delete categorically — Two pushout complement constructions

In category theory, most set-theoretic constructions-union, intersection, etc.-have direct categorical counterparts. But up to now, there is no direct construction of a deletion operation like the set-theoretic complement. In rule-based transformation systems, deletion of parts of a given object is one of the main tasks. In the double pushout approach to algebraic graph transformation, the construction of pushout complements is used in order to locally delete structures from graphs. But in general categories, even if they have pushouts, pushout complements do not necessarily exist or are unique. In this paper, two different constructions for pushout complements are given and compared. Both constructions are based on certain universal constructions in the sense of category theory. More specifically, one uses initial pushouts while the other one uses quasi-coproduct complements. These constructions are applied to examples in the categories of graphs and simple graphs.     

Prime algebraicity

A prime algebraic lattice can be characterised as isomorphic to the downwards-closed subsets, ordered by inclusion, of its complete primes. It is easily seen that the downwards-closed subsets of a partial order form a completely distributive algebraic lattice when ordered by inclusion. The converse also holds; any completely distributive algebraic lattice is isomorphic to such a set of downwards-closed subsets of a partial order. The partial order can be recovered from the lattice as the order of the lattice restricted to its complete primes. Consequently prime algebraic lattices are precisely the completely distributive algebraic lattices. The result extends to Scott domains. Several consequences are explored briefly: the representation of Berry’s dI-domains by event structures; a simplified form of information systems for completely distributive Scott domains; and a simple domain theory for concurrency.     

A distance measure for large graphs based on prime graphs

Graphs are universal modeling tools. They are used to represent objects and their relationships in almost all domains: they are used to represent DNA, images, videos, social networks, XML documents, etc. When objects are represented by graphs, the problem of their comparison is a problem of comparing graphs. Comparing objects is a key task in our daily life. It is the core of a search engine, the backbone of a mining tool, etc. Nowadays, comparing objects faces the challenge of the large amount of data that this task must deal with. Moreover, when graphs are used to model these objects, it is known that graph comparison is very complex and computationally hard especially for large graphs. So, research on simplifying graph comparison gainedan interest and several solutions are proposed. In this paper, we explore and evaluate a new solution for the comparison of large graphs. Our approach relies on a compact encoding of graphs called prime graphs. Prime graphs are smaller and simpler than the original ones but they retain the structure and properties of the encoded graphs. We propose to approximate the similarity between two graphs by comparing the corresponding prime graphs. Simulations results show that this approach is effective for large graphs.     

A conceptual theory of part-whole relations and its applications

This paper shows two applications of a theory of part-whole relations that has been introduced in [1] in two different areas: natural language semantics and modelling parts of physical objects. A short overview of the theory will be given, followed by two sections which present results in the two application areas. In Section 2 we provide an analysis of the domain of solid objects like devices, buildings and other artifacts of our daily life. We first examine in more detail the relevant part-whole relations in that domain. The second part describes how these relations can be represented and manipulated in a hybrid system. In Section 3 it will be shown that there is a strong and immediate correspondence between classes of part-whole-relations and syntactically or lexically motivated classes of genitive constructions. The two applications illustrate the generality of the theory as well as its usefulness for representing and reasoning about part-whole information in totally different domains.     

Internet as a multiple graph structure: The role of the transport layer

This paper discusses how the transport layer (TCP/UDP/SCTP) divides the Internet into a vertical structure consisting of three domains: IP network domain, terminal equipment domain, and applications domain. This subdivision of the Internet has wide consequences both in the way in which business is carried out on the network and with regard to the vulnerability of society caused by the openness of the network. The Internet may also be modelled as a multiple graph structure. The domains may be viewed as independent entities allowing the different aspects of the Internet to be analysed as single graphs within each domain. Furthermore, the vulnerability of society may also be represented as a multiple graph structure where one of the components is a graph instance in the application domain of Internet representing the problem under study. Information security may then be studied at two levels: the vulnerability of the IP network itself and the vulnerability of the distributed processing taking place in the application domain.     

EXPLANATION-BASED NATURAL LANGUAGE ACQUISITION USING UNIVERSAL LINGUISTIC PRINCIPLES AS INNATE DOMAIN THEORY

In this paper, we propose a new natural language acquisition model (called EBNLA) based on explanation-based language ( EBL). To apply EBL to the natural language acquisition domain, suitable universal linguistic principles are incorporated as domain theory. The domain theory consists of two parts: static and dynamic. The static part, which is assumed to he invariant and innate to the model, includes theta theory in government-binding theory and universal fea ture instantiation principles in generalized phrase structure grammar. The dynamic part con tains context-free grammar rules as well as syntactic and thematic features of lexicons. In parsing ( problem solving), both parts work together to parse input sentences. As parsing fails, learning is triggered to enrich and generalize the dynamic part by obeying the principles in the static part. By introducing EBL and the universal linguistic principles, portability of the model and leamabitity of knowledge in the real-world natural language acquisition domain can be improved.     

三维几何约束系统的等价性分析

针对过约束、完整约束和欠约束三维几何约束系统的求解问题,提出了等价性分析方法.该方法基于三维几何约束系统的内在等价性,充分挖掘几何领域知识,依据拆解约束闭环、缩减约束闭环和析出约束闭环等原则,采用等价约束替换来处理几何约束闭环问题,优化几何约束图的结构,实现几何约束系统的优化分解.最后用多个实例验证了该方法的正确性和有...     

High Resolution Sharp Computational Methods for Elliptic and Parabolic Problems in Complex Geometries

We present a review of some of the state-of-the-art numerical methods for solving the Stefan problem and the Poisson and the diffusion equations on irregular domains using (i) the level-set method for representing the (possibly moving) irregular domain’s boundary, (ii) the ghost-fluid method for imposing the Dirichlet boundary condition at the irregular domain’s boundary and (iii) a quadtree/octree node-based adaptive mesh refinement for capturing small length scales while significantly reducing the memory and CPU footprint. In addition, we highlight common misconceptions and describe how to properly implement these methods. Numerical experiments illustrate quantitative and qualitative results.     

Derivation of Glue Code for Agent Interoperation

Getting agents to communicate requires translating the data structures of the sender (the source representation) to the format required by the receiver (the target representation). Assuming that there is a formal theory of the semantics of the two formats, which explains both their meanings in terms of a neutral topic domain, we can cast the translation problem as solving higher-order functional equations. Some simple rules and strategies apparently suffice to solve these equations automatically. The strategies may be summarized as: decompose complex expressions, replacing topic-domain expressions with source-domain expressions when necessary. A crucial issue is getting the required formal theories of the source and target domains. We believe it is sufficient to find partial formalizations that grow as necessary.     

S-ABC: A paradigm of service domain-oriented artificial bee colony algorithms for service selection and composition

With the rapid development of Cloud Computing, Big Data, Social Networks, and the Internet of Things, typical service optimization problems (SOPs) such as service selection, service composition and service resource scheduling in the service computing field have become more and more complicated due to the constant enrichment and dynamic aggregation of large number of services, as well as the unceasing variation of user requirements. Meanwhile, with the long-term development and evolution of business in many application domains, some service domain features (such as priori, correlation and similarity) are usually formed, which have strong influences on solving SOPs. Unfortunately, the existing research efforts on SOPs primarily concentrate on designing general algorithms for specific problems without considering the service domain features. This often leads to undesirable results of SOPs. Therefore, how to design a paradigm of service domain-oriented optimization algorithms with service domain features becomes a challenge for providing optimization strategies and algorithms to solve SOPs effectively. By considering the influences of service domain features on solving SOPs, this paper proposes a set of service domain-oriented artificial bee colony algorithms (S-ABC) based on the optimization mechanism of Artificial Bee Colony (ABC) method. Furthermore, by configuring the items and parameters of the S-ABC paradigm in detail, optimization algorithms for particular SOPs (e.g., service selection and composition) could be derived. In this paper, the superiority of our proposed S-ABC is verified through solving concurrent service selection and service composition problem. By exploiting the artificial bee colony algorithms for the optimization problems in service domains, this work makes novel contributions for solving SOPs, as well as extends the theory of the swarm intelligence optimization.     

Uniform Closures: Order-Theoretically Reconstructing Logic Program Semantics and Abstract Domain Refinements

The notion of uniform closure operator is introduced, and it is shown how this concept surfaces in two different areas of application of abstract interpretation, notably in semantics design for logic programs and in the theory of abstract domain refinements. In logic programming, uniform closures permit generalization, from an order-theoretic perspective, of the standard hierarchy of declarative semantics. In particular, we show how to reconstruct the model-theoretic characterization of the well-known s-semantics using pure order-theoretic concepts only. As far as the systematic refinement operators on abstract domains are concerned, we show that uniform closures capture precisely the property of a refinement of being invertible, namely of admitting a related operator that simplifies as much as possible a given abstract domain of input for that refinement. Exploiting the same argument used to reconstruct the s-semantics of logic programming, we yield a precise relationship between refinements and their inverse operators: we demonstrate that they form an adjunction with respect to a conveniently modified complete order among abstract domains.     

基于因果图启发式的并行概率规划求解

并行概率规划(PPP)是近年来智能规划领域中的研究热点。在该类问题中,动作具有并发性和不确定性,非常贴近现实问题。然而,现有的两种针对PPP的主要求解方法都有明显的缺点。一种基于模拟抽样,以规划器PROST为代表,但求解速度慢;另一种基于迭代深化,以规划器Glutton为代表,但求解质量差。因此,我们尝试使用高效的启发式搜索方法来求解这类问题。目前,因果图启发式(CGH)是启发式规划方法中的佼佼者。考虑到PPP问题采用RDDL语言来描述,其中的条件概率函数(CPF)非常适合用于构建因果图(CG),所以我们引入因果图来对基于RDDL描述的PPP问题进行启发式求解。本文的主要启发式算法称为CGH_RDDL,整体求解方法是使用rddlsim模拟状态演化以及用CGH_RDDL引导搜索。具体做法是：先从领域描述构建出因果图及领域转换图(DTG);然后根据CG和DTG,计算单个状态变量任意一对取值间的转换代价;接着在rddlsim的模拟演化过程中,由CGH_RDDL推送具有最佳估值的后继状态,其中状态的启发值定义为状态轨迹的转换代价和立即回报值的总和;最后累加在限定轮数内rddlsim状态演化的回报值,即为最终的求解质量。在PPP基准领域上的实验结果表明,在不允许手工干预和参数调整的前提下,本文方法的求解效果要好于PROST和Glutton。更进一步地,与其它的基本启发式相比,CGH_RDDL的求解质量高于随机搜索,求解速度快于爬山法。这表明在经典规划领域中高效的启发式搜索策略可扩展去求解这一类非经典规划问题。而非经典规划问题更具有现实意义和应用前景,更值得探讨先进的规划方法去求解它们。     

概念获取的框架表征重述方法*

基于知识的问题求解需要一个丰富而相对完备的信念系统,尤其是当任务具有领域非限定特征时。经典知识工程关于知识获取、表示与使用的方法只能适应领域受限问题,因为它不是从概念发展的角度来建构概念系统的,面临着Framework Problem。针对认知心理学对概念系统发展与表征问题研究有一定的认知深度同时又缺乏系统构造与实现机制研究的情况,提出了一种基于框架表征的概念系统表征与发展方法,详细研究了概念在内的隐水平I、外显水平E1、外显水平E2和外显水平E3上的表征和发展过程。这一研究对于提高基于知识的系统推理能力和问题求解能力具有显著意义。     

A fusion estimation method based on fractional Fourier transform

Image denoising methods have different denoising performance in both spatial and transform domains, and each method has its relative advantages and inherent shortcomings compared with other methods. A very intuitive idea is to find that an effective fusion method that can combine with the advantages of different denoising methods. In this paper, we propose a novel fusion method based on the fractional Fourier transform and apply it to image denoising problem. Our method is mainly divided into three steps: Firstly, a pre-estimation is made by any two denoising method separately in the spatial domain. Secondly, using these two estimated results as well as their Fourier transform, twice Fourier transform and three times Fourier transform, we obtain a fused result in the fractional Fourier transform domain. Thirdly, the inverse fractional Fourier transform and the modulus operation are used to obtain the final fusion result. Obviously, this approach is the fusion method in four different domains. Experimental results on benchmark test images demonstrate that the proposed method outperforms state-of-the-art stand-alone methods as: BM3D, DDID, MLP, EPLL and also superior to the fusion methods such as classic wavelet fusion method, PCA fusion method and the state-of-the-art CIEM fusion method in terms of quantity value such as the peak signal to noise ratio (PSNR), the structural similarity (SSIM), and visual quality.     

可求解多目标优化问题的演化博弈优化算法

借鉴演化博弈的思想和选择机制,提出了一种新的基于演化博弈的优化算法(EGOA)用于多目标问题的求解.算法框架具备对该类问题的通用性.为了对算法性能进行评估,采用了一组多目标优化问题(MOPs)的测试函数进行实验.实验结果表明,使用本算法搜索得到的演化稳定策略集合能够很好地逼近多目标优化问题的帕累托前沿,与一些经典的演化算法相比具有良好的问题求解能力.     

领域知识图谱快速构建和应用框架

快速构建和应用领域知识图谱(domain knowledge graphs, DKG)已成为企业的迫切需求。然而,领域知识图谱的快速构建和应用仍然存在问题:1）构建前,复杂领域场景涉及知识维度广,业务专家短时间内难以构建完备的领域schema;2）构建中,业务和技术专家深度耦合,图谱构建缓慢,难以适应业务快速发展需求;3）构建后,图谱应用严重依赖技术人员开发,业务专家无法自主基于领域知识图谱探索问题解决方案。为解决上述问题,本文提出了领域知识图谱的快速构建和应用框架,其中包括:多人协作构建领域schema解决领域知识的复杂性问题,将业务和技术专家解耦合,提高领域知识图谱的构建效率,最后通过建立基于行业schema的auto-KBQA((knowledge base question answering)解决领域知识图谱在知识问答应用的快速落地。通过实际项目的应用落地,验证了该框架可有效加快领域知识图谱的落地应用,期望该框架给领域知识图谱的快速构建和应用带来一定的启发和帮助。     

多核局部领域适应学习

领域适应(或跨领域)学习旨在利用源领域(或辅助领域)中带标签样本来学习一种鲁棒的目标分类器,其关键问题在于如何最大化地减小领域间的分布差异.为了有效解决领域间特征分布的变化问题,提出一种三段式多核局部领域适应学习(multiple kernel local leaning-based domain adaptation,简称MKLDA)方法:1)基于最大均值差(maximum mean discrepancy,简称MMD)度量准则和结构风险最小化模型,同时,学习一个再生多核Hilbert空间和一个初始的支持向量机(support vector machine,简称SVM),对目标领域数据进行初始划分;2)在习得的多核Hilbert空间,对目标领域数据的类别信息进行局部重构学习;3)最后,利用学习获得的类别信息,在目标领域训练学习一个鲁棒的目标分类器.实验结果显示,所提方法具有优化或可比较的领域适应学习性能.     

开放式系统的自治安全域模型研究

本文对开放式系统的安全域进行了讨论,对安全域之间的关系进行了阐述,针对安全域模型,结合安全域的多级安全的特点,对安全域模型进行了研究。对于开放分布式系统的多级安全域的特点,提出采用自治Ａｇｅｎｔ来实现的多域安全框架。