Interactive foundations of computing

The claim that interactive systems have richer behavior than algorithms is surprisingly easy to prove. Turing machines cannot model interaction machines (which extend Turing machines with interactive input/output) because interaction is not expressible by a finite initial input string. Interaction machines extend the Chomsky hierarchy, are modeled by interaction grammars, and precisely capture fuzzy concepts like open systems and empirical computer science. Computable functions cannot model real-world behavior because functions are too strong an abstraction, sacrificing the ability to model time and other real-world properties to realize formal tractability.Part I of this paper examines extensions to interactive models for algorithms, machines, grammars, and semantics, while Part II considers the expressiveness of different forms of interaction. Interactive identity machines are already more powerful than Turing machines, while noninteractive parallelism and distribution are algorithmic. The extension of Turing to interaction machines parallels that of the lambda to the pi calculus. Asynchronous and nonserializable interaction are shown to be more expressive than sequential interaction (multiple streams are more expressive than a single stream).In Part III, it is shown that interaction machines cannot be described by sound and complete first-order logics (a form of Godel incompleteness), and that incompleteness is inherently necessary to realize greater expressiveness. In the final section the robustness of interactive models in expressing open systems, programming in the large, graphical user interfaces, and agent-oriented artificial intelligence is compared to the robustness of Turing machines. Less technical discussion of these ideas may be found in [25–27]. Applications of interactive models to coordination, objects and components, patterns and frameworks, software engineering, and AI are examined elsewhere [28,29].The propositions P1-P36 embody the principal claims, while observations 01 through 040 provide additional insights.     

Probabilistic finite-state machines--part I

Probabilistic finite-state machines are used today in a variety of areas in pattern recognition, or in fields to which pattern recognition is linked: computational linguistics, machine learning, time series analysis, circuit testing, computational biology, speech recognition, and machine translation are some of them. In Part I of this paper, we survey these generative objects and study their definitions and properties. In Part II, we study the relation of probabilistic finite-state automata with other well-known devices that generate strings as hidden Markov models and n-grams and provide theorems, algorithms, and properties that represent a current state of the art of these objects.     

A computational model for static data flow machines

Computer architects have been constantly looking for new approaches to design high-performance machines. Data flow and VLSI offer two mutually supportive approaches towards a promising design for future super-computers. When very high speed computations are needed, data flow machines may be relied upon as an adequate solution in which extremely parallel processing is achieved.

This paper presents a formal analysis for data flow machines. Moreover, the following three machines are considered: (1) MIT static data flow machine; (2) TI's DDP static data flow machine; (3) LAU data flow machine.

These machines are investigated by making use of a reference model. The contributions of this paper include: (1) Developing a Data Flow Random Access Machine model (DFRAM), for first time, to serve as a formal modeling tool. Also, by making use of this model one can calculate the time cost of various static data machines, as well as the performance of these machines. (2) Constructing a practical Data Flow Simulator (DFS) on the basis of the DFRAM model. Such DFS is modular and portable and can be implemented with less sophistication. The DFS is used not only to study the performance of the underlying data flow machines but also to verify the DFRAM model.     

采用ORM技术的软件开发方法研究

首先介绍对象模型与关系模型的两个基本定义并推出两者之间的映射函数，然后通过UML建立对象模型与关系模型的映射，最后介绍一种实现关系数据库与对象之间自动映射的ORM技术，说明采用ORM框架的软件开发总体设计和关键技术。     

Digital weaving.2

The process of weaving is a great model for making beautiful patterns. The basic ideas are conceptually simple, and the resulting fabrics can be lovely to see. In Part 1 of this series I talked about the basics of looms and drafts, and I showed how to model the basic weaving process mathematically. I also showed a few examples from my digital loom, which implements those ideas. This time I talk about how we can run the weaving process backward and deduce the draft from a fabric sample. I also discuss a language that helps us create and explore complex woven patterns.     

实现能量均衡消耗的传感器网络节点摆放策略

在传感器网络技术应用的民用领域中,采集信息的传感器节点位置固定,并且有些距离汇聚节点太远,需要加入中继节点转发数据。一些中继节点由于承担了过多的数据量而过早耗尽能量,影响了网络的生存周期。该文针对该种情况,提出了一种实现各节点能量均衡消耗的中继节点多级摆放策略,研究了如何通过调整中继节点的摆放位置和转发数据量,使传感器节点和中继节点在每一轮的数据传输中消耗相同的能量。基于该策略,还研究了中继节点数目与网络生存周期之间的关系,为延长网络生命周期和减小中继节点数目的折中提供了一种参考。     

On uniform circuit complexity

We argue that uniform circuit complexity introduced by Borodin is a reasonable model of parallel complexity. Three main results are presented. First, we show that alternating Turing machines are also a surprisingly good model of parallel complexity, by showing that simultaneous size/depth of uniform circuits is the same as space/time of alternating Turing machines, with depth and time within a constant factor and likewise log(size) and space. Second, we apply this to characterize NC, the class of polynomial size and polynomial-in-log depth circuits, in terms of tree-size bounded alternating TMs and other models. In particular, this enables us to show that context-free language recognition is in NC. Third, we investigate various definitions of uniform circuit complexity, showing that it is fairly insensitive to the choice of definition.     

无线传感器网络寿命的一种新定义方法

无线传感器网络是一种能量受限型网络,降低能量消耗、延长网络寿命是无线传感器网络设计的主要目标之一,网络寿命也是评价设计方案性能的重要指标。寿命定义方式对传感器网的设计,尤其是通信协议、任务调度机制的设计具有非常重要的影响。采用的寿命定义不同,网络的设计目标就不相同,针对同一个设计方案的分析结论也可能差别巨大。该文在总结分析传感器网寿命现有定义的基础上,从衡量传感器网络为用户提供服务能力的角度出发,提出了一种基于网络有效覆盖率的寿命定义方法,并对网络寿命的测定流程和仿真过程中的两个关键问题提出了解决方案。     

Combining heterogeneous sources in an interactive multimedia content retrieval model

Interactive multimodal information retrieval systems (IMIR) increase the capabilities of traditional search systems, by adding the ability to retrieve information of different types (modes) and from different sources. This article describes a formal model for interactive multimodal information retrieval. This model includes formal and widespread definitions of each component of an IMIR system. A use case that focuses on information retrieval regarding sports validates the model, by developing a prototype that implements a subset of the features of the model. Adaptive techniques applied to the retrieval functionality of IMIR systems have been defined by analysing past interactions using decision trees, neural networks, and clustering techniques. This model includes a strategy for selecting sources and combining the results obtained from every source. After modifying the strategy of the prototype for selecting sources, the system is re-evaluated using classification techniques. This evaluation compares the normalised discounted cumulative gain (NDCG) measure obtained using two different approaches: the multimodal system using a baseline strategy based on predefined rules as a source selection strategy, and the same multimodal system with the functionality adapted by past user interactions. In the adapted system, a final value of 81,54% was obtained for the NDCG.     

身份认证协议的模型检测分析

提出一个直观、易用的模型来模拟和验证身份认证协议，并给出基于Spin(模型检测工具）的实现，它不仅可以模拟多对参与者同时进行会话，而且还有效缩减了状态空间，从而避免了以前文献中提到的状态爆炸现象，同时该文用Needham-Schroeder公钥协议和TMN协议来说明如何应用该模型。     

基于词共现模型与DOM的石油主题采集策略

提出了一种基于DOM树的词共现模型,首先利用文档的结构信息生成DOM树,并依据DOM树的结构特点来统计文档中主题词的共现信息,最后采用向量空间模型实现对石油主题网页的采集和分类.它改进了原有的词共现模型,突出了利用位置信息来优化词共现模型的特点.实验证明该策略使采集和分类的性能都有了一定的提高.     

基于遗传算法的机场机位分配策略

通过对大型机场机位分配所受约束和最终目标的分析研究,将其模型化,提出使用遗传算法来解决机场机位分配问题,并设计实现了该算法。为促进算法收敛,引入模拟退火思想对适应度函数进行了修正。实验数据表明,该算法相对已有的其它机位分配方法在计算时间、实时性和结果优化程度上都有一定的优势。目前该方法已经成功应用到国内某国际机场。     

Discrete–continuous analysis of optimal equipment replacement

In operations research, the equipment replacement process is usually modeled in discrete time. An alternative approach is represented by continuous‐time vintage capital models that explicitly involve the equipment lifetime and are described by nonlinear integral equations. The paper introduces and analyzes a model that unites both these approaches. The structure of optimal replacement, transition, and long‐term dynamics, and clustering and splitting of replaced machines are discussed and illustrated with numeric examples. Equipment splitting is demonstrated when the optimal equipment lifetime increases.     

基于并行支持向量机的多变量非线性模型预测控制

提出一种基于并行支持向量机的多变量系统非线性模型预测控制算法．首先,通过考虑输入、输出间的耦合,建立基于并行支持向量机的多步预测模型;然后,将该模型用于非线性预测控制,提出新的适用于并行预测模型的反馈校正策略,得到最优控制律．连续搅拌槽式反应器（CSTR）的控制仿真结果表明,该算法的性能优于基于并行神经网络的非线性模型预测控制和基于集成模型的非线性模型预测控制．     

基于Transputer网络的实时黑板模型试验床系统CPES

本文使用“黑板转播器”概念,在Ｔｒａｎｓｕｐｔｅｒ风格上实现了一个可用于实时领域的并行黑板模型试验床系统ＣＰＥＳ,它具有并行度高、模块化性能好的结构特点。本文对ＣＰＥＳ的性能如问题求解速度、并行状态下各项开销情况进行了测试,同时还对并行黑板模型的测试方法、性能衡量指标等进行了初步探讨;测试结果反映出ＣＰＥＳ具有较好的实时黑板模型试验床的性能和功能。     

多级安全DBMS的通用审计策略模型

提出了一种基于多级安全数据库管理系统的通用审计策略模型.该模型具有丰富的表达能力,既可以表达基于时间的审计策略,也可以实现基于规则的审计策略推衍.通过引入对象的属性谓词,还可以表达细粒度的审计策略.证明了该模型的可判定性,并给出了判定任意一个事件是否需要审计的算法.     

基于感知数据概率模型的无线传感器网络采样和通信调度算法

在无线传感器网络中,如何动态地管理能量,最大限度地延长网络的生命周期是一个关键的问题。文中提出了一种基于感知数据概率模型的传感器网络的采样和通信动态调度算法,使传感器节点根据感知数据的概率模型来确定自己的采样和通信时机,最小化采样频率和通信量,减少传感器节点的能量消耗,延长传感器网络的生命期。该算法是一种分布式算法,适用于无线传感器网络。该算法采用了简单的概率模型,资源需求量小,适合于在目前普遍使用的资源受限的传感器节点上运行。模拟试验结果表明,这种方法与其他方法相比,具有很高的能量有效性。     

Profile-based dynamic application assignment with a repairing genetic algorithm for greener data centers

Data centers have become essential to modern society by catering to increasing number of Internet users and technologies. This results in significant challenges in terms of escalating energy consumption. Research on green initiatives that reduce energy consumption while maintaining performance levels is exigent for data centers. However, energy efficiency and resource utilization are conflicting in general. Thus, it is imperative to develop an application assignment strategy that maintains a trade-off between energy and quality of service. To address this problem, a profile-based dynamic energy management framework is presented in this paper for dynamic application assignment to virtual machines (VMs). It estimates application finishing times and addresses real-time issues in application resource provisioning. The framework implements a dynamic assignment strategy by a repairing genetic algorithm (RGA), which employs realistic profiles of applications, virtual machines and physical servers. The RGA is integrated into a three-layer energy management system incorporating VM placement to derive actual energy savings. Experiments are conducted to demonstrate the effectiveness of the dynamic approach to application management. The dynamic approach produces up to 48% better energy savings than existing application assignment approaches under investigated scenarios. It also performs better than the static application management approach with 10% higher resource utilization efficiency and lower degree of imbalance.     

Maximum Matching on Boltzmann Machines

The Boltzmann machine is one of widely used neural network models used to cope with difficult combinatorial optimisation problems. It has been used to find near optimum solutions to such hard problems as graph partitioning and the Travelling Salesman problem. However, very little is known about the time complexity of solving combinatorial optimisation problems on Boltzmann machines. This issue is important because it will help us better understand the power of Boltzmann machines in dealing with hard problems. This paper studies the time complexity of maximum matching in a graph on Boltzmann machines. It is shown that some widely-used Boltzmann machines cannot find a maximum matching in average time polynomial in the number of nodes of the graph although there are conventional deterministic algorithms which solve the problem in polynomial time. On the other hand, this paper also shows that a simpler model of Boltzmann machines, with the 'temperature' parameter fixed at some constant, can find a near maximum matching in polynomial average time.