IDENTIFICATION OF AN OPEN SYSTEM BY ITS RESOURCES

The open thermodynamic system has been identified as an imprecise dynamical observer and as a rotator, each one with a heuristic function of behavior. These two identification models have been obtained by isolation of the open system. They have been determined as patterns with interpretation of the internalized plan and of the oscillations in the open system. The imprecise dynamical observer has been constructed by perceiving the internalized plan as a fuzzy controller of the speed of a mobile robot, by structuring the internalized plan as a dynamical observer and interpreting the internalized plan as a heuristic function for the remaining path to a goal. The rotator has been constructed by perceiving the oscillations as movement along a cycle, by structuring the oscillations as an autoregressive model and by interpreting the oscillations as a heuristic function for the remaining energy to a goal.     

FlexiMine – A Flexible Platform for KDD Research and Application Development

FlexiMine is a KDD system designed as a testbed for data-mining research, as well as a generic knowledge discovery tool for varied database domains. Flexibility is achieved by an open-ended design for extensibility, thus enabling integration of existing data-mining algorithms, new locally developed algorithms, and utility functions such as visualization and preprocessing. Support for new databases is simple and clean: the system interfaces with a standard database server via SQL queries and thus can handle any application database. With a view of serving remote, as well as local, users, internet availability was a design goal. By implementing the system in Java, minor modifications allow us to run the user-end of the system either as a Java applications or (with some limitations on the user) as a Java Applet. This paper reviews the architecture, design and operation of FlexiMine and presents some of the new ideas incorporated in the data-mining algorithms (Association rules, Decision trees, Bayesian knowledge-bases and Meta-queries).     

An attempt to design qualitative differential games†

Obviously enough, a differential game as an extension of a control system, as well as many other systems of dynamics, may be synthesized. In case of qualitative games this may lead to certain classes of differential systems of the game or certain classes of strategies, implying a prescribed outcome in the form of a prescribed qualitative property of the game path. The synthesis procedure may serve as a tool for solving games, as well as the game-methods may help in the synthesis; the proper relation, however, has to be defined.     

A structured marketplace for arbitrary services

Creating simple marketplaces with common rules, that enable the dynamic selection and consumption of functionality, is the missing link to allow small businesses to enter the cloud, not only as consumers, but also as vendors. In this paper, we present the concepts behind a hybrid service and process repository that can act as the foundation for such a marketplace, as well as a prototype that allowed us to test various real-world scenarios. The advantage of a hybrid service and process repository is that, it not only holds a flat list of services, but also exposes a generic set of use cases, that it obtains information on how specific services can be used to implement the use cases as well as information to select services at run-time according to customer’s goal functions.     

Learning Generative Models of Scene Features

We present a method for learning a set of generative models which are suitable for representing selected image-domain features of a scene as a function of changes in the camera viewpoint. Such models are important for robotic tasks, such as probabilistic position estimation (i.e. localization), as well as visualization. Our approach entails the automatic selection of the features, as well as the synthesis of models of their visual behavior. The model we propose is capable of generating maximum-likelihood views, as well as a measure of the likelihood of a particular view from a particular camera position. Training the models involves regularizing observations of the features from known camera locations. The uncertainty of the model is evaluated using cross validation, which allows for a priori evaluation of features and their attributes. The features themselves are initially selected as salient points by a measure of visual attention, and are tracked across multiple views. While the motivation for this work is for robot localization, the results have implications for image interpolation, image-based scene reconstruction and object recognition. This paper presents a formulation of the problem and illustrative experimental results.     

Requirements traceability: Theory and practice

Current literature as well as standards that mandate requirements traceability do not provide a comprehensive model of what information should be captured and used as a part of a traceability scheme, leading to wide variation in the quality and usefulness of traceability practice across systems development efforts. In this paper, we present a framework for representing and developing a traceability scheme. The experiences of an organization using traceability as an important component of a quality software engineering process are discussed. Models describing the traceability practice in the organization, as well as issues and lessons learned, both from organizational and technical perspectives, from implementing a comprehensive traceability practice are presented.     

On graphs of central episturmian words

Episturmian sequences are a natural extension of Sturmian sequences to the case of finite alphabets of arbitrary cardinality. In this paper, we are interested in central episturmian words, or simply, epicentral words, i.e., the palindromic prefixes of standard episturmian sequences. An epicentral word admits a variety of faithful representations including as a directive word, as a certain type of period vector, as a Parikh vector, as a certain type of Fine and Wilf extremal word, as a suitable modular matrix, and as a labeled graph. Various interconnections between the different representations of an epicentral word are analyzed. In particular, we investigate the structure of the graphs of epicentral words proving some curious and surprising properties.     

基于射频识别技术的智能信箱系统设计

针对传统信箱开锁上锁费时、钥匙遗失时须重新换锁、无指示功能等缺点,以C8051F020为核心,利用射频识别技术设计了具有指示灯、电子锁、键盘、液晶显示等功能的智能信箱系统,实现了信箱的多功能化、智能化、人性化。     

Quantale-based autoassociative memories with an application to the storage of color images

In recent years, lattice computing has emerged as a new paradigm for processing lattice ordered data such as intervals, Type-1 and Type-2 fuzzy sets, vectors, images, symbols, graphs, etc. Here, the word “lattice” refers to a mathematical structure that is defined as a special type of a partially ordered set (poset). In particular, a complete lattice is a poset that contains the infimum as well as the supremum of each of its subsets. In this paper, we introduce the quantale-based associative memory (QAM), where the notion of a quantale is defined as a complete lattice together with a binary operation that commutes with the supremum operator. We show that QAMs can be effectively used for the storage and the recall of color images.     

Wearable computing: toward humanistic intelligence

Over the past 20 years, wearable computing has emerged as the perfect tool for embodying humanistic intelligence (HI). HI is intelligence that arises when a human is part of the feedback loop of a computational process in which the human and computer are inextricably intertwined. It is common in the field of human-computer interaction to think of the human and computer as separate entities. (indeed, the term "HCI" emphasizes this separateness by treating the human and computer as different entities that interact.) However, in HI theory, we prefer not to think of the wearer and the computer with its associated I/O apparatus as separate entities. Instead, we regard the computer as a second brain and its sensory modalities as additional senses, in which synthetic synesthesia merges with the wearer's senses. When a wearable computer functions in a successful embodiment of HI, the computer uses the human's mind and body as one of its peripherals, just as the human uses the computer as a peripheral. This reciprocal relationship is at the heart of HI.     

基于J2EE的Web-MIS通用架构的研究与实现

提出用J2EE技术来实现一个基于Wcb的信息管理系统的通用架构。论述了使用Servlet来实现流科的控制器、用JSP实现显示界面、用EJB实现数据模型的原理及方法。讨论了由Servlet、JsP和EJB互相协作，从而实现了一个MVC模式的WC-MlS架构。     

Jack Minker — A profile

This introduction provides a brief synopsis of Jack Minker's career. It discusses his contributions as a teacher, a researcher, as one who has served the computer science and logic programming communities, as an individual deeply committed to human rights, and as a person.     

迈向管理服务化(英文)

Internet上越来越多的应用都具有Web风格,Web本身正逐步成为Internet上各类应用的运行平台,这种现象可称为"Web平台化","Web平台化"为信息技术的发展带来机遇和挑战。文章立足于探讨"Web平台化"所面临的关键技术挑战之一,即Web管理。首先从Web的特征出发,总结其对Web管理的要求;其次提出将"管理服务化"作为Web管理的解决方案,并指出"管理服务化"面临的技术挑战;最后以PKUAS支持的面向服务的管理为例展示"管理服务化"的可行性。     

Abstracting People's Trajectories for Social Robots to Proactively Approach Customers

For a robot providing services to people in a public space such as a shopping mall, it is important to distinguish potential customers, such as window shoppers, from other people, such as busy commuters. In this paper, we present a series of abstraction techniques for people's trajectories and a service framework for using these techniques in a social robot, which enables a designer to make the robot proactively approach customers by only providing information about target local behavior. We placed a ubiquitous sensor network consisting of six laser range finders in a shopping arcade. The system tracks people's positions as well as their local behaviors, such as fast walking, idle walking, wandering, or stopping. We accumulated people's trajectories for a week, applying a clustering technique to the accumulated trajectories to extract information about the use of space and people's typical global behaviors. This information enables the robot to target its services to people who are walking idly or stopping. The robot anticipates both the areas in which people are likely to perform these behaviors as well as the probable local behaviors of individuals a few seconds in the future. In a field experiment, we demonstrate that this service framework enables the robot to serve people efficiently.      

A New FIR Filter for State Estimation and Its Application

This paper proposes a new FIR （finite impulse response） filter under a least squares criterion using a forgetting factor. The proposed FIR filter does not require information of the noise covariances as well as the initial state, and has some inherent properties such as time-invariance, unbiasedness and deadbeat. The proposed FIR filter is represented in a batch form and then a recursive form as an alternative form. Prom discussions about the choice of a forgetting factor and a window length, it is shown that they can be considered as useful parameters to make the estimation performance of the proposed FIR filter as good as possible. It is shown that the proposed FIR filter can outperform the existing FIR filter with incorrect noise covariances via computer simulations. Finally, as a useful application, an image sequence stabilization problem is considered. Through this application, the FIR filtering based approach is shown to be superior to the Kalman filtering based approach.     

Reinforcement learning combined with a fuzzy adaptive learning control network (FALCON-R) for pattern classification

Reinforcement learning has been widely-used for applications in planning, control, and decision making. Rather than using instructive feedback as in supervised learning, reinforcement learning makes use of evaluative feedback to guide the learning process. In this paper, we formulate a pattern classification problem as a reinforcement learning problem. The problem is realized with a temporal difference method in a FALCON-R network. FALCON-R is constructed by integrating two basic FALCON-ART networks as function approximators, where one acts as a critic network (fuzzy predictor) and the other as an action network (fuzzy controller). This paper serves as a guideline in formulating a classification problem as a reinforcement learning problem using FALCON-R. The strengths of applying the reinforcement learning method to the pattern classification application are demonstrated. We show that such a system can converge faster, is able to escape from local minima, and has excellent disturbance rejection capability.     

Computerizing Céline

This article uses recent work on the computer-aided analysis of texts by the French writer Céline as a framework to discuss Olsen's paper on the current state of computer-aided literary analysis. Drawing on analysis of syntactic structures, lexical creativity and use of proper names, it makes two points: (1) given a rich theoretical framework and sufficiently precise models, even simple computer tools such as text editors and concordances can make a valuable contribution to literary scholarship; (2) it is important to view the computer not as a device for finding what we as readers have failed to notice, but rather as a means of focussing more closely on what we have already felt as readers, and of verifying hypotheses we have produced as researchers.     

A graph-oriented object database model

A graph-oriented object database model (GOOD) is introduced as a theoretical basis for database systems in which manipulation as well as conceptual representation of data is transparently graph-based. In the GOOD model, the scheme as well as the instance of an object database is represented by a graph, and the data manipulation is expressed by graph transformations. These graph transformations are described using five basic operations and a method construct, all with a natural semantics. The basic operations add and delete objects and edges as a function of the matchings of a pattern. The expressiveness of the model in terms of object-oriented modeling and data manipulation power is investigated