UML现存的问题和发展道路

自从1997年OMG采纳UML作为其标准建模语言以来,UML受到计算机各界人士的普遍关注,得到了广泛的应用,并在世界范围内形成了其事实上的建模规范的地位．但也无时无刻不受到来自用户、工具开发商、学者和教学者从不同角度的批评．UML先后进行了3次修订(1．3,1．4和2．0),目前计算机各界人士对UML提出了各种意见,并将重点放在目前公认的几个问题上：精简、定义核心、扩展机制以及形式化语义等．     

Generalized Computational Experiment and Verification Problems

Programming and Computer Software - This paper considers the construction of a generalized computational experiment for solving verification problems. The problem of comparative accuracy assessment...     

A Roadmap of Agent Research and Development

This paper provides an overview of research and development activities in the field of autonomous agents and multi-agent systems. It aims to identify key concepts and applications, and to indicate how they relate to one-another. Some historical context to the field of agent-based computing is given, and contemporary research directions are presented. Finally, a range of open issues and future challenges are highlighted.     

Attacking a Conjecture in Mathematical Physics by Combining Methods of Computational Analysis and Scientific Computing

We consider a conjecture on the sum of eigenvalues of two integral operators arising in potential and scattering theory for the case that the underlying surface is a triaxial ellipsoid. This concerns computation of Lamé functions which are anyway of great interest in electromagnetics and mechanics. We provide a new effective scheme for the numerical treatment of these special functions. It involves computing the Lamé functions with high accuracy combined with safe error estimates.     

A Connectivity-Based Method for Enhancing Sampling in Probabilistic Roadmap Planners

The motion planning is a difficult problem but nevertheless, a crucial part of robotics. The probabilistic roadmap planners have shown to be an efficient way to solve these planning problems. In this paper, we present a new algorithm that is based on the principles of the probabilistic roadmap planners. Our algorithm enhances the sampling by intelligently detecting which areas of the configuration space are easy and which parts are not. The algorithm then biases the sampling only to the difficult areas that may contain narrow passages. Our algorithm works by dividing the configuration space into regions at the beginning and then sampling configurations inside each region. Based on the connectivity of the roadmap inside each region, our algorithm aims to detect whether the region is easy or difficult. We tested our algorithm with three different simulated environments and compared it with two other planners. Our experiments showed that with our method it is possible to achieve significantly better results than with other tested planners. Our algorithm was also able to reduce the size of roadmaps.     

A Computational Approach to Uncovering Economic Growth Factors

Computational Economics - The knowledge-based economy is the basis of economics in which all businesses and industries benefit from the distribution and application of knowledge in pursuit of their...     

A Manifold Learning Approach to Data-Driven Computational Elasticity and Inelasticity

Standard simulation in classical mechanics is based on the use of two very different types of equations. The first one, of axiomatic character, is related to balance laws (momentum, mass, energy,...), whereas the second one consists of models that scientists have extracted from collected, natural or synthetic data. Even if one can be confident on the first type of equations, the second one contains modeling errors. Moreover, this second type of equations remains too particular and often fails in describing new experimental results. The vast majority of existing models lack of generality, and therefore must be constantly adapted or enriched to describe new experimental findings. In this work we propose a new method, able to directly link data to computers in order to perform numerical simulations. These simulations will employ axiomatic, universal laws while minimizing the need of explicit, often phenomenological, models. This technique is based on the use of manifold learning methodologies, that allow to extract the relevant information from large experimental datasets.     

A Computational Approach to Finding Causal Economic Laws

This paper states four realities of econometric model buildingand shows that an econometric model can be causal only if theinterpretations given to its coefficients are consistent withthese realities. A numerically stable algorithm for estimatingsuch a model subject to equality and inequality constraints onthe model parameters is presented. This algorithm is designed insuch a way that it can be applied even when the matrix ofobservations on the model's independent variables and thecovariance matrix of the model's errors are deficient in rank.     

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.     

A Secured MultiParty Computational Protocol to Protect Cyber Space

ABSTRACT

In this paper, we show how our secured multiparty computation (SMC) protocols protect the data of an organization during the war from the cyberspace war when a large number of defense units interact with one another, while hiding the identity and computations done by them. SMC is a problem of information security when large organizations interact with one another for huge data sharing and data exchange. It is quite possible that during sharing and exchange, the private data also get hacked. In order to protect and secure the private data, the protocols of SMC need to be deployed in the large computer networks on which the organizations work. The protocols work at the micro-level in terms of cryptography with which the data are encrypted and then shared, while allowing the keys to be used for sharable data while also keeping the keys untouched for private data. At the macro level, multilevel architectures are used for different types of security to be achieved. The computation part of the secured multiparty computation is based on the algorithmic complexity theory. The algorithms realize the protocols in such a way that it is tedious to break (decrypt) the keys to hack the private data.     

A Computational Approach to Etiquette: Operationalizing Brown and Levinson's Politeness Model

A central source of cultural differences is the communication of politeness, which can powerfully affect perception and behavior. Our computational adaptation of a universal theory of human politeness (from Brown and Levinson, 1987) combines culture-specific aspects of social context to generate expectations, score, interpret and recommend polite and impolite behaviors. Tests show this approach could reduce software development costs and increase an intelligent agent's behavior repertoire through the incorporation of modular, cross-cultural etiquette libraries.     

A General and Formal Methodology to Design Stable Nonlinear Fuzzy Control Systems

The price to be paid for the great dynamic richness of nonlinear systems is the lack of a unitary theory that allows control-system design to be tacked in a way that is parallel or analogous to that of linear systems. We propose a general methodology that uses fuzzy logic to systematically and formally synthesize nonlinear control systems, which are stable by design. Although this methodology is based on Lyapunov theory, it avoids searching for Lyapunov functions. This allows the synthesis procedure to be systematic as well as formal and, especially, independent of heuristics. Some examples of nonlinear control are solved in this paper, thus allowing assessment of the proposed methodology.     

A Stable Switched-System Approach to Collision-Free Wheeled Mobile Robot Navigation

This paper presents a novel switched-system approach for obstacle avoidance by mobile robots. This approach does not suffer from common drawbacks of existing methods, such as needing prior knowledge of obstacles, or local minima or chattering in control laws. We define an attractive and an avoidance vector in obstacle-free and obstacle-avoidance regions, respectively. Next, we define an unified velocity vector, which represents either the attractive vector or the avoidance vector, and drives the robot away from the obstacle and ultimately towards the goal. The avoidance vector differs from the repulsive vector commonly used in potential field approaches, rather it is defined always perpendicular to such a repulsive vector and projects positively onto the attractive vector. The unified velocity vector enables the use of a common Lyapunov function in analyzing the stability of the system under arbitrary switching. Novel switching rules are proposed for obstacles that can be well bounded by a circle in the local subset of SE(2). To better handle large, non-circular obstacles, a separate switching signal is proposed. Through the choice of switching rule, we investigate the chattering problem that can hinder some switching controllers. We present two control laws, one with bounded inputs and one with no bounds on inputs. We prove both control schemes are asymptotically stable and guide the robot to the goal while avoiding obstacles. To verify the effectiveness of the proposed approach, as well as compare the control laws and switching rules, several simulations and experiments have been conducted.     

Computational support to record and re-experience visits

Information technology research has mainly focussed on supporting visitors with guides, whilst a lot of opportunities for the development of technology for collecting, manipulating and re-travelling through material from the visits remain unexplored. On the basis of observations from a specific setting, we have developed prototype technology to combine multimedia content with position information. In particular, we developed mobile support to record and organise multimedia using the walked path in order to preserve more of the experience of the visit. We created tools to edit and store multimedia paths. Additional components make it possible to configure a mixed-media environment to navigate a multimedia path, using such physical interfaces as gesturing, and link the recorded media to other artefacts. When discussing field observations of current practices and prototype trials, we investigate what kind of functionality is needed to support the whole activity of collecting, manipulating and playing multimedia content in combination with position information.     

Computational approaches to suspicion in adversarial settings

Intelligence and law enforcement agencies collect large datasets, but have difficulty focusing analyst attention on the most significant records and structures within them. We address this problem using suspicion, which we interpret as relevant anomaly, as the measure associated with data records and individuals. For datasets collected about widespread activities in which the signs of adversarial activity are rare, we suggest ways to build predictive models of suspicion. For datasets collected as the result of lawful interception, we suggest a model of suspicion spreading using the social network implied by the intercepted data.     

Computational Complexity of Certain Problems Related to Carefully Synchronizing Words for Partial Automata and Directing Words for Nondeterministic Automata

We show that the problem of checking careful synchronizability of partial finite automata is PSPACE-complete. Also the problems of checking D ₁-, D ₂-, and D ₃-directability of nondeterministic finite automata are PSPACE-complete; moreover, the restrictions of all these problems to automata with two input letters remain PSPACE-complete.     

A Computational Model to Predict Consumer Behaviour During COVID-19 Pandemic

Computational Economics - The knowledge-based economy has drawn increasing attention recently, particularly in online shopping applications where all the transactions and consumer opinions are...     

A Computational Model for Landmarks Acquisition in Positioning

This paper presents a computational model for landmarks acquisition in vehicle’s positioning. Considering the machine vision, visual attention mechanism of biology, feature-integration theory and the demand of navigation, the computational model is divided into two part: pre-attention state and attention state, and the detailed process includes extraction of feature points, generation of local saliency value, generation of integration saliency value and selection of attention points. At the end of the paper, the proposed computational model is realized through the simulation. What’s more, the robustness of the attention points and the vehicle’s positioning performance when the attention points are used as landmarks are analyzed. Simulation validates that the computational model is availability. Besides, in terms of the performance of the self-attribute and providing positioning reference, the attention points behave well.