Conceptual digital twin modeling based on an integrated five-dimensional framework and TRIZ function model

Digital twin represents a fusion of the informational and physical domains, to bridge the material and virtual worlds. Existing methods of digital twin modeling are mainly based on modular representation, which limits guidance of the modeling process. Such methods do not consider the components or operational rules of the digital twin in detail, thereby preventing designers from applying these methods in their fields. With the increasing application of digital twin to various engineering fields, an effective method of modeling a multi-dimensional digital twin at the conceptual level is required. To such an end, this paper presents a method for the conceptual modeling of a digital twin based on a five-dimensional digital twin framework to represent the complex relationship between digital twin objects and their attributes. The proposed method was used to model the digital twin of an intelligent vehicle at the concept level.     

Evolutionary digital twin: A new approach for intelligent industrial product development

To fulfill increasingly difficult and demanding tasks in the ever-changing complex world, intelligent industrial products are to be developed with higher flexibility and adaptability. Digital twin (DT) brings about a possible means, due to its ability to provide candidate behavior adjustments based on received “feedbacks” from its physical part. However, such candidate adjustments are deterministic, and thus lack of flexibility and adaptability. To address such problem, in this paper an extended concept – evolutionary digital twin (EDT) and an EDT-based new mode for intelligent industrial product development has been proposed. With our proposed EDT, a more precise approximated model of the physical world could be established through supervised learning, based on which the collaborative exploration for optimal policies via parallel simulation in multiple cyberspaces could be performed through reinforcement learning. Hence, more flexibility and adaptability could be brought to industrial products through machine learning (such as supervised learning and reinforcement learning) based self-evolution. As a primary verification of the effectiveness of our proposed approach, a case study has been carried out. The experimental results have well confirmed the effectiveness of our EDT based development mode.     

Assessment with computer agents that engage in conversational dialogues and trialogues with learners

This article describes conversation-based assessments with computer agents that interact with humans through chat, talking heads, or embodied animated avatars. Some of these agents perform actions, interact with multimedia, hold conversations with humans in natural language, and adaptively respond to a person’s actions, verbal contributions, and emotions. Data are logged throughout the interactions in order to assess the individual’s mastery of subject matters, skills, and proficiencies on both cognitive and noncognitive characteristics. There are different agent-based designs that focus on learning and assessment. Dialogues occur between one agent and one human, as in the case of intelligent tutoring systems. Three-party conversations, called trialogues, involve two agents interacting with a human. The two agents can take on different roles (such as tutors and peers), model actions and social interactions, stage arguments, solicit help from the human, and collaboratively solve problems. Examples of assessment with these agent-based environments are presented in the context of intelligent tutoring, educational games, and interventions to help struggling adult readers. Most of these involve assessment at varying grain sizes to guide the intelligent interaction, but conversation-based assessment with agents is also currently being used in high stakes assessments.     

BCD智能功率集成技术简述

简述了BCD智能功率集成技术的构成及其特点,着重介绍了现阶段BCD智能功率集成技术在国内外的发展状况,以及其在军事领域中的广泛用途,简单介绍了BCD智能功率集成技术的未来发展方向以及研究BCD智能功率集成技术的重要性。     

智能家庭网络的实现

介绍了智能家庭网络的概念、要求和结构，指出当前家庭网络存在的问题，提出了相应于OSI模型的家庭网络的分层结构和智能家庭网络的控制平台，剖析了家庭网关结构，并对智能家庭网络的软件结构作了进一步的分析。     

Using Gelfond-Przymusinska’s epistemic specifications to justify (some) heuristic methods used in expert systems and intelligent control

 We show that epistemic specifications, proposed by M. Gelfond and H. Przymusinska in [4], lead to a natural justification of several heuristic methods used in expert systems and in intelligent control. This paper is an overview of several results, some of which have already been published before. In contrast to the original publications, that were targeted specifically towards researchers that design and analyze traditional (degree of certainty, MYCIN-type) expert systems and intelligent control systems, we present the corresponding results in such a way that they become understandable (and hopefully, natural) to the logic programming community as well. The relationship between epistemic specifications and heuristic methods not only makes heuristic methods more reliable, it also adds confidence that the formalism of epistemic specifications, as proposed by M. Gelfond and H. Przymusinska, is an appropriate formalization of knowledge: Indeed, the fact that the language of epistemic specifications, that was originally proposed without any numerical degree of certainty in mind, turns out to be quite consistent with (practically successful) number-valued heuristics, is a strong argument in favor of this language. Received: 18 March 1997/Accepted: 13 May 1997     

基于智能搜索的坦克机动任务规划

在未来高技术局部战争条件下,坦克不得不面临一个动态复杂的战场环境,这就要求坦克能根据战场环境实时地进行任务规划。以单辆坦克在陆地上的自主机动为背景,提出了一种基于智能搜索的坦克机动任务规划方法。在机动任务规划的实施方面,重点描述了两个基本方面：坦克机动环境的评估及坦克机动任务规划的自主实现。构造了一种智能搜索方法,同时应用这种方法提出了实现坦克自主机动的基本思路,并编制应用程序,进行实例检验。结果表明,这种方法科学合理,为坦克机动任务的规划提供了新思路。神经网络评估方法具有普遍意义,能推广应用于坦克其它方面的任务规划。     

基于Agent的智能CBR引导系统的结构设计

描述了一个应用软件Agent技术的智能CBR引导系统的结构设计。系统机架在引导界面Agent里融合了CBR思想。介绍了分布式的引导Agent的交互、引导系统的多媒体界面的设计思想，以及系统在专家系统开发工具上的应用。     

Use of auditory icons as emergency warnings: evaluation within a vehicle collision avoidance application

In the context of emergency warnings, auditory icons, which convey information about system events by analogy with everyday events, have the potential to be understood more quickly and easily than abstract sounds. To test this proposal, an experiment was carried out to evaluate the use of auditory icons for an invehicle collision avoidance application. Two icons, the sounds of a car horn and of skidding tyres, were compared with two conventional warnings, a simple tone and a voice saying ‘ahead’. Participants sat in an experimental vehicle with a road scene projected ahead, and they were required to brake in response to on-screen collision situations and their accompanying warning sounds. The auditory icons produced significantly faster reaction times than the conventional warnings, but suffered from more inappropriate responses, where drivers reacted with a brake press to a non-collision situation. The findings are explained relative to the perceived urgency and inherent meaning of each sound. It is argued that optimal warnings could be achieved by adjusting certain sound attributes of auditory icons, as part of a structured, user-centred design and evaluation procedure.     

Intelligent agents for the management of complexity in multimodal biometrics

Current approaches to personal identity authentication using a single biometric technology are limited, principally because no single biometric is generally considered both sufficiently accurate and user-acceptable for universal application. Multimodal biometrics can provide a more adaptable solution to the security and convenience requirements of many applications. However, such an approach can also lead to additional complexity in the design and management of authentication systems. Additionally, complex hierarchies of security levels and interacting user/provider requirements demand that authentication systems are adaptive and flexible in configuration. In this paper we consider the integration of multimodal biometrics using intelligent agents to address issues of complexity management. The work reported here is part of a major project designated IAMBIC (Intelligent Agents for Multimodal Biometric Identification and Control), aimed at exploring the application of the intelligent agent metaphor to the field of biometric authentication. The paper provides an introduction to a first-level architecture for such a system, and demonstrates how this architecture can provide a framework for the effective control and management of access to data and systems where issues of privacy, confidentiality and trust are of primary concern. Novel approaches to software agent design and agent implementation strategies required for this architecture are also highlighted. The paper further shows how such a structure can define a fundamental paradigm to support the realisation of universal access in situations where data integrity and confidentiality must be robustly and reliably protected .