Iterchanging Discrete Event Simulationprocess Interaction Modelsusing The Web Ontology Language - Owl

Discrete event simulation development requires significant investments in time and resources. Descriptions of discrete event simulation models are associated with world views, including the process interaction orientation. Historically, these models have been encoded using high-level programming languages or special purpose, typically vendor-specific, simulation languages. These approaches complicate simulation model reuse and interchange. The current document-centric World Wide Web is evolving into a Semantic Web that communicates information using ontologies. The Web Ontology Language OWL, was used to encode a Process Interaction Modeling Ontology for Discrete Event Simulations (PIMODES). The PIMODES ontology was developed using ontology engineering processes. Software was developed to demonstrate the feasibility of interchanging models from commercial simulation packages using PIMODES as an intermediate representation. The purpose of PIMODES is to provide a vendor-neutral open representation to support model interchange. Model interchange enables reuse and provides an opportunity to improve simulation quality, reduce development costs, and reduce development times

AFRANCI : multi-layer architecture for cognitive agents

Tese de doutoramento. Engenharia Electrotécnica e de Computadores. Faculdade de Engenharia. Universidade do Porto. 201

An Examination of Personality as a Predictor of Guard Behavior in a Virtual Environment

Military personnel need access to realistic training tools that can provide a safe environment in which to acquire skills that will generalize to real world tasks. A virtual environment (VE) is one such tool. The focus of the present study was to evaluate a VE as a training tool for military guards. The first goal was to examine the potential of VE technology to provide effective training for standing watch at a military checkpoint. The second goal was to study a set of personality traits that might predict performance. Participants completed the NEO Personality Inventory and were trained to perform the role of a military checkpoint guard within a CAVE Automatic Virtual Environment. Trainees interacted with virtual drivers and determined whether drivers exhibited suspicious behavior and met identification requirements for entry onto a fictional base. Results indicated that participants were able to use VE technology to (a) familiarize and immerse themselves in a military checkpoint task, (b) improve performance on training scenarios, and (c) transfer their knowledge from one session to a subsequent session. Examination of personality traits yielded significant results only for openness as a predictor of performance. Collectively, these findings suggest that VEs show potential for scenario-based training

Aerospace medicine and biology: A continuing bibliography with indexes (supplement 323)

This bibliography lists 125 reports, articles and other documents introduced into the NASA Scientific and Technical Information System during April, 1989. Subject coverage includes; aerospace medicine and psychology, life support systems and controlled environments, safety equipment exobiology and extraterrestrial life, and flight crew behavior and performance

Multi-Agents System Approach to Industry 4.0: Enabling Collaboration Considering a Blockchain

Dissertação de Mestrado em Engenharia InformáticaThe evolution of existing technologies and the creation of new ones paved the way for a new revolution in the industrial sector. With the introduction of the existing and new technologies in the manufacturing environment, the industry is moving towards the fourth industrial revolution, called Industry 4.0. The fourth industrial revolution introduces many new components like 3D printing, Internet of things, artificial intelligence, and augmented reality. The automation of the traditional manufacturing processes and the use of smart technology are transforming industries in a more interconnected environment, where there is more transparent information and decentralised decisions. The arrival of Industry 4.0 introduces industries to a new environment, where their manufacturing processes are more evolved, more agile, and with more efficiency. The principles of Industry 4.0 rely on the interconnection of machines, devices, sensors, and people to communicate and connect. The transparency of information guaranties that decision makers are provided with clear and correct information to make informed decisions and the decentralisation of decisions will create the ability for machines and systems to make decisions on their own and to perform tasks autonomously. Industry 4.0 is making manufacturing processes more agile and efficient, but due to the fast pace of trends and the shift from the traditional mass production philosophy towards the mass customisation, following the Industry 4.0 guidelines might not be enough. The mass customisation paradigm was created from the desire that customers have in owning custom made products and services, tailor made to their needs. The idea to perform small tweaks in a product to face the needs of a consumer group, keeping the production costs like the ones from the mass production, without losing efficiency in the production. This paradigm poses great challenges to the industries, since they must be able to always have the capability to answer the demands that may arise from the preparation and production of personalised products and services. In the meantime, organisations will try to increasingly mark its position in the market, with competition getting less relevant and with different organisations worrying less with their performance on an individual level and worrying more about their role in a supply chain. The need for an improved collaboration with Industry 4.0 is the motivation for the model proposed in this work. This model, that perceives a set of organisations as entities in a network that want to interact with each other, is divided into two parts, the knowledge representation and the reasoning and interactions. The first part relies on the Blockchain technology to securely store and manage all the organisation transactions and data, guaranteeing the decentralisation of information and the transparency of the transactions. Each organisation has a public and private profile were the data is stored to allow each organisation to evaluate the others and to allow each organisation to be evaluated by the remainder of the organisations present in the network. Furthermore, this part of the model works as a ledger of the transactions made between the organisations, since that every time two organisations negotiate or interact in any way, the interaction is getting recorded. The ledger is public, meaning that every organisation in the network can view the data stored. Nevertheless, an organisation will have the possibility, in some situations, to keep transactions private to the organisations involved. Despite the idea behind the model is to promote transparency and collaboration, in some selected occasions organisations might want to keep transactions private from the other participants to have some form of competitive advantage. The knowledge representation part also wants to provide security and trust to the organisation that their data will be safe and tamper proof. The second part, reasoning and interactions, uses a Multi-Agent System and has the objective to help improve decision-making. Imagining that one organisation needs a service that can be provided by two other organisations, also present in the network, this part of the model is going to work towards helping the organisations choose what is the best choice, given the scenario and data available. This part of the model is also responsible to represent every organisation present in the network and when organisations negotiate or interact, this component is also going to handle the transaction and communicate the data to the first part of the model.A constante evolução de tecnologias atuais e a criação de novas tecnologias criou as condições necessárias para a existência de uma nova revolução industrial. Com a evolução de dispositivos móveis e com a chegada de novas tecnologias e ferramentas que começaram a ser introduzidas em ambiente industrial, como a impressão 3D, internet das coisas, inteligência artificial, realidade aumentada, entre outros, a industria conseguiu começar a explorar novas tecnologias e automatizar os seus processos de fabrico tradicionais, movendo as industrias para a quarta revolução industrial, conhecida por Industria 4.0. A adoção dos princípios da Indústria 4.0 levam as indústrias a evoluir os seus processos e a ter uma maior e melhor capacidade de produção, uma vez que as mesmas se vão tornar mais ágeis e introduzir melhorias nos seus ambientes de produção. Uma dessas melhorias na questão da interoperabilidade, com máquinas, sensores, dispositivos e pessoas a comunicarem entre si. A transparência da informação vai levar a uma melhor interpretação dos dados para efetuar decisões informadas, com os sistemas a recolher cada vez mais dados e informação dos diferentes pontos do processo de manufatura. (...

The Post‐Modern Transcendental of Language in Science and Philosophy

In this chapter I discuss the deep mutations occurring today in our society and in our culture, the natural and mathematical sciences included, from the standpoint of the “transcendental of language”, and of the primacy of language over knowledge. That is, from the standpoint of the “completion of the linguistic turn” in the foundations of logic and mathematics using Peirce’s algebra of relations. This evolved during the last century till the development of the Category Theory as universal language for mathematics, in many senses wider than set theory. Therefore, starting from the fundamental M. Stone’s representation theorem for Boolean algebras, computer scientists developed a coalgebraic first-order semantics defined on Stone’s spaces, for Boolean algebras, till arriving to the definition of a non-Turing paradigm of coalgebraic universality in computation. Independently, theoretical physicists developed a coalgebraic modelling of dissipative quantum systems in quantum field theory, interpreted as a thermo-field dynamics. The deep connection between these two coalgebraic constructions is the fact that the topologies of Stone spaces in computer science are the same of the C*-algebras of quantum physics. This allows the development of a new class of quantum computers based on coalgebras. This suggests also an intriguing explanation of why one of the most successful experimental applications of this coalgebraic modelling of dissipative quantum systems is just in cognitive neuroscience