Cyber Physical Systems Oriented Robot Development Platform

AbstractThe development of systems, of various levels of complexity that can integrate physical with virtual components has become a priority for research in the context of emerging paradigms such as Cyber-Physical Systems or Internet for the Future. The authors propose a Robotic Development Platform architecture that integrates principles of Cyber-Physical Systems. The proposed architecture, is scalable, by facilitating the integration of different existing development and simulation tools and will allow robot systems to be tested in different environments, with different characteristics, and facilitate the integration of real world simulation with virtual environment simulation

A cyber-physical systems approach to cognitive enterprise

Internet of Things and Cyber-Physical Systems are paradigms that have an important influence on enterprise systems architecture and implementation. The Cognitive Manufacturing as well as the Cognitive Enterprise are emerging models, related to these paradigms, that intend to redesign in the Enterprise Information Model by integrating new information processing and problem-solving methods. This paper intends to analyses and discuss Cognitive Enterprise enablers and principles considering an approach based on models of human brain perception-reasoning-learning processes

Fostering Cyber-Physical Social Systems through an Ontological Approach to Personality Classification Based on Social Media Posts

The exponential increase in social networks has led to emergent convergence of cyber-physical systems (CPS) and social computing, accelerating the creation of smart communities and smart organizations and enabling the concept of cyber-physical social systems. Social media platforms have made a significant contribution to what we call human behavior modeling. This paper presents a novel approach to developing a users’ segmentation tool for the Romanian language, based on the four DISC personality types, based on social media statement analysis. We propose and design the ontological modeling approach of the specific vocabulary for each personality and its mapping with text from posts on social networks. This research proposal adds significant value both in terms of scientific and technological contributions (by developing semantic technologies and tools), as well as in terms of business, social and economic impact (by supporting the investigation of smart communities in the context of cyber-physical social systems). For the validation of the model developed we used a dataset of almost 2000 posts retrieved from 10 social medial accounts (Facebook and Twitter) and we have obtained an accuracy of over 90% in identifying the personality profile of the users

Neuro-inspired Framework for Cognitive Manufacturing Control

There are currently certain categories of manufacturing enterprises whose structure, organization and operating context have an extremely high degree of complexity, especially due to the way in which their various components interact and influence each other. For them, a series of paradigms have been developed, including intelligent manufacturing, smart manufacturing, cognitive manufacturing; which are based equally on information and knowledge management, management and interpretation of data flows and problem solving approaches. This work presents a new vision regarding the evolution of the future enterprise based on concepts and attributes acquired from the field of biology. Our approach addresses in a systemic manner the structural, functional, and behavioral aspects of the enterprise, seen as a complex dynamic system. In this article we are proposing an architecture and management methodology based on the human brain, where the problem solving is achieved by Perception – Memory – Learning and Behavior Generation mechanisms. In order to support the design of such an architecture and to allow a faster learning process, a software modeling and simulation platform was developed and is briefly presented

Retracted: Predictive maintenance and robotic system design

This article was withdrawn and retracted by the Journal of Fundamental and Applied Sciences and has been removed from AJOL at the request of the journal Editor in Chief and the organisers of the conference at which the articles were presented (www.iccmit.net). Please address any queries to [email protected]

An Hybrid Approach for Urban Traffic Prediction and Control in Smart Cities

Smart cities are complex, socio-technological systems built as a strongly connected System of Systems, whose functioning is driven by human–machine interactions and whose ultimate goals are the well-being of their inhabitants. Consequently, controlling a smart city is an objective that may be achieved by using a specific framework that integrates algorithmic control, intelligent control, cognitive control and especially human reasoning and communication. Among the many functions of a smart city, intelligent transportation is one of the most important, with specific restrictions and a high level of dynamics. This paper focuses on the application of a neuro-inspired control framework for urban traffic as a component of a complex system. It is a proof of concept for a systemic integrative approach to the global problem of smart city management and integrates a previously designed urban traffic control architecture (for the city of Bucharest) with the actual purpose of ensuring its proactivity by means of traffic flow prediction. Analyses of requirements and methods for prediction are performed in order to determine the best way for fulfilling the perception function of the architecture with respect to the traffic control problem definition. A parametric method and an AI-based method are discussed in order to predict the traffic flow, both in the short and long term, based on real data. A brief comparative analysis of the prediction performances is also presented

A Perceptive Interface for Intelligent Cyber Enterprises

Large scale, complex, networked enterprises, as may be considered (trans)national energy systems, multi-national manufacturing enterprises, smart cities a.s.o. are structures that can be characterized as systems of systems (SoS) and, as such, require specific modelling paradigms and control architectures to ensure their successful running. Their main characteristic is the necessity of solving practically one-of-a-kind problems with respect to the external context and internal configuration, thus dealing with dynamically evolving flows of data and information. The paper introduces the concept of intelligent cyber-enterprise, as an integrating paradigm that uses information and knowledge dynamics, in order to model and control SoS, especially focusing on the importance of appropriately adapt external and internal perception of an enterprise through a new generation of sensorial systems—the perceptive interfaces. The authors analyze sensing and perception in relation to intelligent cyber enterprise model and propose an implementation for a perceptive system interface

Decision-Making System and Operational Risk Framework for Hierarchical Production Planning

[EN] Business processes are designed to perform in an ideal environment where incidents that disturb regular working processes do not exist. However, this environment is fairly idealist, since business processes are affected by many different events, forcing changes in plans or solutions that allow for business continuity. In the context of hierarchical production planning, unexpected events, such as the lack of availability of materials, rush orders and faulty machines; have to be managed efficiently because they represent a risk for business continuity, depending on their impact and duration. In this sense, operational risk management, supported by decision support systems, allow enterprises to have contingency plans that show the decision maker different ways to manage the specific event through rules that check the event's impact and analyse provenance data stored in data warehouse. In the on-going research of inter-enterprise architecture, it has been labelled its main elements: framework, methodology and modelling languages. This paper proposes a decision-making and operational risk framework, looking for solutions that facilitate the decision-making process under the arrival of unexpected events that affect hierarchical production planning.This paper has been developed as a result of a mobility stay funded by the Erasmus Mundus Programme of the European Commission under the Transatlantic Partnership for Excellence in Engineering - TEE Project and it has been funded by the Sectorial Operational Programme Human Resources Development 2007-2013 of the Ministry of European Funds through the Financial Agreement POSDRU/159/1.5/S/132397, Romania.Vargas-López, AJ.; Day, S.; Boza Garcia, A.; Ortiz Bas, Á.; Ludascher, B.; Sacala, IS.; Moisescu, MA. (2016). Decision-Making System and Operational Risk Framework for Hierarchical Production Planning. Journal of Control Engineering and Applied Informatics. 18(3):72-81. http://hdl.handle.net/10251/80102S728118