32 research outputs found

    Performance Analysis of Encryption Capabilities of ARM-based Single Board Microcomputers

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    In the few years since the Raspberry Pi was released in 2012, countless microcomputers based on the ARM architecture have been introduced.Their small size, high performance relative to their power consumption, and the ability to run the popular Linux operating system make them ideal for a wide range of tasks. Information security is an area of particular importance. Different encryption and encoding algorithms play an important role in almost all areas of information security. However, these algorithms are very computationally intensive, so it is important to investigate which microcomputers can be used for these tasks, and under which trade-offs. The performance of ten different microcomputers is investigated and presented for the application of common symmetric and public-key encryption and decryption, digest creation and message authentication protocols, such as RSA, AES, HMAC, MD5, SHA. Reliable encryption requires the generation of reliable (pseudo)random numbers (Cryptographically Secure Random Numbers, CSRN), and microcomputers based on ARM SoCs usually have hardware implemented (pseudo)random number generators. The applicability of the random number generat er generators. The applicability of the random number generators of different microcomputers are investigated and presented; test methoods are described , and recommendations are made

    A Plug and Produce Framework for Industrial Collaborative Robots

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    Collaborative robots are today ever more interesting in response to the increasing need for agile manufacturing equipment. Contrary to traditional industrial robots, collaborative robots are intended for working in dynamic environments alongside the production staff. To cope with the dynamic environment and workflow, new configuration and control methods are needed compared to those of traditional industrial robots. The new methods should enable shop floor operators to reconfigure the robot. This article presents a plug and produce framework for industrial collaborative robots. The article focuses on the control framework enabling quick and easy exchange of hardware modules as an approach to achieving plug and produce. To solve this, an agent-based system is proposed building on top of the robot operating system. The framework enables robot operating system packages to be adapted into agents and thus supports the software sharing of the robot operating system community. A clear separation of the hardware agents and the higher level task control is achieved through standardization of the functional interface, a standardization maintaining the possibility of specialized function features. A feasibility study demonstrates the validity of the framework through a series of reconfigurations performed on a modular collaborative robot. </jats:p

    Mars Atmospheric Entry Integrated Navigation with Partial Intermittent Measurements

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    Signal degradation suffered by the vehicle is a combination brownout and blackout during Mars atmospheric entry. The communications brownout means that signal fades and blackout means that the signal is lost completely. The communications brownout and blackout periods are analyzed and predicted with an altitude and velocity profiles. In the brownout period, the range measurements between the vehicle and the orbiters are modeled as intermittent measurements with the radio signal arrival probabilities, which are distributed as a Rayleigh distribution of the electron number density around the entry vehicle. A new integrated navigation strategy during the Mars atmospheric entry phase is proposed to consider the probabilities of the radio measurements in the communications brownout and blackout periods under the IMU/beacon scenario based on the information filter with intermittent measurements. Numerical navigation simulations are designed to show the performance of the proposed navigation strategy under the integrated navigation scenario

    From Human-Systems Integration to Human-Systems Inclusion for Use-Centred Inclusive Manufacturing Control Systems

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    The paper discusses about human-systems inclusion as a new way to take into account human factors on systems engineering. This process applies not only principles from human-supported by automation but also those on automation-supported by human to improve autonomy between humans and machines and autonomy between people. The main concern of human-systems integration is the consideration of a low number of future users in the design process or of the feedback of a majority of users in the evaluation process. Human-system inclusion considers that the system has to take into account and adapt to all users whatever their social, economic, physical or cognitive state, or disability. The concept of “human in the loop” or of “human touch” is usually limited to the definition of the role of humans and machines. It does not consider dynamic variability of users and systems abilities, and anticipate the feasible development of autonomous machines by reducing progressively human engagement in the control and supervisory loop. The paper presents both integration and inclusion concepts for Industry 4.0, and then suggests some challenging perspectives for use-centred inclusive manufacturing control systems in terms of opportunities and threats

    An Approach to Automatically Distribute and Access Knowledge within Networked Embedded Systems in Factory Automation

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    This thesis presents a novel approach for automatically distribute and access knowledge within factory automation systems built by networked embedded systems. Developments on information, communication and computational technologies are making possible the distribution of tasks within different control resources, resources which are networked and working towards a common objective optimizing desired parameters. A fundamental task for introducing autonomy to these systems, is the option for represent knowledge, distributed within the automation network and to ensure its access by providing access mechanisms. This research work focuses on the processes for automatically distribute and access the knowledge.Recently, the industrial world has embraced service-oriented as architectural (SOA) patterns for relaxing the software integration costs of factory automation systems. This pattern defines a services provider offering a particular functionality, and service requesters which are entities looking for getting their needs satisfied. Currently, there are a few technologies allowing to implement a SOA solution, among those, Web Technologies are gaining special attention for their solid presence in other application fields. Providers and services using Web technologies for expressing their needs and skills are called Web Services. One of the main advantage of services is the no need for the service requester to know how the service provider is accomplishing the functionality or where the execution of the service is taking place. This benefit is recently stressed by the irruption of Cloud Computing, allowing the execution of certain process by the cloud resources.The caption of human knowledge and the representation of that knowledge in a machine interpretable manner has been an interesting research topic for the last decades. A well stablished mechanism for the representation of knowledge is the utilization of Ontologies. This mechanism allows machines to access that knowledge and use reasoning engines in order to create reasoning machines. The presence of a knowledge base allows as clearly the better identification of the web services, which is achievable by adding semantic notations to the service descriptors. The resulting services are called semantic web services.With the latest advances on computational resources, system can be built by a large number of constrained devices, yet easily connected, building a network of computational nodes, nodes that will be dedicated to execute control and communication tasks for the systems. These tasks are commanded by high level commanding systems, such as Manufacturing Execution Systems (MES) and Enterprise Resource Planning (ERP) modules. The aforementioned technologies allow a vertical approach for communicating commanding options from MES and ERP directly to the control nodes. This scenario allows to break down monolithic MES systems into small distributed functionalities, if these functionalities use Web standards for interacting and a knowledge base as main input for information, then we are arriving to the concept of Open KnowledgeDriven MES Systems (OKD-MES).The automatic distribution of the knowledge base in an OKD-MES mechanism and the accomplishment of the reasoning process in a distributed manner are the main objectives for this research. Thus, this research work describes the decentralization and management of knowledge descriptions which are currently handled by the Representation Layer (RPL) of the OKD-MES framework. This is achieved within the encapsulation of ontology modules which may be integrated by a distributed reasoning process on incoming requests. Furthermore, this dissertation presents the concept, principles and architecture for implementing Private Local Automation Clouds (PLACs), built by CPS.The thesis is an article thesis and is composed by 9 original and referred articles and supported by 7 other articles presented by the author

    µG2-ELM: an upgraded implementation of µ G-ELM

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    µG-ELM is a multiobjective evolutionary algorithm which looks for the best (in terms of the MSE) and most compact artificial neural network using the ELM methodology. In this work we present the µG2-ELM, an upgraded version of µG-ELM, previously presented by the authors. The upgrading is based on three key elements: a specifically designed approach for the initialization of the weights of the initial artificial neural networks, the introduction of a re-sowing process when selecting the population to be evolved and a change of the process used to modify the weights of the artificial neural networks. To test our proposal we consider several state-of-the-art Extreme Learning Machine (ELM) algorithms and we confront them using a wide and well-known set of continuous, regression and classification problems. From the conducted experiments it is proved that the µG2-ELM shows a better general performance than the previous version and also than other competitors. Therefore, we can guess that the combination of evolutionary algorithms with the ELM methodology is a promising subject of study since both together allow for the design of better training algorithms for artificial neural networks
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