Design and Implementation Issues in a Contemporary Remote Laboratory Architecture

MIT has been developing the iLab Shared Architecture (ISA) for remote laboratories since 1998. It has been based around concepts and implementation issues that were in vogue at the time. Recent developments in network architectures and implementation techniques offer opportunities to re-examine the original assumptions, and to contemplate expanded objectives. This paper explores one possible future being explored at The University of Queensland for a remote laboratory architecture based upon the original ideals of MIT’s ISA

Analysis and Development of Instrument Software Paradigms: Conception and Implementation of a New Instrument Control and Data Acquisition System, Proven by Material Scientific Applications

During the last 50 years, the quality of analysis methods in many scientific disciplines has been enhanced by electronic applications, automation and data processing. While the features, performance and usability of these processes have been continually enhanced, it is conspicuous that the majority of institutes operate own proprietary software. This situation arises for both historical and financial reasons, plus a wish to retain autonomy fuelled by the requirement for a system that remains compatible with both new and legacy hardware. This thesis reviews the commonly used scientific software systems and their stakeholders and tries to identify generic problems. The demands on instrument systems are summarized by a requirement specification. Based on these requirements, a basic concept is developed that reflects the current state-of-the art in software design and which may provide a blueprint for instrument system architectures. The results are used to create a proof-of-concept implementation. Core to this approach is an application server that comes with a container, which makes use of the Inversion-of-Control pattern to loosely couple and execute components. These do not need to implement fixed interfaces and are thus decoupled from a specific use-case. Components can, for example, be proxies that control and acquire data from legacy hardware, perform calculations, provide a human-machine interface or act as storage. They are dynamically wired to experiments using XML-based Assembly files. Both Assemblies and Components can be published using a central store on a collaboration platform and shared by the community. This increases reusability and allows the use of existing Assemblies with new hardware by simply replacing the hardware proxy modules. Example components have been provided for the access to legacy and new instrument hardware, the storage of results in the NeXus format, data reduction, simulation with McStas, the execution of customizable scans and the visualization of data

NASA Tech Briefs, August 1995

There is a special focus on computer graphics and simulation in this issue. Topics covered include : Electronic Components and Circuits; Electronic Systems; Physical Sciences; Materials; Computer programs, Mechanics; Machinery; Fabrication Technology; and Mathematics and Information Sciences. There is a section on for Laser Technology, which includes a feature on Moving closer to the suns power

Intelligent maintenance management in a reconfigurable manufacturing environment using multi-agent systems

Thesis (M. Tech.) -- Central University of Technology, Free State, 2010Traditional corrective maintenance is both costly and ineffective. In some situations it is more cost effective to replace a device than to maintain it; however it is far more likely that the cost of the device far outweighs the cost of performing routine maintenance. These device related costs coupled with the profit loss due to reduced production levels, makes this reactive maintenance approach unacceptably inefficient in many situations. Blind predictive maintenance without considering the actual physical state of the hardware is an improvement, but is still far from ideal. Simply maintaining devices on a schedule without taking into account the operational hours and workload can be a costly mistake. The inefficiencies associated with these approaches have contributed to the development of proactive maintenance strategies. These approaches take the device health state into account. For this reason, proactive maintenance strategies are inherently more efficient compared to the aforementioned traditional approaches. Predicting the health degradation of devices allows for easier anticipation of the required maintenance resources and costs. Maintenance can also be scheduled to accommodate production needs. This work represents the design and simulation of an intelligent maintenance management system that incorporates device health prognosis with maintenance schedule generation. The simulation scenario provided prognostic data to be used to schedule devices for maintenance. A production rule engine was provided with a feasible starting schedule. This schedule was then improved and the process was determined by adhering to a set of criteria. Benchmarks were conducted to show the benefit of optimising the starting schedule and the results were presented as proof. Improving on existing maintenance approaches will result in several benefits for an organisation. Eliminating the need to address unexpected failures or perform maintenance prematurely will ensure that the relevant resources are available when they are required. This will in turn reduce the expenditure related to wasted maintenance resources without compromising the health of devices or systems in the organisation

The Sensor Network Workbench: Towards Functional Specification, Verification and Deployment of Constrained Distributed Systems

As the commoditization of sensing, actuation and communication hardware increases, so does the potential for dynamically tasked sense and respond networked systems (i.e., Sensor Networks or SNs) to replace existing disjoint and inflexible special-purpose deployments (closed-circuit security video, anti-theft sensors, etc.). While various solutions have emerged to many individual SN-centric challenges (e.g., power management, communication protocols, role assignment), perhaps the largest remaining obstacle to widespread SN deployment is that those who wish to deploy, utilize, and maintain a programmable Sensor Network lack the programming and systems expertise to do so. The contributions of this thesis centers on the design, development and deployment of the SN Workbench (snBench). snBench embodies an accessible, modular programming platform coupled with a flexible and extensible run-time system that, together, support the entire life-cycle of distributed sensory services. As it is impossible to find a one-size-fits-all programming interface, this work advocates the use of tiered layers of abstraction that enable a variety of high-level, domain specific languages to be compiled to a common (thin-waist) tasking language; this common tasking language is statically verified and can be subsequently re-translated, if needed, for execution on a wide variety of hardware platforms. snBench provides: (1) a common sensory tasking language (Instruction Set Architecture) powerful enough to express complex SN services, yet simple enough to be executed by highly constrained resources with soft, real-time constraints, (2) a prototype high-level language (and corresponding compiler) to illustrate the utility of the common tasking language and the tiered programming approach in this domain, (3) an execution environment and a run-time support infrastructure that abstract a collection of heterogeneous resources into a single virtual Sensor Network, tasked via this common tasking language, and (4) novel formal methods (i.e., static analysis techniques) that verify safety properties and infer implicit resource constraints to facilitate resource allocation for new services. This thesis presents these components in detail, as well as two specific case-studies: the use of snBench to integrate physical and wireless network security, and the use of snBench as the foundation for semester-long student projects in a graduate-level Software Engineering course

Improving Laboratory Learning Outcomes: An Investigation Into the Effect of Contextualising Laboratories Using Virtual Worlds and Remote Laboratories.

This thesis presents research into improving learning outcomes in laboratories. It was hypothesised that domain specific context can aid students in understanding the relationship between a laboratory (as a proxy for reality), the theoretical model being investigated within the laboratory activity and the real world. Specifically, the research addressed whether adding domain context to a laboratory activity could improve students' ability to identify the strengths and limitations of models as predictors of real-world behaviour. The domain context was included in a laboratory activity with the use of a remote radiation lab set within a context-rich virtual world. The empirical investigation used a pretest-posttest control group design to assess whether there was a statistically significant difference in the learning outcome between a treatment group who completed the lab in a contextualised virtual world, and the control group who conducted the activity in an empty virtual world. The results showed that there were no statistically significant differences between the groups and therefore there are cases where contextualising a laboratory activity will not have an effect on students' ability to identify the strengths and limitations of models as predictors of real-world behaviour. This research postulates that previous exposure to the model, the level of awareness students had of the context and the lack time available for reflection may have masked or attenuated the effect of the context. This research has contributed a framework for the analysis and design of domain context in laboratory activities, and an interface for integrating iLabs laboratories into the Open Wonderland virtual world. It has explicitly clarified the relationship between context, labs, models and the real world. Most significantly, this research has contributed knowledge to the field of laboratory learning outcomes and the understanding of how domain context affects laboratory activities

Building the Future Internet through FIRE

The Internet as we know it today is the result of a continuous activity for improving network communications, end user services, computational processes and also information technology infrastructures. The Internet has become a critical infrastructure for the human-being by offering complex networking services and end-user applications that all together have transformed all aspects, mainly economical, of our lives. Recently, with the advent of new paradigms and the progress in wireless technology, sensor networks and information systems and also the inexorable shift towards everything connected paradigm, first as known as the Internet of Things and lately envisioning into the Internet of Everything, a data-driven society has been created. In a data-driven society, productivity, knowledge, and experience are dependent on increasingly open, dynamic, interdependent and complex Internet services. The challenge for the Internet of the Future design is to build robust enabling technologies, implement and deploy adaptive systems, to create business opportunities considering increasing uncertainties and emergent systemic behaviors where humans and machines seamlessly cooperate