Co-universal algebras associated to product systems, and gauge-invariant uniqueness theorems

Let X be a product system over a quasi-lattice ordered group. Under mild hypotheses, we associate to X a C*-algebra which is co-universal for injective Nica covariant Toeplitz representations of X which preserve the gauge coaction. Under appropriate amenability criteria, this co-universal C*-algebra coincides with the Cuntz-Nica-Pimsner algebra introduced by Sims and Yeend. We prove two key uniqueness theorems, and indicate how to use our theorems to realise a number of reduced crossed products as instances of our co-universal algebras. In each case, it is an easy corollary that the Cuntz-Nica-Pimsner algebra is isomorphic to the corresponding full crossed product.Comment: 40 pages, 2 figures; v2: minor changes to the introduction, references added and update

Wireless Communication in Process Control Loop: Requirements Analysis, Industry Practices and Experimental Evaluation

Wireless communication is already used in process automation for process monitoring. The next stage of implementation of wireless technology in industrial applications is for process control. The need for wireless networked control systems has evolved because of the necessity for extensibility, mobility, modularity, fast deployment, and reduced installation and maintenance cost. These benefits are only applicable given that the wireless network of choice can meet the strict requirements of process control applications, such as latency. In this regard, this paper is an effort towards identifying current industry practices related to implementing process control over a wireless link and evaluates the suitability of ISA100.11a network for use in process control through experiments

Research challenges in applying intelligent wireless sensors in the oil, gas and resources industries

The monitoring of oil, gas and resources plant performance and the operational environment through sensors allows for greater insight into potential safety problems and operational requirements. Such solutions promote a safe and healthy work environment for all stakeholders and optimized operations. Intelligent techniques and the monitoring of key historical operational properties can be used to realize certain characteristics and patterns in operation data. Such solutions may enhance operational visualization, foresight, forecasting and maintenance schedules for effective and efficient operation and maintenance. This optimizes plant safety, production, turnarounds, shutdowns and maintenance and improves error tolerance and recovery.However, the development of robust devices that are able to perform in these remote and hostile requirements along with the intelligent solutions to structure, store, process and retrieve this information are difficult to realize. This paper investigates the use of wireless sensors and the related intelligent solutions in the oil, gas and resource industries

Taxonomy of Wireless Sensor Network Cyber Security Attacks in the Oil and Gas Industries

The monitoring of oil and gas plants using sensors allows for greater insight into safety and operational performance. However, as a result of strict installation regulations of powered sensors near oil and gas fittings, the introduction of new wired sensors to optimize end-of-lifecycle plants has been expensive, complex and time consuming. Recent advances in wireless technology have enabled low-cost Wireless Sensor Networks (WSNs) capable of robust and reliable communication. However, the critical WSN security issues have not been sparsely investigated. The goal of this paper is to define the security issues surrounding WSNs with specific focus on the oil and gas industry

Applications of Wireless Sensor Networks in the Oil, Gas and Resources Industries

The paper provides a study on the use of Wireless Sensor Networks (WSNs) in refineries, petrochemicals, underwater development facilities, and oil and gas platforms. The work focuses on networks that monitor the production process, to either prevent or detect health and safety issues or to enhance production. WSN applications offer great opportunities for production optimization where the use of wired counterparts may prove to be prohibitive. They can be used to remotely monitor pipelines, natural gas leaks, corrosion, H2S, equipment condition, and real-time reservoir status. Data gathered by such devices enables new insights into plant operation and innovative solutions that aids the oil, gas and resources industries in improving platform safety, optimizing operations, preventing problems, tolerating errors, and reducing operating costs. In this paper, we survey a number of WSN applications in oil, gas and resources industry operations

The role of wireless sensor networks (WSNs) in industrial oil and gas condition monitoring

Wireless sensor networks have a vast amount of applications including environmental monitoring, military, ecology, agriculture, inventory control, robotics and health care. This paper focuses on the area of monitoring and protection of oil and gas operations using wireless sensor networks that are optimized to decrease installation, and maintenance cost, energy requirements, increase reliability and improve communication efficiency. In addition, simulation experiments using the proposed model are presented. Such models could provide new tools for research in predictive maintenance and condition-based monitoring of factory machinery in general and for “open architecture machining systems” in particular. Wireless sensing no longer needs to be relegated to locations where access is difficult or where cabling is not practical. Wireless condition monitoring systems can be cost effectively implemented in extensive applications that were historically handled by running routes with data collectors.The result would be a lower cost program with more frequent data collection, increased safety, and lower spare parts inventories. Facilities would be able to run leaner because they will have more confidence in their ability to avoid downtime

Temporal non-independence of foraging dive and surface duration sequences in the European shag Gulosus aristotelis

Studies of foraging behaviour and respiratory physiology in breath-holding divers often assume that each dive cycle (dive plus surface duration) is physiologically and ecologically independent within a series (or "bout ") of sequential dives. We tested this assumption using time depth recorders and GPS data for more than 42,000 dives in 1289 bouts by 39 pairs of male and female European shags (Gulosus aristotelis) provisioning nestlings. We found distinct patterns of temporal autocorrelation over several dives within bouts, but this was driven mainly by consecutive dives of the same type, that is, runs of V-shaped (presumably prey searching) versus U-shaped (presumably active hunting) dives. We found no evidence of cumulative physiological effects (i.e. fatigue and/or lowered body temperature) across dives within a bout. However, within-individual variation in dive behaviour revealed complex interactions. Longer bouts were associated with more V-shaped dives, including more and longer runs of V-shaped dives. Meanwhile, more U-shaped dives and longer runs of U-shaped dives acted as limiting factors to bout lengths, with longer bouts being associated with more U-shaped dives only later in the bout. Interactions between bout length and body mass, and between dive order within the bout and body mass, also suggested various size-specific patterns in the temporal distribution of U-shaped dives. Long bouts and bouts ending in longer runs of V-shaped dives were more likely to indicate the termination of foraging activity. However, neither dive type nor bout length predicted whether individuals subsequently (i) stayed to forage in the same location or (ii) moved to a new location to continue foraging within the same trip from the nest. European shags therefore showed temporal non-independence across successive dive cycles and successive bouts of dives, likely as a result of temporal and spatial variation in prey availabilities rather than cumulative physiological effects that might contravene the assumptions in models of optimal dive behaviour