Recommendations for in-situ data Near Real Time Quality Control

With the construction of operational oceanography systems, the need for real-time has become more and more important. A lot of work had been done in the past, within National Data Centres (NODC) and International Oceanographic Data and Information Exchange (IODE) to standardise delayed mode quality control procedures. Concerning such quality control procedures applicable in real-time (within hours to a maximum of a week from acquisition), which means automatically, some recommendations were set up for physical parameters but mainly within projects without consolidation with other initiatives. During the past ten years the EuroGOOS community has been working on such procedures within international programs such as Argo, OceanSites or GOSUD, or within EC projects such as Mersea, MFSTEP, FerryBox, ECOOP, and MyOcean. In collaboration with the FP7 SeaDataNet project that is standardizing the delayed mode quality control procedures in NODCs, and MyOcean GMES FP7 project that is standardizing near real time quality control procedures for operational oceanography purposes, the DATA-MEQ working group decided to put together this document to summarize the recommendations for near real-time QC procedures that they judged mature enough to be advertised and recommended to EuroGOOS.

A mitochondrial species identification assay for Australian blacktip sharks (Carcharhinus tilstoni, C. limbatus and C. amblyrhynchoides) using real-time PCR and high-resolution melt analysis

Tropical Australian shark fisheries target two morphologically indistinguishable blacktip sharks, the Australian blacktip (Carcharhinus tilstoni) and the common blacktip (C. limbatus). Their relative contributions to northern and eastern Australian coastal fisheries are unclear because of species identification difficulties. The two species differ in their number of precaudal vertebrae, which is difficult and time consuming to obtain in the field. But, the two species can be distinguished genetically with diagnostic mutations in their mitochondrial DNA ND4 gene. A third closely related sister species, the graceful shark C. amblyrhynchoides, can also be distinguished by species-specific mutations in this gene. DNA sequencing is an effective diagnostic tool, but is relatively expensive and time consuming. In contrast, real-time high-resolution melt (HRM) PCR assays are rapid and relatively inexpensive. These assays amplify regions of DNA with species-specific genetic mutations that result in PCR products with unique melt profiles. A real-time HRM PCR species-diagnostic assay (RT-HRM-PCR) has been developed based on the mtDNA ND4 gene for rapid typing of C. tilstoni, C. limbatus and C. amblyrhynchoides. The assay was developed using ND4 sequences from 66 C. tilstoni, 33. C. limbatus and five C. amblyrhynchoides collected from Indonesia and Australian states and territories; Western Australia, the Northern Territory, Queensland and New South Wales. The assay was shown to be 100% accurate on 160 unknown blacktip shark tissue samples by full mtDNA ND4 sequencing.

“Deep-Arvor”: A new profiling float to extend the Argo observations down to 4000m depth.

The international Argo program, consisting of a global array of more than 3000 free-drifting profiling floats, has now been monitoring the upper 2000 meters of the ocean for several years. One of its main proposed evolutions is to be able to reach the deeper ocean in order to better observe and understand the key role of the deep ocean in the climate system. For this purpose, Ifremer has designed the new “Deep-Arvor” profiling float: it extends the current operational depth down to 4000 meters, and measures temperature and salinity for up to 150 cycles with CTD pumping continuously and 200 cycles in spot sampling mode. High resolution profiles (up to 2000 points) can be transmitted and data are delivered in near real time according to Argo requirements. Deep-Arvor can be deployed everywhere at sea without any pre-ballasting operation and its light weight (~ 26kg) makes its launching easy. Its design was done to target a cost effective solution. Predefined spots have been allocated to add an optional oxygen sensor and a connector for an extra sensor. Extensive laboratory tests were successful. The results of the first at sea experiments showed that the expected performances of the operational prototypes had been reached (i.e. to perform up to 150 cycles). Meanwhile, the industrialization phase was completed in order to manufacture the Deep-Arvor float for the pilot experiment in 2015. In this paper, we detail all the steps of the development work and present the results from the at sea experiments.

Uma arquitetura de referência para o processamento distribuído de stream de dados em soluções analíticas de near real-time

Dissertação (mestrado)—Universidade de Brasília, Faculdade de Tecnologia, Departamento de Engenharia Elétrica, 2015.

Análise do desempenho de um queimador infravermelho funcionando com gás liquefeito de petróleo e glicerina

The use of infrared burners in industrial applications has many advantages in terms of technical-operational, for example, uniformity in the heat supply in the form of radiation and convection, with greater control of emissions due to the passage of exhaust gases through a macro-porous ceramic bed. This paper presents an infrared burner commercial, which was adapted an experimental ejector, capable of promoting a mixture of liquefied petroleum gas (LPG) and glycerin. By varying the percentage of dual-fuel, it was evaluated the performance of the infrared burner by performing an energy balance and atmospheric emissions. It was introduced a temperature controller with thermocouple modulating two-stage (low heat / high heat), using solenoid valves for each fuel. The infrared burner has been tested and tests by varying the amount of glycerin inserted by a gravity feed system. The method of thermodynamic analysis to estimate the load was used an aluminum plate located at the exit of combustion gases and the distribution of temperatures measured by a data acquisition system which recorded real-time measurements of the thermocouples attached. The burner had a stable combustion at levels of 15, 20 and 25% of adding glycerin in mass ratio of LPG gas, increasing the supply of heat to the plate. According to data obtained showed that there was an improvement in the efficiency of the 1st Law of infrared burner with increasing addition of glycerin. The emission levels of greenhouse gases produced by combustion (CO, NOx, SO2 and HC) met the environmental limits set by resolution No. 382/2006 of CONAMA

Rapid identification and differentiation of Mycobacterium avium subspecies paratuberculosis types by use of real-time PCR and high-resolution melt analysis of the MAP1506 locus

High-resolution melt (HRM) analysis can identify sequence polymorphisms by comparing the melting curves of amplicons generated by real-time PCR amplification. We describe the application of this technique to identify Mycobacterium avium subspecies paratuberculosis types I, II, and III. The HRM approach was based on type-specific nucleotide sequences in MAP1506, a member of the PPE (proline-proline-glutamic acid) gene family.

Airborne systems laboratory for automation research

This paper presents an Airborne Systems Laboratory for Automation Research. The Airborne Systems Laboratory (ASL) is a Cessna 172 aircraft that has been specially modified and equipped by ARCAA specifically for research in future aircraft automation technologies, including Unmanned Airborne Systems (UAS). This capability has been developed over a long period of time, initially through the hire of aircraft, and finally through the purchase and modification of a dedicated flight-testing capability. The ASL has been equipped with a payload system that includes the provision of secure mounting, power, aircraft state data, flight management system and real-time subsystem. Finally, this system has been deployed in a cost effective platform allowing real-world flight-testing on a range of projects.

A hidden Markov model and relative entropy rate approach to vision-based dim target detection for UAV sense-and-avoid

Uninhabited aerial vehicles (UAVs) are a cutting-edge technology that is at the forefront of aviation/aerospace research and development worldwide. Many consider their current military and defence applications as just a token of their enormous potential. Unlocking and fully exploiting this potential will see UAVs in a multitude of civilian applications and routinely operating alongside piloted aircraft. The key to realising the full potential of UAVs lies in addressing a host of regulatory, public relation, and technological challenges never encountered be- fore. Aircraft collision avoidance is considered to be one of the most important issues to be addressed, given its safety critical nature. The collision avoidance problem can be roughly organised into three areas: 1) Sense; 2) Detect; and 3) Avoid. Sensing is concerned with obtaining accurate and reliable information about other aircraft in the air; detection involves identifying potential collision threats based on available information; avoidance deals with the formulation and execution of appropriate manoeuvres to maintain safe separation. This thesis tackles the detection aspect of collision avoidance, via the development of a target detection algorithm that is capable of real-time operation onboard a UAV platform. One of the key challenges of the detection problem is the need to provide early warning. This translates to detecting potential threats whilst they are still far away, when their presence is likely to be obscured and hidden by noise. Another important consideration is the choice of sensors to capture target information, which has implications for the design and practical implementation of the detection algorithm. The main contributions of the thesis are: 1) the proposal of a dim target detection algorithm combining image morphology and hidden Markov model (HMM) filtering approaches; 2) the novel use of relative entropy rate (RER) concepts for HMM filter design; 3) the characterisation of algorithm detection performance based on simulated data as well as real in-flight target image data; and 4) the demonstration of the proposed algorithm's capacity for real-time target detection. We also consider the extension of HMM filtering techniques and the application of RER concepts for target heading angle estimation. In this thesis we propose a computer-vision based detection solution, due to the commercial-off-the-shelf (COTS) availability of camera hardware and the hardware's relatively low cost, power, and size requirements. The proposed target detection algorithm adopts a two-stage processing paradigm that begins with an image enhancement pre-processing stage followed by a track-before-detect (TBD) temporal processing stage that has been shown to be effective in dim target detection. We compare the performance of two candidate morphological filters for the image pre-processing stage, and propose a multiple hidden Markov model (MHMM) filter for the TBD temporal processing stage. The role of the morphological pre-processing stage is to exploit the spatial features of potential collision threats, while the MHMM filter serves to exploit the temporal characteristics or dynamics. The problem of optimising our proposed MHMM filter has been examined in detail. Our investigation has produced a novel design process for the MHMM filter that exploits information theory and entropy related concepts. The filter design process is posed as a mini-max optimisation problem based on a joint RER cost criterion. We provide proof that this joint RER cost criterion provides a bound on the conditional mean estimate (CME) performance of our MHMM filter, and this in turn establishes a strong theoretical basis connecting our filter design process to filter performance. Through this connection we can intelligently compare and optimise candidate filter models at the design stage, rather than having to resort to time consuming Monte Carlo simulations to gauge the relative performance of candidate designs. Moreover, the underlying entropy concepts are not constrained to any particular model type. This suggests that the RER concepts established here may be generalised to provide a useful design criterion for multiple model filtering approaches outside the class of HMM filters. In this thesis we also evaluate the performance of our proposed target detection algorithm under realistic operation conditions, and give consideration to the practical deployment of the detection algorithm onboard a UAV platform. Two fixed-wing UAVs were engaged to recreate various collision-course scenarios to capture highly realistic vision (from an onboard camera perspective) of the moments leading up to a collision. Based on this collected data, our proposed detection approach was able to detect targets out to distances ranging from about 400m to 900m. These distances, (with some assumptions about closing speeds and aircraft trajectories) translate to an advanced warning ahead of impact that approaches the 12.5 second response time recommended for human pilots. Furthermore, readily available graphic processing unit (GPU) based hardware is exploited for its parallel computing capabilities to demonstrate the practical feasibility of the proposed target detection algorithm. A prototype hardware-in- the-loop system has been found to be capable of achieving data processing rates sufficient for real-time operation. There is also scope for further improvement in performance through code optimisations. Overall, our proposed image-based target detection algorithm offers UAVs a cost-effective real-time target detection capability that is a step forward in ad- dressing the collision avoidance issue that is currently one of the most significant obstacles preventing widespread civilian applications of uninhabited aircraft. We also highlight that the algorithm development process has led to the discovery of a powerful multiple HMM filtering approach and a novel RER-based multiple filter design process. The utility of our multiple HMM filtering approach and RER concepts, however, extend beyond the target detection problem. This is demonstrated by our application of HMM filters and RER concepts to a heading angle estimation problem.

Implementation of an embedded sensor network for the coordination of Slocum gliders for coastal monitoring and observation

Autonomous Underwater Vehicles (AUVs) are revolutionizing oceanography through their versatility, autonomy and endurance. However, they are still an underutilized technology. For coastal operations, the ability to track a certain feature is of interest to ocean scientists. Adaptive and predictive path planning requires frequent communication with significant data transfer. Currently, most AUVs rely on satellite phones as their primary communication. This communication protocol is expensive and slow. To reduce communication costs and provide adequate data transfer rates, we present a hardware modification along with a software system that provides an alternative robust disruption- tolerant communications framework enabling cost-effective glider operation in coastal regions. The framework is specifically designed to address multi-sensor deployments. We provide a system overview and present testing and coverage data for the network. Additionally, we include an application of ocean-model driven trajectory design, which can benefit from the use of this network and communication system. Simulation and implementation results are presented for single and multiple vehicle deployments. The presented combination of infrastructure, software development and deployment experience brings us closer to the goal of providing a reliable and cost-effective data transfer framework to enable real-time, optimal trajectory design, based on ocean model predictions, to gather in situ measurements of interesting and evolving ocean features and phenomena.

A reliable real-time transport protocol for networked control systems over wireless networks

Deploying wireless networks in networked control systems (NCSs) has become more and more popular during the last few years. As a typical type of real-time control systems, an NCS is sensitive to long and nondeterministic time delay and packet losses. However, the nature of the wireless channel has the potential to degrade the performance of NCS networks in many aspects, particularly in time delay and packet losses. Transport layer protocols could play an important role in providing both reliable and fast transmission service to fulfill NCS’s real-time transmission requirements. Unfortunately, none of the existing transport protocols, including the Transport Control Protocol (TCP) and the User Datagram Protocol (UDP), was designed for real-time control applications. Moreover, periodic data and sporadic data are two types of real-time data traffic with different priorities in an NCS. Due to the lack of support for prioritized transmission service, the real-time performance for periodic and sporadic data in an NCS network is often degraded significantly, particularly under congested network conditions. To address these problems, a new transport layer protocol called Reliable Real-Time Transport Protocol (RRTTP) is proposed in this thesis. As a UDP-based protocol, RRTTP inherits UDP’s simplicity and fast transmission features. To improve the reliability, a retransmission and an acknowledgement mechanism are designed in RRTTP to compensate for packet losses. They are able to avoid unnecessary retransmission of the out-of-date packets in NCSs, and collisions are unlikely to happen, and small transmission delay can be achieved. Moreover, a prioritized transmission mechanism is also designed in RRTTP to improve the real-time performance of NCS networks under congested traffic conditions. Furthermore, the proposed RRTTP is implemented in the Network Simulator 2 for comprehensive simulations. The simulation results demonstrate that RRTTP outperforms TCP and UDP in terms of real-time transmissions in an NCS over wireless networks.

The ECOS Project. An interactive simulation to promote an ECO-friendly universe.

Custom designed for display on the Cube Installation situated in the new Science and Engineering Centre (SEC) at QUT, the ECOS project is a playful interface that uses real-time weather data to simulate how a five-star energy building operates in climates all over the world. In collaboration with the SEC building managers, the ECOS Project incorporates energy consumption and generation data of the building into an interactive simulation, which is both engaging to users and highly informative, and which invites play and reflection on the roles of green buildings. ECOS focuses on the principle that humans can have both a positive and negative impact on ecosystems with both local and global consequence. The ECOS project draws on the practice of Eco-Visualisation, a term used to encapsulate the important merging of environmental data visualization with the philosophy of sustainability. Holmes (2007) uses the term Eco-Visualisation (EV) to refer to data visualisations that ‘display the real time consumption statistics of key environmental resources for the goal of promoting ecological literacy’. EVs are commonly artifacts of interaction design, information design, interface design and industrial design, but are informed by various intellectual disciplines that have shared interests in sustainability. As a result of surveying a number of projects, Pierce, Odom and Blevis (2008) outline strategies for designing and evaluating effective EVs, including ‘connecting behavior to material impacts of consumption, encouraging playful engagement and exploration with energy, raising public awareness and facilitating discussion, and stimulating critical reflection.’ Consequently, Froehlich (2010) and his colleagues also use the term ‘Eco-feedback technology’ to describe the same field. ‘Green IT’ is another variation which Tomlinson (2010) describes as a ‘field at the juncture of two trends… the growing concern over environmental issues’ and ‘the use of digital tools and techniques for manipulating information.’ The ECOS Project team is guided by these principles, but more importantly, propose an example for how these principles may be achieved. The ECOS Project presents a simplified interface to the very complex domain of thermodynamic and climate modeling. From a mathematical perspective, the simulation can be divided into two models, which interact and compete for balance – the comfort of ECOS’ virtual denizens and the ecological and environmental health of the virtual world. The comfort model is based on the study of psychometrics, and specifically those relating to human comfort. This provides baseline micro-climatic values for what constitutes a comfortable working environment within the QUT SEC buildings. The difference between the ambient outside temperature (as determined by polling the Google Weather API for live weather data) and the internal thermostat of the building (as set by the user) allows us to estimate the energy required to either heat or cool the building. Once the energy requirements can be ascertained, this is then balanced with the ability of the building to produce enough power from green energy sources (solar, wind and gas) to cover its energy requirements. Calculating the relative amount of energy produced by wind and solar can be done by, in the case of solar for example, considering the size of panel and the amount of solar radiation it is receiving at any given time, which in turn can be estimated based on the temperature and conditions returned by the live weather API. Some of these variables can be altered by the user, allowing them to attempt to optimize the health of the building. The variables that can be changed are the budget allocated to green energy sources such as the Solar Panels, Wind Generator and the Air conditioning to control the internal building temperature. These variables influence the energy input and output variables, modeled on the real energy usage statistics drawn from the SEC data provided by the building managers.

Functional genes and gene array analysis as tools for monitoring hydrocarbon biodegradation

Bioremediation, which is the exploitation of the intrinsic ability of environmental microbes to degrade and remove harmful compounds from nature, is considered to be an environmentally sustainable and cost-effective means for environmental clean-up. However, a comprehensive understanding of the biodegradation potential of microbial communities and their response to decontamination measures is required for the effective management of bioremediation processes. In this thesis, the potential to use hydrocarbon-degradative genes as indicators of aerobic hydrocarbon biodegradation was investigated. Small-scale functional gene macro- and microarrays targeting aliphatic, monoaromatic and low molecular weight polyaromatic hydrocarbon biodegradation were developed in order to simultaneously monitor the biodegradation of mixtures of hydrocarbons. The validity of the array analysis in monitoring hydrocarbon biodegradation was evaluated in microcosm studies and field-scale bioremediation processes by comparing the hybridization signal intensities to hydrocarbon mineralization, real-time polymerase chain reaction (PCR), dot blot hybridization and both chemical and microbiological monitoring data. The results obtained by real-time PCR, dot blot hybridization and gene array analysis were in good agreement with hydrocarbon biodegradation in laboratory-scale microcosms. Mineralization of several hydrocarbons could be monitored simultaneously using gene array analysis. In the field-scale bioremediation processes, the detection and enumeration of hydrocarbon-degradative genes provided important additional information for process optimization and design. In creosote-contaminated groundwater, gene array analysis demonstrated that the aerobic biodegradation potential that was present at the site, but restrained under the oxygen-limited conditions, could be successfully stimulated with aeration and nutrient infiltration. During ex situ bioremediation of diesel oil- and lubrication oil-contaminated soil, the functional gene array analysis revealed inefficient hydrocarbon biodegradation, caused by poor aeration during composting. The functional gene array specifically detected upper and lower biodegradation pathways required for complete mineralization of hydrocarbons. Bacteria representing 1 % of the microbial community could be detected without prior PCR amplification. Molecular biological monitoring methods based on functional genes provide powerful tools for the development of more efficient remediation processes. The parallel detection of several functional genes using functional gene array analysis is an especially promising tool for monitoring the biodegradation of mixtures of hydrocarbons.

Methods of monitoring of metro lining in Prague

There are several reasons for monitoring of underground structures and they have already been discussed many times, e.g. from the view of ageing or state after accidental event like flooding of Prague metro in 2002. Monitoring of Prague metro is realized in the framework of international research project sponsored by ESF-S3T. The monitoring methods used in Prague are either classical one or new or developing one. The reason for different monitoring methods is the different precision of each method and also for cross-checking between them and their evaluation. Namely we use convergence, tiltmetres, crackmetres, geophysical methods, laser scanning, computer vision and finally installation of MEMS monitoring devices. In the paper more details of each method and obtained results will be presented. The monitoring methods are complemented by wireless data collection and transfer for real-time monitoring. © 2012 Taylor & Francis Group.

移动对象数据库模型、查询语言及实时交通流分析

提出一种移动对象数据库模型——Dynamic Transportation Network Based Moving Objects Database(简称DTNMOD),并给出了DTNMOD中基于移动对象时空轨迹的网络实时动态交通流分析方法.在DTNMOD中,交通网络被表示成动态的时空网络,可以描述交通状态、拓扑结构以及交通参数随时间的变化过程;网络受限的移动对象则用网络移动点表示.DTNMOD模型包含了完整的数据类型和查询操作的定义,因此可以在任何可扩充数据库(如PostgreSQL或SECONDO)中实现,从而得到完整的数据库模型和查询语言.为了对相关模型的性能进行比较与分析,基于PostgreSQL实现了一个原型系统并进行了一系列的实验.实验结果表明,DTNMOD提供了良好的区域查询及连接查询性能.

机载SAR实时成像系统中的数据可视化研究

SAR实时成像系统在国防等很多领域都有着重要的应用 ,系统对数据可视化方面的要求也越来越高 ,但目前国内对SAR实时成像系统的数据可视化方面的研究还不多 提出了一种针对SAR实时成像系统的新的数据可视化方案 ,并已在实际的飞行成像中得到了检验 新方案实时提供的信息更全面、更直观、可分析性更强 ,具有较强的信息表现能力和双向实时交互能力 ,能够较好地辅助对图像的在线分析 还对方案的重要组成部分———缩略图的原理和实现算法做了概括介绍