Working towards an Improved Monitoring Infrastructure to support Disaster Management, Humanitarian Relief and Civil Security

Within this paper experiences and results from the work in the context of the European Initiative on Global Monitoring for Environment and Security (GMES) as they were gathered within the German Remote Sensing Data Center (DFD) are reported. It is described how data flows, analysis methods and information networks can be improved to allow better and faster access to remote sensing data and information in order to support the management of crisis situations. This refers to all phases of a crisis or disaster situation, including preparedness, response and recovery. Above the infrastructure and information flow elements, example cases of different crisis situations in the context of natural disasters, humanitarian relief activities and civil security are discussed. This builds on the experiences gained during the very active participation in the network of Excellence on Global Monitoring for Stability and Security (GMOSS), the GMES Service Element RESPOND, focussing on Humanitarian Relief Support and supporting the International Charter on Space and Major Disasters as well as while linking closely to national, European and international entities related to civil human security. It is suggested to further improve the network of national and regional centres of excellence in this context in order to improve local, regional and global monitoring capacities. Only when optimum interoperability and information flow can be achieved among systems and data providers on one hand side and the decision makers on the other, efficient monitoring and analysis capacities can be established successfully

Analysis of novel geometry-independent method for dialysis access pressure-flow monitoring

Abstract Background End-stage renal disease (ESRD) confers a large health-care burden for the United States, and the morbidity associated with vascular access failure has stimulated research into detection of vascular access stenosis and low flow prior to thrombosis. We present data investigating the possibility of using differential pressure (ΔP) monitoring to estimate access flow (Q) for dialysis access monitoring, with the goal of utilizing micro-electro-mechanical systems (MEMS) pressure sensors integrated within the shaft of dialysis needles. Methods A model of the arteriovenous graft fluid circuit was used to study the relationship between Q and the ΔP between two dialysis needles placed 2.5–20.0 cm apart. Tubing was varied to simulate grafts with inner diameters of 4.76–7.95 mm. Data were compared with values from two steady-flow models. These results, and those from computational fluid dynamics (CFD) modeling of ΔP as a function of needle position, were used to devise and test a method of estimating Q using ΔP and variable dialysis pump speeds (variable flow) that diminishes dependence on geometric factors and fluid characteristics. Results In the fluid circuit model, ΔP increased with increasing volume flow rate and with increasing needle-separation distance. A nonlinear model closely predicts this ΔP-Q relationship (R2 > 0.98) for all graft diameters and needle-separation distances tested. CFD modeling suggested turbulent needle effects are greatest within 1 cm of the needle tip. Utilizing linear, quadratic and combined variable flow algorithms, dialysis access flow was estimated using geometry-independent models and an experimental dialysis system with the pressure sensors separated from the dialysis needle tip by distances ranging from 1 to 5 cm. Real-time ΔP waveform data were also observed during the mock dialysis treatment, which may be useful in detecting low or reversed flow within the access. Conclusion With further experimentation and needle design, this geometry-independent approach may prove to be a useful access flow monitoring method.http://deepblue.lib.umich.edu/bitstream/2027.42/112774/1/12976_2008_Article_178.pd

A one-pass clustering based sketch method for network monitoring

Network monitoring solutions need to cope with increasing network traffic volumes, as a result, sketch-based monitoring methods have been extensively studied to trade accuracy for memory scalability and storage reduction. However, sketches are sensitive to skewness in network flow distributions due to hash collisions, and need complicated performance optimization to adapt to line-rate packet streams. We provide Jellyfish, an efficient sketch method that performs one-pass clustering over the network stream. One-pass clustering is realized by adapting the monitoring granularity from the whole network flow to fragments called subflows, which not only reduces the ingestion rate but also provides an efficient intermediate representation for the input to the sketch. Jellyfish provides the network-flow level query interface by reconstructing the network-flow level counters by merging subflow records from the same network flow. We provide probabilistic analysis of the expected accuracy of both existing sketch methods and Jellyfish. Real-world trace-driven experiments show that Jellyfish reduces the average estimation errors by up to six orders of magnitude for per-flow queries, by six orders of magnitude for entropy queries, and up to ten times for heavy-hitter queries.This work was supported in part by the National Natural Science Foundation of China (NSFC) under Grant 61972409; in part by Hong Kong Research Grants Council (RGC) under Grant TRS T41-603/20-R, Grant GRF-16213621, and Grant ITF ACCESS; in part by the Spanish I+D+i project TRAINER-A, funded by MCIN/AEI/10.13039/501100011033, under Grant PID2020-118011GB-C21; and in part by the Catalan Institution for Research and Advanced Studies (ICREA Academia).Peer ReviewedPostprint (author's final draft

BISM: Bytecode-Level Instrumentation for Software Monitoring

BISM (Bytecode-Level Instrumentation for Software Monitoring) is a lightweight bytecode instrumentation tool that features an expressive high-level control-flow-aware instrumentation language. The language follows the aspect-oriented programming paradigm by adopting the joinpoint model, advice inlining, and separate instrumentation mechanisms. BISM provides joinpoints ranging from bytecode instruction to method execution, access to comprehensive static and dynamic context information, and instrumentation methods. BISM runs in two instrumentation modes: build-time and load-time. We demonstrate BISM effectiveness using two experiments: a security scenario and a general runtime verification case. The results show that BISM instrumentation incurs low runtime and memory overheads

A new technique for measuring fistula flow using venous blood gas oxygen saturation in patients with a central venous catheter

Background. Doppler ultrasound (DU) monitoring early after arteriovenous fistula (AVF) creation allows the identification of low blood flow (Qa) requiring prompt revision, but it is costly (needs skilled operators and technical instruments) and is not available in all dialysis units. Therefore alternative first-line methods to measure Qa would be welcomed.We reasoned that once an AVF is created, an increment in central venous oxygen saturation (ScvO2) is predictable and proportional to Qa. Methods. Accordingly, in patients receiving dialysis through a central venous catheter (CVC) in whom an AVF was created, we measured, by means of blood gas analysis, the ScvO2 increment before and after manual compression of the arteriovenous shunt and verified its correlation with DU-measured Qa. Results. We sampled blood gas in 18 patients with CVC and AVF before and after 30 s manual compression of the AVF. ScvO2 averaged 70.563% before and 65.263% after AVF closure, with an average drop of 5.163% (range 1–12). AVF Qa, which was measured within 24h by means of DU, averaged 6356349 mL/min (range 50–1300) and was strictly and positively correlated with DScvO2 (r ¼ 0.954, P<0.0001). Conclusions. Therefore we suggest that in patients with CVC and a newly created AVF, it is possible to monitor AVF Qa without DU by simply measuring blood gas and DScvO2. This technique is simple, cheap, repeatable, non-invasive and operator independent and represents a new useful screening test to detect delayed AVF access maturation deserving prompt DU measurement and surgical revision. It helps to quickly identify patients in urgent need of DU verification and possible surgical revision. Regrettably, it is applicable only in patients with CVC

Developing GPS river flow tracers (GRiFTers) to investigate large scale river flow phenomena

Existing flow measurement methods in natural gravel rivers are largely based on a series of point measurements detached from the dynamic nature of river flow. Traditional measurement methods are limited in many environments and locations due to an inability to access directly the channel; this situation is further complicated at high discharges where entry into the channel becomes impossible. The inadequacy of currently utilised flow measurement methods is highlighted in the study of riffle-pool sequences where limited data has produced gaps in the understanding of these fundamentally important bedform structures. Within the study of riffle-pool sequences the most prominent debates concern the precise means of sequence development and maintenance, the existence / operation of the velocity reversal hypothesis and the spatial compositions and periodicity of these quasi-regular bedform features.The expanding usage of remote sensor monitoring techniques, the incorporation of GPS receivers into drifters to provide improved positioning, and the adaptation of drifters for use in the surf zone and in estuaries and lakes have combined to highlight the potential of producing a GPS river flow tracer (GRiFTer). The development of a GRiFTer suitable for deployment in a natural gravel bed river system is described whilst the logistics of performing a field based GRiFTer investigation, data acquisition and analysis methods and the achievable accuracy of the approach are also considered.The development of a GPS River Flow Tracer provides an innovative approach to the acquisition of surface velocity measurements through the development of a series of GRiFTer based analysis tools and techniques. The suite of tools developed to date includes; the ability to measure a single primary flowline through a reach, a means of independently measuring the effective width of channel flow, the identification of low velocity zones (and the direction of flow within these areas), three different methods for the measurement of surface flow velocity (primary flowline, cross-sectional averaged and reach scale) and a means of defining riffles and pools from the relationship between depth and surface flow velocities.The study ultimately concludes with a conceptual model for the development and maintenance of riffle-pool sequences based on an adaptation of the flow convergence routing hypothesis

FUSE – using artificial intelligence in the energy grid of tomorrow

The objective of Future Smart Energy (FUSE), a Finnish-German research and development project, is to develop methods based on artificial intelligence (AI) that will help to increase the resilience of future energy distribution grids. The use cases that are investigated include both condition monitoring/predictive maintenance, and distributed demand-side management in medium-voltage and low-voltage grids. The FUSE concept foresees a hierarchical infrastructure of sensing- and data processing nodes that use AI to transform raw data into information on asset and grid status and performance. FUSE supports the upward flow of data and aggregation of information into high-level visualisations for grid operators, as well as the downward flow of soft control signals that trigger the distributed self-control of assets. This study outlines the FUSE concept and presents the first results.This is an open access article published by the IET under the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0/)fi=vertaisarvioitu|en=peerReviewed

A Primer for Monitoring Water Funds

This document is intended to assist people working on Water Funds to understand their information needs and become familiar with the strengths and weaknesses of various monitoring approaches. This primer is not intended to make people monitoring experts, but rather to help them become familiar with and conversant in the major issues so they can communicate effectively with experts to design a scientifically defensible monitoring program.The document highlights the critical information needs common to Water Fund projects and summarizes issues and steps to address in developing a Water Fund monitoring program. It explains key concepts and challenges; suggests monitoring parameters and an array of sampling designs to consider as a starting-point; and provides suggestions for further reading, links to helpful resources,and an annotated bibliography of studies on the impacts that result from activities commonly implemented in Water Fund projects