Unintentional islanding events cause potential threats to the safety of dc microgrids. Selected frequency islanding detection is considered a promising technology thanks to its good power quality and ...high detection accuracy. However, the conventional frequency-domain-based islanding detection parameter boundary cannot consider the impact of detection time, which causes a quite slow detection speed and thus leads to detection failure. To overcome this obstacle, a linear model of the islanding dc system is developed first to analyze the steady-state response of the voltage at the point of common coupling (PCC). On top of that, the components of the islanding system characteristic equation are analyzed based on modal analysis, which lays a good foundation for simplifying the time-domain response model of the PCC voltage. Then, the oscillation trajectory of the PCC voltage triggered by the islanding event is characterized in the time domain, which facilitates the analysis and calculation of islanding detection time. Furthermore, the boundary of the islanding detection parameters considering the detection time effect is accurately depicted to guide the resonator design. In this manner, the effect of resonant parameters on the detection time can be evaluated visually while the fast detection speed is also ensured. Finally, the proposed method is validated in simulations and hardware-in-loop experiments.
Emergency medical dispatchers fail to identify approximately 25% of cases of out of hospital cardiac arrest, thus lose the opportunity to provide the caller instructions in cardiopulmonary ...resuscitation. We examined whether a machine learning framework could recognize out-of-hospital cardiac arrest from audio files of calls to the emergency medical dispatch center.
For all incidents responded to by Emergency Medical Dispatch Center Copenhagen in 2014, the associated call was retrieved. A machine learning framework was trained to recognize cardiac arrest from the recorded calls. Sensitivity, specificity, and positive predictive value for recognizing out-of-hospital cardiac arrest were calculated. The performance of the machine learning framework was compared to the actual recognition and time-to-recognition of cardiac arrest by medical dispatchers.
We examined 108,607 emergency calls, of which 918 (0.8%) were out-of-hospital cardiac arrest calls eligible for analysis. Compared with medical dispatchers, the machine learning framework had a significantly higher sensitivity (72.5% vs. 84.1%, p < 0.001) with lower specificity (98.8% vs. 97.3%, p < 0.001). The machine learning framework had a lower positive predictive value than dispatchers (20.9% vs. 33.0%, p < 0.001). Time-to-recognition was significantly shorter for the machine learning framework compared to the dispatchers (median 44 seconds vs. 54 s, p < 0.001).
A machine learning framework performed better than emergency medical dispatchers for identifying out-of-hospital cardiac arrest in emergency phone calls. Machine learning may play an important role as a decision support tool for emergency medical dispatchers.
We consider the problem of computing, for a detector surface waiting for a quantum particle to arrive, the probability distribution of the time and place at which the particle gets detected, from the ...initial wave function of the particle in the non-relativistic regime. Although the standard rules of quantum mechanics offer no operator for the time of arrival, quantum mechanics makes an unambiguous prediction for this distribution, defined by first solving the Schrödinger equation for the big quantum system formed by the particle of interest, the detector, a clock, and a device that records the time and place of detection, then making a quantum measurement of the record at a very late time, and finally using the distribution of the recorded time and place. This leads to the question whether there is also a practical, simple rule for computing this distribution, at least approximately (i.e., for an idealized detector). We argue here in favor of a rule based on a 1-particle Schrödinger equation with a certain (absorbing) boundary condition at the ideal detecting surface, first considered by Werner in 1987. We present a novel derivation of this rule and describe how it arises as a limit of a “soft” detector represented by an imaginary potential.
•Concerns the problem of arrival time in non-relativistic quantum mechanics.•That is, to compute the probability distribution of the time and place of detection.•We assume an ideal detector surface.•We propose an “absorbing boundary rule,” based on a boundary condition on the Schrödinger equation.•We give a derivation of this rule and report its key properties.
Calcium dobesilate (CD) is a synthetic venoactive drug used in veterinary medicine to treat equine navicular disease. Etamsylate is a haemostatic agent used in horses for the treatment of ...exercise-induced pulmonary haemorrhage. Both etamsylate and CD dissociate in the circulatory system with 2,5-HBSA as the active drug. The aim of the research was to be able to provide detection time (DT) advice from pharmacokinetic (PK) studies in Thoroughbred horses to better inform trainers, and their veterinary surgeons, prescribing these substances for treatment of Thoroughbred racehorses. Two (pilot study) and six (final study) horses were given 28 and 9 repeated dose of CD (3 mg/kg BID) respectively. Two horses were each given a single intravenous (IV) dose of etamsylate (10 mg/kg). Plasma and urine 2,5-HBSA concentrations were measured by liquid chromatography-tandem mass spectrometry (LC-MS/MS). The CD pilot study revealed that steady state could be reached with a few days and that 2,5-HBSA in plasma and urine shows instability during storage at -20°C but appears stable at -80°C. A novel holistic non-linear mixed-effects three-compartmental PK model was developed that described both plasma and urine concentrations of 2,5-HBSA, from either CD or etamsylate administration. Typical values for 2,5-HBSA clearance and bioavailability were 2.0 mL/min/kg and 28% respectively. Using the parameters obtained from this PK model, in conjunction with methodology developed by Toutain, afforded a possible screening limit (SL) that can regulate for a DT of 3 days in urine; however, a corresponding SL in plasma would be below current levels of detection. However, it is the responsibility of the individual racing authorities to apply their own risk management with regard to SLs and DTs.
A Eu-doped metal-organic framework (Uio-66-NH2-Eu) has been synthesized under a appropriate hydrothermal condition. Under UV-light irradiation, Uio-66-NH2-Eu shows blue luminescence which can be ...readily observed by naked eye. Uio-66-NH2-Eu shows excellent luminescence and good fluorescence stability in water which performs a remarkable enhancement effect (∼13 times as much as original one) in the luminescence emission of Eu3+ upon the introduction of Cd2+. Most importantly, the luminescence probe of Cd2+ shows a low detection limit (0.22μM), a broad linear range (0.22-500μM), fast detection time (<5min), and the signals can be observed by the naked eyes under the irradiation of UV light of 365nm.
•A Eu-doped metal-organic framework (Uio-66-NH2-Eu) has been synthesized under appropriate hydrothermal.•Uio-66-NH2-Eu shows excellent luminescence and good fluorescence stability in water. It performs a remarkable enhancement effect (∼13 times as much as original one) of Eu3+ upon the introduction of Cd2+.•The luminescence probe of Cd2+ shows a low detection limit (0.22μM), a broad linear range (0.22-500μM), fast detection time (<5min), and the signals can be observed by the naked eyes under the irradiation of UV light.
A Eu-doped metal-organic framework (Uio-66-NH2-Eu) has been synthesized under an appropriate hydrothermal condition and used as a luminescence sensor for Cd2+ detection. Uio-66-NH2-Eu shows excellent luminescence and good fluorescence stability in water which performs a remarkable enhancement effect (∼13 times as much as original one) in the luminescence emission of Eu3+ upon the introduction of Cd2+. This is a better example for detecting Cd2+ in aqueous solutions based on a lanthanide functionalized metal-organic frameworks (MOFs). Most importantly, the luminescence probe of Cd2+ shows a low detection limit (0.22μM), a broad linear range (0.22-500μM), fast detection time (<5min), and the signals can be observed by the naked eyes under the irradiation of UV light of 365nm. Subsequently, Uio-66-NH2-Eu was developed as a highly selective and sensitive probe for detection of Cd2+ in aqueous solutions. This work may be provided a possibility for Cd-detection in other biological systems.
Dynamic Coverage of Mobile Sensor Networks Benyuan Liu; Dousse, Olivier; Nain, P. ...
IEEE transactions on parallel and distributed systems,
02/2013, Volume:
24, Issue:
2
Journal Article
Peer reviewed
Open access
We study the dynamic aspects of the coverage of a mobile sensor network resulting from continuous movement of sensors. As sensors move around, initially uncovered locations may be covered at a later ...time, and intruders that might never be detected in a stationary sensor network can now be detected by moving sensors. However, this improvement in coverage is achieved at the cost that a location is covered only part of the time, alternating between covered and not covered. We characterize area coverage at specific time instants and during time intervals, as well as the time durations that a location is covered and uncovered. We further consider the time it takes to detect a randomly located intruder and prove that the detection time is exponentially distributed with parameter 2λrv̅ s where λ represents the sensor density, r represents the sensor's sensing range, and v̅ s denotes the average sensor speed. For mobile intruders, we take a game theoretic approach and derive optimal mobility strategies for both sensors and intruders. We prove that the optimal sensor strategy is to choose their directions uniformly at random between (0, 2π). The optimal intruder strategy is to remain stationary. This solution represents a mixed strategy which is a Nash equilibrium of the zero-sum game between mobile sensors and intruders.
•A new morphological filter is used for AC-DC faults protection in DC microgrid.•Fault current signals are denoised and fault inception is detected using two new morphological operators.•Multiscale ...operation of structuring element is optimized using spaese Kurtosis index.•Multi-class Adaboost approach is used to classify both AC feeder and DC fault types.
DC microgrids with energy storage systems based on photovoltaic (PV) and wind energy are gaining popularity as a means to offer users with reliable supply in either a stand-alone or grid connected mode. However, because DC and AC side faults have similar current–voltage profiles, developing a viable safety strategy for the proposed integrated DC microgrid is difficult. Traditional protection techniques based on pre-defined thresholds are unable to discriminate between DC and AC side faults, and so fail to offer independent control actions in both circumstances. In this context, new morphological operators with improved AdaBoost algorithm is proposed for detecting and classifying the AC and DC side faults in the proposed DC microgrid. To explore this, current signals are captured at the DC bus of the proposed integrated DC microgrid. The captured signals comprise background noise which is eliminated by dilation erosion difference operator (DEDO) and opening closing difference (OCDO) operators. The two operators work together to meet the accurate fault detection to avoid nuisance tripping by multiscale operation of structuring element (SE). For effective outcomes the multiple scales are optimized by sparse kurtosis (SK) index. The optimized scales are passes through target features to retrieve the data. The acquired data is sent into the multi-class AdaBoost approach, which recognizes faults by modifying the distribution of data and iteratively adjusting the weight of each instance. The proposed system's efficacy is tested using the MATLAB/Simulink platform under various operating situations such as load variation, irradiation and fault resistance changes. The proposed algorithm's superiority is demonstrated by comparing it to existing approaches using confusion matrix (CM) parameters.
Abstract Because open‐path gas detectors offer superior technical performance, leakage monitoring systems tend to use a hybrid layout of point and open‐path gas detectors. However, most research on ...the optimized layout of leakage monitoring has focused only on point gas detectors. In this paper, an optimization model for a hybrid layout of point and open‐path gas detectors was proposed considering the cost–benefit ratio and detection time. As the measured value of an open‐path gas detector is an integral concentration, a monitor line in the simulation was calculated via the approximate rectangle method. The results showed that the use of a multiobjective gas detector layout considering the cost–benefit ratio and an improved non‐dominated sorting genetic algorithm (NSGA‐II) could optimize the layout of hybrid detectors. The hybrid layout was analyzed in a case study of process facilities at a natural gas station. As the number of detectors increased (safety investment), the proportion of open‐path gas detectors increased, improving both leakage monitoring performance and the cost–benefit ratio. Additionally, the layout of the point gas detectors was analyzed. A comparison of objective function values for detection time showed the superiority of the hybrid layout in our research.
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