Efficient disjointness tests for private datasets

We present efficient protocols for private set disjointness tests. We start from an intuition of our protocols that applies Sylvester matrices. Unfortunately, this simple construction is insecure as it reveals information about the cardinality of the intersection. More specifically, it discloses its lower bound. By using the Lagrange interpolation we provide a protocol for the honest-but-curious case without revealing any additional information. Finally, we describe a protocol that is secure against malicious adversaries. The protocol applies a verification test to detect misbehaving participants. Both protocols require O(1) rounds of communication. Our protocols are more efficient than the previous protocols in terms of communication and computation overhead. Unlike previous protocols whose security relies on computational assumptions, our protocols provide information theoretic security. To our knowledge, our protocols are first ones that have been designed without a generic secure function evaluation. More importantly, they are the most efficient protocols for private disjointness tests for the malicious adversary case.

Integrated approach for diagnostics and prognostics of HP LNG pump based on health state probability estimation

Effective machine fault prognostic technologies can lead to elimination of unscheduled downtime and increase machine useful life and consequently lead to reduction of maintenance costs as well as prevention of human casualties in real engineering asset management. This paper presents a technique for accurate assessment of the remnant life of machines based on health state probability estimation technique and historical failure knowledge embedded in the closed loop diagnostic and prognostic system. To estimate a discrete machine degradation state which can represent the complex nature of machine degradation effectively, the proposed prognostic model employed a classification algorithm which can use a number of damage sensitive features compared to conventional time series analysis techniques for accurate long-term prediction. To validate the feasibility of the proposed model, the five different level data of typical four faults from High Pressure Liquefied Natural Gas (HP-LNG) pumps were used for the comparison of intelligent diagnostic test using five different classification algorithms. In addition, two sets of impeller-rub data were analysed and employed to predict the remnant life of pump based on estimation of health state probability using the Support Vector Machine (SVM) classifier. The results obtained were very encouraging and showed that the proposed prognostics system has the potential to be used as an estimation tool for machine remnant life prediction in real life industrial applications.

Application of machine learning technique in wind turbine fault diagnosis

In this study, a machine learning technique called anomaly detection is employed for wind turbine bearing fault detection. Basically, the anomaly detection algorithm is used to recognize the presence of unusual and potentially faulty data in a dataset, which contains two phases: a training phase and a testing phase. Two bearing datasets were used to validate the proposed technique, fault-seeded bearing from a test rig located at Case Western Reserve University to validate the accuracy of the anomaly detection method, and a test to failure data of bearings from the NSF I/UCR Center for Intelligent Maintenance Systems (IMS). The latter data set was used to compare anomaly detection with SVM, a previously well-known applied method, in rapidly finding the incipient faults.

Fault detection of slow speed rolling element bearing with noise removal techniques

Rolling Element Bearings (REBs) are vital components in rotating machineries for providing rotating motion. In slow speed rotating machines, bearings are normally subjected to heavy static loads and a catastrophic failure can cause enormous disruption to production and human safety. Due to its low operating speed the impact energy generated by the rotating elements on the defective components is not sufficient to produce a detectable vibration response. This is further aggravated by the inability of general measuring instruments to detect and process the weak signals at the initiation of the defect accurately. Furthermore, the weak signals are often corrupted by background noise. This is a serious problem faced by maintenance engineers today and the inability to detect an incipient failure of the machine can significantly increases the risk of functional failure and costly downtime. This paper presents the application of noise removal techniques for enhancing the detection capability for slow speed REB condition monitoring. Blind deconvolution (BD) and adaptive line enhancer (ALE) are compared to evaluate their performance in enhancing the source signal with consequential removal of background noise. In the experimental study, incipient defects were seeded on a number of roller bearings and the signals were acquired using acoustic emission (AE) sensor. Kurtosis and modified peak ratio (mPR) were used to determine the detectability of signal corrupted by noise.

Risk-management of UAS robust autonomy for its integration into civil aviation safety frameworks

This paper discusses a model of the civil aviation reg- ulation framework and shows how the current assess- ment of reliability and risk for piloted aircraft has limited applicability for Unmanned Aircraft Systems (UAS) with high levels of autonomous decision mak- ing. Then, a new framework for risk management of robust autonomy is proposed, which arises from combining quantified measures of risk with normative decision making. The term Robust Autonomy de- scribes the ability of an autonomous system to either continue or abort its operation whilst not breaching a minimum level of acceptable safety in the presence of anomalous conditions. The decision making associ- ated with risk management requires quantifying prob- abilities associated with the measures of risk and also consequences of outcomes related to the behaviour of autonomy. The probabilities are computed from an assessment under both nominal and anomalous sce- narios described by faults, which can be associated with the aircraft’s actuators, sensors, communication link, changes in dynamics, and the presence of other aircraft in the operational space. The consequences of outcomes are characterised by a loss function which rewards the certification decision

Evaluation of robust autonomy and implications on UAS certification and design

As the number of potential applications of Unmanned Aircraft Systems (UAS) grows in civilian operations and national security, National Airworthiness Authorities are under increasing pressure to provide a path for certification and allow UAS integration into the national airspace. The success of this integration depends on developments in improved UAS reliability and safety, regulations for certification, and technologies for operational performance and safety assessment. This paper focusses on the latter and describes the use of a framework for evaluating robust autonomy of UAS, namely, the autonomous system’s ability to either continue operation in the presence of faults or safely shut down. The paper draws parallels between the proposed evaluation framework and the evaluation of pilots during the licensing process. It also discusses how the data from the proposed evaluation can be uses as an aid for decision making in certification and UAS designs.

Direct and quantitative detection of bacteriophage by “hearing” surface detachment using a quartz crystal microbalance

We show that it is possible to detect specifically adsorbed bacteriophage directly by breaking the interactions between proteins displayed on the phage coat and ligands immobilized on the surface of a quartz crystal microbalance (QCM). This is achieved through increasing the amplitude of oscillation of the QCM surface and sensitively detecting the acoustic emission produced when the bacteriophage detaches from the surface. There is no interference from nonspecifically adsorbed phage. The detection is quantitative over at least 5 orders of magnitude and is sensitive enough to detect as few as 20 phage. The method has potential as a sensitive and low-cost method for virus detection.

A nonlinear observer for estimating transverse stability parameters of marine surface vessels

This paper presents a nonlinear observer for estimating parameters associated with the restoring term of a roll motion model of a marine vessel in longitudinal waves. Changes in restoring, also referred to as transverse stability, can be the result of changes in the vessel's centre of gravity due to, for example, water on deck and also in changes in the buoyancy triggered by variations in the water-plane area produced by longitudinal waves -- propagating along the fore-aft direction along the hull. These variations in the restoring can change dramatically the dynamics of the roll motion leading to dangerous resonance. Therefore, it is of interest to estimate and detect such changes.

A framework for testing robust autonomy of UAS during design and certification

As the number of Uninhabited Airborne Systems (UAS) proliferates in civil applications, industry is increasingly putting pressure on regulation authorities to provide a path for certification and allow UAS integration into regulated airspace. The success of this integration depends on developments in improved UAS reliability and safety, regulations for certification, and technologies for operational performance and safety assessment. This paper focusses on the last topic and describes a framework for quantifying robust autonomy of UAS, which quantifies the system's ability to either continue operating in the presence of faults or safely shut down. Two figures of merit are used to evaluate vehicle performance relative to mission requirements and the consequences of autonomous decision making in motion control and guidance systems. These figures of merit are interpreted within a probabilistic framework, which extends previous work in the literature. The valuation of the figures of merit can be done using stochastic simulation scenarios during both vehicle development and certification stages with different degrees of integration of hardware-in-the-loop simulation technology. The objective of the proposed framework is to aid in decision making about the suitability of a vehicle with respect to safety and reliability relative to mission requirements.

CoRE : a context-aware relation extraction method for relation completion

We identify relation completion (RC) as one recurring problem that is central to the success of novel big data applications such as Entity Reconstruction and Data Enrichment. Given a semantic relation, RC attempts at linking entity pairs between two entity lists under the relation. To accomplish the RC goals, we propose to formulate search queries for each query entity α based on some auxiliary information, so that to detect its target entity β from the set of retrieved documents. For instance, a pattern-based method (PaRE) uses extracted patterns as the auxiliary information in formulating search queries. However, high-quality patterns may decrease the probability of finding suitable target entities. As an alternative, we propose CoRE method that uses context terms learned surrounding the expression of a relation as the auxiliary information in formulating queries. The experimental results based on several real-world web data collections demonstrate that CoRE reaches a much higher accuracy than PaRE for the purpose of RC.

Joint motion control and control allocation design for UAS flight control systems

As Unmanned Aircraft Systems (UAS) grow in complexity, and their level of autonomy increases|moving away from the concept of a remotely piloted systems and more towards autonomous systems|there is a need to further improve reliability and tolerance to faults. The traditional way to accommodate actuator faults is by using standard control allocation techniques as part of the flight control system. The allocation problem in the presence of faults often requires adding constraints that quantify the maximum capacity of the actuators. This in turn requires on-line numerical optimisation. In this paper, we propose a framework for joint allocation and constrained control scheme via vector input scaling. The actuator configuration is used to map actuator constraints into the space of the aircraft generalised forces, which are the magnitudes demanded by the light controller. Then by constraining the output of controller, we ensure that the allocation function always receive feasible demands. With the proposed framework, the allocation problem does not require numerical optimisation, and since the controller handles the constraints, there is not need to implement heuristics to inform the controller about actuator saturation.

Direct and quantitative detection of bacteriophage by "hearing" surface detachment using a quartz crystal microbalance

We show that it is possible to detect specifically adsorbed bacteriophage directly by breaking the interactions between proteins displayed on the phage coat and ligands immobilized on the surface of a quartz crystal microbalance (QCM). This is achieved through increasing the amplitude of oscillation of the QCM surface and sensitively detecting the acoustic emission produced when the bacteriophage detaches from the surface. There is no interference from nonspecifically adsorbed phage. The detection is quantitative over at least 5 orders of magnitude and is sensitive enough to detect as few as 20 phage. The method has potential as a sensitive and low-cost method for virus detection.

Protocol : A highly sensitive RT-PCR method for detection and quantification of microRNAs

MicroRNAs (miRNAs) are a class of small non-coding RNAs with a critical role in development and environmental responses. Efficient and reliable detection of miRNAs is an essential step towards understanding their roles in specific cells and tissues. However, gel-based assays currently used to detect miRNAs are very limited in terms of throughput, sensitivity and specificity. Here we provide protocols for detection and quantification of miRNAs by RT-PCR. We describe an end-point and real-time looped RT-PCR procedure and demonstrate detection of miRNAs from as little as 20 pg of plant tissue total RNA and from total RNA isolated from as little as 0.1 l of phloem sap. In addition, we have developed an alternative real-time PCR assay that can further improve specificity when detecting low abundant miRNAs. Using this assay, we have demonstrated that miRNAs are differentially expressed in the phloem sap and the surrounding vascular tissue. This method enables fast, sensitive and specific miRNA expression profiling and is suitable for facilitation of high-throughput detection and quantification of miRNA expression.

Conductometric gas sensors based on nanostrutured WO3 thin films

Nanostructured WO3 thin films have been prepared bythermal evaporation to detect hydrogen at low t emperatures. The influence of heat treatment on the physical, chemical and electronic properties of these films has been investigated. The films were annealed at 400oC for 2 hours in air. AFM and TEM analysis revealed that the as-deposited WO3 film is high amorphous and made up of cluster of particles. Annealing at 400oC for 2 hours in air resulted in very fine grain size of the order of 5 nm and porous structure. GIXRD and Raman analysis revealed that annealing improved the crystallinity of WO3 film. Gas sensors based on annealed WO3 films have shown a high response towards various concentrations (10-10000 ppm) H2 at an operating temperature of 150oC. The improved sensing performance at low operating temperature is due to the optimum physical, chemical and electronic properties achieved in the WO3 film through annealing. - See more at: http://dl4.globalstf.org/?wpsc-product=conductometric-gas-sensors-based-on-nanostructured-wo3-thin-films-2#sthash.IrfhlZ6H.dpuf

Polarized infrared absorption spectrum of matrix-isolated methylperoxyl radicals, CH3OO (X)over-tilde 2A ''

We have used a tandem pair of supersonic nozzles to produce clean samples of CH3OO radicals in cryogenic matrices. One hyperthermal nozzle decomposes azomethane (CH3NNCH3) to generate intense pulses of CH3 radicals, While the second nozzle alternately fires a burst Of O-2/Ar at the 20 K matrix. The CH3/O-2/20 K argon radical sandwich acts to produce target methylperoxyl radicals: CH3 + O-2 --> CH3OO. The absorption spectra of the radicals are monitored with a Fourier transform infrared spectrometer. We report 10 of the 12 fundamental infrared bands of the methylperoxyl radical CH3OO, (X) over tilde (2)A", in an argon matrix at 20 K. The experimental frequencies (cm(-1)) and polarizations follow: the a' modes are 3032, 2957, 1448, 1410, 1180, 1109, 90, 492, while the a" modes are 3024 and 1434. We cannot detect the asymmetric CH3 rocking mode, nu(11), nor the torsion, nu(12). The infrared spectra of (CH3OO)-O-18-O-18, (CH3OO)-C-13, and CD3OO have been measured as well in order to determine the isotopic shifts. The experimental frequencies, {nu}, for the methylperoxyl radicals are compared to harmonic frequencies, {omega}, resulting from a UB3LYP/6-311G(d,p) electronic structure calculation. Linear dichroism spectra were measured with photooriented radical samples in order to establish the experimental polarizations of most vibrational bands. The methylperoxyl radical matrix frequencies listed above are within +/-2% of the gas-phase vibrational frequencies. A final set of vibrational frequencies for the H radical, are recommended. See also http://ellison.colorado.edu/methylperoxyl.