We have developed and tested two electroencephalogram (EEG)-based brain-computer interfaces (BCI) for users to control a cursor on computer display. Our system uses an adaptive algorithm, based kernel partial least squares classification (KPLS), associate patterns in multichannel EEG frequency spectra with controls. first BCI, Target Practice, is one-dimensional device control, which participants use biofeedback learn voluntary of their spectra. Practice KPLS classifier map power...

The world-wide aviation system is one of the most complex dynamical systems ever developed and generating data at an extremely rapid rate. Most modern commercial aircraft record several hundred flight parameters including information from guidance, navigation, control systems, avionics propulsion pilot inputs into aircraft. These may be continuous measurements or binary categorical recorded in second intervals for duration flight. Currently, approaches to safety are reactive, meaning that...

Due to the emergence of numerous flexible electronic devices, design and fabrication rechargeable batteries with high energy density have attracted great attention.

The modern National Airspace System (NAS) is an extremely safe system and the aviation industry has experienced a steady decrease in fatalities over years. This part due airlines, manufacturers, FAA, research institutions all continually working to improve safety of operations. However, current approach for identifying vulnerabilities NAS operations leverages domain expertise using knowledge about how should behave within expected tolerances known margins. works well when well-defined...

The problem of distance-based outlier detection is difficult to solve efficiently in very large datasets because potential quadratic time complexity. We address this and develop sequential distributed algorithms that are significantly more efficient than state-of-the-art methods while still guaranteeing the same outliers. By combining simple but effective indexing disk block accessing techniques, we have developed a algorithm iOrca up an order-of-magnitude faster state-of-the-art. scheme...

The worldwide civilian aviation system is one of the most complex dynamical systems created. Most modern commercial aircraft have onboard flight data recorders that record several hundred discrete and continuous parameters at approximately 1 Hz for entire duration flight. These contain information about control systems, actuators, engines, landing gear, avionics, pilot commands. In this paper, recent advances in development a novel knowledge discovery process consisting suite mining...

Detecting anomalies in datasets, where each data object is a multivariate time series, possibly of different length for object, emerging as key problem certain domains. The considered the context aviation safety, objects are flights various durations and series corresponds to sensor readings. goal then detect anomalous flight segments, due mechanical, environmental, or human factors. In this paper, general framework presented anomaly detection such settings by representing using vector...

In this work we consider the problem of anomaly detection in heterogeneous, multivariate, variable-length time series datasets. Our focus is on aviation safety domain, where data objects are flights and sensor readings pilot switches. context goal to detect anomalous flight segments, due mechanical, environmental, or human factors order identifying operationally significant events highlight potential risks. For purpose, propose a framework which represents each using semi-Markov switching...

This article describes the results of applying four unsupervised anomaly detection algorithms to data from two rocket propulsion testbeds.The first testbed uses historical Space Shuttle Main Engine. The second an experimental engine test stand located at NASA Stennis Center. nine anomalies detected by algorithms.The use different definitions anomalousness. Orca a nearest-neighbor approach, defining point be if its nearest neighbors in space are far away it. Inductive Monitoring System...

Unique Li₄Ti₅O₁₂/TiO₂ multilayer arrays from a substrate-free method demonstrate advanced surface lithium storage capability.

Identifying safety anomalies and vulnerabilities in the aviation domain is a very expensive time-consuming task. Currently, it accomplished via manual forensic reviews by subject matter experts (SMEs). However, with increase amount of data produced airspace operations, relying on such impractical. Automated approaches, as exceedance detection, have been deployed to flag events which surpass pre-defined threshold. These however, completely rely knowledge outcome SMEs’ can only identify purely...

We are developing electromyographic and electroencephalographic methods, which draw control signals for human-computer interfaces from the human nervous system. have made progress in four areas: 1) real-time pattern recognition algorithms decoding sequences of forearm muscle activity associated with gestures; 2) signal-processing strategies computer using electroencephalogram (EEG) signals; 3) a flexible computation framework neuroelectric interface research; d) noncontact sensors, measure...

This paper describes an application of data mining technology called Distributed Fleet Monitoring (DFM) to Flight Operational Quality Assurance (FOQA) collected from a fleet commercial aircraft. DFM transforms the into list abnormaly performing aircraft, abnormal flight-to-flight trends, and individual flight anomalies by fitting large scale multi-level regression model entire set. The takes account fixed effects: vehicle-to-vehicle variability. parameters include aerodynamic coefficients...

For the purposes of this paper, National Airspace System (NAS) encompasses operations all aircraft which are subject to air traffic control procedures. The NAS is a highly complex dynamic system that sensitive aeronautical decision-making and risk management skills. In order ensure healthy with safe flights systematic approach anomaly detection very important when evaluating given set circumstances for determination best possible course action. Given fact vast loosely integrated network...

In the cloud computing environment resources are accessed as services rather than a product. Monitoring this system for performance is crucial because of typical pay-per- use packages bought by users their jobs. With huge number machines currently in system, it often extremely difficult administrators to keep track all using distributed monitoring programs such Ganglia1 which lacks health assessment and summarization capabilities. To overcome problem, we propose technique automated anomaly...

We measured multichannel EEG spectra during a continuous mental arithmetic task and created statistical learning models of cognitive fatigue for single subjects. Sixteen subjects (4 F, 18-38 y) viewed 4-digit problems on computer, solved the problems, pressed keys to respond (inter-trial interval = 1 s). Subjects performed until either they felt exhausted or three hours had elapsed. Pre- post-task measures mood (Activation Deactivation Adjective Checklist, Visual Analogue Mood Scale)...

Health monitoring is highly dependent on sensor systems that are capable of performing in various engine environmental conditions and able to transmit a signal upon predetermined crack length, while acting neutral form the overall performance system. Efforts under way at NASA Glenn Research Center through support Intelligent Vehicle Management Project (IVHM) develop implement such technology for wide variety applications. These efforts focused developing high temperature, wireless, low cost,...

We develop an algorithm for automatic discovery of precursors in time series data (ADOPT). In a setting, precursor may be considered as any event that precedes and increases the likelihood adverse event. multivariate data, there are exponential number events which makes brute force search intractable. ADOPT works by breaking down problem into two steps - (1) inferring model nominal (data without event) considering to generated hidden expert (2) using expert's benchmark evaluate identify...

Amid the growing concerns about air toxics from pollution sources, much emphasis has been placed on their impacts human health. However, there limited research conducted to assess cumulative country-wide impact of both terrestrial and aquatic ecosystems, as well complex interactions within food webs. Traditional approaches, including those United States Environmental Protection Agency (US EPA), lack versatility in addressing diverse emission sources distinct ecological repercussions. This...