In Pursuit of Aviation Cybersecurity: Experiences and Lessons From a Competitive Approach

The passive and independent localization of aircraft has been the subject of much cyberphysical security research. We designed a multistage open competition focusing on the offline batch localization problem using opportunistic data sources. We discuss setup, results, and lessons learned

Translation of EEG spatial filters from resting to motor imagery using independent component analysis.

Electroencephalogram (EEG)-based brain-computer interfaces (BCIs) often use spatial filters to improve signal-to-noise ratio of task-related EEG activities. To obtain robust spatial filters, large amounts of labeled data, which are often expensive and labor-intensive to obtain, need to be collected in a training procedure before online BCI control. Several studies have recently developed zero-training methods using a session-to-session scenario in order to alleviate this problem. To our knowledge, a state-to-state translation, which applies spatial filters derived from one state to another, has never been reported. This study proposes a state-to-state, zero-training method to construct spatial filters for extracting EEG changes induced by motor imagery. Independent component analysis (ICA) was separately applied to the multi-channel EEG in the resting and the motor imagery states to obtain motor-related spatial filters. The resultant spatial filters were then applied to single-trial EEG to differentiate left- and right-hand imagery movements. On a motor imagery dataset collected from nine subjects, comparable classification accuracies were obtained by using ICA-based spatial filters derived from the two states (motor imagery: 87.0%, resting: 85.9%), which were both significantly higher than the accuracy achieved by using monopolar scalp EEG data (80.4%). The proposed method considerably increases the practicality of BCI systems in real-world environments because it is less sensitive to electrode misalignment across different sessions or days and does not require annotated pilot data to derive spatial filters

The D0 Run II Impact Parameter Trigger

Many physics topics to be studied by the D0 experiment during Run II of the Fermilab Tevatron ppbar collider give rise to final states containing b--flavored particles. Examples include Higgs searches, top quark production and decay studies, and full reconstruction of B decays. The sensitivity to such modes has been significantly enhanced by the installation of a silicon based vertex detector as part of the DO detector upgrade for Run II. Interesting events must be identified initially in 100-200 microseconds to be available for later study. This paper describes custom electronics used in the DO trigger system to provide the real--time identification of events having tracks consistent with the decay of b--flavored particles.Comment: To be submitted to Nucl. Instrum. Methods A. 56 pages, 31 figure

The performance of the CMS muon detector in proton-proton collisions at √s = 7 TeV at the LHC

The performance of all subsystems of the CMS muon detector has been studied by using a sample of proton-proton collision data at √s = 7 TeV collected at the LHC in 2010 that corresponds to an integrated luminosity of approximately 40 pb^(-1). The measured distributions of the major operational parameters of the drift tube (DT), cathode strip chamber (CSC), and resistive plate chamber (RPC) systems met the design specifications. The spatial resolution per chamber was 80–120 μm in the DTs, 40–150 μm in the CSCs, and 0.8–1.2 cm in the RPCs. The time resolution achievable was 3 ns or better per chamber for all 3 systems. The efficiency for reconstructing hits and track segments originating from muons traversing the muon chambers was in the range 95–98%. The CSC and DT systems provided muon track segments for the CMS trigger with over 96% efficiency, and identified the correct triggering bunch crossing in over 99.5% of such events. The measured performance is well reproduced by Monte Carlo simulation of the muon system down to the level of individual channel response. The results confirm the high efficiency of the muon system, the robustness of the design against hardware failures, and its effectiveness in the discrimination of backgrounds