Network intrusion detection systems (NIDSs) have become an indispensable component for the current network security infrastructure. However, a large number of alarms especially false alarms are a big problem for these systems which greatly lowers the effectiveness of NIDSs and causes heavier analysis workload. To address this problem, a lot of intelligent methods (e.g., machine learning algorit...

Background Disposable electrocardiographic lead wires (ECG-LWs) may not be as durable as reusable ones. Objective To examine differences in alarm events between disposable and reusable ECG-LWs. Method Two cardiac telemetry units were randomized to reusable ECG-LWs, and 2 units alternated between disposable and reusable ECG-LWs for 4 months. A remote monitoring team, blinded to ECG-LW type, asse...

In this paper we present the sensor-fusion results based on the measurements obtained within the European research project GEODE (Ground Explosive Ordnance DEtection system) that strives for the realisation of a vehicle-mounted, multisensor, anti-personnel land-mine detection system for humanitarian demining. The applied decision-level sensor-fusion techniques are Bayesian approaches, applicati...

Cryptanalytic time memory tradeoff algorithms are generic one-way function inversion techniques that utilize pre-computation. Even though the online time complexity is known up to a small multiplicative factor for any tradeoff algorithm, false alarms pose a major obstacle in its accurate assessment. In this work, we study the expected pre-image size for an iteration of functions and use the res...

Two experiments (modeled after J. Deese's 1959 study) revealed remarkable levels of false recall and false recognition in a list learning paradigm. In Experiment 1, subjects studied lists of 12 words (e.g., bed, rest, awake); each list was composed of associates of 1 nonpresented word (e.g., sleep). On immediate free recall tests, the nonpresented associates were recalled 40% of the time and we...