Improved energy detector for random signals in gaussian noise [PDF]
New and improved energy detector for random signals in Gaussian noise is proposed by replacing the squaring operation of the signal amplitude in the conventional energy detector with an arbitrary positive power operation. Numerical results show that the best power operation depends on the probability of false alarm, the probability of detection, the ...
openaire +1 more source
Randomization and Failure Detection: A Hybrid Approach to Solve Consensus [PDF]
. We present a Consensus algorithm that combines randomization and unreliable failure detection, two well-known techniques for solving Consensus in asynchronous systems with crash failures.
Sam Toueg +3 more
core +1 more source
Detector Randomization and Stochastic Signaling for Minimum Probability of Error Receivers [PDF]
-Optimal receiver design is studied for a communications system in which both detector randomization and stochastic signaling can be performed. First, it is proven that stochastic signaling without detector randomization cannot achieve a smaller average ...
Senior Member, IEEE Sinan Gezici +1 more
core
Incidence of fires and related injuries after giving out free smoke alarms: cluster randomised controlled trial [PDF]
Objective To measure the effect of giving out free smoke alarms on rates of fires and rates of fire related injury in a deprived multiethnic urban population. Design Cluster randomised controlled trial.
Edwards, P. +23 more
core +1 more source
Tight asymptotic key rate for the Bennett-Brassard 1984 protocol with local randomization and device imprecisions [PDF]
Local randomization is a preprocessing procedure in which one of the legitimate parties of a quantum key distribution (QKD) scheme adds noise to their version of the key and was found by Kraus et al. [Phys. Rev. Lett.
Woodhead, Erik
core +1 more source
Locally optimal detection and randomization defenses against universal adversarial perturbations [PDF]
Submission published under a 24 month embargo labeled 'U of I Access', the embargo will last until 2024-12-01The student, Amish Goel, accepted the attached license on 2022-08-19 at 11:12.The student, Amish Goel, submitted this Dissertation for approval ...
Goel, Amish
core
Hardening Random Forest Cyber Detectors Against Adversarial Attacks [PDF]
Machine learning algorithms are effective in several applications, but they are not as much successful when applied to intrusion detection in cyber security. Due to the high sensitivity to their training data, cyber detectors based on machine learning are vulnerable to targeted adversarial attacks that involve the perturbation of initial samples ...
Giovanni Apruzzese +3 more
openaire +3 more sources
Random Variation of Detector Efficiency: A Countermeasure Against Detector Blinding Attacks for Quantum Key Distribution [PDF]
In the recent decade, it has been discovered that QKD systems are extremely vulnerable to side-channel attacks. In particular, by exploiting the internal working knowledge of practical detectors, it is possible to bring them to an operating region whereby only certain target detectors are sensitive to detections.
Lim, Ci Wen +4 more
openaire +3 more sources
ABSTRACT Objectives The association between exposure to dinutuximab beta (DB) and event‐free survival (EFS) or overall survival (OS) of neuroblastoma patients was assessed using data collected during three clinical trials (five cohorts). Methods A systematic review (March 2026) was conducted to identify relevant studies (prospective; registered DB ...
Przemysław Holko +19 more
wiley +1 more source
Progressive Randomization For Steganalysis [PDF]
In this paper, we describe a new methodology to detect the presence of hidden digital content in the Least Significant Bits (LSB) of images. We introduce the Progressive Randomization (PR) technique that captures statistical artifacts inserted during the
Goldenstein S., Rocha A.
core +1 more source

