Results 71 to 80 of about 79,918 (254)
Abstract If sexual assault survivors report the assault to the criminal legal system, they often need informal support from family and friends throughout the long and frequently retraumatizing process of investigation and prosecution. This study is part of a long‐term community‐based participatory action research project in a predominately Black ...
Rebecca Campbell +4 more
wiley +1 more source
Machine learning (ML) and deep neural networks (DNN) have emerged as powerful tools for enhancing intrusion detection systems (IDS) in cybersecurity.
Zeinab Awad, Magdy Zakaria, Rasha Hassan
doaj +1 more source
Prioritizing Feasible and Impactful Actions to Enable Secure AI Development and Use in Biology
ABSTRACT As artificial intelligence continues to enhance biological innovation, the potential for misuse must be addressed to fully unlock the potential societal benefits. While significant work has been done to evaluate general‐purpose AI and specialized biological design tools (BDTs) for biothreat creation risks, actionable steps to mitigate the risk
Josh Dettman +4 more
wiley +1 more source
ABSTRACT Despite growing public knowledge of false confession cases, research with students and community members continues to find that people assume confessions indicate guilt. The present research explored the implications of belief perseverance: the tendency to maintain a belief even when confronted with compelling contradictory evidence.
Taya D. Henry +2 more
wiley +1 more source
Efficient Defenses Against Adversarial Attacks [PDF]
Following the recent adoption of deep neural networks (DNN) accross a wide range of applications, adversarial attacks against these models have proven to be an indisputable threat. Adversarial samples are crafted with a deliberate intention of undermining a system. In the case of DNNs, the lack of better understanding of their working has prevented the
Zantedeschi, Valentina +2 more
openaire +2 more sources
A Deep Learning Framework for Forecasting Medium‐Term Covariance in Multiasset Portfolios
ABSTRACT Forecasting the covariance matrix of asset returns is central to portfolio construction, risk management, and asset pricing. However, most existing models struggle at medium‐term horizons, several weeks to months, where shifting market regimes and slower dynamics prevail.
Pedro Reis, Ana Paula Serra, João Gama
wiley +1 more source
Major Cybersecurity Breaches: Shaping Corporate Cybersecurity Policies and Closing the Gaps
ABSTRACT As digitalization accelerates, cybercrime has intensified in both scale and impact over the past two decades. This study aims to critically examine major cybersecurity events, assess them through the lens of routine activity theory, examine insight from three other established criminological and organizational theories, and address central ...
Laura K. Rickett, Deborah Smith
wiley +1 more source
Automatic modulation classification models based on deep learning models are at risk of being interfered by adversarial attacks. In an adversarial attack, the attacker causes the classification model to misclassify the received signal by adding carefully
Fanghao Xu +5 more
doaj +1 more source
PuVAE: A Variational Autoencoder to Purify Adversarial Examples
Deep neural networks are widely used and exhibit excellent performance in many areas. However, they are vulnerable to adversarial attacks that compromise networks at inference time by applying elaborately designed perturbations to input data.
Uiwon Hwang +4 more
doaj +1 more source
ABSTRACT As organizations increasingly adopt human‐AI teams (HATs), understanding how to enhance team performance is paramount. A crucially underexplored area for supporting HATs is training, particularly helping human teammates to work with these inorganic counterparts.
Caitlin M. Lancaster +5 more
wiley +1 more source

