Use of Bayesian Networks for the Forensic Evaluation of Gunshot Residue
Bayesian Networks can help evaluate gunshot residue given activity level propositions. This review discusses the different approaches that have been taken in the past and the challenges we are facing, with recommendations for future research. ABSTRACT Gunshot residue is a common type of trace considered in forensic science.
Yingxiu Guo +2 more
wiley +1 more source
Toward leveraging intrinsic point cloud features in 3D adversarial attacks. [PDF]
Naderi H, Dinesh C, Bajić IV, Kasaei S.
europepmc +1 more source
AI and Big Data in Consumer Behavior Analysis. ABSTRACT The rapid expansion of digital consumer data has challenged traditional approaches to understanding behavior in digital marketing. Existing reviews often focus on individual methods and give limited guidance on how analytical techniques compare or how they should be selected for specific marketing
Leonidas Theodorakopoulos +1 more
wiley +1 more source
Risk, Overlap, and Two Forms of Aggregation
ABSTRACT In this paper, we introduce a new class of cases to the debate on rescue dilemmas and whether to save the greater number. We argue that situations involving both risk and overlap shine a new light on some of the most important issues within this discussion.
Lukas Tank +2 more
wiley +1 more source
Evaluating the Adversarial Robustness and Clinical Safety of Quantized Hierarchical Transformers for Edge-Based Malaria Microscopy. [PDF]
Hasan U, Alghamdi TG, Nayeem MA.
europepmc +1 more source
Ideology on Trial: How CEO Political Leanings Shape Firms' Propensity to Litigate Over Patents
ABSTRACT This study investigates how CEOs' political ideology affects corporate decisions to sue for patent infringement. Integrating upper‐echelons and behavioral‐agency perspectives, we theorize that conservative‐leaning CEOs—marked by heightened threat sensitivity and low tolerance for ambiguity—frame infringement as a looming loss and therefore ...
Ali Radfard, Luca Pistilli
wiley +1 more source
DeDiAttack: Enhancing Transferability of Unrestricted Adversarial Examples via Deformation-Constrained Diffusion. [PDF]
Qu B, Peng A, Zhao S.
europepmc +1 more source
Deep Learning‐Assisted Coherent Raman Scattering Microscopy
The analytical capabilities of coherent Raman scattering microscopy are augmented through deep learning integration. This synergistic paradigm improves fundamental performance via denoising, deconvolution, and hyperspectral unmixing. Concurrently, it enhances downstream image analysis including subcellular localization, virtual staining, and clinical ...
Jianlin Liu +4 more
wiley +1 more source
Adversarial robust EEG-based brain-computer interfaces using a hierarchical convolutional neural network. [PDF]
Samuel J +5 more
europepmc +1 more source
Deep Learning‐Assisted Design of Mechanical Metamaterials
This review examines the role of data‐driven deep learning methodologies in advancing mechanical metamaterial design, focusing on the specific methodologies, applications, challenges, and outlooks of this field. Mechanical metamaterials (MMs), characterized by their extraordinary mechanical behaviors derived from architected microstructures, have ...
Zisheng Zong +5 more
wiley +1 more source

