Results 101 to 110 of about 20,368 (248)
‘Let's Turn the Grass Into Meat’: Animal Husbandry as Women's Work in Cold War North Korea
Gender &History, EarlyView.ABSTRACT In postcolonial North Korea, the future of the nation was said to be a function of the feedlot. Unobtainable on the battlefields of the recently ended Korean War, liberation and unification of the peninsula became a question of competitive developmentalism.
Sunho Ko, Derek J. Kramer
wiley +1 more source
From Human Hands to Machine Minds: Financing AI‐Driven Entrepreneurship in Reward‐Based Crowdfunding
Accounting &Finance, EarlyView.ABSTRACT This study examines the effect of artificial intelligence (AI) adoption on financing performance in reward‐based crowdfunding. Using Kickstarter data from US projects, we find that AI projects have lower pledged amounts, receive fewer donations and attract fewer backers.
Zirui Song, Yihui Lan, Yuan George Shan
wiley +1 more source
American Journal of Agricultural Economics, EarlyView.Abstract When quality attributes of a product are not directly observable, third‐party certification (TPC) enables buyers to distinguish between quality levels and reward sellers accordingly. We study the adoption of TPC by traders in smallholder‐based agricultural value chains in low‐income countries, where traders aggregate products from many small ...
Gashaw T. Abate +4 more
wiley +1 more source
Unveiling the factors of aesthetic preferences with explainable AI
British Journal of Psychology, EarlyView.Abstract The allure of aesthetic appeal in images captivates our senses, yet the underlying intricacies of aesthetic preferences remain elusive. In this study, we pioneer a novel perspective by utilizing several different machine learning (ML) models that focus on aesthetic attributes known to influence preferences.
Derya Soydaner, Johan Wagemans
wiley +1 more source
Applied aspects of modern non-blind image deconvolution methods
Компьютерная оптикаThe focus of this paper is the study of modern non-blind image deconvolution methods and their application to practical tasks. The aim of the study is to determine the current state-of-the-art in non-blind image deconvolution and to identify the ...
O.B. Chaganova +3 more
doaj +1 more source
Hierarchical Differentiable Fluid Simulation
Computer Graphics Forum, EarlyView.We introduce a two‐step algorithm that significantly reduces memory usage for solving control problems using differentiable fluid simulation techniques: our method first optimizes for bulk forces at reduced resolution, then refines local details over sub‐domains while maintaining differentiability. In trading runtime for memory, it enables optimization
Xiangyu Kong +4 more
wiley +1 more source
Adaptive Sampling for BRDF Acquisition
Computer Graphics Forum, EarlyView.We propose a data‐driven adaptive sampling strategy that predicts the optimal sampling pattern and count for BRDF acquisition from a single image, reducing capture time while preserving quality. Abstract The bidirectional reflectance distribution function (BRDF) describes the ratio of incoming radiance to outgoing radiance for all possible pairs of ...
Behnaz Kavoosighafi +3 more
wiley +1 more source
Journal of Microscopy, EarlyView.Abstract X‐ray phase contrast imaging (XPCI), when implemented in micro‐computed tomography (micro‐CT) mode, offers high‐contrast 3D imaging of weakly‐attenuating material samples. In the so‐called single‐mask edge illumination approach, a mask with periodically spaced transmitting apertures is used to split the x‐ray beam into narrow beamlets; when ...
Khushal Shah +8 more
wiley +1 more source
Do robots boost productivity? A quantitative meta‐study
Journal of Economic Surveys, EarlyView.ABSTRACT This meta‐study analyzes the productivity effects of industrial robots. More than 1800 estimates from 85 primary studies are collected. The meta‐analytic evidence suggests that robotization has so far provided, at best, a small boost to productivity. There is strong evidence of publication bias in the positive direction.
Florian Schneider
wiley +1 more source
Blind Image Deblurring via Bayesian Estimation Using Expected Loss
IEEE AccessThis paper introduces a new approach to single image blind deblurring via Bayesian estimation using expected loss, diverging from traditional maximum a posteriori (MAP) estimation methods that are limited by the delta kernel problem-a phenomenon where ...
Jinook Lee, Moon Gi Kang
doaj +1 more source