Results 41 to 50 of about 4,207,378 (350)
Discrete Dynamics in Nature and Society, 2021 Based on the active interference suppression algorithm, this study combines the radar working mode and the interference type and realizes the effective detection of the flaw detection signal by successively processing the radar receiving signal and the ...
Wenping Wu
doaj +1 more source
Business Strategy &Development, Volume 5, Issue 4, Page 361-374, December 2022., 2022 Abstract Worker voice tools can support multinational companies to monitor social compliance within complex multi‐tier apparel supply chains. This study presents findings from an adaptation of a worker voice tool that contacted 11,555 workers in two informal ‘Ready‐made Garment’ (RMG) production hubs in Bangladesh.
Sheila Chanani +4 more
wiley +1 more source
On Human Predictions with Explanations and Predictions of Machine Learning Models: A Case Study on Deception Detection [PDF]
FAT, 2018 Humans are the final decision makers in critical tasks that involve ethical and legal concerns, ranging from recidivism prediction, to medical diagnosis, to fighting against fake news.
Vivian Lai, Chenhao Tan
semanticscholar +1 more source
Business Strategy and the Environment, Volume 32, Issue 1, Page 686-703, January 2023., 2023 Abstract This study explores the quality of carbon reporting (QCR) by New Zealand (NZ) firms and its changes over time. It also explores the impact of QCR on the market reputation of firms. Using a sample of 300 company‐year observations between 2015 and 2020 from top listed firms of NZ, the study develops a 14‐item QCR index.
Habib Zaman Khan +2 more
wiley +1 more source
Detecting spontaneous deception in the brain
Human Brain Mapping, 2022 AbstractDeception detection can be of great value during the juristic investigation. Although the neural signatures of deception have been widely documented, most prior studies were biased by difficulty levels. That is, deceptive behavior typically required more effort, making deception detection possibly effort detection.
Yen‐Ju Feng +2 more
openaire +4 more sources
BERTective: Language Models and Contextual Information for Deception Detection
Conference of the European Chapter of the Association for Computational Linguistics, 2021 Spotting a lie is challenging but has an enormous potential impact on security as well as private and public safety. Several NLP methods have been proposed to classify texts as truthful or deceptive.
Tommaso Fornaciari +3 more
semanticscholar +1 more source
Identity Unbiased Deception Detection by 2D-to-3D Face Reconstruction
IEEE Workshop/Winter Conference on Applications of Computer Vision, 2021 Deception is a common phenomenon in society, both in our private and professional lives. However, humans are notoriously bad at accurate deception detection.
L. Ngô +6 more
semanticscholar +1 more source
Interviewing to Detect Deception [PDF]
European Psychologist, 2014 DePaulo et al.’s (2003) meta-analysis of verbal and nonverbal cues to deception showed that cues to deception are faint and unreliable. If liars do not spontaneously display diagnostic cues to deceit, a logical step is to make sure that investigators elicit or enhance such cues in interviews through specific interview technique.
openaire +4 more sources
Detecting deception: the scope and limits [PDF]
Trends in Cognitive Sciences, 2008 With the increasing interest in the neuroimaging of deception and its commercial application, there is a need to pay more attention to methodology. The weakness of studying deception in an experimental setting has been discussed intensively for over half a century.
Chris D. Frith +5 more
openaire +2 more sources
APSIPA Transactions on Signal and Information Processing, 2021 While deceptive behaviors are a natural part of human life, it is well known that human is generally bad at detecting deception. In this study, we present an automatic deception detection framework by comprehensively integrating prior domain knowledge in
Huang-Cheng Chou +2 more
semanticscholar +1 more source