Psycholinguists have developed a number of measures to tap different aspects of a word's semantic representation. The influence of these measures on lexical processing has collectively been described as semantic richness effects. However, the effects of these word properties on memory are currently not well understood. This study examines the relative contributions of lexical and semantic variables in free recall and recognition memory at the item-level, using a megastudy approach. Hierarchical regression of recall and recognition performance on a number of lexical-semantic variables showed task-general effects where the structural component, frequency, number of senses, and arousal accounted for unique variance in both free recall and recognition memory. Task-specific effects included number of features, imageability, and body-object interaction, which accounted for unique variance in recall, whereas age of acquisition, familiarity, and extremity of valence accounted for unique variance in recognition. Forward selection regression analyses generally converged on these findings. Hierarchical regression also revealed that lexical variables accounted for more variance in recognition compared with recall, whereas semantic variables accounted for more unique variance above and beyond lexical variables in recall compared with recognition. Implications of the findings are discussed.
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http://dx.doi.org/10.1177/1747021817739834 | DOI Listing |
Sensors (Basel)
January 2025
Cognitive Systems Lab, University of Bremen, 28359 Bremen, Germany.
Over recent years, automated Human Activity Recognition (HAR) has been an area of concern for many researchers due to its widespread application in surveillance systems, healthcare environments, and many more. This has led researchers to develop coherent and robust systems that efficiently perform HAR. Although there have been many efficient systems developed to date, still, there are many issues to be addressed.
View Article and Find Full Text PDFSensors (Basel)
December 2024
College of Engineering, Shanxi Agricultural University, Jinzhong 030801, China.
In order to solve the problems of high planting density, similar color, and serious occlusion between spikes in sorghum fields, such as difficult identification and detection of sorghum spikes, low accuracy and high false detection, and missed detection rates, this study proposes an improved sorghum spike detection method based on YOLOv8s. The method involves augmenting the information fusion capability of the YOLOv8 model's neck module by integrating the Gold feature pyramid module. Additionally, the SPPF module is refined with the LSKA attention mechanism to heighten focus on critical features.
View Article and Find Full Text PDFSensors (Basel)
December 2024
Department of Biomedical Engineering, Lebanese International University, Beirut P.O. Box 146404, Lebanon.
The integration of liveness detection into biometric systems is crucial for countering spoofing attacks and enhancing security. This study investigates the efficacy of photoplethysmography (PPG) signals, which offer distinct advantages over traditional biometric techniques. PPG signals are non-invasive, inherently contain liveness information that is highly resistant to spoofing, and are cost-efficient, making them a superior alternative for biometric authentication.
View Article and Find Full Text PDFAnimals (Basel)
December 2024
College of Agricultural Equipment Engineering, Henan University of Science and Technology, Luoyang 471023, China.
Top-view systems for lameness detection have advantages such as easy installation and minimal impact on farm work. However, the unclear lameness motion characteristics of the back result in lower recognition accuracy for these systems. Therefore, we analysed the compensatory behaviour of cows based on top-view walking videos, extracted compensatory motion features (CMFs), and constructed a model for recognising lameness in cows.
View Article and Find Full Text PDFCogn Neuropsychol
January 2025
Department of Psychological Sciences, Rice University, Houston, Texas, USA.
Many aspects of human performance require producing sequences of items in serial order. The current study takes a multiple-case approach to investigate whether the system responsible for serial order is shared across cognitive domains, focusing on working memory (WM) and word production. Serial order performance in three individuals with post-stroke language and verbal WM disorders (hereafter persons with aphasia, PWAs) were assessed using recognition and recall tasks for verbal and visuospatial WM, as well as error analyses in spoken and written production tasks to assess whether there was a tendency to produce the correct phonemes/letters in the wrong order.
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