The contextual interference (CI) effect has been investigated through practice schedule manipulations within both basic and applied studies. Despite extensive research activity there is little conclusive evidence regarding the optimal practice structure of real world manipulative tasks in professional training settings. The present study therefore assessed the efficacy of practising simple and complex knot-tying skills in professional fire-fighters training. Forty-eight participants were quasi-randomly assigned to various practice schedules along the CI continuum. Twenty-four participants were students selected for their novice knot-tying capabilities and 24 were experienced fire-fighters who were more 'experienced knot-tiers'. They were assessed for skill acquisition, retention and transfer effects having practiced tying knots classified as simple or complex. Surprisingly, high levels of CI scheduling enhance learning for novices even when practising a complex task. The findings also revealed that CI benefits are most apparent as learners engage in tasks high in transfer distality. In conclusion, complexity and experience are mediating factors influencing the potency of the CI training effect in real-world settings.
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http://dx.doi.org/10.1016/j.actpsy.2004.08.003 | DOI Listing |
Atten Percept Psychophys
January 2025
Department of Psychology, The Ohio State University, 1835 Neil Ave, Columbus, OH, 43210, USA.
Our attention can sometimes be disrupted by salient but irrelevant objects in the environment. This distractor interference can be reduced when distractors appear frequently, allowing us to anticipate their presence. However, it remains unknown whether distractor frequency can be learned implicitly across distinct contexts.
View Article and Find Full Text PDFSensors (Basel)
December 2024
College of Information Engineering, Henan University of Science and Technology, Luoyang 471023, China.
In order to achieve infrared aircraft detection under interference conditions, this paper proposes an infrared aircraft detection algorithm based on high-resolution feature-enhanced semantic segmentation network. Firstly, the designed location attention mechanism is utilized to enhance the current-level feature map by obtaining correlation weights between pixels at different positions. Then, it is fused with the high-level feature map rich in semantic features to construct a location attention feature fusion network, thereby enhancing the representation capability of target features.
View Article and Find Full Text PDFSci Rep
January 2025
School of Information and Communication Engineering, North University of China, Taiyuan, 030051, China.
The Insulated Gate Bipolar Transistor (IGBT) is a crucial power semiconductor device, and the integrity of its internal structure directly influences both its electrical performance and long-term reliability. However, the precise semantic segmentation of IGBT ultrasonic tomographic images poses several challenges, primarily due to high-density noise interference and visual distortion caused by target warping. To address these challenges, this paper constructs a dedicated IGBT ultrasonic tomography (IUT) dataset using Scanning Acoustic Microscopy (SAM) and proposes a lightweight Multi-Scale Fusion Network (LMFNet) aimed at improving segmentation accuracy and processing efficiency in ultrasonic images analysis.
View Article and Find Full Text PDFBiol Sport
January 2025
Department of Training and Movement Science, Institute of Sport Science, Johannes Gutenberg-University Mainz, Mainz, Germany.
Despite the development of various motor learning models over many decades, the question of which model is most effective under which conditions to optimize the acquisition of skills remains a heated and recurring debate. This is particularly important in connection with learning sports movements with a high strength component. This study aims to examine the acute effects of various motor learning models on technical efficiency and force production during the Olympic snatch movement.
View Article and Find Full Text PDFSensors (Basel)
December 2024
School of Surveying and Geo-Informatics, Shandong Jianzhu University, Fengming Road, Jinan 250101, China.
Optical remote sensing images have a wide range of applications but are often affected by cloud cover, which interferes with subsequent analysis. Therefore, cloud removal has become indispensable in remote sensing data processing. The Tibetan Plateau, as a sensitive region to climate change, plays a crucial role in the East Asian water cycle and regional climate due to its snow cover.
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