Journal articles: 'Coordinate Attention'

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Battich, Lucas, Merle Fairhurst, and Ophelia Deroy. "Coordinating attention requires coordinated senses." Psychonomic Bulletin & Review 27, no. 6 (July 14, 2020): 1126–38. http://dx.doi.org/10.3758/s13423-020-01766-z.

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AbstractFrom playing basketball to ordering at a food counter, we frequently and effortlessly coordinate our attention with others towards a common focus: we look at the ball, or point at a piece of cake. This non-verbal coordination of attention plays a fundamental role in our social lives: it ensures that we refer to the same object, develop a shared language, understand each other’s mental states, and coordinate our actions. Models of joint attention generally attribute this accomplishment to gaze coordination. But are visual attentional mechanisms sufficient to achieve joint attention, in all cases? Besides cases where visual information is missing, we show how combining it with other senses can be helpful, and even necessary to certain uses of joint attention. We explain the two ways in which non-visual cues contribute to joint attention: either as enhancers, when they complement gaze and pointing gestures in order to coordinate joint attention on visible objects, or as modality pointers, when joint attention needs to be shifted away from the whole object to one of its properties, say weight or texture. This multisensory approach to joint attention has important implications for social robotics, clinical diagnostics, pedagogy and theoretical debates on the construction of a shared world.

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Xie, Chao, Hongyu Zhu, and Yeqi Fei. "Deep coordinate attention network for single image super‐resolution." IET Image Processing 16, no. 1 (November 16, 2021): 273–84. http://dx.doi.org/10.1049/ipr2.12364.

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Golomb, J. D., M. M. Chun, and J. A. Mazer. "The Native Coordinate System of Spatial Attention Is Retinotopic." Journal of Neuroscience 28, no. 42 (October 15, 2008): 10654–62. http://dx.doi.org/10.1523/jneurosci.2525-08.2008.

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Barrett, Doug J. K., Mark F. Bradshaw, and David Rose. "Endogenous Shifts of Covert Attention Operate within Multiple Coordinate Frames: Evidence from a Feature-Priming Task." Perception 32, no. 1 (January 2003): 41–52. http://dx.doi.org/10.1068/p3298.

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The locations of visual objects and events in the world are represented in a number of different coordinate frameworks. For example, a visual transient is known to attract (exogenous) attention and facilitate performance within an egocentric framework. However, when attention is allocated voluntarily to a particular visual feature (ie endogenous attention), the location of that feature appears to be variously encoded either within an allocentric framework or in a spatially invariant manner. In three experiments we investigated the importance of location for the allocation of endogenous attention and whether egocentric and/or allocentric spatial frameworks are involved. Primes and targets were presented in four conditions designed to vary systematically their spatial relationships in egocentric and allocentric coordinates. A reliable effect of egocentric priming was found in all three experiments, which suggests that endogenous shifts of attention towards targets defined by a particular feature operate in an egocentric representation of visual space. In addition, allocentric priming was also found for targets primed by their colour or shape. This suggests that attending to targets primed by nonspatial attributes results in facilitation that is localised in more than one coordinate frame of spatial reference.

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Pavlovskaya, Marina, Itzhak Glass, Nachum Soroker, Baruch Blum, and Zeev Groswasser. "Coordinate Frame for Pattern Recognition in Unilateral Spatial Neglect." Journal of Cognitive Neuroscience 9, no. 6 (November 1997): 824–34. http://dx.doi.org/10.1162/jocn.1997.9.6.824.

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The present research examines the effect of spatial (object-centered) attentional constraints on pattern recognition. Four normal subjects and two right-hemisphere-damaged patients with left visual neglect participated in the study. Small, letterlike, prelearned patterns served as stimuli. Short exposure time prevented overt scanpaths during stimulus presentation. Attention was attracted to a central (midsagittal) hation point by precuing this location prior to each stimulus presentation. Minute (up to 1.5° of visual angle) rightward and leftward stimulus shifts caused attention to be allocated each time to a different location on the object space, while remaining in a fixed central position in viewercentered coordinates. The task was to decide which of several prelearned patterns was presented in each trial. In the normal subjects, best performance was achieved when the luminance centroid (LC; derived from the analysis of low-spatial frequencies in the object space) of each pattern coincided with the spatial position of the precue. In contrast, the patients with neglect showed optimal recognition performance when precuing attracted attention to locations within the object space, to the left of the LC. The normal performance suggests that the LC may serve as a center of gravity for attention allocation during pattern recognition. This point seems to be the target location where focal attention is normally directed, following a primary global analysis based on the low spatial frequencies. Thus, the LC of a simple pattern may serve as the origin point for an object-centered-coordiate-frame (OCCF), dividing it into right and left. This, in turn, serves to create a prototype description of the pattern, in its own coordinates, in memory, to be addressed during subsequent recognition tasks. The best match of the percept with the stored description may explain the observed advantage of allocating attention to the LC. The performance of the brain- damaged patients can be explained in terms of neglect operating in the OCCE

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Suslin, V. P., A. V. Dzhunkovsky, A. V. Popovkin, and D. A. Holodov. "Virtual coordinate-measuring machine." Izvestiya MGTU MAMI 6, no. 2-2 (March 20, 2012): 189–93. http://dx.doi.org/10.17816/2074-0530-68503.

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The article considers the principles of construction and realization of the virtual coordinate-measuring machine, which allows to develop on the personal computers the control programs for real coordinate-measuring machines not occupying their production time. In the development of virtual coordinate-measuring machine special attention is paid to increase the realism of the simulation of measurements on the screen of your PC and increase the performance of the software modules to create a regime of real time.

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Zhang, Yuhao, and Zhongwei Wang. "Concrete Surface Crack Recognition Based on Coordinate Attention Neural Networks." Computational Intelligence and Neuroscience 2022 (August 11, 2022): 1–8. http://dx.doi.org/10.1155/2022/7454746.

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In highway transportation infrastructure such as highways and tunnels, the proportion of concrete consumption is the highest, and concrete cracks are common concrete problems. Concrete cracks will greatly affect the bearing capacity and safety of the structure, easily leading to the interruption of transportation lines, causing great economic losses, and endangering personnel safety. Therefore, the effective identification and timely reporting of concrete cracks is of great significance for the maintenance of infrastructure such as roads and tunnels. In this paper, the CaNet, a deep learning network for identifying concrete cracks, is proposed, which takes ResNet50 as the backbone network. In order to capture the area with a small proportion of cracks, we added coordinate attention to the residual unit of ResNet50 to capture the cross-channel information, direction-aware information, and position-sensitive information from many vertical and horizontal directions so that the network can more accurately locate the narrow crack area. In experiments 3.2 and 3.3, the CaNet has an accuracy rate of 89.6%, which is higher than that of the compared network. In addition, the recall, F1 score, and precision of the CaNet network are 86%, 85%, and 87% , respectively. Therefore, the CaNet model is effective for identifying concrete cracks.

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Li, Xinze, Bangyu Wu, Xu Zhu, and Hui Yang. "Consecutively Missing Seismic Data Interpolation Based on Coordinate Attention Unet." IEEE Geoscience and Remote Sensing Letters 19 (2022): 1–5. http://dx.doi.org/10.1109/lgrs.2021.3128511.

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Hilo-Merkovich, Rinat, and Shlomit Yuval-Greenberg. "The coordinate system of endogenous spatial attention during smooth pursuit." Journal of Vision 20, no. 7 (July 28, 2020): 26. http://dx.doi.org/10.1167/jov.20.7.26.

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Ben Mocha, Yitzchak, Roger Mundry, and Simone Pika. "Joint attention skills in wild Arabian babblers ( Turdoides squamiceps ): a consequence of cooperative breeding?" Proceedings of the Royal Society B: Biological Sciences 286, no. 1900 (April 3, 2019): 20190147. http://dx.doi.org/10.1098/rspb.2019.0147.

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Human cooperation strongly relies on the ability of interlocutors to coordinate each other's attentional state: joint attention. One predominant hypothesis postulates that this hallmark of the unique cognitive system of humans evolved due to the combination of an ape-like cognitive system and the prosocial motives that facilitate cooperative breeding. Here, we tested this hypothesis by investigating communicative interactions of a cooperatively breeding bird species, the Arabian babbler ( Turdoides squamiceps ). The behaviour of 12 wild social groups was observed focusing on two distinct communicative behaviours: object presentation and babbler walk . The results showed that both behaviours fulfilled the criteria for first-order intentional communication and involved co-orientation of recipients' attention. In turn, recipients responded with cooperative and communicative acts that resulted in coordinated joint travel between interlocutors. These findings provide the first evidence that another animal species shows several key criteria traditionally used to infer joint attention in prelinguistic human infants. Furthermore, they emphasize the influence of cooperative breeding on sophisticated socio-cognitive performances, while questioning the necessity of an ape-like cognitive system underlying joint attentional behaviour.

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Guo, Runze, Zhen Zuo, Shaojing Su, and Bei Sun. "A Surface Target Recognition Algorithm Based on Coordinate Attention and Double-Layer Cascade." Wireless Communications and Mobile Computing 2022 (May 10, 2022): 1–11. http://dx.doi.org/10.1155/2022/6317691.

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As a branch of target recognition, surface target recognition plays an irreplaceable role in both military and civilian applications. However, the large target size variation, low image resolution, and high real-time requirements pose challenges to existing algorithms. To address the issues, we take YOLOv5 as a backbone and adopt coordinate attention and a double-layer cascade structure to enhance both the recognition performance and speed. Specifically, coordinate attention is introduced to guide the corresponding network to focus on discriminative features by capturing channel and location information. Meanwhile, the double-layer cascade structure is designed for finely extracting and aggregating semantic features and spatial features at different scales. We test the model on the COCO dataset, the VOC dataset, and self-built surface target dataset. Experimental results show that proposed coordinate attention module and multiscale module improve the recognition effect of multiscale surface targets and meet the requirement of real time.

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Wang, Zengkun, Yang Cao, Hongfei Yu, Caihua Sun, Xuejian Chen, Zhanggen Jin, and Weili Kong. "Scene Classification of Remote Sensing Images Using EfficientNetV2 with Coordinate Attention." Journal of Physics: Conference Series 2289, no. 1 (June 1, 2022): 012026. http://dx.doi.org/10.1088/1742-6596/2289/1/012026.

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Abstract The high intra class diversity of remote sensing image scene often leads to the problem of difficult classification of remote sensing image scenes. Therefore, this paper proposes the CA-EfficientNetV2 model, embedding the coordinate attention into the head of the EfficientNetV2 network to enhance the classification effect. The coordinate attention is used to generate the position relationship between image spaces and channels so as to learn features efficiently. We trained three improved models CA-EfficientNetV2-S, CA-EfficientNetV2-M and CA-EfficientNetV2-L on UC Merced remote sensing dataset respectively. The classification accuracy reached 99.55%, 97.49% and 97.09% respectively. Among them, CA-EfficientNetV2-S had the best effect, which was improved by 0.8% compared with the original network.

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Li, Min, Mengshan Li, Bilong Liu, Jiang Liu, Zhen Liu, and Dijia Luo. "Spatio-Temporal Traffic Flow Prediction Based on Coordinated Attention." Sustainability 14, no. 12 (June 16, 2022): 7394. http://dx.doi.org/10.3390/su14127394.

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Traffic flow prediction can provide effective support for traffic management and control and plays an important role in the traffic system. Traffic flow has strong spatio-temporal characteristics, and existing traffic flow prediction models tend to extract long-term dependencies of traffic flow in the temporal and spatial dimensions individually, often ignoring the potential correlations existing between spatio-temporal information of traffic flow. In order to further improve the prediction accuracy, this paper proposes a coordinated attention-based spatio-temporal graph convolutional network (CVSTGCN) model for simultaneously and dynamically capturing the long-term dependencies existing between the spatio-temporal information of traffic flows. CVSTGCN is composed of a full convolutional network structure, which combines coordinate methods to specify the influence degrees of different feature information in different spatio-temporal dimensions, and the spatio-temporal information of different spatio-temporal dimensions by the graph convolutional network. In addition, the hard-swish activation function is introduced to replace the Rectified Linear Unit (ReLU) activation function in the prediction of traffic flow. Finally, evaluation experiments are conducted on two real datasets to demonstrate that the proposed model has the best prediction performance in both short-term and long-term forecasting.

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Park, Brian Seongyup. "How Hybrid Organizations Coordinate Multiple Demands by Sequential and Flexible Attention." Academy of Management Proceedings 2013, no. 1 (January 2013): 15306. http://dx.doi.org/10.5465/ambpp.2013.15306abstract.

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Barrett, Doug J. K., Mark F. Bradshaw, David Rose, John Everatt, and Peter J. Simpson. "Reflexive Shifts of Covert Attention Operate in an Egocentric Coordinate Frame." Perception 30, no. 9 (September 2001): 1083–91. http://dx.doi.org/10.1068/p3165.

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Covert shifts of attention have been shown to improve detection and discrimination thresholds for a range of visual stimuli. Although there is some evidence to suggest that the allocation of attention to a particular region of interest occurs in a retinotopic frame of reference, the importance of an allocentric, or object-based, framework has gained widespread empirical support. The current experiment investigates the nature of the spatial representation in which covert shifts of attention occur in response to a reflexive prime. Primes and targets were presented in four conditions designed to vary systematically the validity of the spatial relationship between the prime and target in egocentric or allocentric coordinate frameworks. A significant advantage, in terms of reaction time and correct identification, was found for targets located in positions previously primed in an egocentric (but not allocentric) framework whereas there was no advantage for locations primed in an allocentric (but not egocentric) framework. These results suggest that the allocation of covert spatial attention within an egocentric framework may be more important than previously thought.

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Shao, Mingyue, Peitong He, Yanqi Zhang, Shuo Zhou, Ning Zhang, and Jianhua Zhang. "Identification Method of Cotton Leaf Diseases Based on Bilinear Coordinate Attention Enhancement Module." Agronomy 13, no. 1 (December 27, 2022): 88. http://dx.doi.org/10.3390/agronomy13010088.

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Cotton is an important cash crop. Cotton diseases have a considerable adverse influence on cotton yield and quality. Timely and accurate identification of cotton disease types is important. The accuracy of cotton leaf disease identification is limited by unpredictable factors in natural settings, such as the presence of a complex background. Therefore, this paper proposes a cotton leaf disease identification model based on a bilinear coordinate attention enhancement module. It reduces the loss of feature information by bilinear coordinate attention embedding feature maps spatial coordinate information and feature fusion. Hence the model is more focused on the leaf disease region and reduces the attention to redundant information such as healthy regions. It also achieves the precise localization and amplification of attention to the leaf disease region through data enhancement, which effectively improves the recognition accuracy of cotton leaf diseases in a natural setting. By experiments, the identification accuracy of the proposed model is 96.61% and the parameter size is 21.55 × 106. Compared with other existing models, the identification accuracy of the proposed model is greatly improved without increasing the parameter size. This study can not only provide decision support for the timely diagnosis and prevention of cotton leaf diseases but also validate a paradigm for the identification of other crop leaf diseases.

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Astle, D. E. "Going from a Retinotopic to a Spatiotopic Coordinate System for Spatial Attention." Journal of Neuroscience 29, no. 13 (April 1, 2009): 3971–73. http://dx.doi.org/10.1523/jneurosci.5929-08.2009.

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Okubo, Matia, Bruno Laeng, Ayako Saneyoshi, and Chikashi Michimata. "Exogenous attention differentially modulates the processing of categorical and coordinate spatial relations." Acta Psychologica 135, no. 1 (September 2010): 1–11. http://dx.doi.org/10.1016/j.actpsy.2010.04.004.

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Liu, Yong, Weixun Wang, Yujing Hu, Jianye Hao, Xingguo Chen, and Yang Gao. "Multi-Agent Game Abstraction via Graph Attention Neural Network." Proceedings of the AAAI Conference on Artificial Intelligence 34, no. 05 (April 3, 2020): 7211–18. http://dx.doi.org/10.1609/aaai.v34i05.6211.

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In large-scale multi-agent systems, the large number of agents and complex game relationship cause great difficulty for policy learning. Therefore, simplifying the learning process is an important research issue. In many multi-agent systems, the interactions between agents often happen locally, which means that agents neither need to coordinate with all other agents nor need to coordinate with others all the time. Traditional methods attempt to use pre-defined rules to capture the interaction relationship between agents. However, the methods cannot be directly used in a large-scale environment due to the difficulty of transforming the complex interactions between agents into rules. In this paper, we model the relationship between agents by a complete graph and propose a novel game abstraction mechanism based on two-stage attention network (G2ANet), which can indicate whether there is an interaction between two agents and the importance of the interaction. We integrate this detection mechanism into graph neural network-based multi-agent reinforcement learning for conducting game abstraction and propose two novel learning algorithms GA-Comm and GA-AC. We conduct experiments in Traffic Junction and Predator-Prey. The results indicate that the proposed methods can simplify the learning process and meanwhile get better asymptotic performance compared with state-of-the-art algorithms.

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Wang, Xiaohang, and Hongmin Deng. "A Multi-Feature Representation of Skeleton Sequences for Human Interaction Recognition." Electronics 9, no. 1 (January 19, 2020): 187. http://dx.doi.org/10.3390/electronics9010187.

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Inspired from the promising performances achieved by recurrent neural networks (RNN) and convolutional neural networks (CNN) in action recognition based on skeleton, this paper presents a deep network structure which combines both CNN for classification and RNN to achieve attention mechanism for human interaction recognition. Specifically, the attention module in this structure is utilized to give various levels of attention to various frames by different weights, and the CNN is employed to extract the high-level spatial and temporal information of skeleton data. These two modules seamlessly form a single network architecture. In addition, to eliminate the impact of different locations and orientations, a coordinate transformation is conducted from the original coordinate system to the human-centric coordinate system. Furthermore, three different features are extracted from the skeleton data as the inputs of three subnetworks, respectively. Eventually, these subnetworks fed with different features are fused as an integrated network. The experimental result shows the validity of the proposed approach on two widely used human interaction datasets.

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Beigie, Darin. "Coordinate Plane Set Detective." Mathematics Teaching in the Middle School 9, no. 5 (January 2004): 251–55. http://dx.doi.org/10.5951/mtms.9.5.0251.

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Coordinate plane graphing is usually introduced to students by asking them to plot specified ordered pairs and identify points on the coordinate plane. A popular example involves plotting a collection of ordered pairs and connecting the resulting points with line segments to form geometric shapes or pictures (e.g., see Mystery Media 1990). This article describes an extension beyond plotting specified points that involves plotting collections of ordered pairs according to prescribed set conditions, such as the one shown in figure 1. These coordinate plane sets can form points, line segments, rays, lines, curves, and regions. I give these problems in an informal manner to my prealgebra students to foster a more robust appreciation of ordered pairs and the coordinate plane before progressing to table-of-values calculations. The problems ask students to investigate the coordinate plane and make decisions about appropriate ordered pairs, to see patterns, to construct pairs, and to make comparisons. The problems encourage thinking and questioning that help with algebraic topics discussed later on, such as solving for the intercepts of an equation, graphing an equation like x = 5, invoking the zero product property, and graphing an inequality (e.g., see Larson, Boswell, Kanold, and Stiff 2001 for a discussion of these algebraic topics). Furthermore, these set problems generally stretch students' minds, often requiring open-ended search and discovery as well as careful investigation and attention to computational details involving absolute values, inequalities, integer operations, arithmetic expressions, and number theory.

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Yu, Chen, and Linda B. Smith. "Joint Attention without Gaze Following: Human Infants and Their Parents Coordinate Visual Attention to Objects through Eye-Hand Coordination." PLoS ONE 8, no. 11 (November 13, 2013): e79659. http://dx.doi.org/10.1371/journal.pone.0079659.

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Yi, Shi, Junjie Li, Xi Liu, and Xuesong Yuan. "CCAFFMNet: Dual-spectral semantic segmentation network with channel-coordinate attention feature fusion module." Neurocomputing 482 (April 2022): 236–51. http://dx.doi.org/10.1016/j.neucom.2021.11.056.

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김덕중, Hyung-Chul Li, and 김신우. "Spatial attention allocation in retinal vs. spatial coordinate with and without referential background." Korean Journal of Cognitive and Biological Psychology 26, no. 3 (September 2014): 151–69. http://dx.doi.org/10.22172/cogbio.2014.26.3.002.

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Cazzato, Valentina, Emiliano Macaluso, Filippo Crostella, and Salvatore Maria Aglioti. "Mapping reflexive shifts of attention in eye-centered and hand-centered coordinate systems." Human Brain Mapping 33, no. 1 (March 9, 2011): 165–78. http://dx.doi.org/10.1002/hbm.21202.

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Serences, John T., Sarah Shomstein, Andrew B. Leber, Xavier Golay, Howard E. Egeth, and Steven Yantis. "Coordination of Voluntary and Stimulus-Driven Attentional Control in Human Cortex." Psychological Science 16, no. 2 (February 2005): 114–22. http://dx.doi.org/10.1111/j.0956-7976.2005.00791.x.

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Visual attention may be voluntarily directed to particular locations or features (voluntary control), or it may be captured by salient stimuli, such as the abrupt appearance of a new perceptual object (stimulus-driven control). Most often, however, the deployment of attention is the result of a dynamic interplay between voluntary attentional control settings (e.g., based on prior knowledge about a target's location or color) and the degree to which stimuli in the visual scene match these voluntary control settings. Consequently, nontarget items in the scene that share a defining feature with the target of visual search can capture attention, a phenomenon termed contingent attentional capture. We used functional magnetic resonance imaging to show that attentional capture by target-colored distractors is accompanied by increased cortical activity in corresponding regions of retinotopically organized visual cortex. Concurrent activation in the temporo-parietal junction and ventral frontal cortex suggests that these regions coordinate voluntary and stimulus-driven attentional control settings to determine which stimuli effectively compete for attention.

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Kaplan, Frédéric, and Verena V. Hafner. "The challenges of joint attention." Epigenetic robotics 7, no. 2 (June 29, 2006): 135–69. http://dx.doi.org/10.1075/is.7.2.04kap.

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This article discusses the concept of joint attention and the different skills underlying its development. Research in developmental psychology clearly states that the development of skills to understand, manipulate and coordinate attentional behavior plays a pivotal role for imitation, social cognition and the development of language. However, beside the fact that joint attention has recently received an increasing interest in the robotics community, existing models concentrate only on partial and isolated elements of these phenomena. In the line of Tomasello’s research, we argue that joint attention is much more than simultaneous looking because it implies a shared intentional relation to the world. This requires skills for attention detection, attention manipulation, social coordination and, most importantly, intentional understanding. After defining joint attention and its challenges, the current state-of-the-art of robotic and computational models relevant for this issue is discussed in relation to a developmental timeline drawn from results in child studies. From this survey, we identify open issues and challenges that still need to be addressed to understand the development of the various aspects of joint attention and conclude with the potential contribution of robotic models.

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Fedyaev, Vladimir, Peter Lyudogovsky, and Maria Komkova. "Estimation of the Error in Measuring the Coordinates of Vibrating Objects Using Laser Coordinate Measuring Systems. General Provisions." MATEC Web of Conferences 346 (2021): 03110. http://dx.doi.org/10.1051/matecconf/202134603110.

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The issues of assessing the measurement error using laser coordinate measuring systems (LCMS) of the geometric parameters of vibrating, and also vibrating objects are considered. At the same time, attention is focused on their time-average values. In a number of special cases, calculated relations are given to estimate the average errors in measuring the amplitude and frequency of vibrations of the objects under consideration, their geometric parameters, such as the distance to the laser tracker, coordinates of points on the surface, and other indicators. It is noted that these ratios were obtained for the first time, therefore, in order to increase their reliability, it is possible to introduce them into the corresponding dependences of correcting coefficients and functions.

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Rothenberg, Katheryn E., and Rodrigo Fernandez-Gonzalez. "Forceful closure: cytoskeletal networks in embryonic wound repair." Molecular Biology of the Cell 30, no. 12 (June 2019): 1353–58. http://dx.doi.org/10.1091/mbc.e18-04-0248.

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Embryonic tissues heal wounds rapidly and without scarring, in a process conserved across species and driven by collective cell movements. The mechanisms of coordinated cell movement during embryonic wound closure also drive tissue development and cancer metastasis; therefore, embryonic wound repair has received considerable attention as a model of collective cell migration. During wound closure, a supracellular actomyosin cable at the wound edge coordinates cells, while actin-based protrusions contribute to cell crawling and seamless wound healing. Other cytoskeletal networks are reorganized during wound repair: microtubules extend into protrusions and along cell–cell boundaries as cells stretch into damaged regions, septins accumulate at the wound margin, and intermediate filaments become polarized in the cells adjacent to the wound. Thus, diverse cytoskeletal networks work in concert to maintain tissue structure, while also driving and organizing cell movements to promote rapid repair. Understanding the signals that coordinate the dynamics of different cytoskeletal networks, and how adhesions between cells or with the extracellular matrix integrate forces across cells, will be important to elucidate the mechanisms of efficient embryonic wound healing and may have far-reaching implications for developmental and cancer cell biology.

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Fukushima, T., M. K. Fujimoto, H. Kinoshita, and S. Aoki. "System of astronomical constants in the relativistic framework." Symposium - International Astronomical Union 114 (1986): 187–88. http://dx.doi.org/10.1017/s0074180900148156.

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The relation between the units and the readings of time and space coordinates of the terrestrial and the barycentric frames is discussed from the viewpoint of general relativity. Attention is paid to the unit of space coordinates since the International Astronomical Union (IAU) regulates only the unit of time coordinate in the above two frames. Two definitions on unit of length are examined and their effects on the numerical expression of coordinate transformation, equations of planetary motions, and those for light propagation time are discussed. A clear conflict is found between the IAU(1976) recommendation on the definition of the time-scales in different frames and the statement that all constants in the IAU(1976) new system of astronomical constants are defined in terms of the international system of units (SI units). In order to dissolve this conflict, one of the two examined definitions on unit of length is proposed to be adopted, which requests the least alteration on the current procedures to analyze the astrometric observations such as radar/laser rangings, range and range-rate measurements, and very long baseline interferometric observations. An interpretation of numerical values in the IAU(1976) system of astronomical constants is also presented. It is stressed that the definition proposed in this paper requires that a slightly different formula from the current one be used in the numerical transformation of coordinates between the terrestrial and the barycentric frames.

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Li, Zhong, Chen Wu, Qi Han, Mingyang Hou, Guorong Chen, and Tengfei Weng. "CASI-Net: A Novel and Effect Steel Surface Defect Classification Method Based on Coordinate Attention and Self-Interaction Mechanism." Mathematics 10, no. 6 (March 17, 2022): 963. http://dx.doi.org/10.3390/math10060963.

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The surface defects of a hot-rolled strip will adversely affect the appearance and quality of industrial products. Therefore, the timely identification of hot-rolled strip surface defects is of great significance. In order to improve the efficiency and accuracy of surface defect detection, a lightweight network based on coordinate attention and self-interaction (CASI-Net), which integrates channel domain, spatial information, and a self-interaction module, is proposed to automatically identify six kinds of hot-rolled steel strip surface defects. In this paper, we use coordinate attention to embed location information into channel attention, which enables the CASI-Net to locate the region of defects more accurately, thus contributing to better recognition and classification. In addition, features are converted into aggregation features from the horizontal and vertical direction attention. Furthermore, a self-interaction module is proposed to interactively fuse the extracted feature information to improve the classification accuracy. The experimental results show that CASI-Net can achieve accurate defect classification with reduced parameters and computation.

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Shuang, Feng, Pei Li, Yong Li, Zhenxin Zhang, and Xu Li. "MSIDA-Net: Point Cloud Semantic Segmentation via Multi-Spatial Information and Dual Adaptive Blocks." Remote Sensing 14, no. 9 (May 3, 2022): 2187. http://dx.doi.org/10.3390/rs14092187.

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Large-scale 3D point clouds are rich in geometric shape and scale information but they are also scattered, disordered and unevenly distributed. These characteristics lead to difficulties in learning point cloud semantic segmentations. Although many works have performed well in this task, most of them lack research on spatial information, which limits the ability to learn and understand the complex geometric structure of point cloud scenes. To this end, we propose the multispatial information and dual adaptive (MSIDA) module, which consists of a multispatial information encoding (MSI) block and dual adaptive (DA) blocks. The MSI block transforms the information of the relative position of each centre point and its neighbouring points into a cylindrical coordinate system and spherical coordinate system. Then the spatial information among the points can be re-represented and encoded. The DA blocks include a Coordinate System Attention Pooling Fusion (CSAPF) block and a Local Aggregated Feature Attention (LAFA) block. The CSAPF block weights and fuses the local features in the three coordinate systems to further learn local features, while the LAFA block weights the local aggregated features in the three coordinate systems to better understand the scene in the local region. To test the performance of the proposed method, we conducted experiments on the S3DIS, Semantic3D and SemanticKITTI datasets and compared the proposed method with other networks. The proposed method achieved 73%, 77.8% and 59.8% mean Intersection over Union (mIoU) on the S3DIS, Semantic3D and SemanticKITTI datasets, respectively.

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Zha, Mingfeng, Wenbin Qian, Wenlong Yi, and Jing Hua. "A Lightweight YOLOv4-Based Forestry Pest Detection Method Using Coordinate Attention and Feature Fusion." Entropy 23, no. 12 (November 27, 2021): 1587. http://dx.doi.org/10.3390/e23121587.

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Traditional pest detection methods are challenging to use in complex forestry environments due to their low accuracy and speed. To address this issue, this paper proposes the YOLOv4_MF model. The YOLOv4_MF model utilizes MobileNetv2 as the feature extraction block and replaces the traditional convolution with depth-wise separated convolution to reduce the model parameters. In addition, the coordinate attention mechanism was embedded in MobileNetv2 to enhance feature information. A symmetric structure consisting of a three-layer spatial pyramid pool is presented, and an improved feature fusion structure was designed to fuse the target information. For the loss function, focal loss was used instead of cross-entropy loss to enhance the network’s learning of small targets. The experimental results showed that the YOLOv4_MF model has 4.24% higher mAP, 4.37% higher precision, and 6.68% higher recall than the YOLOv4 model. The size of the proposed model was reduced to 1/6 of that of YOLOv4. Moreover, the proposed algorithm achieved 38.62% mAP with respect to some state-of-the-art algorithms on the COCO dataset.

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Borst, Gregoire, and Stephen M. Kosslyn. "Varying the scope of attention alters the encoding of categorical and coordinate spatial relations." Neuropsychologia 48, no. 9 (July 2010): 2769–72. http://dx.doi.org/10.1016/j.neuropsychologia.2010.04.027.

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Liu, Chen, Degang Yang, Liu Tang, Xun Zhou, and Yi Deng. "A Lightweight Object Detector Based on Spatial-Coordinate Self-Attention for UAV Aerial Images." Remote Sensing 15, no. 1 (December 23, 2022): 83. http://dx.doi.org/10.3390/rs15010083.

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Object detection is one of the most widespread applications for numerous Unmanned Aerial Vehicle (UAV) tasks. Due to the shooting angle and flying height of the UAV, compared with general scenarios, small objects account for a large proportion of aerial images, and common object detectors are not extremely effective in aerial images. Moreover, since the computing resources of UAV platforms are generally limited, the deployment of common detectors with a large number of parameters on UAV platforms is difficult. This paper proposes a lightweight object detector YOLO-UAVlite for aerial images. Firstly, the spatial attention module and coordinate attention module are modified and combined to form a novel Spatial-Coordinate Self-Attention (SCSA) module, which integrates spatial, location, and channel information to enhance object representation. On this basis, we construct a lightweight backbone, named SCSAshufflenet, which combines the Enhanced ShuffleNet (ES) network with the proposed SCSA module to improve feature extraction and reduce model size. Secondly, we propose an improved feature pyramid model, namely Slim-BiFPN, where we construct new lightweight convolutional blocks to reduce the information loss during the feature map fusion process while reducing the model weights. Finally, the localization loss function is modified to increase the bounding box regression rate while improving the localization accuracy. Extensive experiments conducted on the VisDrone-DET2021 dataset indicate that, compared with the YOLOv5-N baseline, the proposed YOLO-UAVlite reduces the number of parameters by 25.8% and achieves gains of 10.9% in mAP0.50. Compared with other lightweight detectors, both the mAP and the number of parameters are improved.

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SANDON, PETER A. "CONTROL OF EYE AND ARM MOVEMENTS USING ACTIVE, ATTENTIONAL VISION." International Journal of Pattern Recognition and Artificial Intelligence 08, no. 06 (December 1994): 1471–91. http://dx.doi.org/10.1142/s0218001494000711.

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Recent related approaches in the areas of vision, motor control and planning are attempting to reduce the computational requirements of each process by restricting the class of problems that can be addressed. Active vision, differential kinematics and reactive planning are all characterized by their minimal use of representations, which simplifies both the required computations and the acquisition of models. This paper describes an approach to visually-guided motor control that is based on active vision and differential kinematics, and is compatible with reactive planning. Active vision depends on an ability to choose a region of the visual environment for task-specific processing. Visual attention provides a mechanism for choosing the region to be processed in a task-specific way. In addition, this attentional mechanism provides the interface between the vision and motor systems by representing visual position information in a 3-D retinocentric coordinate frame. Coordinates in this frame are transformed into eye and arm motor coordinates using kinematic relations expressed differentially. A real-time implementation of these visuomotor mechanisms has been used to develop a number of visually-guided eye and arm movement behaviors.

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Sleptsov, V. V., V. L. Afonin, A. E. Ablaeva, and Ba Phuong Dinh. "Development of an information measuring and control system for a quadrocopter." Russian Technological Journal 9, no. 6 (December 2, 2021): 26–36. http://dx.doi.org/10.32362/2500-316x-2021-9-6-26-36.

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The article deals with the issues of synthesis and analysis of information-measuring and control systems of quadrocopters. The main sensors and modules used to determine the parameters of the coordinates of quadrocopters are given. The speed-controlled electric drives used for control and the features of their choice are considered. The coordinate systems (fixed and mobile) and the kinematic scheme are given, according to which a system of differential equations is presented. The system describes the dynamics of the quadrocopter movement and takes into account the expected smooth movement of the quadrocopter with small roll and pitch angles. A functional scheme and a mathematical model of the information-measuring and control system of the quadrocopter in the form of a block diagram are developed taking into account the influence of delays in the receipt of information from the sensors of the quadrocopter parameters. A special feature of this work is to take into account the specific characteristics of the elements: adjustable electric drives (both direct and alternating current), parameter sensors (barometers, accelerometers, rangefinders, etc.). The paper studies an illustrative algorithm for the operation of the informationmeasuring and control system of the quadcopter. The type and parameters of the controllers of the quadrocopter control systems are determined. Special attention is paid to the settings for the control contours at the corresponding coordinates. The influence of the controllers of the coordinate control systems of the information-measuring and control systems of the quadrocopter on the effects of the interaction of coordinates is considered. The simulation results are presented. The optimal number of control loops for the coordinates of the information-measuring and control systems of the quadrocopter and the optimal type of settings for obtaining smooth transients (without overshoot) and for excluding the interaction of coordinates on quality indicators are determined.

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Rao, P. K. "Moving Toward the Next G-20 Summit." Global Economy Journal 9, no. 1 (March 2009): 1850160. http://dx.doi.org/10.2202/1524-5861.1481.

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This brief paper a) focuses on important elements of the November Summit of G-20 Countries that resulted in the Washington Declaration; b) highlights problems with credit rating agencies and financial regulation; c) argues that the IMF is a laggard in being able to coordinate any major efforts to prevent, mitigate, or coordinate global issues; and d) identifies a number of important issues that deserve attention at the next G-20 Summit to be held in London on April 2nd.

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Zhang, Yao, Yang Li, and Zhisong Pan. "Inferior and Coordinate Distillation for Object Detectors." Sensors 22, no. 15 (July 30, 2022): 5719. http://dx.doi.org/10.3390/s22155719.

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Current distillation methods only distill between corresponding layers, and do not consider the knowledge contained in preceding layers. To solve this problem, we analyzed the guiding effect of the inferior features of a teacher model on the coordinate feature of a student model, and proposed inferior and coordinate distillation for object detectors. The proposed method utilizes the rich information contained in different layers of the teacher model; such that the student model can review the old information and learn the new information, in addition to the dark knowledge in the teacher model. Moreover, the refine module is used to align the features of different layers, distinguish the spatial and channel to extract attention, strengthen the correlation between the features of different stages, and prevent the disorder caused by merging. Exclusive experiments were conducted on different object detectors. The results for the mean average precision (mAP) obtained using Faster R-CNN, RetinaNet, and fully convolutional one-stage object detector (FCOS) with ResNet-50 as its backbone were 40.5%, 39.8%, and 42.8% with regard to the COCO dataset, respectively; which are 2.1%, 2.4%, and 4.3% higher than the benchmark, respectively.

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Chen, Shaolong, Changzhen Qiu, Weiping Yang, and Zhiyong Zhang. "Multiresolution Aggregation Transformer UNet Based on Multiscale Input and Coordinate Attention for Medical Image Segmentation." Sensors 22, no. 10 (May 18, 2022): 3820. http://dx.doi.org/10.3390/s22103820.

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The latest medical image segmentation methods uses UNet and transformer structures with great success. Multiscale feature fusion is one of the important factors affecting the accuracy of medical image segmentation. Existing transformer-based UNet methods do not comprehensively explore multiscale feature fusion, and there is still much room for improvement. In this paper, we propose a novel multiresolution aggregation transformer UNet (MRA-TUNet) based on multiscale input and coordinate attention for medical image segmentation. It realizes multiresolution aggregation from the following two aspects: (1) On the input side, a multiresolution aggregation module is used to fuse the input image information of different resolutions, which enhances the input features of the network. (2) On the output side, an output feature selection module is used to fuse the output information of different scales to better extract coarse-grained information and fine-grained information. We try to introduce a coordinate attention structure for the first time to further improve the segmentation performance. We compare with state-of-the-art medical image segmentation methods on the automated cardiac diagnosis challenge and the 2018 atrial segmentation challenge. Our method achieved average dice score of 0.911 for right ventricle (RV), 0.890 for myocardium (Myo), 0.961 for left ventricle (LV), and 0.923 for left atrium (LA). The experimental results on two datasets show that our method outperforms eight state-of-the-art medical image segmentation methods in dice score, precision, and recall.

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Ding, Chen, Youfa Chen, Runze Li, Dushi Wen, Xiaoyan Xie, Lei Zhang, Wei Wei, and Yanning Zhang. "Integrating Hybrid Pyramid Feature Fusion and Coordinate Attention for Effective Small Sample Hyperspectral Image Classification." Remote Sensing 14, no. 10 (May 13, 2022): 2355. http://dx.doi.org/10.3390/rs14102355.

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In recent years, hyperspectral image (HSI) classification (HSIC) methods that use deep learning have proved to be effective. In particular, the utilization of convolutional neural networks (CNNs) has proved to be highly effective. However, some key issues need to be addressed when classifying hyperspectral images (HSIs), such as small samples, which can influence the generalization ability of the CNNs and the HSIC results. To address this problem, we present a new network that integrates hybrid pyramid feature fusion and coordinate attention for enhancing small sample HSI classification results. The innovative nature of this paper lies in three main areas. Firstly, a baseline network is designed. This is a simple hybrid 3D-2D CNN. Using this baseline network, more robust spectral-spatial feature information can be obtained from the HSI. Secondly, a hybrid pyramid feature fusion mechanism is used, meaning that the feature maps of different levels and scales can be effectively fused to enhance the feature extracted by the model. Finally, coordinate attention mechanisms are utilized in the network, which can not only adaptively capture the information of the spectral dimension, but also include the direction-aware and position sensitive information. By doing this, the proposed CNN structure can extract more useful HSI features and effectively be generalized to test samples. The proposed method was shown to obtain better results than several existing methods by experimenting on three public HSI datasets.

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Cui, Jialiang, Qianwen Zhong, Shubin Zheng, Lele Peng, and Jing Wen. "A Lightweight Model for Bearing Fault Diagnosis Based on Gramian Angular Field and Coordinate Attention." Machines 10, no. 4 (April 17, 2022): 282. http://dx.doi.org/10.3390/machines10040282.

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The key to ensuring rotating machinery’s safe and reliable operation is efficient and accurate faults diagnosis. Intelligent fault diagnosis technology based on deep learning (DL) has gained increasing attention. A critical challenge is how to embed the characteristics of time series into DL to obtain stable features that correlate with equipment conditions. This study proposes a lightweight rolling bearing fault diagnosis method based on Gramian angular field (GAF) and coordinated attention (CA) to improve rolling bearing recognition performance and diagnosis efficiency. Firstly, the time domain signal is encoded into GAF images after downsampling and segmentation. This method retains the temporal relation of the time series and provides valuable features for DL. Secondly, a lightweight convolution neural network (CNN) model is constructed through depthwise separable convolution, inverse residual block, and linear bottleneck layer to learn advanced features. After that, CA is employed to capture the long-range dependencies and identify the precise position information of the GAF images with nearly no additional computational overhead. The proposed method is tested and evaluated by CWRU bearing dataset and experimental dataset. The results demonstrate that the CNN based on GAF and CA (GAF-CA-CNN) model can effectively reduce the calculation overhead of the model and achieve high diagnostic accuracy.

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Franciotti, Raffaella, Stefania D’Ascenzo, Alberto Di Domenico, Marco Onofrj, Luca Tommasi, and Bruno Laeng. "Focusing Narrowly or Broadly Attention When Judging Categorical and Coordinate Spatial Relations: A MEG Study." PLoS ONE 8, no. 12 (December 26, 2013): e83434. http://dx.doi.org/10.1371/journal.pone.0083434.

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de Freitas, Miguel Citeli, and Viktor V. Dodonov. "Coherent Phase States in the Coordinate and Wigner Representations." Quantum Reports 4, no. 4 (November 8, 2022): 509–22. http://dx.doi.org/10.3390/quantum4040036.

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In this paper, we numerically study the coordinate wave functions and the Wigner functions of the coherent phase states (CPS), paying particular attention to their differences from the standard (Klauder–Glauber–Sudarshan) coherent states, especially in the case of the high mean values of the number operator. In this case, the CPS can possess a strong coordinate (or momentum) squeezing, which is roughly twice weaker than for the vacuum squeezed states. The Robertson–Schrödinger invariant uncertainty product in the CPS logarithmically increases with the mean value of the number operator (whereas it is constant for the standard coherent states). Some measures of the (non)Gaussianity of CPS are considered.

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Huang, Feiyan, Shangyou Zeng, Jie Ke, Songtong Lei, and JinJin Wang. "A Video Description Model with Improved Attention Mechanism." Journal of Physics: Conference Series 2384, no. 1 (December 1, 2022): 012015. http://dx.doi.org/10.1088/1742-6596/2384/1/012015.

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Abstract Video description generation refers to the automatic generation of text descriptions of videos by computers, which belongs to the intersection of computer vision and natural language processing. Aiming at the problem that the traditional attention mechanism has insufficient ability to extract video features, the model is complex and the description quality is not high, this paper proposes a video description model with an improved attention mechanism. The model is based on the encoder-decoder structure, uses inception-v4 as the encoder to extract features, and introduces a lightweight coordinate attention module (CA) into the attention mechanism, which improves the feature extraction effect and reduces the model complexity, and sends the extracted important feature information into the decoder long short-term memory network (LSTM) to generate the description sentence corresponding to the video. The model is validated on the MSVD dataset using various evaluation metrics (BLEU, ROUGEL, CIDEr, METEOR). The experimental results show that the improved attention mechanism of the video description model proposed in this paper has better accuracy in different performance metrics and can further improve the performance of video description.

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BEZERRA, V. B., C. ROMERO, and SERGEY CHERVON. "EXACT SOLUTIONS OF SO(3) NONLINEAR SIGMA MODEL IN A CONIC SPACE BACKGROUND." International Journal of Modern Physics D 14, no. 11 (November 2005): 1927–40. http://dx.doi.org/10.1142/s0218271805007474.

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We consider a nonlinear sigma model coupled to the metric of a conic space. We obtain restrictions for a nonlinear sigma model to be a source of the conic space. We then study a nonlinear sigma model in the conic space background. We find coordinate transformations which reduce the chiral fields equations in the conic space background to field equations in Minkowski space–time. This enables us to apply the same methods for obtaining exact solutions in Minkowski space–time to the case of a conic space–time. In the case the solutions depend on two spatial coordinates we employ Ivanov's geometrical ansatz. We give a general analysis and also present classes of solutions in which there is dependence on three and four coordinates. We discuss with special attention the intermediate, instanton and meron solutions and their analogous in the conic space. We find differences in the total actions and topological charges of these solutions and discuss the role of the deficit angle.

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Ardliansyah, Moelki Fahmi. "IMPLEMENTASI TITIK KOORDINAT TENGAH KABUPATEN ATAU KOTA DALAM PERHITUNGAN JADWAL WAKTU SALAT." Al-Ahkam 27, no. 2 (December 1, 2017): 213. http://dx.doi.org/10.21580/ahkam.2017.27.2.1981.

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Study literature of Islamic Astronomy in case prayer times, is less from getting specific attention. Furthermore, the schedule of prayer times is very complex. Such as its still being distributed in form converting one to another area. It should be computed based on each district or city. Appearing new case that is coordinates point data (latitude and longitude) where used as center point computations. This thesis is researched the effect and importance implementation of center coordinate point from district or city in the determining of prayer times schedule. The research used mathemathic analytic descriptive and comparative analysis methods. With purpose to know in detail the comparation result from prayer times computations using center coordinate point and otherwise. The result of research shows the effect prayer times schedule can be applied for one district or city area. Meanwhile, computed prayer times schedule that use another center point coordinate not exactly can be applied in one district or city area. Though coordinate different value more than 0,5° and its position located in the south and east center coordinate point. Center coordinate point must be applied because at the base this coordinate point have been considered geographical aspect. Where in width side for the north, south, east and west have been considered and have the equilibrium distance.[]Kajian studi Astronomi Islam dalam persoalan waktu salat kurang mendapat perhatian khusus. Padahal persoalan jadwal waktu salat sangat komplek, seperti masih beredarnya jadwal waktu salat yang dikonversi dari satu daerah ke daerah lain. Sudah seharusnya jadwal waktu salat disusun berdasarkan kabupaten atau kota masing-masing. Persoalan baru yang muncul adalah data titik koordinat (lintang dan bujur) mana yang akan digunakan sebagai acuan perhitungannya. Dalam tulisan ini meneliti dampak dan perlunya implementasi titik koordinat tengah kabupaten atau kota dalam perhitungan jadwal waktu salat. Penelitian ini menggunakan metode deskriptif analitis matematis dan analisis komparatif, yang bertujuan untuk mengetahui secara detail hasil perbandingan perhitungan jadwal waktu salat dengan menggunakan titik koordinat tengah dan selain titik koordinat tengah. Penelitian ini menemukan bahwa, dampaknya jadwal waktu salat dapat diberlakukan untuk satu wilayah kabupaten atau kota. Sedangkan jadwal waktu salat yang diperhitungkan menggunakan selain titik koordinat tengah belum tentu dapat diberlakukan untuk satu wilayah kabupaten atau kota, apalagi selisih koordinatnya diatas 0,5° dan posisinya berada di sebelah selatan dan timur dari titik koordinat tengah. Titik koordinat tengah perlu diimplementasikan, karena pada dasarnya titik koordinat ini telah mempertimbangkan aspek geografis. Dimana dalam segi luas untuk bagian utara, selatan dan timur, barat nya telah dipertimbangkan dan jaraknya pun seimbang.

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Colonius, Hans, and Adele Diederich. "Multisensory Interaction in Saccadic Reaction Time: A Time-Window-of-Integration Model." Journal of Cognitive Neuroscience 16, no. 6 (July 2004): 1000–1009. http://dx.doi.org/10.1162/0898929041502733.

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Saccadic reaction time to visual targets tends to be faster when stimuli from another modality (in particular, audition and touch) are presented in close temporal or spatial proximity even when subjects are instructed to ignore the accessory input (focused attention task). Multisensory interaction effects measured in neural structures involved in saccade generation (in particular, the superior colliculus) have demonstrated a similar spatio-temporal dependence. Neural network models of multisensory spatial integration have been shown to generate convergence of the visual, auditory, and tactile reference frames and the sensorimotor coordinate transformations necessary for coordinated head and eye movements. However, because these models do not capture the temporal coincidences critical for multisensory integration to occur, they cannot easily predict multisensory effects observed in behavioral data such as saccadic reaction times. This article proposes a quantitative stochastic framework, the time-window-of-integration model, to account for the temporal rules of multisensory integration. Saccadic responses collected from a visual–tactile focused attention task are shown to be consistent with the time-window-of-integration model predictions.

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Kazemi, Ehsan, and Liqiang Wang. "Asynchronous Delay-Aware Accelerated Proximal Coordinate Descent for Nonconvex Nonsmooth Problems." Proceedings of the AAAI Conference on Artificial Intelligence 33 (July 17, 2019): 1528–35. http://dx.doi.org/10.1609/aaai.v33i01.33011528.

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Nonconvex and nonsmooth problems have recently attracted considerable attention in machine learning. However, developing efficient methods for the nonconvex and nonsmooth optimization problems with certain performance guarantee remains a challenge. Proximal coordinate descent (PCD) has been widely used for solving optimization problems, but the knowledge of PCD methods in the nonconvex setting is very limited. On the other hand, the asynchronous proximal coordinate descent (APCD) recently have received much attention in order to solve large-scale problems. However, the accelerated variants of APCD algorithms are rarely studied. In this paper, we extend APCD method to the accelerated algorithm (AAPCD) for nonsmooth and nonconvex problems that satisfies the sufficient descent property, by comparing between the function values at proximal update and a linear extrapolated point using a delay-aware momentum value. To the best of our knowledge, we are the first to provide stochastic and deterministic accelerated extension of APCD algorithms for general nonconvex and nonsmooth problems ensuring that for both bounded delays and unbounded delays every limit point is a critical point. By leveraging Kurdyka-Łojasiewicz property, we will show linear and sublinear convergence rates for the deterministic AAPCD with bounded delays. Numerical results demonstrate the practical efficiency of our algorithm in speed.

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Stapleton, Timothy, and Helen Sumin Koo. "Bicyclist biomotion visibility aids: a 3D eye-tracking analysis." International Journal of Clothing Science and Technology 29, no. 2 (April 18, 2017): 262–69. http://dx.doi.org/10.1108/ijcst-05-2016-0060.

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Purpose The purpose of this paper is to investigate the effectiveness of biomotion visibility aids for nighttime bicyclists compared to other configurations via 3D eye-tracking technology in a blind between-subjects experiment. Design/methodology/approach A total of 40 participants were randomly assigned one of four visibility aid conditions in the form of videos: biomotion (retroreflective knee and ankle bands), non-biomotion (retroreflective vest configuration), pseudo-biomotion (vertical retroreflective stripes on the back of the legs), and control (all-black clothing). Gaze fixations on a screen were measured with a 3D eye-tracking system; coordinate data for each condition were analyzed via one-way ANOVA and Tukey’s post-hoc analyses with supplementary heatmaps. Post-experimental questionnaires addressed participants’ qualitative assessments. Findings Significant differences in eye gaze location were found between the four reflective clothing design conditions in X-coordinate values (p<0.01) and Y-coordinate values (p<0.05). Practical implications This research has the potential to further inform clothing designers and manufacturers on how to incorporate biomotion to increase bicyclist visibility and safety. Social implications This research has the potential to benefit both drivers and nighttime bicyclists through a better understanding of how biomotion can increase visibility and safety. Originality/value There is lack of literature addressing the issue of the commonly administered experimental task of recognizing bicyclists and its potential bias on participants’ attention and natural driving state. Eye-tracking has the potential to implicitly determine attention and visibility, devoid of biases to attention. A new retroreflective visibility aid design, pseudo-biomotion, was also introduced in this experiment.

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Journal articles on the topic 'Coordinate Attention'

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