Academic literature on the topic 'Attentional Network Theory'
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Journal articles on the topic "Attentional Network Theory"
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Chou, Kenny F., and Kamal Sen. "AIM: A network model of attention in auditory cortex." PLOS Computational Biology 17, no. 8 (August 27, 2021): e1009356. http://dx.doi.org/10.1371/journal.pcbi.1009356.
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Attentional modulation of cortical networks is critical for the cognitive flexibility required to process complex scenes. Current theoretical frameworks for attention are based almost exclusively on studies in visual cortex, where attentional effects are typically modest and excitatory. In contrast, attentional effects in auditory cortex can be large and suppressive. A theoretical framework for explaining attentional effects in auditory cortex is lacking, preventing a broader understanding of cortical mechanisms underlying attention. Here, we present a cortical network model of attention in primary auditory cortex (A1). A key mechanism in our network is attentional inhibitory modulation (AIM) of cortical inhibitory neurons. In this mechanism, top-down inhibitory neurons disinhibit bottom-up cortical circuits, a prominent circuit motif observed in sensory cortex. Our results reveal that the same underlying mechanisms in the AIM network can explain diverse attentional effects on both spatial and frequency tuning in A1. We find that a dominant effect of disinhibition on cortical tuning is suppressive, consistent with experimental observations. Functionally, the AIM network may play a key role in solving the cocktail party problem. We demonstrate how attention can guide the AIM network to monitor an acoustic scene, select a specific target, or switch to a different target, providing flexible outputs for solving the cocktail party problem.
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Cohen, Noga, Avishai Henik, and Nilly Mor. "Can Emotion Modulate Attention? Evidence for Reciprocal Links in the Attentional Network Test." Experimental Psychology 58, no. 3 (November 1, 2011): 171–79. http://dx.doi.org/10.1027/1618-3169/a000083.
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Evolution theory suggests that adaptive behavior depends on our ability to give preferential attention to emotional information when it is necessary for our survival, and to down-regulate irrelevant emotional influence. However, empirical work has shown that the interaction between emotion and attention varies, based on the attentional network in question. The aim of the current research was to examine the influence of stimulus emotionality on attention in three attentional networks: alerting, orienting, and executive functions. In two studies, using negative and neutral cues in a modified version of the Attention Network Test, it was found that negative cues impaired task performance in the absence of executive conflict, but not when executive processes were activated. Moreover, it was found that the influence of negative cues on task performance in a given trial was attenuated following activation of executive processes in the previous trial. These results suggest that when executive resources are required, inhibitory mechanisms are recruited to decrease the disruptive effect of emotional stimuli. More importantly, these findings indicate that the effect of emotional stimuli on attention is down-regulated both during cognitive conflict and after the conflict has already ended.
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Li, Yu, Yuan Tian, Jiawei Zhang, and Yi Chang. "Learning Signed Network Embedding via Graph Attention." Proceedings of the AAAI Conference on Artificial Intelligence 34, no. 04 (April 3, 2020): 4772–79. http://dx.doi.org/10.1609/aaai.v34i04.5911.
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Learning the low-dimensional representations of graphs (i.e., network embedding) plays a critical role in network analysis and facilitates many downstream tasks. Recently graph convolutional networks (GCNs) have revolutionized the field of network embedding, and led to state-of-the-art performance in network analysis tasks such as link prediction and node classification. Nevertheless, most of the existing GCN-based network embedding methods are proposed for unsigned networks. However, in the real world, some of the networks are signed, where the links are annotated with different polarities, e.g., positive vs. negative. Since negative links may have different properties from the positive ones and can also significantly affect the quality of network embedding. Thus in this paper, we propose a novel network embedding framework SNEA to learn Signed Network Embedding via graph Attention. In particular, we propose a masked self-attentional layer, which leverages self-attention mechanism to estimate the importance coefficient for pair of nodes connected by different type of links during the embedding aggregation process. Then SNEA utilizes the masked self-attentional layers to aggregate more important information from neighboring nodes to generate the node embeddings based on balance theory. Experimental results demonstrate the effectiveness of the proposed framework through signed link prediction task on several real-world signed network datasets.
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Fitzhugh, Megan C., B. Blair Braden, Marwan N. Sabbagh, Corianne Rogalsky, and Leslie C. Baxter. "Age-Related Atrophy and Compensatory Neural Networks in Reading Comprehension." Journal of the International Neuropsychological Society 25, no. 6 (April 29, 2019): 569–82. http://dx.doi.org/10.1017/s1355617719000274.
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AbstractObjectives: Despite changes to brain integrity with aging, some functions like basic language processes remain remarkably preserved. One theory for the maintenance of function in light of age-related brain atrophy is the engagement of compensatory brain networks. This study examined age-related changes in the neural networks recruited for simple language comprehension. Methods: Sixty-five adults (native English-speaking, right-handed, and cognitively normal) aged 17–85 years underwent a functional magnetic resonance imaging (fMRI) reading paradigm and structural scanning. The fMRI data were analyzed using independent component analysis to derive brain networks associated with reading comprehension. Results: Two typical frontotemporal language networks were identified, and these networks remained relatively stable across the wide age range. In contrast, three attention-related networks showed increased activation with increasing age. Furthermore, the increased recruitment of a dorsal attention network was negatively correlated to gray matter thickness in temporal regions, whereas an anterior frontoparietal network was positively correlated to gray matter thickness in insular regions. Conclusions: We found evidence that older adults can exert increased effort and recruit additional attentional resources to maintain their reading abilities in light of increased cortical atrophy.
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Craig, Curtis M., and Martina I. Klein. "The Abbreviated Vigilance Task and Its Attentional Contributors." Human Factors: The Journal of the Human Factors and Ergonomics Society 61, no. 3 (January 25, 2019): 426–39. http://dx.doi.org/10.1177/0018720818822350.
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Objective: To measure contributing attentional processes, particularly that of executive attention, to two iterations of the abbreviated vigilance task. Background: Joel Warm was at the forefront of vigilance research for decades, and resource theory is currently the dominant explanation for the vigilance decrement. The underlying mechanisms contributing to both overall performance and the decrement are only partly understood. Method: Seventy-eight participants answered questionnaires about their attentional skills and stress state, performed the Attention Network Test and two blocks of the 12-min abbreviated vigilance task, with a brief break between the two vigils during which they viewed images intended to affect performance. Changes in oxygenated hemoglobin were measured with functional near-infrared imaging. Results: Expected patterns were observed for both iterations of the abbreviated vigilance task, with performance declining after the first 2 min. Manipulations intended to evaluate whether executive processes contributed to vigilance performance failed to observe an effect. Other factors, particularly orienting and alerting attentional networks, task engagement, and subclinical ADHD symptomology were associated with performance. Significant factors for the first and second vigilance blocks were different. Conclusion: We suggest that (a) cognitive control is not a predominant factor, at least for the abbreviated vigilance task, and (b) attentional mechanisms and stress states affecting performance on the abbreviated vigilance task change over time. Application: Potential applications of this research include the use of breaks for sustained attention tasks involving high sensory load, and implications for the use of the abbreviated vigilance task as a proxy for general vigilance processes.
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MAX, JEFFREY E., DONALD A. ROBIN, H. GERRY TAYLOR, KEITH O. YEATES, PETER T. FOX, JACK L. LANCASTER, FACUNDO F. MANES, KATHERINE MATHEWS, and SHANNON AUSTERMANN. "Attention function after childhood stroke." Journal of the International Neuropsychological Society 10, no. 7 (November 2004): 976–86. http://dx.doi.org/10.1017/s1355617704107066.
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We investigated attentional outcome after childhood stroke and orthopedic diagnosis in medical controls. Twenty-nine children with focal stroke lesions and individually matched children with clubfoot or scoliosis were studied with standardized attention and neuroimaging assessments. Stroke lesions were quite varied in location and commonly involved regions implicated in Posner's model of attention networks. Children with stroke lesions performed significantly more poorly regarding attention function compared with controls. Performance on the Starry Night, a test demanding alerting and sensory-orienting but not executive attention function, was significantly associated with lesion size in the alerting and sensory-orienting networks but not the executive attention network. Furthermore, earlier age at lesion acquisition was significantly associated with poorer attention function even when lesion size was controlled. These findings support the theory of dissociable networks of attention and add to evidence from studies of children with diffuse and focal brain damage that early insults are associated with worse long-term outcomes in many domains of neuropsychological function. In addition, these results may provide clues towards the understanding of mechanisms underlying attention in children. (JINS, 2004,10, 976–986.)
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Li, Ying, Jia-Jie Xu, Peng-Peng Zhao, Jun-Hua Fang, Wei Chen, and Lei Zhao. "ATLRec: An Attentional Adversarial Transfer Learning Network for Cross-Domain Recommendation." Journal of Computer Science and Technology 35, no. 4 (July 2020): 794–808. http://dx.doi.org/10.1007/s11390-020-0314-8.
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Duecker, Felix, Elia Formisano, and Alexander T. Sack. "Hemispheric Differences in the Voluntary Control of Spatial Attention: Direct Evidence for a Right-Hemispheric Dominance within Frontal Cortex." Journal of Cognitive Neuroscience 25, no. 8 (August 2013): 1332–42. http://dx.doi.org/10.1162/jocn_a_00402.
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Lesion studies in neglect patients have inspired two competing models of spatial attention control, namely, Heilman's “hemispatial” theory and Kinsbourne's “opponent processor” model. Both assume a functional asymmetry between the two hemispheres but propose very different mechanisms. Neuroimaging studies have identified a bilateral dorsal frontoparietal network underlying voluntary shifts of spatial attention. However, lateralization of attentional processes within this network has not been consistently reported. In the current study, we aimed to provide direct evidence concerning the functional asymmetry of the right and left FEF during voluntary shifts of spatial attention. To this end, we applied fMRI-guided neuronavigation to disrupt individual FEF activation foci with a longer-lasting inhibitory patterned TMS protocol followed by a spatial cueing task. Our results indicate that right FEF stimulation impaired the ability of shifting spatial attention toward both hemifields, whereas the effects of left FEF stimulation were limited to the contralateral hemifield. These results provide strong direct evidence for right-hemispheric dominance in spatial attention within frontal cortex supporting Heilman's “hemispatial” theory. This complements previous TMS studies that generally conform to Kinsbourne's “opponent processor” model after disruption of parietal cortex, and we therefore propose that both theories are not mutually exclusive.
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McGrew, Kevin S., W. Joel Schneider, Scott L. Decker, and Okan Bulut. "A Psychometric Network Analysis of CHC Intelligence Measures: Implications for Research, Theory, and Interpretation of Broad CHC Scores “Beyond g”." Journal of Intelligence 11, no. 1 (January 16, 2023): 19. http://dx.doi.org/10.3390/jintelligence11010019.
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For over a century, the structure of intelligence has been dominated by factor analytic methods that presume tests are indicators of latent entities (e.g., general intelligence or g). Recently, psychometric network methods and theories (e.g., process overlap theory; dynamic mutualism) have provided alternatives to g-centric factor models. However, few studies have investigated contemporary cognitive measures using network methods. We apply a Gaussian graphical network model to the age 9–19 standardization sample of the Woodcock–Johnson Tests of Cognitive Ability—Fourth Edition. Results support the primary broad abilities from the Cattell–Horn–Carroll (CHC) theory and suggest that the working memory–attentional control complex may be central to understanding a CHC network model of intelligence. Supplementary multidimensional scaling analyses indicate the existence of possible higher-order dimensions (PPIK; triadic theory; System I-II cognitive processing) as well as separate learning and retrieval aspects of long-term memory. Overall, the network approach offers a viable alternative to factor models with a g-centric bias (i.e., bifactor models) that have led to erroneous conclusions regarding the utility of broad CHC scores in test interpretation beyond the full-scale IQ, g.
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Chen, Feiyang, Ying Jiang, Xiangrui Zeng, Jing Zhang, Xin Gao, and Min Xu. "PUB-SalNet: A Pre-Trained Unsupervised Self-Aware Backpropagation Network for Biomedical Salient Segmentation." Algorithms 13, no. 5 (May 19, 2020): 126. http://dx.doi.org/10.3390/a13050126.
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Salient segmentation is a critical step in biomedical image analysis, aiming to cut out regions that are most interesting to humans. Recently, supervised methods have achieved promising results in biomedical areas, but they depend on annotated training data sets, which requires labor and proficiency in related background knowledge. In contrast, unsupervised learning makes data-driven decisions by obtaining insights directly from the data themselves. In this paper, we propose a completely unsupervised self-aware network based on pre-training and attentional backpropagation for biomedical salient segmentation, named as PUB-SalNet. Firstly, we aggregate a new biomedical data set from several simulated Cellular Electron Cryo-Tomography (CECT) data sets featuring rich salient objects, different SNR settings, and various resolutions, which is called SalSeg-CECT. Based on the SalSeg-CECT data set, we then pre-train a model specially designed for biomedical tasks as a backbone module to initialize network parameters. Next, we present a U-SalNet network to learn to selectively attend to salient objects. It includes two types of attention modules to facilitate learning saliency through global contrast and local similarity. Lastly, we jointly refine the salient regions together with feature representations from U-SalNet, with the parameters updated by self-aware attentional backpropagation. We apply PUB-SalNet for analysis of 2D simulated and real images and achieve state-of-the-art performance on simulated biomedical data sets. Furthermore, our proposed PUB-SalNet can be easily extended to 3D images. The experimental results on the 2d and 3d data sets also demonstrate the generalization ability and robustness of our method.
Dissertations / Theses on the topic "Attentional Network Theory"
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Gullstrand, Mattias, and Stefan Maraš. "Using Graph Neural Networks for Track Classification and Time Determination of Primary Vertices in the ATLAS Experiment." Thesis, KTH, Matematisk statistik, 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-288505.
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Starting in 2027, the high-luminosity Large Hadron Collider (HL-LHC) will begin operation and allow higher-precision measurements and searches for new physics processes between elementary particles. One central problem that arises in the ATLAS detector when reconstructing event information is to separate the rare and interesting hard scatter (HS) interactions from uninteresting pileup (PU) interactions in a spatially compact environment. This problem becomes even harder to solve at higher luminosities. This project relies on leveraging the time dimension and determining a time of the HS interactions to separate them from PU interactions by using information measured by the upcoming High-Granularity Timing Detector (HGTD). The current method relies on using a boosted decision tree (BDT) together with the timing information from the HGTD to determine a time. We suggest a novel approach of utilizing a graph attentional network (GAT) where each bunch-crossing is represented as a graph of tracks and the properties of the GAT are applied on a track level to inspect if such a model can outperform the current BDT. Our results show that we are able to replicate the results of the BDT and even improve some metrics at the expense of increasing the uncertainty of the time determination. We conclude that although there is potential for GATs to outperform the BDT, a more complex model should be applied. Finally, we provide some suggestions for improvement and hope to inspire further study and advancements in this direction which shows promising potential.Från och med 2027 kommer \textit{high-luminosity Large Hadron Collider} (HL-LHC) att tas i drift och möjliggöra mätningar med högre precision och utforskningar av nya fysikprocesser mellan elementarpartiklar. Ett centralt problem som uppstår i ATLAS-detektorn vid rekonstruktionen av partikelkollisioner är att separera sällsynta och intressanta interaktioner, så kallade \textit{hard-scatters} (HS) från ointressanta \textit{pileup}-interaktioner (PU) i den kompakta rumsliga dimensionen. Svårighetsgraden för detta problem ökar vid högre luminositeter. Med hjälp av den kommande \textit{High-Granularity Timing-detektorns} (HGTD) mätningar kommer även tidsinformation relaterat till interaktionerna att erhållas. I detta projekt används denna information för att beräkna tiden för enskillda interaktioner vilket därmed kan användas för att separera HS-interaktioner från PU-interaktioner. Den nuvarande metoden använder en trädregressionsmetod, s.k. boosted decision tree (BDT) tillsammans med tidsinformationen från HGTD för att bestämma en tid. Vi föreslår ett nytt tillvägagångssätt baserat på ett s.k. uppvaktande grafnätverk (GAT), där varje protonkollision representeras som en graf över partikelspåren och där GAT-egenskaperna tillämpas på spårnivå. Våra resultat visar att vi kan replikera de BDT-baserade resultaten och till och med förbättra resultaten på bekostnad av att öka osäkerheten i tidsbestämningarna. Vi drar slutsatsen att även om det finns potential för GAT-modeller att överträffa BDT-modeller, bör mer komplexa versioner av de förra tillämpas. Vi ger slutligen några förbättringsförslag som vi hoppas ska kunna inspirera till ytterligare studier och framsteg inom detta område, vilket visar lovande potential.
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Lozo, Peter. "Neural theory and model of selective visual attention and 2D shape recognition in visual clutter /." Title page, contents and abstract only, 1996. http://web4.library.adelaide.edu.au/theses/09PH/09phl925.pdf.
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Berr, Katharina. "Slaves to our Screens? : A Critical Approach to Self-Regulation of Smartphone Use at the Example of Apple’s Screen Time Feature." Thesis, Stockholms universitet, JMK, 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:su:diva-172680.
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The increasingly ubiquitous role of smartphones in our everyday lives causes concerns regarding our relationship with the devices. While some raise the question whether smartphones are addictive (Alter 2017; Lopez-Fernandez 2019), others regard this concern as the most recent manifestation of moral panics (Cashmore, Cleland & Dixon 2018; Leick 2019). Meanwhile advocates of the attention economy argument claim that the problem is the design of technology occupying users’ attention (CHT 2019a-d). Somewhere in between, media and communication studies search for empirical evidence. From this vantage point of ideas this study explores the role of Screen Time, shaping and being shaped by this discourse. As a feature of Apple’s iOS software it is supposed to support users in regulating their smartphone use. Applying the walkthrough method as proposed by Light, Burgess & Duguay (2018) combined with an analysis of user experiences, shows how the technology company shapes a concept of self-regulation for users to adopt to. A concept, which first and foremost follows corporate and not the users’ best interest. This thesis poses the the question whether we are slaves to our screens, but arrives at the conclusion that we carry chains of self-regulation. The question remains, how we can create more sustainable and meaningful environments for protecting our attention.
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Undy, JW. "Acute effects of caffeine on behavioural and ERP indices of attention in healthy, low consumers of caffeine." Thesis, 2018. https://eprints.utas.edu.au/31168/1/Undy_whole_thesis.pdf.
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Caffeine is commonly used to enhance attentional processes. However, contention remains regarding the extent to which each attentional mechanism is affected by caffeine, and whether caffeine enhances attention over-and-above improvements in general arousal and sustained attention. Subsequently, the present study examined the acute effects of caffeine on behavioural (reaction time & accuracy) and electrophysiological (N1 ERP amplitude) measures of attention. During two separate sessions (separated by 7-14 days), twenty (14 female & 6 male) healthy, low consumers of caffeine (<150mg/day) completed an Attentional Network Task prior to ingesting either caffeine (200mg) or placebo, and again 30-minutes following ingestion. While a partial effect of caffeine upon the alerting and executive control networks was found, results of the present study suggested improvements in reaction time and accuracy following caffeine predominantly reflected a maintenance of general arousal and tonic alertness. It was concluded that caffeine primarily enhanced attentional processing by preventing fatigue and sustaining attention.
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Lozo, Peter. "Neural theory and model of selective visual attention and 2D shape recognition in visual clutter / by Peter Lozo." Thesis, 1996. http://hdl.handle.net/2440/18925.
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Bibliography: leaves 328-352.xxxi, 352 leaves : ill. ; 30 cm.
This thesis proposes a neural theory, Selective Attention Adaptive Resonance Theory, and a neuro-engineered solution to selective visual attention, memory guided processing and illumination invariant recognition of complete (unoccluded), but distorted 2D shapes of 3D objects in cluttered visual images.
Thesis (Ph.D.)--University of Adelaide, Dept. of Electrical and Electronic Engineering, 1997?
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Verster, Blanche. "Gestaltterapeutiese intervensieplan wat gerig is op die kind met ATHV en sy steunstelsels." Thesis, 2009. http://hdl.handle.net/10500/2870.
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Summaries in Afrikaans and EnglishADHD is a well-known disorder affecting approximately 8% of children in South Africa. Despite years of research and development re the disorder, it seems that parents and teachers sometimes do not have the ability to handle a child with ADHD. Since a lot of the information is contradictory, confusion exists among parents and teachers who act as the support system of the child with ADHD. ADHD is a serious and destructive disorder and can influence the child’s social functioning negatively. Due to continuous failure, the child with ADHD has a low self-esteem. These aspects are the point of reference for the aim of this study, namely the development and implementation of a Gestalt therapeutic intervention plan aimed at the empowerment of the child with ADHD in the middle childhood years, his supporting systems and the evaluation of the impact thereof. The empirical data was gathered by a process of intervention research. A combination of the qualitative and quantitative approach was used. During the use of the qualitative method, a quasi-experimental one-group-pretest-posttest design was utilized. During the qualitative phase, the phenomenological perspective was used. An in-depth literature study was done in respect of ADHD, the theoretic basis of ADHD, the child with ADHD in the middle childhood years and the ADHD from a Gestalt therapeutic perspective. This literature study was the starting point for the development of the comprehensive holistic intervention plan. The intervention plan consists of three programmes: Firstly an empowering program of six sessions aimed at the child in the middle childhood years with ADHD – attention was given to emotional awareness and the dealing with unfinished business. Secondly an empowering programme aimed at the parents consisting of four parental guidance sessions, and thirdly an empowerment programme aimed at the teachers, consisting of two workshops.
AandagTekortHiperaktiwiteitsVersteuring (ATHV) is 'n welbekende versteuring wat ongeveer 8% van SuidAfrikaanse kinders be'invloed. Ten spyte van jarelange navorsing en die verbetering van begrip vir die versteuring, blyk dit dat ouers en onderwysers steeds nie altyd oor die vermoe beskik om 'n kind met A THV te hanteer nie. Aangesien daar baie teenstrydige inligting beskikbaar is, word verwarring geskep by ouers en onderwysers, wat as die kind met A THV se steunstelsels moet dien. A THV is 'n ernstige en verwoestende versteuring en kan die kind se maatskaplike funksionering negatief be'invloed. As gevolg van voortdurende mislukking het die kind met ATHV dikwels 'n lae selfwaarde. Hierdie aspekte het as uitgangspunt gedien vir die doel van die ondersoek, naamlik die ontwikkeling en implementering van 'n Gestaltterapeutiese intervensieplan gerig op die bemagtiging van sowel die kind met A THV in die middelkinderjare, asook sy steunstelsels, en om die impak daarvan te evalueer. Tydens die ondersoek is 'n proses van intervensienavorsing gevolg wat 'n gekombineerde kwalitatiewe en kwantitatiewe navorsingsmetode is. In die benutting van die kwalitatiewe metode is 'n kwasie-eksperimentele een-groep-voortoets-natoetsstrategie benut. By die kwalitatiewe metode is vanuit die fenomenologiese perspektief gewerk. 'n Diepgaande literatuurstudie is gedoen ten opsigte van ATHV, die teoretiese begronding van ATHV, die kind met ATHV in die middelkinderjare en ATHV vanuit 'n Gestaltterapieperspektief. Hierdie literatuurstudie het as basis vir die ontwikkeling van 'n omvattende holistiese intervensieplan gedien. Die intervensieplan bestaan uit drie programme. Eerstens 'n bemagtigingsprogram van ses sessies gerig op die kind met A THV in die middelkinderjare waar die klem geplaas is op emosionele bewuswording en die hantering van onvoltooidhede. Tweedens 'n bemagtigingsprogram gerig op die ouers tydens vier ouerleidingsessies. Derdens 'n bemagtigingsprogram gerig op die onderwysers bestaande uit twee werkwinkels. Gestaltterapie het nie slegs as teoretiese verwysingsraamwerk tydens die ondersoek gedien nie, maar Gestaltterapeutiesemetodes is ook benut tydens die implementering van die intervensieplan. Resultate vanuit die empiriese gegewens dui aan dat die ouers en onderwysers se kennis ten opsigte van ATHV verbeter het, want hulle het hanteringstrategiee aangeleer en begin toepas, en daar was beter begrip tussen die skool en die ouers waarby die kinders gebaat het. Die kinders se selfwaarde is ook verhoog en hulle maatskaplike funksionering het verbeter.
Social Work
D. Diac. (Play Therapy)
Books on the topic "Attentional Network Theory"
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Astrahancevaa, Irina, Sergey Bobkov, Vadim Mizonov, and Sergey Boykov. Modeling of systems. ru: INFRA-M Academic Publishing LLC., 2022. http://dx.doi.org/10.12737/1831624.
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The textbook discusses general issues of system modeling, analytical, empirical and simulation approaches to modeling. Typical mathematical schemes used in the analytical approach, methods and tools of simulation modeling of systems are given. Attention is also paid to network and agent-based alternative approaches to modeling.
Meets the requirements of the federal state educational standards of higher education of the latest generation.
It is intended for undergraduate students studying in the direction of 09.03.02 "Information systems and technologies", whose working curricula include the discipline "Systems Modeling". It is assumed that the training plans also include training courses "Discrete Mathematics", "Mathematical logic and theory of algorithms", "System analysis". The manual will also be useful for master's degree students studying in the direction 09.04.02 "Information systems and technologies" (discipline "Models of information processes and systems").
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Gaputina, Violetta. Mediadiscourse of fashion: processes, phenomena, effects. ru: Publishing Center RIOR, 2021. http://dx.doi.org/10.29039/02079-1.
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The monograph is devoted to the study of the Russian-language discourse
of fashion, actualized in the space of modern mass media: in television broadcasts and glossy magazines, blogs and social networks.
The main attention is paid to the processes of hybridization of fashion discourse
and media discourse and their linguistic and speech manifestations, reflecting
the intersection of fashion discourse with other types of discourse.
The book is addressed to specialists in the field of media linguistics and journalism, students, teachers and researchers, employees of the fashion industry, as well as all those who are interested
in fashion and style issues.
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Vavrenyuk, Aleksandr, Viktor Makarov, and Stanislav Kutepov. Operating systems. UNIX bases. ru: INFRA-M Academic Publishing LLC., 2016. http://dx.doi.org/10.12737/11186.
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In the manual basics command interfey-are covered
са operating systems of UNIX family. Much attention is paid
to practical use of teams of system and opportunities of language
programming, shell provided by a cover. In a grant vklyu-
Chena also some sections devoted to bases administrirova-
niya and to network means of OS. At the end of each section there are questions
for self-checking, the appendix contains a large number at -
mayors of writing of shell-procedures.
The manual is addressed to the students studying the modern
information technologies according to programs of a bachelor degree, and also all,
who wants to master the OS command interface of family independently
UNIX in the shortest possible time.
The edition can also be used as the short reference book on wasps -
new UNIX OS.
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Domhoff, G. William. Dreaming Is an Intensified Form of Mind-Wandering, Based in an Augmented Portion of the Default Network. Edited by Kalina Christoff and Kieran C. R. Fox. Oxford University Press, 2018. http://dx.doi.org/10.1093/oxfordhb/9780190464745.013.7.
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This chapter argues that dreaming is an intensified form of mind-wandering that makes use of embodied simulation. It further hypothesizes that the neural network that enables dreaming is very likely an augmented portion of the default network. This network is activated whenever there is (1) a mature and intact neural substrate that can support the cognitive process of dreaming; (2) an adequate level of cortical activation; (3) an occlusion of external stimuli; (4) a cognitively mature imagination system (a necessity indicated by the virtual lack of dreaming in preschoolers and its relative paucity until ages 8–9); and (5) the loss of conscious self-control, which may be neurologically mediated in the final step in a complex process by the decoupling of the dorsal attentional network from the anterior portions of the default network. If this testable theory proves to be correct, then dreaming may be the quintessential cognitive simulation.
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Posner, Michael I., Mary K. Rothbart, and M. Rosario Rueda. Developing Attention and Self-Regulation in Childhood. Edited by Anna C. (Kia) Nobre and Sabine Kastner. Oxford University Press, 2014. http://dx.doi.org/10.1093/oxfordhb/9780199675111.013.023.
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This chapter views attention as an organ system consisting of three brain networks with their own unique anatomy, connectivity, neuromodulators, and functions. These networks underlie the functions of attention including: obtaining and maintaining the alert state, orienting to sensory events, and voluntary control of responses. It traces the development of these attentional networks from infancy to adulthood. All three networks are present in infancy, but their functions and connectivity change in development. The change of control from the orienting to the executive network that takes place between infancy and childhood underlies the increasing role of voluntary control of emotions and thoughts. It examines how genes and environment influence this development and suggests avenues for further understanding of how attention develops.
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Bramoullé, Yann, Andrea Galeotti, and Brian W. Rogers, eds. The Oxford Handbook of the Economics of Networks. Oxford University Press, 2016. http://dx.doi.org/10.1093/oxfordhb/9780199948277.001.0001.
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This handbook represents the frontier of research into the economics of networks: how and why they form, how they influence behavior, how they help govern outcomes in an interactive world, and how they shape collective decision making, opinion formation, and diffusion dynamics. From a methodological perspective, the authors devote attention to theory, field experiments, laboratory experiments, and econometrics. Theoretical work in network formation, games played on networks, repeated games, and the interaction between linking and behavior are synthesized. A number of chapters are devoted to studying social processes mediated by networks. Topics here include opinion formation, diffusion of information and disease, and learning. There are also chapters devoted to financial contagion and systemic risk. Next, the handbook includes a section that discusses communities more generally, with applications including social trust, favor exchange, and social collateral; the importance of communities for migration patterns, and the role that networks and communities play in the labor market. A prominent role of networks, from an economic perspective, is that they mediate trade. Several chapters cover bilateral trade in networks, strategic intermediation, and the role of networks in international trade. The handbook also discusses the role of networks for organizations. One chapter discusses the role of networks for the performance of organizations, while two other chapters discuss managing networks of consumers and pricing in the presence of network-based spillovers. Finally, the handbook covers the Internet as a network, with attention to the issue of net neutrality.
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Theodoulou, Stella Z., and Ravi K. Roy. 7. Globalization and the rise of network governance. Oxford University Press, 2016. http://dx.doi.org/10.1093/actrade/9780198724230.003.0007.
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The forces of globalization are compelling public administrators to direct their attention increasingly towards transnational forms of governance. ‘Globalization and the rise of network governance’ shows that in network governance-type systems, power and authority tend to be decentralized and dispersed among a variety of autonomous stakeholders operating beyond the scope and control of national governments. They are organized around values, concerns, issues, and problems ranging from global climate change to human security. Flexible and fluid in their organizational structure, they allow participants to flow in and out of a network as circumstances change. Examples of how governing networks have been particularly influential in addressing the climate change crisis are provided.
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Berardo, Ramiro, Isabella Alcañiz, Jennifer Hadden, and Lorien Jasny. Networks and the Politics of the Environment. Edited by Jennifer Nicoll Victor, Alexander H. Montgomery, and Mark Lubell. Oxford University Press, 2016. http://dx.doi.org/10.1093/oxfordhb/9780190228217.013.26.
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This chapter surveys recent research that utilizes the measures and techniques of social network analysis (SNA) to explain socioecological outcomes. The chapter focuses on the role of key characteristics of networks—including density and fragmentation, bonding and bridging social capital, brokerage and leadership—in promoting adaptive governance and co-management, and in turn, successful environmental management outcomes. It argues that network structures affect the ability of actors to coordinate their behavior, cooperate with one another, share information, and adapt their behavior to new circumstances. The chapter concludes by discussing limitations and future directions for research, drawing attention to the need for more work integrating ecological and social networks, comparative SNA, and analyses of network formation and evolution.
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Bianconi, Ginestra. Synchronization, Non-linear Dynamics and Control. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780198753919.003.0015.
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This chapter is entirely devoted to characterizing non-linear dynamics on multilayer networks. Special attention is given to recent results on the stability of synchronization that extend the Master Stability Function approach to the multilayer networks scenario. Discontinous synchronization transitions on multiplex networks recently reported in the literature are also discussed, and their application discussed in the context of brain networks. This chapter also presents an overview of the major results regarding pattern formation in multilayer networks, and the proposed characterization of multivariate time series using multiplex visibility graphs. Finally, the chapter discusses several approaches for multiplex network control where the dynamical state of a multiplex network needs to be controlled by eternal signals placed on replica nodes satisfying some structural constraints.
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Murdie, Amanda, and Marc Polizzi. Human Rights and Transnational Advocacy Networks. Edited by Jennifer Nicoll Victor, Alexander H. Montgomery, and Mark Lubell. Oxford University Press, 2016. http://dx.doi.org/10.1093/oxfordhb/9780190228217.013.31.
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Human rights advocates have been argued to be working as part of a larger “network” of actors supporting the respect and security of individuals. However, until recently, much scholarship in this area has used “network” as a synonym for “connected actors” instead of examining the network characteristics of advocacy actors and the ways in which the nature of the advocacy network could influence human rights outcomes. This chapter examines the growing literature that focuses on human rights advocacy using network theory and methodologies. It outlines both global and local data collection efforts and the state of the literature and addresses how this literature has drawn on the larger political networks literature. It concludes with a call for future work on how the network characteristics of advocacy actors influences both which human rights issues receive international attention and whether this attention translates into improvements in human rights practices on the ground.
Book chapters on the topic "Attentional Network Theory"
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Taylor, John G. "Towards a Control Theory of Attention." In Artificial Neural Networks – ICANN 2006, 461–70. Berlin, Heidelberg: Springer Berlin Heidelberg, 2006. http://dx.doi.org/10.1007/11840930_48.
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Nguyen, Khanh Duy Tung, Anh Phan Viet, and Tuan Hao Hoang. "Vietnamese Document Classification Using Hierarchical Attention Networks." In Frontiers in Intelligent Computing: Theory and Applications, 120–30. Singapore: Springer Singapore, 2019. http://dx.doi.org/10.1007/978-981-13-9920-6_13.
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Choi, Sang-Bok, Sang-Woo Ban, Minho Lee, Jang-Kyoo Shin, Dae-Wha Seo, and Hyun-Seung Yang. "Biologically Motivated Trainable Selective Attention Model Using Adaptive Resonance Theory Network." In Biologically Inspired Approaches to Advanced Information Technology, 456–71. Berlin, Heidelberg: Springer Berlin Heidelberg, 2004. http://dx.doi.org/10.1007/978-3-540-27835-1_33.
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Deco, Gustavo, and Edmund Rolls. "A Neurodynamical Theory of Visual Attention: Comparisons with fMRI- and Single-Neuron Data." In Artificial Neural Networks — ICANN 2002, 3–8. Berlin, Heidelberg: Springer Berlin Heidelberg, 2002. http://dx.doi.org/10.1007/3-540-46084-5_1.
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Xu, Zhikang, Bofeng Zhang, Haijie Fu, Xiaodong Yue, and Ying Lv. "Multi-branch Recurrent Attention Convolutional Neural Network with Evidence Theory for Fine-Grained Image Classification." In Belief Functions: Theory and Applications, 177–84. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-88601-1_18.
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Grassia, Marco, and Giuseppe Mangioni. "wsGAT: Weighted and Signed Graph Attention Networks for Link Prediction." In Complex Networks & Their Applications X, 369–75. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-93409-5_31.
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van den Boogaard, Erik, Jan Treur, and Maxim Turpijn. "A Neurologically Inspired Network Model for Graziano’s Attention Schema Theory for Consciousness." In Natural and Artificial Computation for Biomedicine and Neuroscience, 10–21. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-59740-9_2.
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Tobin, Sarah A., Benjamin Etzold, Fawwaz Momani, Tamara Adel Al Yakoub, Rola Fares Saleem AlMassad, and Ahmad Ghanem Shdefat. "Ambivalent Entanglements: Syrian Refugees’ Network Relations and (Im)mobilities in Protracted Displacement." In IMISCOE Research Series, 99–119. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-12503-4_5.
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AbstractPlace-based or territorially confined approaches in forced migration studies are well-suited to investigating how displaced people live and interact with others in certain localities and navigate their way through governance regimes of aid and asylum. They may, however, fail to capture the inherent multi-sitedness of many displaced people’s everyday lives and their translocal connections across the globe. This chapter presents the role of family- and kin-network figurations in mobilities for Syrian refugees in Jordan. As part of the EU-funded Horizon 2020 project ‘Transnational Figurations of Displacement’ (TRAFIG), the chapter asserts that a key prospect for getting out of protracted displacement is the role of figurations, including family- and kin-based networks. Inspired by figurational sociology, the chapter seeks to highlight how ambiguous and uncertain family and kin networks are experienced by Syrian refugees in these ‘translocal figurations of displacement’ and how they impact on their mobility. Utilising 23 interviews – 6 males and 17 females aged between 20 and 49 – we examine the ways in which figurational networks of family and kin shaped and reshape refugees’ experiences with and desires for mobility both into and within Jordan and their aspirations beyond Jordan. In particular, we find that family and kin networks provide key socio-cultural structures and figurational contours to the mobilities experienced by Syrians through (1) knowledge-sharing and (2) trust-based interactions. We pay careful attention to the idea that future mobility is as much about imaginations and aspirations that reflect the family- and kin-network figurations, which may or may not be grounded in the real possibilities for mobility.
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Tokatli, Nebahat. "Networks as Facilitators of Innovation in Technology-Based Industries: The Case of Flat Glass." In Knowledge for Governance, 441–60. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-47150-7_19.
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AbstractIn this chapter, I question the extent to which the networks of the flat glass industry facilitated innovation in the past and continue to do so now. So far, students of technology-based industries have focused their attention on a number of high-technology industries including, for example, biotechnology. Since the manufacturing and secondary processing of flat glass require the application of a degree of technological expertise, the flat glass industry is also considered a technology-based industry, though not a high-technology industry in the sense that biotechnology is. This particularity of the industry enables me not only to provide a reasonably complete account of the extent to which the networks of the flat glass industry facilitate innovation, but also to explore whether or not we need a different sort of network thinking for this particular industry—different from the thinking that the students of high-technology industries subscribe to as they study, for example, biotechnology.
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Khellat-Kihel, Souad, Zhenan Sun, and Massimo Tistarelli. "An Hybrid Attention-Based System for the Prediction of Facial Attributes." In Lecture Notes in Computer Science, 116–27. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-82427-3_9.
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AbstractRecent research on face analysis has demonstrated the richness of information embedded in feature vectors extracted from a deep convolutional neural network. Even though deep learning achieved a very high performance on several challenging visual tasks, such as determining the identity, age, gender and race, it still lacks a well grounded theory which allows to properly understand the processes taking place inside the network layers. Therefore, most of the underlying processes are unknown and not easy to control. On the other hand, the human visual system follows a well understood process in analyzing a scene or an object, such as a face. The direction of the eye gaze is repeatedly directed, through purposively planned saccadic movements, towards salient regions to capture several details. In this paper we propose to capitalize on the knowledge of the saccadic human visual processes to design a system to predict facial attributes embedding a biologically-inspired network architecture, the HMAX. The architecture is tailored to predict attributes with different textural information and conveying different semantic meaning, such as attributes related and unrelated to the subject’s identity. Salient points on the face are extracted from the outputs of the S2 layer of the HMAX architecture and fed to a local texture characterization module based on LBP (Local Binary Pattern). The resulting feature vector is used to perform a binary classification on a set of pre-defined visual attributes. The devised system allows to distill a very informative, yet robust, representation of the imaged faces, allowing to obtain high performance but with a much simpler architecture as compared to a deep convolutional neural network. Several experiments performed on publicly available, challenging, large datasets demonstrate the validity of the proposed approach.
Conference papers on the topic "Attentional Network Theory"
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Shi, Min, Yu Huang, Xingquan Zhu, Yufei Tang, Yuan Zhuang, and Jianxun Liu. "GAEN: Graph Attention Evolving Networks." In Thirtieth International Joint Conference on Artificial Intelligence {IJCAI-21}. California: International Joint Conferences on Artificial Intelligence Organization, 2021. http://dx.doi.org/10.24963/ijcai.2021/213.
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Real-world networked systems often show dynamic properties with continuously evolving network nodes and topology over time. When learning from dynamic networks, it is beneficial to correlate all temporal networks to fully capture the similarity/relevance between nodes. Recent work for dynamic network representation learning typically trains each single network independently and imposes relevance regularization on the network learning at different time steps. Such a snapshot scheme fails to leverage topology similarity between temporal networks for progressive training. In addition to the static node relationships within each network, nodes could show similar variation patterns (e.g., change of local structures) within the temporal network sequence. Both static node structures and temporal variation patterns can be combined to better characterize node affinities for unified embedding learning. In this paper, we propose Graph Attention Evolving Networks (GAEN) for dynamic network embedding with preserved similarities between nodes derived from their temporal variation patterns. Instead of training graph attention weights for each network independently, we allow model weights to share and evolve across all temporal networks based on their respective topology discrepancies. Experiments and validations, on four real-world dynamic graphs, demonstrate that GAEN outperforms the state-of-the-art in both link prediction and node classification tasks.
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Cheng, Dawei, Xiaoyang Wang, Ying Zhang, and Liqing Zhang. "Risk Guarantee Prediction in Networked-Loans." In Twenty-Ninth International Joint Conference on Artificial Intelligence and Seventeenth Pacific Rim International Conference on Artificial Intelligence {IJCAI-PRICAI-20}. California: International Joint Conferences on Artificial Intelligence Organization, 2020. http://dx.doi.org/10.24963/ijcai.2020/618.
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The guaranteed loan is a debt obligation promise that if one corporation gets trapped in risks, its guarantors will back the loan. When more and more companies involve, they subsequently form complex networks. Detecting and predicting risk guarantee in these networked-loans is important for the loan issuer. Therefore, in this paper, we propose a dynamic graph-based attention neural network for risk guarantee relationship prediction (DGANN). In particular, each guarantee is represented as an edge in dynamic loan networks, while companies are denoted as nodes. We present an attention-based graph neural network to encode the edges that preserve the financial status as well as network structures. The experimental result shows that DGANN could significantly improve the risk prediction accuracy in both the precision and recall compared with state-of-the-art baselines. We also conduct empirical studies to uncover the risk guarantee patterns from the learned attentional network features. The result provides an alternative way for loan risk management, which may inspire more work in the future.
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M. Alves, Lorraine, Klaus F. Côco, Mariane L. de Souza, and Patrick M. Ciarelli. "Graph Theory Analysis of Microstates in Attention-Deficit Hyperactivity Disorder." In Congresso Brasileiro de Automática - 2020. sbabra, 2020. http://dx.doi.org/10.48011/asba.v2i1.1481.
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Attention-Deficit Hyperactivity Disorder (ADHD) is one of the most common disorders of childhood and youth. The diagnosis of ADHD remains essentially clinical, based on history and questionnaires for symptom assessment, therefore, a biomarker can be of great value to reduce the inherent uncertainty of clinical diagnosis. In recent years, several studies have been carried out to assess the usefulness of neurophysiological (electroencephalography - EEG)and functional image data to assist in the process of diagnosing ADHD. Previous researches have revealed evidences that microstates are selectively affected by ADHD, indicating that their analysis may be a useful tool in methods of automatic disease identication. In this paper is proposed a new methodology for the detection of ADHD using EEG microstate analysis and graph theory. The proposed method allows modeling and interpreting each microstate as a complex network, which permits to identify the effect of ADHD on some characteristics of the built networks. In addition, it provides useful information to identify ADHD and subtypes patients with an accuracy around 99%, indicating that the proposed method is promising.
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Zhao, Zhou, Lingtao Meng, Jun Xiao, Min Yang, Fei Wu, Deng Cai, Xiaofei He, and Yueting Zhuang. "Attentional Image Retweet Modeling via Multi-Faceted Ranking Network Learning." In Twenty-Seventh International Joint Conference on Artificial Intelligence {IJCAI-18}. California: International Joint Conferences on Artificial Intelligence Organization, 2018. http://dx.doi.org/10.24963/ijcai.2018/442.
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Retweet prediction is a challenging problem in social media sites (SMS). In this paper, we study the problem of image retweet prediction in social media, which predicts the image sharing behavior that the user reposts the image tweets from their followees. Unlike previous studies, we learn user preference ranking model from their past retweeted image tweets in SMS. We first propose heterogeneous image retweet modeling network (IRM) that exploits users' past retweeted image tweets with associated contexts, their following relations in SMS and preference of their followees. We then develop a novel attentional multi-faceted ranking network learning framework with multi-modal neural networks for the proposed heterogenous IRM network to learn the joint image tweet representations and user preference representations for prediction task. The extensive experiments on a large-scale dataset from Twitter site shows that our method achieves better performance than other state-of-the-art solutions to the problem.
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Xi, Wu-Dong, Ling Huang, Chang-Dong Wang, Yin-Yu Zheng, and Jianhuang Lai. "BPAM: Recommendation Based on BP Neural Network with Attention Mechanism." In Twenty-Eighth International Joint Conference on Artificial Intelligence {IJCAI-19}. California: International Joint Conferences on Artificial Intelligence Organization, 2019. http://dx.doi.org/10.24963/ijcai.2019/542.
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Inspired by the significant success of deep learning, some attempts have been made to introduce deep neural networks (DNNs) in recommendation systems to learn users' preferences for items. Since DNNs are well suitable for representation learning, they enable recommendation systems to generate more accurate prediction. However, they inevitably result in high computational and storage costs. Worse still, due to the relatively small number of ratings that can be fed into DNNs, they may easily lead to over-fitting. To tackle these problems, we propose a novel recommendation algorithm based on Back Propagation (BP) neural network with Attention Mechanism (BPAM). In particular, the BP neural network is utilized to learn the complex relationship of the target users and their neighbors. Compared with deep neural network, the shallow neural network, i.e., BP neural network, can not only reduce the computational and storage costs, but also prevent the model from over-fitting. In addition, an attention mechanism is designed to capture the global impact on all nearest target users for each user. Extensive experiments on eight benchmark datasets have been conducted to evaluate the effectiveness of the proposed model.
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Zhao, Zhou, Ben Gao, Vincent W. Zheng, Deng Cai, Xiaofei He, and Yueting Zhuang. "Link Prediction via Ranking Metric Dual-Level Attention Network Learning." In Twenty-Sixth International Joint Conference on Artificial Intelligence. California: International Joint Conferences on Artificial Intelligence Organization, 2017. http://dx.doi.org/10.24963/ijcai.2017/493.
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Link prediction is a challenging problem for complex network analysis, arising in many disciplines such as social networks and telecommunication networks. Currently, many existing approaches estimate the proximity of the link endpoints for link prediction from their feature or the local neighborhood around them, which suffer from the localized view of network connections and insufficiency of discriminative feature representation. In this paper, we consider the problem of link prediction from the viewpoint of learning discriminative path-based proximity ranking metric embedding. We propose a novel ranking metric network learning framework by jointly exploiting both node-level and path-level attentional proximity of the endpoints for link prediction. We then develop the path-based dual-level reasoning attentional learning method with recurrent neural network for proximity ranking metric embedding. The extensive experiments on two large-scale datasets show that our method achieves better performance than other state-of-the-art solutions to the problem.
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Fang, Songtao, Zhenya Huang, Ming He, Shiwei Tong, Xiaoqing Huang, Ye Liu, Jie Huang, and Qi Liu. "Guided Attention Network for Concept Extraction." In Thirtieth International Joint Conference on Artificial Intelligence {IJCAI-21}. California: International Joint Conferences on Artificial Intelligence Organization, 2021. http://dx.doi.org/10.24963/ijcai.2021/200.
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Concept extraction aims to find words or phrases describing a concept from massive texts. Recently, researchers propose many neural network-based methods to automatically extract concepts. Although these methods for this task show promising results, they ignore structured information in the raw textual data (e.g., title, topic, and clue words). In this paper, we propose a novel model, named Guided Attention Concept Extraction Network (GACEN), which uses title, topic, and clue words as additional supervision to provide guidance directly. Specifically, GACEN comprises two attention networks, one of them is to gather the relevant title and topic information for each context word in the document. The other one aims to model the implicit connection between informative words (clue words) and concepts. Finally, we aggregate information from two networks as input to Conditional Random Field (CRF) to model dependencies in the output. We collected clue words for three well-studied datasets. Extensive experiments demonstrate that our model outperforms the baseline models with a large margin, especially when the labeled data is insufficient.
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Wang, Guangtao, Rex Ying, Jing Huang, and Jure Leskovec. "Multi-hop Attention Graph Neural Networks." In Thirtieth International Joint Conference on Artificial Intelligence {IJCAI-21}. California: International Joint Conferences on Artificial Intelligence Organization, 2021. http://dx.doi.org/10.24963/ijcai.2021/425.
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Self-attention mechanism in graph neural networks (GNNs) led to state-of-the-art performance on many graph representation learning tasks. Currently, at every layer, attention is computed between connected pairs of nodes and depends solely on the representation of the two nodes. However, such attention mechanism does not account for nodes that are not directly connected but provide important network context. Here we propose Multi-hop Attention Graph Neural Network (MAGNA), a principled way to incorporate multi-hop context information into every layer of attention computation. MAGNA diffuses the attention scores across the network, which increases the receptive field for every layer of the GNN. Unlike previous approaches, MAGNA uses a diffusion prior on attention values, to efficiently account for all paths between the pair of disconnected nodes. We demonstrate in theory and experiments that MAGNA captures large-scale structural information in every layer, and has a low-pass effect that eliminates noisy high-frequency information from graph data. Experimental results on node classification as well as the knowledge graph completion benchmarks show that MAGNA achieves state-of-the-art results: MAGNA achieves up to 5.7% relative error reduction over the previous state-of-the-art on Cora, Citeseer, and Pubmed. MAGNA also obtains the best performance on a large-scale Open Graph Benchmark dataset. On knowledge graph completion MAGNA advances state-of-the-art on WN18RR and FB15k-237 across four different performance metrics.
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Fan, Minghui, Lei Xiao, Xiangming He, and Yawei Chen. "Trash Classification Network Based on Attention Mechanism." In 2022 15th International Conference on Advanced Computer Theory and Engineering (ICACTE). IEEE, 2022. http://dx.doi.org/10.1109/icacte55855.2022.9943600.
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Zheng, Zhijie, Yuhang Jiao, and Guangyou Fang. "Upsampling Attention Network for Single Image Super-resolution." In 16th International Conference on Computer Vision Theory and Applications. SCITEPRESS - Science and Technology Publications, 2021. http://dx.doi.org/10.5220/0010283603990406.
Full textReports on the topic "Attentional Network Theory"
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Soloviev, Volodymyr Mykolayovych, and Viktoriya Volodymyrivna Solovyova. Universal tools of modeling different nature complex systems. ФОП Однорог Т.В., 2018. http://dx.doi.org/10.31812/123456789/2865.
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It is shown that there is а powerful set of tools for the study of self-organization in complex systems, both natural and artificial origin. They characterize the multidimensional nature of complexity - multifractality, irreversibility, non-linearity, recurrence, nonstability, emeregence, etc., and quantitative evaluation of individual dynamical measures of complexity allows for monitoring, predicting and preventing unwanted critical or crisis. Particular attention is paid to measures of network complexity, which are fully applicable to build synergistic network of pedagogical systems.
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Deng, Yingjun, ShengJing Liu, Ming Zhao, Feng Zhao, Jun Guo, and Bin Yan. Diet-induced male infertility in mice models: a systematic review and network meta-analysis. INPLASY - International Platform of Registered Systematic Review and Meta-analysis Protocols, May 2022. http://dx.doi.org/10.37766/inplasy2022.5.0116.
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Review question / Objective: In order to compare the different high energy diet such as high-fat diet and high sugar diet how to damage the male mice model in metabolize and fertility,and explore a reliable mice model method in the study of obesity with male infertility. P：obesity mice model with male infertility. I: High energy diet such as High-fat or High-sugar diet. C:High-fat diet,High-sugar diet, compared with normal diet in mice model. O:High energy diet induce male mice obesity model and damage their fertility. S: Use network meta-analysis. Condition being studied: The relationship between obesity and male infertility attacth more and more attention at present.So many animal expriments are carried out on this problem,there are enough exprimental article to support this meta analysis.
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Dudoit, Alain, Molivann Panot, and Thierry Warin. Towards a multi-stakeholder Intermodal Trade-Transportation Data-Sharing and Knowledge Exchange Network. CIRANO, December 2021. http://dx.doi.org/10.54932/mvne7282.
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The performance of supply chains used to be mainly the concern of academics and professionals who studied the potential efficiencies and risks associated with this aspect of globalisation. In 2021, major disruptions in this critical sector of our economies are making headlines and attracting the attention of policy makers around the world. Supply chain bottlenecks create shortages, fuel inflation, and undermine economic recovery. This report provides a transversal and multidisciplinary analysis of the challenges and opportunities regarding data interoperability and data sharing as they relate to the ‘Great Lakes - St. Lawrence Seaway Trade Corridor’ (GLSLTC)’s intermodal transportation and trade data strategy. The size and scope of this trade corridor are only matched by the complexity of its multimodal freight transportation systems and growing urbanization on both sides of the Canada-US border. This complexity is exacerbated by the lack of data interoperability and effective collaborations between the different stakeholders within the various jurisdictions and amongst them. Our analytical work relies on : 1) A review of the relevant documentation on the latest challenges to supply chains (SC), intermodal freight transport and international trade, identifying any databases that are to be used.; 2) A comparative review of selected relevant initiatives to give insights into the best practices in digital supply chains implemented in Canada, the United States, and the European Union.; 3) Interviews and discussions with experts from Transport Canada, Statistics Canada, the Canadian Centre on Transportation Data (CCTD) and Global Affairs Canada, as well as with CIRANO’s research community and four partner institutions to identify databases and data that they use in their research related to transportation and trade relevant data availabilities and methodologies as well as joint research opportunities. Its main findings can be summarized as follow: GLSLTC is characterized by its critical scale, complexity, and strategic impact as North America’s most vital trade corridor in the foreseeable further intensification of continental trade. 4% of Canadian GDP is attributed to the Transportation and Logistics sector (2018): $1 trillion of goods moved every year: Goods and services imports are equivalent to 33% of Canada’s GDP and goods and services exports equivalent to 32%. The transportation sector is a key contributor to the achievement of net-zero emissions commitment by 2050. All sectors of the Canadian economy are affected by global supply chain disruptions. Uncertainty and threats extend well beyond the COVID-19 Pandemic. “De-globalization” and increasing supply chains regionalization pressures are mounting. Innovation and thus economic performance—increasingly hinges on the quantity and quality of data. Data is transforming Canada’s economy/society and is now at the center of global trade “Transport data is becoming less available: Canada needs to make data a priority for a national transportation strategy.” * “How the Government of Canada collects, manages, and governs data—and how it accesses and shares data with other governments, sectors, and Canadians—must change.”
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Chen, Ziying, Zefei Jiang, Ziyun Guo, Mengchao Wang, Zhen Wang, and Liwei Chen. Comparative efficacy of different types of acupuncture for cancer-related fatigue: a protocol for systematic review and network meta-analysis. INPLASY - International Platform of Registered Systematic Review and Meta-analysis Protocols, July 2022. http://dx.doi.org/10.37766/inplasy2022.7.0012.
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Review question / Objective: To evaluate the efficacy and safety of all current acupuncture therapies for the treatment of CRF through network meta-analysis. Condition being studied: Cancer-related fatigue (CRF) has been defined as a distressing, persistent, subjective sense of physical, emotional, and/or cognitive tiredness or exhaustion related to cancer and/or cancer treatment that is not proportional to recent activity and interferes with usual functioning, as one of the most common symptoms in cancer and related therapies, presents a huge challenge to the quality of life for cancer patients. Unlike general fatigue that can be relieved with rest, CRF is more debilitating, more persistent, and manifests itself in various ways, both physically and mentally. The estimated prevalence of CRF varies widely by various fatigue evaluation indicators, types of cancer, and cancer treatments, ranging from 14.03% to 100%, however, the latest systematic review show that it can have a pooled prevalence of up to 52%, this deserves our attention. But there has been no gold standard treatment for CRF.
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Udupa, Sahana. Small Platforms and the Gray Zones of Deep Extreme Speech. MediaWell, Social Science Research Council, October 2021. http://dx.doi.org/10.35650/md.2093.d.2021.
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Recent trends of migration to smaller social media platforms among right wing actors have raised a caution that an excessive focus on large, transnational social media companies might lose sight of the volatile spaces of homegrown and niche platforms, which have begun to offer diverse “alternative” avenues to extreme speech. Such trends, which drew global media attention during Trump supporters’ attempted exodus to Parler, are also gaining salience in Europe and the global South. Turning the focus to these developments, this article pries open three pertinent features of extreme speech on small platforms: its propensity to migrate between platforms, its embeddedness in domestic regulatory and technological innovations, and its evolving role in facilitating hateful language and disinformation in and through deep trust-based networks. Rather than assuming that smaller platforms are on an obvious trajectory toward progressive alternatives, their diverse entanglements with exclusionary extreme speech, I suggest, should be an important focal point for policy measures.
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Droogan, Julian, Lise Waldek, Brian Ballsun-Stanton, and Jade Hutchinson. Mapping a Social Media Ecosystem: Outlinking on Gab & Twitter Amongst the Australian Far-right Milieu. RESOLVE Network, September 2022. http://dx.doi.org/10.37805/remve2022.6.
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Attention to the internet and the online spaces in which violent extremists interact and spread content has increased over the past decades. More recently, that attention has shifted from understanding how groups like the self-proclaimed Islamic State use the internet to spread propaganda to understanding the broader internet environment and, specifically, far-right violent extremist activities within it. This focus on how far right violent extremist—including far-right racially and ethnically motivated violent extremists (REMVEs) within them—create, use, and exploit the online networks in which they exist to promote their hateful ideology and reach has largely focused on North America and Europe. However, in recent years, examinations of those online dynamics elsewhere, including in Australia, is increasing. Far right movements have been active in Australia for decades. While these movements are not necessarily extremist nor violent, understanding how violent far right extremists and REMVEs interact within or seek to exploit these broader communities is important in further understanding the tactics, reach, and impact of REMVEs in Australia. This is particularly important in the online space access to broader networks of individuals and ideas is increasingly expanding. Adding to a steadily expanding body of knowledge examining online activities and networks of both broader far right as well as violent extremist far right populations in Australia, this paper presents a data-driven examination of the online ecosystems in which identified Australian far-right violent extremists exist and interact,1 as mapped by user generated uniform resource locators (URL), or ‘links’, to internet locations gathered from two online social platforms—Twitter and Gab. This link-based analysis has been used in previous studies of online extremism to map the platforms and content shared in online spaces and provide further detail on the online ecosystems in which extremists interact. Data incorporating the links was automatically collected from Twitter and Gab posts from users existing within the online milieu in which those identified far right extremists were connected. The data was collected over three discrete one-month periods spanning 2019, the year in which an Australian far right violent extremist carried out the Christchurch attack. Networks of links expanding out from the Twitter and Gab accounts were mapped in two ways to explore the extent and nature of the online ecosystems in which these identified far right Australian violent extremists are connected, including: To map the extent and nature of these ecosystems (e.g., the extent to which other online platforms are used and connected to one another), the project mapped where the most highly engaged links connect out to (i.e., website domain names), and To explore the nature of content being spread within those ecosystems, what sorts of content is found at the end of the most highly engaged links. The most highly engaged hashtags from across this time are also presented for additional thematic analysis. The mapping of links illustrated the interconnectedness of a social media ecosystem consisting of multiple platforms that were identified as having different purposes and functions. Importantly, no links to explicitly violent or illegal activity were identified among the top-most highly engaged sites. The paper discusses the implications of the findings in light of this for future policy, practice, and research focused on understanding the online ecosystems in which identified REMVE actors are connected and the types of thematic content shared and additional implications in light of the types of non-violent content shared within them.
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Lenhardt, Amanda. The Social Economic Impacts of Covid-19 in Informal Urban Settlements. Institute of Development Studies, September 2021. http://dx.doi.org/10.19088/cc.2021.008.
Full textAbstract:
The social economic impacts of the Covid-19 crisis in informal urban settlements are widely discussed in the literature, as are the risk factors for particular social and economic groups in these areas. However, government responses and evidence of their impact do not appear to rise to the challenges posed by these studies. Pre-pandemic analyses of risk factors in informal urban settlements and newly collected evidence from different contexts are available to understand the unique and pressing challenges that the pandemic poses to wellbeing in informal urban settlements. In contrast, there is little evidence of effective policy and programme solutions to address these challenges, which is likely driven by the absence of targeted policies and programmes to support people living in informal urban settlements. As a result, many communities have had to rely on their own limited resources and support networks to respond to the crisis (Wilkinson, 2021). This report briefly summarises the range of available evidence on the social economic impacts of the Covid-19 crisis in informal urban settlements and the intersectional differences in how different identity groups living in them have experienced the pandemic. Following a short introduction to the context of the Covid-19 crisis in these areas, the report outlines three thematic areas that have received significant attention in the literature and policy discourses – livelihoods and poverty, food security, and education. While not an exhaustive list, this range of topics is indicative of the range of evidence available and outstanding gaps. The remaining section details evidence of how different identity groups living in informal urban settlements have experienced the pandemic based on gender, disability, age, and migration status. The review draws on a mixture of academic and grey literature, with some opinion pieces and blogs also included given the ongoing nature of the pandemic.
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Hotsur, Oksana. FROM THE ECONOMIC CRISIS TO COVID-19: FEATURES OF THE DEVELOPMENT OF THE PRINT MEDIA MARKET OF UKRAINE. Ivan Franko National University of Lviv, February 2022. http://dx.doi.org/10.30970/vjo.2022.51.11396.
Full textAbstract:
The study analyzes the traditional media during 2013-2021 and draws attention to a number of factors, factors of economic and global nature in the historical context, which affect the general state of the media market in Ukraine. The main goal is to outline the peculiarities of the development of the print media market in modern conditions and challenges. The study uses socio-communicative and axiological approaches, methods of content analysis, synthesis and general are the main methods that were used in the research process. In addition to catalysts for abrupt changes in the print media market of Ukraine, factors have been identified that significantly affect the development trends of the general media market: digitalization, destruction of logistics, periodicals, outflow of advertisers from traditional media (television, radio, newspapers and magazines). There are already forecasts that due to the increase in the price of paper on the world market there will be an increase in prices for printed products by 40%), the lack of a culture of consumption of subscription information, as there is a free alternative (social networks, search engines). Results/findings and conclusions of my research: a set of three crisis periods, as a result of which the factors identified in the study are the main characteristics of the development of the modern print media market in Ukraine. The print media market, due to the global situation through COVID-19, is going through difficult times. In fact, the prospect for further scientific research may be the study of the financial component of the Ukrainian media market in the context of general world trends.
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Bano, Masooda, and Zeena Oberoi. Embedding Innovation in State Systems: Lessons from Pratham in India. Research on Improving Systems of Education (RISE), December 2020. http://dx.doi.org/10.35489/bsg-rise-wp_2020/058.
Full textAbstract:
The learning crisis in many developing countries has led to searches for innovative teaching models. Adoption of innovation, however, disrupts routine and breaks institutional inertia, requiring government employees to change their way of working. Introducing and embedding innovative methods for improving learning outcomes within state institutions is thus a major challenge. For NGO-led innovation to have largescale impact, we need to understand: (1) what factors facilitate its adoption by senior bureaucracy and political elites; and (2) how to incentivise district-level field staff and school principals and teachers, who have to change their ways of working, to implement the innovation? This paper presents an ethnographic study of Pratham, one of the most influential NGOs in the domain of education in India today, which has attracted growing attention for introducing an innovative teaching methodology— Teaching at the Right Level (TaRL) – with evidence of improved learning outcomes among primary-school students and adoption by a number of states in India. The case study suggests that while a combination of factors, including evidence of success, ease of method, the presence of a committed bureaucrat, and political opportunity are key to state adoption of an innovation, exposure to ground realities, hand holding and confidence building, informal interactions, provision of new teaching resources, and using existing lines of communication are core to ensuring the co-operation of those responsible for actual implementation. The Pratham case, however, also confirms existing concerns that even when NGO-led innovations are successfully implemented at a large scale, their replication across the state and their sustainability remain a challenge. Embedding good practice takes time; the political commitment leading to adoption of an innovation is often, however, tied to an immediate political opportunity being exploited by the political elites. Thus, when political opportunity rather than a genuine political will creates space for adoption of an innovation, state support for that innovation fades away before the new ways of working can replace the old habits. In contexts where states lack political will to improve learning outcomes, NGOs can only hope to make systematic change in state systems if, as in the case of Pratham, they operate as semi-social movements with large cadres of volunteers. The network of volunteers enables them to slow down and pick up again in response to changing political contexts, instead of quitting when state actors withdraw. Involving the community itself does not automatically lead to greater political accountability. Time-bound donor-funded NGO projects aiming to introduce innovation, however large in scale, simply cannot succeed in bringing about systematic change, because embedding change in state institutions lacking political will requires years of sustained engagement.
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Werny, Rafaela, Marie Reich, Miranda Leontowitsch, and Frank Oswald. EQualCare Policy Report Germany : Alone but connected? Digital (in)equalities in care work and generational relationships among older people living alone. Frankfurter Forum für interdisziplinäre Alternsforschung, Goethe-Universität Frankfurt am Main, October 2022. http://dx.doi.org/10.21248/gups.69905.
Full textAbstract:
The policy review is part of the project EQualCare: Alone but connected? Digital (in)equalities in care work and generational relationships among older people living alone, a three-year international project involving four countries: Finland, Germany, Latvia and Sweden. EQualCare interrogates inequalities by gender, cultural and socio-economic background between countries, with their different demographics and policy backgrounds. As a first step into empirical analysis, the policy review aims to set the stage for a better understanding of, and policy development on, the intersections of digitalisation with intergenerational care work and care relationships of older people living alone in Germany. The policy review follows a critical approach, in which the problems policy documents address are not considered objective entities, but rather discursively produced knowledge that renders visible some parts of the problem which is to be solved as other possible perspectives are simultaneously excluded. Twenty publicly available documents were studied to analyse the processes in which definitions of care work and digital (in)equalities are circulated, translated and negotiated between the different levels of national government, regional governments and municipalities as well as other agencies in Germany. The policy review consists of two parts: a background chapter providing information on the social structure of Germany, including the historical development of Germany after the Second World War, its political structure, information on the demographic situation with a focus on the 60+ age group, and the income of this age group. In addition, the background presents the structure of work and welfare, the organisation of care for old people, and the state of digitalisation in Germany. The analysis chapter includes a description of the method used as well as an overview of the documents chosen and analysed. The focus of this chapter is on the analysis of official documents that deal with the interplay of living alone in old age, care, and digitalisation. The analysis identified four themes: firstly, ageing is framed largely as a challenge to society, whereas digitalisation is framed as a potential way to tackle social challenges, such as an ageing society. Secondly, challenges of ageing, such as need of care, are set at the individual level, requiring people to organise their care within their own families and immediate social networks, with state support following a principle of subsidiarity. Thirdly, voluntary peer support provides the basis for addressing digital support needs and strategies. Publications by lobby organisations highlight the important work done by voluntary peer support for digital training and the benefits this approach has; they also draw attention to the over-reliance on this form of unpaid support and call for an increase in professional support in ensuring all older people are supported in digital life. Fourthly, ageing as a hinderance to participation in digital life is seen as an interim challenge among younger old people already online.