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Academic literature on the topic 'HETEROGENOUS MEAN FIELD'

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Published: 10 March 2023

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Journal articles on the topic "HETEROGENOUS MEAN FIELD"

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Xu, Can, Yonggang Wu, Zhigang Zheng, and Longkun Tang. "Partial locking in phase-oscillator populations with heterogenous coupling." Chaos: An Interdisciplinary Journal of Nonlinear Science 32, no. 6 (June 2022): 063106. http://dx.doi.org/10.1063/5.0093318.

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We consider a variant of the mean-field model of coupled phase oscillators with uniform distribution of natural frequencies. By establishing correlations between the quenched disorder of intrinsic frequencies and coupling strength with both in- and out-coupling heterogeneities, we reveal a generic criterion for the onset of partial locking that takes place in a domain with the coexistence of phase-locked oscillators and drifters. The critical points manifesting the instability of the stationary states are obtained analytically. In particular, the bifurcation mechanism of the equilibrium states is uncovered by the use of frequency-dependent version of the Ott–Antonsen reduction consistently with the analysis based on the self-consistent approach. We demonstrate that both the manner of coupling heterogeneity and correlation exponent have influence on the emergent patterns of partial locking. Our research could find applicability in better understanding the phase transitions and related collective phenomena involving synchronization control in networked systems.
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Chicchi, Lorenzo, Gloria Cecchini, Ihusan Adam, Giuseppe de Vito, Roberto Livi, Francesco Saverio Pavone, Ludovico Silvestri, Lapo Turrini, Francesco Vanzi, and Duccio Fanelli. "Reconstruction scheme for excitatory and inhibitory dynamics with quenched disorder: application to zebrafish imaging." Journal of Computational Neuroscience 49, no. 2 (April 7, 2021): 159–74. http://dx.doi.org/10.1007/s10827-020-00774-1.

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AbstractAn inverse procedure is developed and tested to recover functional and structural information from global signals of brains activity. The method assumes a leaky-integrate and fire model with excitatory and inhibitory neurons, coupled via a directed network. Neurons are endowed with a heterogenous current value, which sets their associated dynamical regime. By making use of a heterogenous mean-field approximation, the method seeks to reconstructing from global activity patterns the distribution of in-coming degrees, for both excitatory and inhibitory neurons, as well as the distribution of the assigned currents. The proposed inverse scheme is first validated against synthetic data. Then, time-lapse acquisitions of a zebrafish larva recorded with a two-photon light sheet microscope are used as an input to the reconstruction algorithm. A power law distribution of the in-coming connectivity of the excitatory neurons is found. Local degree distributions are also computed by segmenting the whole brain in sub-regions traced from annotated atlas.
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Forbes, Emily, Matthew Back, Andrew Brooks, Natalia B. Petrovskaya, Sergei V. Petrovskii, Tom Pope, and Keith F. A. Walters. "Stability of Patches of Higher Population Density within the Heterogenous Distribution of the Gray Field Slug Deroceras reticulatum in Arable Fields in the UK." Insects 12, no. 1 (December 25, 2020): 9. http://dx.doi.org/10.3390/insects12010009.

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Exploitation of heterogenous distributions of Deroceras reticulatum, in arable fields by targeting molluscicide applications toward areas with higher slug densities, relies on these patches displaying sufficient spatio-temporal stability. Regular sampling of slug activity/distribution was undertaken using 1 ha rectangular grids of 100 refuge traps established in 22 commercial arable field crops. Activity varied significantly between the three years of the study, and the degree of aggregation (Taylor’s Power Law) was higher in fields with higher mean trap catches. Hot spot analysis detected statistically significant spatial clusters in all fields, and in 162 of the 167 individual assessment visits. The five assessment visits in which no clusters were detected coincided with low slug activity (≤0.07 per trap). Generalized Linear Models showed significant spatial stability of patches in 11 fields, with non-significant fields also characterized by low slug activity (≤1.2 per trap). Mantel’s permutation tests revealed a high degree of correlation between location of individual patches between sampling dates. It was concluded that patches of higher slug density were spatio-temporally stable, but detection using surface refuge traps (which rely on slug activity on the soil surface) was less reliable when adverse environmental conditions resulted in slugs retreating into the upper soil horizons.
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Hamdioui, S., and L. Vaivre-Douret. "Psycho-socio-emotional characteristics in high intellectual potential child regarding IQ profile (Homogenous/Heterogenous)." European Psychiatry 65, S1 (June 2022): S419. http://dx.doi.org/10.1192/j.eurpsy.2022.1064.

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Introduction Few studies have analyzed the psychometric profile (Homogenous/Heterogenous), established by the Wechsler scale in high intellectual potential children (HIP, IQ>130), regarding the psycho-socio-emotional characteristics. Objectives We aimed to look at the links between the IQ-profile and the psycho-socio-emotional characteristics in HIP. Methods Anamnestic questionnaire and Wechsler-Intelligence-Scale for children (WISC-V) were conducted and analyzed in 58 healthy children with HIP, aged 7-to-13 years-old (mean 10y; SD 1.8). It was possible to distinguished 27 Homogenousvs 30 Heterogenous IQ-profile. Results No significant difference between homogenous/heterogonous groups, FIQ was positively significantly correlated with “Reacting very little emotionally”, “Tendency to isolation”. Visual-Spatial-Index (VSI) with “Ability to adapt to new people” (r=-0.4, p=0.02), “few interests” (r=0.5, p=0.008). Verbal-Comprehension-Index (VCI) with “Reacting strongly to frustration”, “Difficulties to understand limits”, “Separation anxiety”. A significant difference between homogenous/heterogonous groups was shown regarding “few interests” with high rate in the heterogonous group (t= -2.34, p=0.023). Conclusions HIP seems to cover specific psycho-socio-emotional characteristics linked to IQ index distribution. Thus, it appears interesting to assess more the emotional and socio-cognitive field to understand these characteristics in HIP children. Disclosure No significant relationships.
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Allmeier, Sebastian, and Nicolas Gast. "Mean Field and Refined Mean Field Approximations for Heterogeneous Systems." ACM SIGMETRICS Performance Evaluation Review 50, no. 1 (June 20, 2022): 103–4. http://dx.doi.org/10.1145/3547353.3522653.

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Mean field approximation is a powerful technique to study the performance of large stochastic systems represented as n interacting objects. Applications include load balancing models, epidemic spreading, cache replacement policies, or large-scale data centers. Mean field approximation is asymptotically exact for systems composed of n homogeneous objects under mild conditions. In this paper, we study what happens when objects are heterogeneous. This can represent servers with different speeds or contents with different popularities. We define an interaction model that allows obtaining asymptotic convergence results for stochastic systems with heterogeneous object behavior and show that the error of the mean field approximation is of order O(1/n). More importantly, we show how to adapt the refined mean field approximation, developed by the authors of Gast et al. 2019, and show that the error of this approximation is reduced to O(1/n2). To illustrate the applicability of our result, we present two examples. The first addresses a list-based cache replacement model, RANDOM(m), which is an extension of the RANDOM policy. The second is a heterogeneous supermarket model. These examples show that the proposed approximations are computationally tractable and very accurate. For moderate system sizes (n ≈ 30) the refined mean field approximation tends to be more accurate than simulations for any reasonable simulation time.
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Allmeier, Sebastian, and Nicolas Gast. "Mean Field and Refined Mean Field Approximations for Heterogeneous Systems." Proceedings of the ACM on Measurement and Analysis of Computing Systems 6, no. 1 (February 24, 2022): 1–43. http://dx.doi.org/10.1145/3508033.

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Mean field approximation is a powerful technique to study the performance of large stochastic systems represented as n interacting objects. Applications include load balancing models, epidemic spreading, cache replacement policies, or large-scale data centers. Mean field approximation is asymptotically exact for systems composed of n homogeneous objects under mild conditions. In this paper, we study what happens when objects are heterogeneous. This can represent servers with different speeds or contents with different popularities. We define an interaction model that allows obtaining asymptotic convergence results for stochastic systems with heterogeneous object behavior, and show that the error of the mean field approximation is of order $O(1/n)$. More importantly, we show how to adapt the refined mean field approximation, developed by Gast et al., and show that the error of this approximation is reduced to O(1/n^2). To illustrate the applicability of our result, we present two examples. The first addresses a list-based cache replacement model, RANDOM(m), which is an extension of the RANDOM policy. The second is a heterogeneous supermarket model. These examples show that the proposed approximations are computationally tractable and very accurate. They also show that for moderate system sizes (30) the refined mean field approximation tends to be more accurate than simulations for any reasonable simulation time.
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Jumaah, Hayder A. "Modified Archie’s parameters for estimating water saturation for carbonate reservoir in north of Iraq." Journal of Petroleum Exploration and Production Technology 11, no. 10 (August 21, 2021): 3689–97. http://dx.doi.org/10.1007/s13202-021-01258-3.

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AbstractArchie’s parameters, cementation factor (m), saturation exponent (n) and tortuosity factor (a), are general factor that have effects on water saturation magnitude, due to their sensitivity to pores distribution, lithofacies properties and wettability, particularly in carbonate reservoirs. Water saturation magnitude has a direct effect in estimating initial oil-in-place values, and inaccuracy in its values will lead to huge impact errors in initial oil-in-place values, so it would affect the economics of field management and development plans. In this paper, the main objective was to investigate the impact of using conventional and modified Archie’s parameters in the determination of water saturation from well log interpretation for Tertiary reservoir in Khabaz oil field, a heterogenous carbonite reservoir in the north of Iraq which was affected by different digenesis processes that impacted the reservoir quality. Tertiary reservoir of Khabaz field consists of five geological units (A, B, C, D and E), and the selected well penetrated the top of the reservoir at 2200.5 m RTKB and passed through five geological units and reached total depth at 2348 m RTKB. The geothermal gradient of the field was 1.12 ℉ per 100 ft, and formation water resistivity (Rw) was about 0.029 Ω m. Water saturation was at first estimated from resistivity logs by Archie model with conventional known values of parameters (a, m and n) (1, 2 and 2), respectively, and then Archie’s parameters were modified and determined by graphical technique of Pickett plot for each geological unit to estimate water saturation. Finally, the results show the water saturation value was more sensitive for Archie’s parameter in low-porosity and high-clay-volume zone, but less sensitive in clean high-porosity zone, and water saturation values determined by modified Archie model were less about 18.5% at mean than their value by using conventional Archie’s parameters.
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Alabi, Tunrayo R., Julius Adewopo, Ojo Patrick Duke, and P. Lava Kumar. "Banana Mapping in Heterogenous Smallholder Farming Systems Using High-Resolution Remote Sensing Imagery and Machine Learning Models with Implications for Banana Bunchy Top Disease Surveillance." Remote Sensing 14, no. 20 (October 18, 2022): 5206. http://dx.doi.org/10.3390/rs14205206.

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Banana (and plantain, Musa spp.), in sub-Saharan Africa (SSA), is predominantly grown as a mixed crop by smallholder farmers in backyards and small farmlands, typically ranging from 0.2 ha to 3 ha. The crop is affected by several pests and diseases, including the invasive banana bunchy top virus (BBTV, genus Babuvirus), which is emerging as a major threat to banana production in SSA. The BBTV outbreak in West Africa was first recorded in the Benin Republic in 2010 and has spread to the adjoining territories of Nigeria and Togo. Regular surveillance, conducted as part of the containment efforts, requires the identification of banana fields for disease assessment. However, small and fragmented production spread across large areas poses complications for identifying all banana farms using conventional field survey methods, which is also time-consuming and expensive. In this study, we developed a remote sensing approach and machine learning (ML) models that can be used to identify banana fields for targeted BBTV surveillance. We used medium-resolution synthetic aperture radar (SAR), Sentinel 2A satellite imagery, and high-resolution RGB and multispectral aerial imagery from an unmanned aerial vehicle (UAV) to develop an operational banana mapping framework by combining the UAV, SAR, and Sentinel 2A data with the Support Vector Machine (SVM) and Random Forest (RF) machine learning algorithms. The ML algorithms performed comparatively well in classifying the land cover, with a mean overall accuracy (OA) of about 93% and a Kappa coefficient (KC) of 0.89 for the UAV data. The model using fused SAR and Sentinel 2A data gave an OA of 90% and KC of 0.86. The user accuracy (UA) and producer accuracy (PA) for the banana class were 83% and 78%, respectively. The BBTV surveillance teams used the banana mapping framework to identify banana fields in the BBTV-affected southwest Ogun state of Nigeria, which helped in detecting 17 sites with BBTV infection. These findings suggest that the prediction of banana and other crops in the heterogeneous smallholder farming systems is feasible, with the precision necessary to guide BBTV surveillance in large areas in SSA.
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Dias, C., and M. O. Hase. "Weakening connections in heterogeneous mean-field models." Journal of Statistical Mechanics: Theory and Experiment 2021, no. 1 (January 20, 2021): 013404. http://dx.doi.org/10.1088/1742-5468/abd4ca.

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Chong, Carsten, and Claudia Klüppelberg. "Partial mean field limits in heterogeneous networks." Stochastic Processes and their Applications 129, no. 12 (December 2019): 4998–5036. http://dx.doi.org/10.1016/j.spa.2018.12.018.

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Dissertations / Theses on the topic "HETEROGENOUS MEAN FIELD"

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Martorello, Cristiane Dias de Souza. "Epidemiology in complex networks - modified heterogeneous mean-field model." Universidade de São Paulo, 2018. http://www.teses.usp.br/teses/disponiveis/100/100132/tde-16012019-173906/.

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The study of complex networks presented a huge development in last decades. In this dissertation we want to analyze the epidemic spread in scale-free networks through the Susceptible - Infected - Susceptible (SIS) model. We review the fundamental concepts to describe complex networks and the classical epidemiological models. We implement an algorithm that produces a scale-free network and explore the Quenched Mean-Field (QMF) dynamics in a scale-free network. Moreover, we simulate a change on the topology of the network according to the states of the nodes, and it generates a positive epidemic threshold. We show analytically that the fraction of infected vertices follows a power-law distribution in the vicinity of this critical point
O estudo de redes complexas tem se desenvolvido muito nos últimos anos. Nesta dissertação queremos analisar o processo de propagação de epidemia em redes livres de escala através do modelo Suscetível - Infectado - Suscetível (SIS). Apresentamos uma revisão de redes e as principais características dos modelos epidemiológicos clássicos. Implementamos um algoritmo que produz uma rede livre de escala dado um expoente e exploramos a dinâmica do modelo Quenched Mean-Field (QMF) inserido em uma rede livre de escala. Além disso, foi simulada uma possível alteração na topologia da rede, devido aos estados dos vértices infectados, que gerou um limiar epidêmico positivo no modelo e a probabilidade de vértices infectados seguiu uma lei de potência na vizinhança desse ponto crítico
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Berthier, Serge. "Théories de la fonction diélectrique optique des milieux inhomogènes : application aux propriétés électromagnétiques des cermets." Paris 6, 1986. http://www.theses.fr/1986PA066283.

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Analyse comparative des différentes théories de la fonction diélectrique optique des milieux inhomogènes aléatoires macroscopiques (MIAM). Résultats expérimentaux sur le comportement diélectrique de 5 échantillons au-MGO dont la concentration volumique en métal n'excède pas 0,41; apparition de la résonnance de plasmon de surface sur tous les échantillons entre 550 et 600 nm. Nouvelles approches: théorie de Bruggeman modifiée, méthode des groupes de renormalisation. Applications dans les capteurs solaires
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Adam, Ihusan. "Structure and collective behaviour: a focus on the inverse problem." Doctoral thesis, 2021. http://hdl.handle.net/2158/1230776.

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The aim of this thesis is to inform our understanding of the exquisite relationship between function and structure of complex systems with a particular focus on the inverse problem of inferring structure from collective expression. There exists a rich body of work explaining complex collective behaviour through its interdependence on structure and this forms the core subject matter of the field complex networks. However, in many cases of interest, the underlying structure of the observed system is often unknown and can only be studied through limited measurements. The first chapters of this thesis develop and refine a method of inferring the structure of a priori unknown networks by leveraging the celebrated Heterogeneous mean-field approximations. The inverse protocol is first formulated for and rigorously challenged against synthetic simulations of reactive-random-walkers to successfully recover the degree distributions from partial observations of the system. The reconstruction framework developed is powerful enough to be applicable to many real-world systems of great interest. This is demonstrated by the extension of the method to a nonlinear Leaky-Integrate and Fire (LIF) excitatory neuronal model evolving on a directed network support to recover both the in-degree distribution and the distribution of associated current in Chapter 5. In this chapter, this method is also applied to wide-field calcium imaging data from the brains of mice undergoing stroke and rehabilitation, which is presented as a spatiotemporal analysis in Chapter 4. The findings of Chapters 4 and 5 complement each other to showcase two potential non-invasive ways of tracking the post-stroke recovery of these animals. One analysis focuses on the subtle changes in propagation patterns quantified through three novel biomarkers, while the other shifts the attention to the changes in structure and inherent dynamics as seen through the inverse protocol. This reconstruction recipe has also been extended to a more general two species LIF model accounting for both inhibitory and excitatory neurons. in Chapter 6. This was applied to two-photon light-sheet microscopy data from zebrafish brains upon successful validation in silico. Lastly, Chapter 7 studies a particular phenomenon of interest where structure and inherent dynamics affect the function in a different but popular class of networks. A zero-mean noise-like prestrain is used to induce contractions in 1D Elastic Network Models. The analysis shows that the exact solution is difficult to probe analytically, while the mean behaviours of the networks are predictable and controllable by tuning the magnitude of the applied prestrain.
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Books on the topic "HETEROGENOUS MEAN FIELD"

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Soret, Agathe Camille. Mean field games with heterogeneous players: From portfolio optimization to network effects. [New York, N.Y.?]: [publisher not identified], 2022.

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Sun, Emily. On the Horizon of World Literature. Fordham University Press, 2021. http://dx.doi.org/10.5422/fordham/9780823294787.001.0001.

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This book compares Romantic England and Republican China as asynchronous moments of incipient literary modernity in different lifeworlds. These moments were oriented alike by “world literature” as a discursive framework of classifications that connected and re-organized local articulations of literary histories and literary modernities. The book examines select literary forms—the literary manifesto, the tale collection, the familiar essay, and the domestic novel—as textual sites for the enactment of new socio-political forms-of-life. These forms function as testing grounds for questions of both literary-aesthetic and socio-political importance: What does it mean to attain a voice? What is a common reader? How does one dwell in the ordinary? What is a woman? In different languages, activating heterogeneous literary and philosophical traditions, the texts analyzed explore by literary means the far-from-settled problem of what it means to be modern in different lifeworlds and ongoing traditions. Authors studied include Percy Bysshe Shelley, Lu Xun, Charles and Mary Lamb, Lin Shu, Zhou Zuoren, Jane Austen, and Eileen Chang. This book contributes to the fields of comparative literature, British Romanticism, and modern Chinese literature.
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Grisold, Wolfgang, Walter Struhal, and Thomas Grisold, eds. Advocacy in Neurology. Oxford University Press, 2019. http://dx.doi.org/10.1093/med/9780198796039.001.0001.

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The concept of advocacy literally means to speak for someone. Rooted in law, the term has been increasingly used in medical and patient-related contexts in the past years. This book focuses on advocacy activities in the field of neurology. Neurology deals with heterogeneous and diverse populations of patients, who suffer from disability, chronic, and often progressive diseases. The complex characteristics of neurological diseases yield exceptional challenges to plan for and implement advocacy activities on all levels. All stakeholders are challenged to provide the support patients need; advocacy facilitates this process and bundles efforts to reach the objective of the advocacy task. Building on the premise that advocacy goes beyond merely theoretical claims, this book collects and organizes advocacy approaches in practice. Thereby, we draw on different dimensions of ‘advocacy in neurological practice’ and discuss implications for management, healthcare, planning, and policymaking. We place special emphasis on what advocacy means for several different diseases, such as amyotrophic lateral sclerosis (ALS), brain tumours, MS, epilepsy among others. Contributions include best practices, lessons learnt, and tools to be used. The main goal of this book is to raise awareness for advocacy in neurology and empower readers to plan for and implement appropriate activities. In advocacy, anyone can be both an advocate and an advocatee. This book offers a seminal contribution for anyone who is pursuing or intending to pursue advocacy in neurology and related fields.
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Brydan, David. Franco's Internationalists. Oxford University Press, 2019. http://dx.doi.org/10.1093/oso/9780198834595.001.0001.

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This book tells the story of the experts who sold the idea of Franco’s ‘social state’. Despite the repression, violence, and social hardship which characterized Spanish life in the 1940s and 1950s, the Franco regime sought to win popular support by promoting its apparent commitment to social justice. This book reveals the vital role which the idea of the social state also played in the regime’s ongoing search for international legitimacy. It shows how social experts, particularly those working in the fields of public health, medicine, and social insurance, were at the forefront of efforts to promote the regime to the outside world. By working with international organizations and transnational networks across Europe, Africa, and Latin America, they sought to sell the idea of Franco’s Spain as a respectable, modern, and socially just state. In doing so the book also seeks to disrupt our understanding of the modern history of internationalism. Exploring what it meant for Francoist experts to think and act internationally, it challenges dominant accounts of internationalism as a liberal, progressive movement by foregrounding the history of fascist, nationalist, imperialist, and religious forms of international cooperation. The case of Spain reveals the contested and heterogenous nature of mid-twentieth-century internationalism, characterized by the tumultuous interplay of overlapping global, regional, and imperial projects. It also brings into focus the overlooked continuities between international structures and projects before and after 1945.
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Book chapters on the topic "HETEROGENOUS MEAN FIELD"

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Kiss, István Z., Joel C. Miller, and Péter L. Simon. "Mean-field approximations for heterogeneous networks." In Interdisciplinary Applied Mathematics, 165–205. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-50806-1_5.

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Li, Quan-Lin, and Feifei Yang. "Mean-Field Analysis for Heterogeneous Work Stealing Models." In Communications in Computer and Information Science, 28–40. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-25861-4_3.

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Bonaccorsi, Stefano, and Silvia Turri. "Deterministic and Stochastic Mean-Field SIRS Models on Heterogeneous Networks." In Discrete and Continuous Models in the Theory of Networks, 67–89. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-44097-8_3.

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Qu, Bo, and Huijuan Wang. "The Accuracy of Mean-Field Approximation for Susceptible-Infected-Susceptible Epidemic Spreading with Heterogeneous Infection Rates." In Studies in Computational Intelligence, 499–510. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-50901-3_40.

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"Advanced Kinetics: Breakdown of Mean Field Approximation." In Modern Heterogeneous Catalysis, 145–66. Weinheim, Germany: Wiley-VCH Verlag GmbH & Co. KGaA, 2017. http://dx.doi.org/10.1002/9783527810253.ch5.

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Shorter, Edward. "Trials." In The Rise and Fall of the Age of Psychopharmacology, edited by Edward Shorter, 177–88. Oxford University Press, 2021. http://dx.doi.org/10.1093/med/9780197574430.003.0011.

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In the years after 1980, drug trials departed increasingly from the concept of treating real patients. Clinical trials accompanied psychopharmacology as a basic means of gathering evidence in the field, but they also served as the premier means of evasion and distortion used fraudulently and covertly to corrupt the evidence base of psychopharmacology. The fundamental problem in running clinical trials of depression treatments was that the “patients” were considered heterogeneous or “fantasy patients” who really had nothing. Leo Hollister recommended that depression trials be confined to patients with serious or “endogenous” depression, who were the minority of patients encountered in clinical practice.
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Rubin, Yoram. "The Eulerian Picture Principles of the Eulerian Approach to Modeling the Transport of Solutes." In Applied Stochastic Hydrogeology. Oxford University Press, 2003. http://dx.doi.org/10.1093/oso/9780195138047.003.0013.

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In this chapter we consider the diffusive and mixing properties of fluids moving in heterogeneous porous media by means of Eulerian velocity fields. We shall discuss here the basic principles of advection and dispersion in heterogeneous media from an Eulerian perspective. The common theme for the various methods we shall explore is the treatment of the concentration as an SRF. The first approach models the concentration through its statistical moments, such as the expected value and the variance, and computes them through a set of differential equations, an equation for each statistical moment. The second approach is MC based, and it computes an ensemble of physically plausible realizations of the concentration field, which can then be used for computing the statistics of the concentration, and from there the probability of events such as the concentration exceeding a threshold value at specified locations and times. Let us emphasize that stochastic modeling of contaminant transport is not just about the effects of media heterogeneity. There is also room for stochastic modeling in uniform media if there is uncertainty with regard to the media's parameters. Prediction with parameter error is discussed in chapter 13. Let us consider the case of passive solutes which are injected into a fluid body at rest.
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Zemmouchi-Ghomari, Leila. "Linked Data." In Advances in Human and Social Aspects of Technology, 87–113. IGI Global, 2019. http://dx.doi.org/10.4018/978-1-5225-6367-9.ch005.

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The data on the web is heterogeneous and distributed, which makes its integration a sine qua non-condition for its effective exploitation within the context of the semantic web or the so-called web of data. A promising solution for web data integration is the linked data initiative, which is based on four principles that aim to standardize the publication of structured data on the web. The objective of this chapter is to provide an overview of the essential aspects of this fairly recent and exciting field, including the model of linked data: resource description framework (RDF), its query language: simple protocol, and the RDF query language (SPARQL), the available means of publication and consumption of linked data, and the existing applications and the issues not yet addressed in research.
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Rouillard, José. "Plastic Interfaces for Ubiquitous Learning." In Ubiquitous and Pervasive Computing, 1582–600. IGI Global, 2010. http://dx.doi.org/10.4018/978-1-60566-960-1.ch098.

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This chapter presents research around pervasive and ubiquitous computing, particularly oriented in the field of human learning. We are studying several solutions to deliver content over a heterogeneous networks and devices. Converting and transmitting documents across electronic networks is not sufficient. We have to deal with contents and containers simultaneously. Related work in interface adaptation and plasticity (the capacity of a user interface to withstand variations of both the system physical characteristics and the environment while preserving usability) is presented and some examples of context-aware adaptation are exposed. We present an adaptive pervasive learning environment, based on contextual QR Codes, where information is presented to learner at the appropriate time and place, and according to a particular task. This learning environment is called PerZoovasive, where learning activities take place in a zoo and are meant to enhance classroom activities.
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Iber, Johannes, Tobias Rauter, and Christian Kreiner. "A Self-Adaptive Software System for Increasing the Reliability and Security of Cyber-Physical Systems." In Advances in Systems Analysis, Software Engineering, and High Performance Computing, 223–46. IGI Global, 2018. http://dx.doi.org/10.4018/978-1-5225-2845-6.ch009.

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The advancement and interlinking of cyber-physical systems offer vast new opportunities for industry. The fundamental threat to this progress is the inherent increase of complexity through heterogeneous systems, software, and hardware that leads to fragility and unreliability. Systems cannot only become more unreliable, modern industrial control systems also have to face hostile security attacks that take advantage of unintended vulnerabilities overseen during development and deployment. Self-adaptive software systems offer means of dealing with complexity by observing systems externally. In this chapter the authors present their ongoing research on an approach that applies a self-adaptive software system in order to increase the reliability and security of control devices for hydro-power plant units. The applicability of the approach is demonstrated by two use cases. Further, the chapter gives an introduction to the field of self-adaptive software systems and raises research challenges in the context of cyber-physical systems.
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Conference papers on the topic "HETEROGENOUS MEAN FIELD"

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Allmeier, Sebastian, and Nicolas Gast. "Mean Field and Refined Mean Field Approximations for Heterogeneous Systems." In SIGMETRICS/PERFORMANCE '22: ACM SIGMETRICS/IFIP PERFORMANCE Joint International Conference on Measurement and Modeling of Computer Systems. New York, NY, USA: ACM, 2022. http://dx.doi.org/10.1145/3489048.3522653.

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Khan, Mohammad Rasheed, Shams Kalam, and Asiya Abbasi. "Integrating Pore Geometrical Characteristics for Permeability Prediction of Tight Carbonates Utilizing Artificial Intelligence." In Abu Dhabi International Petroleum Exhibition & Conference. SPE, 2021. http://dx.doi.org/10.2118/208005-ms.

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Abstract Accurate permeability estimation in tight carbonates is a key reservoir characterization challenge, more pronounced with heterogeneous pore structures. Experiments on large volumes of core samples are required to precisely characterize permeability in such reservoirs which means investment of large amounts of time and capital. Therefore, it is imperative that an integrated model exists that can predict field-wide permeability for un-cored sections to optimize reservoir strategies. Various studies exist with a scope to address this challenge, however, most of them lack universality in application or do not consider important carbonate geometrical features. Accordingly, this work presents a novel correlation to determine permeability of tight carbonates as a function of carbonate pore geometry utilizing a combination of machine learning and optimization algorithms. Primarily, a Deep Learning Neural Network (NN) is constructed and further optimized to produce a data-driven permeability predictor. Customization of the model to tight-heterogenous pore-scale features is accomplished by considering key geometrical carbonate topologies, porosity, formation resistivity, pore cementation representation, characteristic pore throat diameter, pore diameter, and grain diameter. Multiple realizations are conducted spanning from a perceptron-based model to a multi-layered neural net with varying degrees of activation and transfer functions. Next, a physical equation is derived from the optimized model to provide a stand-alone equation for permeability estimation. Validation of the proposed model is conducted by graphical and statistical error analysis of model testing on unseen dataset. A major outcome of this study is the development of a physical mathematical equation which can be used without diving into the intricacy of artificial intelligence algorithms. To evaluate performance of the new correlation, an error metric comprising of average absolute percentage error (AAPE), root mean squared error (RMSE), and correlation coefficient (CC) was used. The proposed correlation performs with low error values and gives CC more than 0.95. A possible reason for this outcome is that the machine learning algorithms can construct relationship between various non-linear inputs (for e.g., carbonate heterogeneity) and output (permeability) parameters through its inbuilt complex interaction of transfer and activation function methodologies.
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Shrivastava, Chandramani, Matthew Blyth, Naoki Sakiyama, Hiroaki Yamamoto, and Adam Haecker. "Ultrasonic Slowness Images for Geological Interpretation: Investigating Field Test Examples of a New LWD Technology." In SPE Annual Technical Conference and Exhibition. SPE, 2021. http://dx.doi.org/10.2118/206264-ms.

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Abstract Borehole images have long been used for various applications related to geological interpretation, geomechanics and well-placement objectives. Based on the physical measurement used, the resolution and detection limit of the image logs vary considerably thereby limiting or enhancing the applications envelope against specific objectives. A new logging-while-drilling (LWD) technology of pitch-catch (PC) ultrasonic is under development, that can also provide borehole images of compressional and shear slowness in anisotropic and / or heterogenous formations both in water and oil-based-mud. Geological application of these images (which have inch-scale resolution) is being assessed and investigated with respect to the already established ultrasonic pulse-echo (PE) LWD images. While PE images show details of the borehole wall and are thus subject to the effects of drilling practices, the PC images reflect the rock mechanical properties of the formation at the depth of investigation of the measurement, in the same fashion as density images. Two case-studies are presented to assess the quality and application of these images; with one vertical and one horizontal well. The PC images are shown to provide a lot of meaningful information in addition to PE images, though the PC images lose out on detailed information related to texture and subtle structural features. In fact, the gross geological features of bedding and some sedimentation sequences have been imaged with confidence, with manifestation of the features available across the entire azimuthal coverage with the new-technology images and confident dips with sinusoidal fits are picked for gross geological variations. The horizontal well PC images have picked up higher confidence low-angled features than the vertical well PC images due to the longer intersection with borehole wall. The slowness images are found to provide confident bed-boundaries, also some fracture-traces are visible only on the slowness images. However, major vertical fractures and drilling-induced fractures (DIF) are more prominent on the PE amplitude images. The results show that slowness images offer the capability to understand gross structural dip and facies variability at a better resolution than conventional LWD images of similar resolution, and with the benefit of not needing to utilize a chemical source in the drilling bottom-hole assembly (BHA) for density images. Although the slowness measurements azimuthally have been developed to investigate near wellbore geomechanical concerns, such as stress, heterogeneity, and anisotropy, it is clear that the resultant images also have geological applications that is demonstrated by the datasets shown. These applications mean that the images could offer a more sustainable geosteering capability if delivered in real-time.
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Yin, Huibing, Prashant G. Mehta, Sean P. Meyn, and Uday V. Shanbhag. "Bifurcation analysis of a heterogeneous mean-field oscillator game model." In 2011 50th IEEE Conference on Decision and Control and European Control Conference (CDC-ECC 2011). IEEE, 2011. http://dx.doi.org/10.1109/cdc.2011.6161203.

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Xie, Tinghan, and Bing-Chang Wang. "Social Optima in Linear Quadratic Mean Field Control with Heterogeneous Agents." In 2022 13th Asian Control Conference (ASCC). IEEE, 2022. http://dx.doi.org/10.23919/ascc56756.2022.9828290.

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Zheng, Tongjia, Qing Han, and Hai Lin. "Backstepping Mean-Field Density Control for Large-Scale Heterogeneous Nonlinear Stochastic Systems." In 2022 American Control Conference (ACC). IEEE, 2022. http://dx.doi.org/10.23919/acc53348.2022.9867882.

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Zhang, Hengxi, Huaze Tang, Yuanquan Hu, Xiaoli Wei, Chenye Wu, Wenbo Ding, and Xiao-Ping Zhang. "Heterogeneous Mean-Field Multi-Agent Reinforcement Learning for Communication Routing Selection in SAGI-Net." In 2022 IEEE 96th Vehicular Technology Conference (VTC2022-Fall). IEEE, 2022. http://dx.doi.org/10.1109/vtc2022-fall57202.2022.10012942.

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Zhou, Zejian, and Hao Xu. "Decentralized Optimal Multi-agent System Tracking Control Using Mean Field Games with Heterogeneous Agent." In 2021 IEEE Conference on Control Technology and Applications (CCTA). IEEE, 2021. http://dx.doi.org/10.1109/ccta48906.2021.9659203.

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Al-Zahrani, Ali Y., F. Richard Yu, and Minyi Huang. "A mean-field game approach for distributed interference and resource management in heterogeneous cellular networks." In 2013 IEEE Global Communications Conference (GLOBECOM 2013). IEEE, 2013. http://dx.doi.org/10.1109/glocomw.2013.6855737.

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wang, tingting, min hu, and lan kou. "A Information Propagation Model Based on Various Emotions and Heterogeneous Mean Field in Social Networks." In 12th EAI International Conference on Mobile Multimedia Communications, Mobimedia 2019, 29th - 30th Jun 2019, Weihai, China. EAI, 2019. http://dx.doi.org/10.4108/eai.29-6-2019.2282013.

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Reports on the topic "HETEROGENOUS MEAN FIELD"

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Russo, David, Daniel M. Tartakovsky, and Shlomo P. Neuman. Development of Predictive Tools for Contaminant Transport through Variably-Saturated Heterogeneous Composite Porous Formations. United States Department of Agriculture, December 2012. http://dx.doi.org/10.32747/2012.7592658.bard.

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The vadose (unsaturated) zone forms a major hydrologic link between the ground surface and underlying aquifers. To understand properly its role in protecting groundwater from near surface sources of contamination, one must be able to analyze quantitatively water flow and contaminant transport in variably saturated subsurface environments that are highly heterogeneous, often consisting of multiple geologic units and/or high and/or low permeability inclusions. The specific objectives of this research were: (i) to develop efficient and accurate tools for probabilistic delineation of dominant geologic features comprising the vadose zone; (ii) to develop a complementary set of data analysis tools for discerning the fractal properties of hydraulic and transport parameters of highly heterogeneous vadose zone; (iii) to develop and test the associated computational methods for probabilistic analysis of flow and transport in highly heterogeneous subsurface environments; and (iv) to apply the computational framework to design an “optimal” observation network for monitoring and forecasting the fate and migration of contaminant plumes originating from agricultural activities. During the course of the project, we modified the third objective to include additional computational method, based on the notion that the heterogeneous formation can be considered as a mixture of populations of differing spatial structures. Regarding uncertainly analysis, going beyond approaches based on mean and variance of system states, we succeeded to develop probability density function (PDF) solutions enabling one to evaluate probabilities of rare events, required for probabilistic risk assessment. In addition, we developed reduced complexity models for the probabilistic forecasting of infiltration rates in heterogeneous soils during surface runoff and/or flooding events Regarding flow and transport in variably saturated, spatially heterogeneous formations associated with fine- and coarse-textured embedded soils (FTES- and CTES-formations, respectively).We succeeded to develop first-order and numerical frameworks for flow and transport in three-dimensional (3-D), variably saturated, bimodal, heterogeneous formations, with single and dual porosity, respectively. Regarding the sampling problem defined as, how many sampling points are needed, and where to locate them spatially in the horizontal x₂x₃ plane of the field. Based on our computational framework, we succeeded to develop and demonstrate a methdology that might improve considerably our ability to describe quntitaively the response of complicated 3-D flow systems. The results of the project are of theoretical and practical importance; they provided a rigorous framework to modeling water flow and solute transport in a realistic, highly heterogeneous, composite flow system with uncertain properties under-specified by data. Specifically, they: (i) enhanced fundamental understanding of the basic mechanisms of field-scale flow and transport in near-surface geological formations under realistic flow scenarios, (ii) provided a means to assess the ability of existing flow and transport models to handle realistic flow conditions, and (iii) provided a means to assess quantitatively the threats posed to groundwater by contamination from agricultural sources.
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Russo, David, and William A. Jury. Characterization of Preferential Flow in Spatially Variable Unsaturated Field Soils. United States Department of Agriculture, October 2001. http://dx.doi.org/10.32747/2001.7580681.bard.

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Preferential flow appears to be the rule rather than the exception in field soils and should be considered in the quantitative description of solute transport in the unsaturated zone of heterogeneous formations on the field scale. This study focused on both experimental monitoring and computer simulations to identify important features of preferential flow in the natural environment. The specific objectives of this research were: (1) To conduct dye tracing and multiple tracer experiments on undisturbed field plots to reveal information about the flow velocity, spatial prevalence, and time evolution of a preferential flow event; (2) To conduct numerical experiments to determine (i) whether preferential flow observations are consistent with the Richards flow equation; and (ii) whether volume averaging over a domain experiencing preferential flow is possible; (3) To develop a stochastic or a transfer function model that incorporates preferential flow. Regarding our field work, we succeeded to develop a new method for detecting flow patterns faithfully representing the movement of water flow paths in structured and non-structured soils. The method which is based on application of ammonium carbonate was tested in a laboratory study. Its use to detect preferential flow was also illustrated in a field experiment. It was shown that ammonium carbonate is a more conservative tracer of the water front than the popular Brilliant Blue. In our detailed field experiments we also succeeded to document the occurrence of preferential flow during soil water redistribution following the cessation of precipitation in several structureless field soils. Symptoms of the unstable flow observed included vertical fingers 20 - 60 cm wide, isolated patches, and highly concentrated areas of the tracers in the transmission zone. Soil moisture and tracer measurements revealed that the redistribution flow became fingered following a reversal of matric potential gradient within the wetted area. Regarding our simulation work, we succeeded to develop, implement and test a finite- difference, numerical scheme for solving the equations governing flow and transport in three-dimensional, heterogeneous, bimodal, flow domains with highly contrasting soil materials. Results of our simulations demonstrated that under steady-state flow conditions, the embedded clay lenses (with very low conductivity) in bimodal formations may induce preferential flow, and, consequently, may enhance considerably both the solute spreading and the skewing of the solute breakthrough curves. On the other hand, under transient flow conditions associated with substantial redistribution periods with diminishing water saturation, the effect of the embedded clay lenses on the flow and the transport might diminish substantially. Regarding our stochastic modeling effort, we succeeded to develop a theoretical framework for flow and transport in bimodal, heterogeneous, unsaturated formations, based on a stochastic continuum presentation of the flow and a general Lagrangian description of the transport. Results of our analysis show that, generally, a bimodal distribution of the formation properties, characterized by a relatively complex spatial correlation structure, contributes to the variability in water velocity and, consequently, may considerably enhance solute spreading. This applies especially in formations in which: (i) the correlation length scales and the variances of the soil properties associated with the embedded soil are much larger than those of the background soil; (ii) the contrast between mean properties of the two subdomains is large; (iii) mean water saturation is relatively small; and (iv) the volume fraction of the flow domain occupied by the embedded soil is relatively large.
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