Academic literature on the topic 'Temporary Network Structure'
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Journal articles on the topic "Temporary Network Structure"
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Zhou, Qiang, Shi-Min Cai, and Yi-Cheng Zhang. "Multiscale community estimation based on temporary local balancing strategy." International Journal of Modern Physics C 31, no. 04 (February 12, 2020): 2050056. http://dx.doi.org/10.1142/s0129183120500564.
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Community division in complex networks has become one of the hot topics in the field of network science. Most of the methods developed based on network topology ignore the dynamic characteristics underlying the structure. By exploring the diffusion process in the network based on random walk, this paper sums up the general rule with temporal characteristics as a temporary local balancing strategy which can be used in the community division. The strategy divides the network into different communities according to the duration of a stable local balancing state in the diffusion process. The longer the duration, the more stable the structure of the community in that state. Applying the strategy to computer-generated and real-world networks, respectively, it is proved that these temporary local balancing states existing in the diffusion process can reveal the internal community structure of the network. In addition, the modular structure appears at different time scales of diffusion process, similar to the hierarchical organization, and also provides a new perspective for multiscale network community detection.
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Song, Kyungwoo, Mingi Ji, Sungrae Park, and Il-Chul Moon. "Hierarchical Context Enabled Recurrent Neural Network for Recommendation." Proceedings of the AAAI Conference on Artificial Intelligence 33 (July 17, 2019): 4983–91. http://dx.doi.org/10.1609/aaai.v33i01.33014983.
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A long user history inevitably reflects the transitions of personal interests over time. The analyses on the user history require the robust sequential model to anticipate the transitions and the decays of user interests. The user history is often modeled by various RNN structures, but the RNN structures in the recommendation system still suffer from the long-term dependency and the interest drifts. To resolve these challenges, we suggest HCRNN with three hierarchical contexts of the global, the local, and the temporary interests. This structure is designed to withhold the global long-term interest of users, to reflect the local sub-sequence interests, and to attend the temporary interests of each transition. Besides, we propose a hierarchical context-based gate structure to incorporate our interest drift assumption. As we suggest a new RNN structure, we support HCRNN with a complementary bi-channel attention structure to utilize hierarchical context. We experimented the suggested structure on the sequential recommendation tasks with CiteULike, MovieLens, and LastFM, and our model showed the best performances in the sequential recommendations.
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Xin, Lai, Zhao De Cun, Huang Long Yang, and Wu D. Ti. "Hybrid Air Route Network Simulation Based on Improved RW-Bucket Algorithm." International Journal of Information Technologies and Systems Approach 15, no. 1 (January 1, 2022): 1–19. http://dx.doi.org/10.4018/ijitsa.304808.
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The fixed-route network is the basis for airlines to carry out flight direction planning. Some countries and regions have introduced temporary routes as a supplement to the fixed route structure. Temporary routes have the advantages of intercepting curves and straightening, and less detouring areas, which can save airlines fuel consumption and improve operational efficiency. This article takes the mixed airline's route network as the research object. Firstly, the structural properties of mixed air route networks are analyzed by using complex network theory. Secondly, the RW-bucket algorithm to generate a mixed air route network structure is analyzed. According to the conclusion of the analysis, the RW-bucket algorithm is improved. Finally two flight information region route network data are used to verify the proposed hybrid route network construction method by computer simulation.
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Zhang, Wenbo, Jing Wang, Guangjie Han, Xinyue Zhang, and Yongxin Feng. "A Cluster Sleep-Wake Scheduling Algorithm Based on 3D Topology Control in Underwater Sensor Networks." Sensors 19, no. 1 (January 4, 2019): 156. http://dx.doi.org/10.3390/s19010156.
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3D topology control in underwater sensor networks is of great significance to ensuring reliable and efficient operation of the network. In this paper, by analyzing the characteristics of an underwater sensor network, we take the cube as the basic unit to perform 3D partition of the monitoring area, define the 3D partition unit and basic cluster structure of the underwater sensor network, and arrange rotating temporary control nodes in the cluster. Then, a cluster sleep-wake scheduling algorithm is proposed that compares the remaining node energy. It selects the node with the largest remaining energy as the working node, and the remaining nodes complete the transition of dormancy and waiting states as long as they reach the preset dormancy time. The node state settings of this phase are completed by the temporary control node. Temporary control nodes selecting and sleep-wake scheduling are used in the algorithm through 3D topology control, which reduces energy consumption and guarantees maximum sensing coverage of the entire network and the connection rate of active nodes. Simulation results further verify the effectiveness of the proposed algorithm.
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Ngoc, Quang Tran, Seunghyun Lee, and Byung Cheol Song. "Facial Landmark-Based Emotion Recognition via Directed Graph Neural Network." Electronics 9, no. 5 (May 6, 2020): 764. http://dx.doi.org/10.3390/electronics9050764.
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Facial emotion recognition (FER) has been an active research topic in the past several years. One of difficulties in FER is the effective capture of geometrical and temporary information from landmarks. In this paper, we propose a graph convolution neural network that utilizes landmark features for FER, which we called a directed graph neural network (DGNN). Nodes in the graph structure were defined by landmarks, and edges in the directed graph were built by the Delaunay method. By using graph neural networks, we could capture emotional information through faces’ inherent properties, like geometrical and temporary information. Also, in order to prevent the vanishing gradient problem, we further utilized a stable form of a temporal block in the graph framework. Our experimental results proved the effectiveness of the proposed method for datasets such as CK+ (96.02%), MMI (69.4%), and AFEW (32.64%). Also, a fusion network using image information as well as landmarks, is presented and investigated for the CK+ (98.47% performance) and AFEW (50.65% performance) datasets.
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Vitomsky, E. V., and D. N. Somov. "Methods for protecting local wireless network aimed at providing temporary silency of signals and information interaction structure." Issues of radio electronics, no. 3 (April 26, 2020): 35–40. http://dx.doi.org/10.21778/2218-5453-2020-3-35-40.
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This work is devoted to the security problem of wireless local area networks. It is known that against a number of typical attacks, the most common IEEE802.11 networks are poorly protected. Existing ways of solving this problem with the help of regular wireless device software are not effective enough, and against some attacks, it is even not possible. One of the reasons, which complicates the solution of this problem, is low level of temporal and spatial security of modern wireless network. Based on the analysis of common attacks on Wi-Fi networks, original protection methods have been developed to consider this aspect. These methods were embodied in a real device. Protection methods are implemented by slightly modifying the standard software of the device having an open hardware platform. An experiment was carried out using this device, which confirmed the possibility of deploying a local wireless network which security was enhanced using the methods proposed in this paper.
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Cheng, Le Feng, Lin Fei Yin, Jing Jiang, and Tao Yu. "Temporary Grounding Lines Detection Method for Distribution Network and its EMTDC Simulation." Advanced Materials Research 971-973 (June 2014): 1361–67. http://dx.doi.org/10.4028/www.scientific.net/amr.971-973.1361.
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In order to solve the safety problem of disassembling the grounding wire temporarily for line maintenance and prevent an anthropogenic short-circuit accident from happening, this paper firstly proposes two safe and convenient detection methods based on directly signal injecting and induced voltage. Then, adopt the power system simulation software PSCAD/EMTDC to build model, some important factors affecting the effect of detecting are studied, which include frequency of signal, no-load transformer, magnetic induced voltage, joint use on the same tower, etc. Finally, a temporary ground wire detection device is developed which is based on the detection methods proposed and also based on modern power electronics technology and signal processing technology, and the field test verify the feasibility and practicability. The developed detection device has some advantages, such as safe-testing, simple structure and operation, easy promotion and so on.
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Obermann, Anne, Irene Molinari, Jean-Philippe Métaxian, Francesco Grigoli, Wilfried Strauch, and Stefan Wiemer. "Structure of Masaya and Momotombo volcano, Nicaragua, investigated with a temporary seismic network." Journal of Volcanology and Geothermal Research 379 (July 2019): 1–11. http://dx.doi.org/10.1016/j.jvolgeores.2019.04.013.
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Cho, Kwang Soo, Jae Woo Kim, Jung-Eun Bae, Ji Ho Youk, Hyun Jeong Jeon, and Ki-Won Song. "Effect of temporary network structure on linear and nonlinear viscoelasticity of polymer solutions." Korea-Australia Rheology Journal 27, no. 2 (May 2015): 151–61. http://dx.doi.org/10.1007/s13367-015-0015-y.
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Goev, Andrey, Sergey Volosov, Irina Sanina, Nataliya Konstantinovskaya, and Margarita Nesterkina. "Registration opportunities of the temporary seismological network of IDG RAS on EEC." Russian Journal of Seismology 2, no. 2 (June 23, 2020): 84–90. http://dx.doi.org/10.35540/2686-7907.2020.2.08.
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In 2017, as a part of the study of the deep structure of the central part of the East European craton (EEC), three temporary seismic observation points were installed. They were equipped with broadband three-component sensors. The position of the stations is due to the need to build a seismic section in the sub-latitudinal direction in order to study the collision zone of the triple junction of mega blocks in the central part of the EEC. Together with the small-aperture seismic array "Mikhnevo" (MHVAR), temporary seismic stations form an area observation system with distances between stations of the order of 100 km. In 2018, the stations of the temporary network of the IDG RAS had registered 765 events of various nature: 222 industrial explosions and 543 earthquakes. During the year, the "Mikhnevo" array records about 5000 events, of which about 1000 are earthquakes at teleseismic and regional distances, and about 900 are identified as industrial explosions. Mutual processing of observed data on the temporary network and on the "Mikhnevo" in some cases (17%) made it possible to specify the results of the location of industrial explosions obtained previously at the "Mikhnevo" over 10 km.
Dissertations / Theses on the topic "Temporary Network Structure"
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LOSITO, MARIO. "What matters for ideation? A cross-level investigation of individual, group, and network factors." Doctoral thesis, Luiss Guido Carli, 2012. http://hdl.handle.net/11385/200805.
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Paper I: The power of star ideators: Does star ideator alone drive the success of
ideas? The virtues and limits of star ideator presence in groups. Paper II: (with Magnusson, M.) The effect of diversity and group familiarity on performance in ideation groups. Paper III: (with Björk, J.) Temporary Network Structure and Group ideation
performance - the effect of centrality and structural holes.
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YEGHIKYAN, Gevorg. "Urban Structure and Mobility as Spatio-temporal complex Networks." Doctoral thesis, Scuola Normale Superiore, 2020. http://hdl.handle.net/11384/94477.
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Contemporary urban life and functioning have become increasingly dependent on mobility. Having become an inherent constituent of urban dynamics, the role of urban moblity in influencing urban processes and morphology has increased dramat- ically. However, the relationship between urban mobility and spatial socio-economic structure has still not been thoroughly understood. This work will attempt to take a complex network theoretical approach to studying this intricate relationship through
• the spatio-temporal evolution of ad-hoc developed network centralities based on the Google PageRank,
• multilayer network regression with statistical random graphs respecting net- work structures for explaining urban mobility flows from urban socio-economic attributes,
• and Graph Neural Networks for predicting mobility flows to or from a specific location in the city.
Making both practical and theoretical contributions to urban science by offering methods for describing, monitoring, explaining, and predicting urban dynamics, this work will thus be aimed at providing a network theoretical framework for developing tools to facilitate better decision-making in urban planning and policy making.
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Gallacher, Kelly Marie. "Using river network structure to improve estimation of common temporal patterns." Thesis, University of Glasgow, 2016. http://theses.gla.ac.uk/7208/.
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Statistical models for data collected over space are widely available and commonly used. These models however usually assume relationships between observations depend on Euclidean distance between monitoring sites whose location is determined using two dimensional coordinates, and that relationships are not direction dependent. One example where these assumptions fail is when data are collected on river networks. In this situation, the location of monitoring sites along a river network relative to other sites is as important as the location in two dimensional space since it can be expected that spatial patterns will depend on the direction of water flow and distance between monitoring sites measured along the river network. Euclidean distance therefore might no longer be the most appropriate distance metric to consider. This is further complicated where it might be necessary to consider both Euclidean distance and distance along the river network if the observed variable is influenced by the land in which the river network is embedded. The Environment Agency (EA), established in 1996, is the government agency responsible for monitoring and improving the water quality in rivers situated in England (and Wales until 2013). A key responsibility of the EA is to ensure that efforts are made to improve and maintain water quality standards in compliance with EU regulations such as the Water Framework Directive (WFD, European Parliament (2000)) and Nitrates Directive (European Parliament, 1991). Environmental monitoring is costly and in many regions of the world funding for environmental monitoring is decreasing (Ferreyra et al., 2002). It is therefore important to develop statistical methods that can extract as much information as possible from existing or reduced monitoring networks. One way to do this is to identify common temporal patterns shared by many monitoring sites so that redundancy in the monitoring network could be reduced by removing non-informative sites exhibiting the same temporal patterns. In the case of river water quality, information about the shape of the river network, such as flow direction and connectivity of monitoring sites, could be incorporated into statistical techniques to improve statistical power and provide efficient inference without the increased cost of collecting more data. Reducing the volume of data required to estimate temporal trends would improve efficiency and provide cost savings to regulatory agencies. The overall aim of this thesis is to investigate how information about the spatial structure of river networks can be used to augment and improve the specfic trends obtained when using a variety of statistical techniques to estimate temporal trends in water quality data. Novel studies are designed to investigate the effect of accounting for river network structure within existing statistical techniques and, where necessary, statistical methodology is developed to show how this might be achieved. Chapter 1 provides an introduction to water quality monitoring and a description of several statistical methods that might be used for this. A discussion of statistical problems commonly encountered when modelling spatiotemporal data is also included. Following this, Chapter 2 applies a dimension reduction technique to investigate temporal trends and seasonal patterns shared among catchment areas in England and Wales. A novel comparison method is also developed to identify differences in the shape of temporal trends and seasonal patterns estimated using several different statistical methods, each of which incorporate spatial information in different ways. None of the statistical methods compared in Chapter 2 specifically account for features of spatial structure found in river networks: direction of water flow, relative influence of upstream monitoring sites on downstream sites, and stream distance. Chapter 3 therefore provides a detailed investigation and comparison of spatial covariance models that can be used to model spatial relationships found in river networks to standard spatial covariance models. Further investigation of the spatial covariance function is presented in Chapter 4 where a simulation study is used to assess how predictions from statistical models based on river network spatial covariance functions are affected by reducing the size of the monitoring network. A study is also developed to compare the predictive performance of statistical models based on a river network spatial covariance function to models based on spatial covariate information, but assuming spatial independence of monitoring sites. Chapters 3 and 4 therefore address the aim of assessing the improvement in information extracted from statistical models after the inclusion of information about river network structure. Following this, Chapter 5 combines the ideas of Chapters 2, 3 and 4 and proposes a novel statistical method where estimated common temporal patterns are adjusted for known spatial structure, identified in Chapters 3 and 4. Adjusting for known structure in the data means that spatial and temporal patterns independent of the river network structure can be more clearly identified since they are no longer confounded with known structure. The final chapter of this thesis provides a summary of the statistical methods investigated and developed within this thesis, identifies some limitations of the work carried out and suggests opportunities for future research. An Appendix provides details of many of the data processing steps required to obtain information about the river network structure in an appropriate form.
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Bazzi, Marya. "Community structure in temporal multilayer networks, and its application to financial correlation networks." Thesis, University of Oxford, 2015. https://ora.ox.ac.uk/objects/uuid:c3f6aa78-904c-4d10-97f3-ae56bb1f574a.
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Many real-world applications in the social, biological, and physical sciences involve large systems of entities that interact together in some way. The number of components in these systems can be extremely large, so some simplification is typically needed for tractable analysis. A common representation of interacting entities is a network. In its simplest form, a network consists of a set of nodes that represent entities and a set of edges between pairs of nodes that represent interactions between those entities. In this thesis, we investigate clustering techniques for time-dependent networks. An important mesoscale feature in networks is communities. Most community-detection methods are designed for time-independent networks. A recent framework for representing temporal networks is multilayer networks. In this thesis, we focus primarily on community detection in temporal networks represented as multilayer networks. We investigate three main topics: a community-detection method known as multilayer modularity maximization, the development of a benchmark for community detection in temporal networks, and the application of multilayer modularity maximization to temporal financial asset-correlation networks. We first investigate theoretical and computational issues in multilayer modularity maximization. We introduce a diagnostic to measure persistence of community structure in a multilayer network partition and we show how communities one obtains with multilayer modularity maximization reflect a trade-off between time-independent community structure within layers and temporal persistence between layers. We discuss computational issues that can arise when solving this method in practice and we suggest ways to mitigate them. We then propose a benchmark for community detection in temporal networks and carry out various numerical experiments to compare the performance of different methods and computational heuristics on our benchmark. We end with an application of multilayer modularity maximization to temporal financial correlation networks.
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Shertil, M. S. "On the induction of temporal structure by recurrent neural networks." Thesis, Nottingham Trent University, 2014. http://irep.ntu.ac.uk/id/eprint/27915/.
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Language acquisition is one of the core problems in artificial intelligence (AI) and it is generally accepted that any successful AI account of the mind will stand or fall depending on its ability to model human language. Simple Recurrent Networks (SRNs) are a class of so-called artificial neural networks that have a long history in language modelling via learning to predict the next word in a sentence. However, SRNs have also been shown to suffer from catastrophic forgetting, lack of syntactic systematicity and an inability to represent more than three levels of centre-embedding, due to the so-called 'vanishing gradients' problem. This problem is caused by the decay of past input information encoded within the error-gradients which vanish exponentially as additional input information is encountered and passed through the recurrent connections. That said, a number of architectural variations have been applied which may compensate for this issue, such as the Nonlinear Autoregressive Network with exogenous inputs (NARX) network and the multi-recurrent network (MRN). In addition to this, Echo State Networks (ESNs) are a relatively new class of recurrent neural network that do not suffer from the vanishing gradients problem and have been shown to exhibit state-of-the-art performance in tasks such as motor control, dynamic time series prediction, and more recently language processing. This research re-explores the class of SRNs and evaluates them against the state-of-the-art ESN to identify which model class is best able to induce the underlying finite-state automaton of the target grammar implicitly through the next word prediction task. In order to meet its aim, the research analyses the internal representations formed by each of the different models and explores the conditions under which they are able to carry information about long term sequential dependencies beyond what is found in the training data. The findings of the research are significant. It reveals that the traditional class of SRNs, trained with backpropagation through time, are superior to ESNs for the grammar prediction task. More specifically, the MRN, with its state-based memory of varying rigidity, is more able to learn the underlying grammar than any other model. An analysis of the MRN’s internal state reveals that this is due to its ability to maintain a constant variance within its state-based representation of the embedded aspects (or finite state machines) of the target grammar. The investigations show that in order to successfully induce complex context free grammars directly from sentence examples, then not only are a hidden layer and output layer recurrency required, but so is self-recurrency on the context layer to enable varying degrees of current and past state information, that are integrated over time.
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Henri, Dominic Charles. "From individuals to ecosystems : a study of the temporal and spatial variation in ecological network structure." Thesis, University of Exeter, 2014. http://hdl.handle.net/10871/15726.
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Ecological network theory has developed from studies of static, binary trophic relationships to the analysis of quantitative, dynamic communities consisting of multiple link-types. Particularly, work has focused on the dynamic nature of ecological networks, which maintains stability in complex communities. However, there are few in situ network-level studies of the determinants of temporal and spatial variation in community structure. This thesis utilises data from a 10-year study of a host-parasitoid network and a collaborative study in an applied ecological setting to identify individual level factors important to network structure. The work aims towards an empirical, predictive framework linking adaptive foraging behaviour to ecological network structure. The results show that condition-dependent foraging behaviours structure host-parasitoid networks. The realised niches of the studied parasitoid species were generally biased towards larger host species and condition-dependent sex ratio allocation increased the likelihood that females would eclose from relatively larger hosts and males from relatively smaller hosts, which resulted in sex ratios deviating from Hamiltonian (50:50) predictions. Further, both of these aspects of behaviour are plastic, where parasitoid behaviour responded to environmental heterogeneity. Particularly, host preference behaviour conformed to an egg-/time-limitation framework, where the size dependency of the behaviour is greater when individuals have a greater likelihood of being egg-limited. Both the size-dependency and the plasticity of these behaviours differed significantly between secondary parasitoid species. This species identity effect interacted with landscape heterogeneity, which may explain some inter- and intra-specific variation in network structure. With respect to applied ecology, the results show that the benefits of natural vegetation for pest control are dependent upon the dispersal capabilities and the diet breadth of the pest and its natural enemies. The findings are evaluated towards a predictive framework for understanding the effects of future climate change on community structure and stability. We consider this framework in terms of applied ecology, particularly pest control ecosystem services provided by natural vegetation in an agricultural environment. The synergistic nature of the multiple determinants of network structure found in this thesis suggest that future studies should focus on the whole network, which is not necessarily the sum of its parts.
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Alrajebah, Nora. "Investigating cascades in social networks : structural and temporal aspects." Thesis, University of Southampton, 2018. https://eprints.soton.ac.uk/420625/.
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There has been significant interest in studying social interactions in online social networks, such as how people exchange opinions, disseminate information, and adopt certain behaviours. One phenomenon addressed is information diffusion: the way information is spread in social networks. Since their emergence, online social networks have been used by people to create and share content. They provide a set of functionalities that facilitate these and other tasks, allowing users to interact with each other. For researchers, these platforms became the basis for understanding complex human behaviours, one of which is the ‘urge’ to share content with others. Online social networks allow users to create and share various types of content daily. In fact, the bulk of the content displayed on these platforms is not original but shared. Thus, the ability to decipher the phenomenon of information diffusion became essential in diverse fields, such as marketeers who wish to create content that spreads, sociologists who wish to understand the underlying phenomenon, and web scientists who wish to understand the web as a sociotechnical entity. In its simplest form, the information diffusion process in online social networks consists of the content that spreads, the context that facilitates the spread, and the outcome of the process. The underlying structure on which the content spreads is the network of connections between users (the social network). Therefore, the structure of the diffusion is also a network that links users, and is based on information about who influences whom to spread the content. This network is known as the cascade. In the literature, diffusion and cascades are intersecting concepts, and they are often used interchangeably. However, this work differentiates the two. Diffusion is used to ii refer to the phenomenon while cascade is used to refer to the result of the diffusion, i.e. the structural representation of the diffusion process. This work investigates information diffusion on Tumblr, an online social network platform that provides reblogging functionality. Reblogging allows users to reblog posts, which creates a cascading behaviour that can be observed. The reblogging history is provided as a list of notes attached to each post and all of its reblogged copies. In practice, these notes have two parts: structural (who reblogged from whom) and temporal (when did the reblogging occur). These two aspects complement each other in providing an understanding of the diffusion process as it manifests in the form of a cascade. Studying such explicit cascades is important as it allows understanding the information diffusion, a phenomenon that occurs in many implicit forms on the Web. This work’s contributions include proposing an information diffusion framework that conceptualises the elements of the diffusion (namely, the content, context and cascade) and how they relate to each other. It also proposes construction models that create cascade networks minimal contextual information and missing/degraded data. In addition, this work provides a survey of the structural and temporal features of cascades, including their definitions and implications. It also investigates Tumblr as a platform for information diffusion, analyses the structural and temporal aspects of Tumblr’s cascades and compares its features with cascades obtained from other platforms. The main findings show that Tumblr’s most popular content create ‘large’ cascades that are deep, branching into a large number of separate and long paths, having a consistent number of reblogs at each depth and at each given time. These cascades gain their popularity throughout time in various ways; some of them feature high reblogging activities followed by idleness phases, others fluctuate more slowly accumulating rebloggings. Few cascades regain their popularity after long periods of idleness, while the majority have one outstanding popularity phase that is never repeated.
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Gardner, Brian C. "Learning spatio-temporally encoded pattern transformations in structured spiking neural networks." Thesis, University of Surrey, 2016. http://epubs.surrey.ac.uk/810241/.
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Increasing evidence indicates that biological neurons process information conveyed by the precise timings of individual spikes. Such observations have prompted studies on artificial networks of spiking neurons, or Spiking Neural Networks (SNNs), that use temporal encodings to represent input features. Potentially, SNNs used in this way are capable of increased computational power in comparison with rate-based networks. This thesis investigates general learning methods for SNNs which utilise the timings of single and multiple output spikes to encode information. To this end, three distinct contributions to SNN learning are made as follows. The first contribution is a proposed reward-modulated synaptic plasticity method for training SNNs to learn sequences of precisely-timed output spikes in response to spatio-temporal input patterns. Results demonstrate the high temporal accuracy of this method, even when synaptic weights in the network are modified by a delayed feedback signal. This method is potentially of biological significance, since synaptic strength modifications have been observed to be modulated by a reward signal, such as dopamine, in the nervous system. The second contribution proposes two new supervised learning rules for SNNs that perform input-output transformations of spatio-temporal spike patterns. Simulations demonstrate the rules are capable of encoding large numbers of input patterns as precisely timed output spikes, comparing favourably with existing work. The final contribution is a new supervised learning rule, termed MultilayerSpiker, for training SNNs containing hidden layers of spiking neurons to temporally encode spatio-temporal spike patterns using single or multiple output spikes. Simulations show MultilayerSpiker supports a very large number of encodings, that is a substantial improvement over existing spike-based multilayer rules, and provides increased classification accuracy when using the timings of multiple rather than single output spikes to identify input patterns.
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Cortés, Rudyar. "Scalable location-temporal range query processing for structured peer-to-peer networks." Thesis, Paris 6, 2017. http://www.theses.fr/2017PA066106/document.
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La recherche et l'indexation de données en fonction d'une date ou d'une zone géographique permettent le partage et la découverte d'informations géolocalisées telles que l'on en trouve sur les réseaux sociaux comme Facebook, Flickr, ou Twitter. Cette réseau social connue sous le nom de Location Based Social Network (LBSN) s'applique à des millions d'utilisateurs qui partagent et envoient des requêtes ciblant des zones spatio-temporelles, permettant d'accéder à des données géolocalisées générées dans une zone géographique et dans un intervalle de temps donné. Un des principaux défis pour de telles applications est de fournir une architecture capable de traiter la multitude d'insertions et de requêtes spatio-temporelles générées par une grande quantité d'utilisateurs. A ces fins, les Tables de Hachage Distribué (DHT) et le paradigme Pair-à-Pair (P2P) sont autant de primitives qui forment la base pour les applications de grande envergure. Cependant, les DHTs sont mal adaptées aux requêtes ciblant des intervalles donnés; en effet, l'utilisation de fonctions de hachage sacrifie la localité des données au profit d'un meilleur équilibrage de la charge. Plusieurs solutions ajoutent le support de requêtes ciblant des ensembles aux DHTs. En revanche ces solutions ont tendance à générer un nombre de messages et une latence élevée pour des requêtes qui ciblent des intervalles. Cette thèse propose deux solutions à large échelle pour l'indexation des données géolocaliséesIndexing and retrieving data by location and time allows people to share and explore massive geotagged datasets observed on social networks such as Facebook, Flickr, and Twitter. This scenario known as a Location Based Social Network (LBSN) is composed of millions of users, sharing and performing location-temporal range queries in order to retrieve geotagged data generated inside a given geographic area and time interval. A key challenge is to provide a scalable architecture that allow to perform insertions and location-temporal range queries from a high number of users. In order to achieve this, Distributed Hash Tables (DHTs) and the Peer-to-Peer (P2P) computing paradigms provide a powerful building block for implementing large scale applications. However, DHTs are ill-suited for supporting range queries because the use of hash functions destroy data locality for the sake of load balance. Existing solutions that use a DHT as a building block allow to perform range queries. Nonetheless, they do not target location-temporal range queries and they exhibit poor performance in terms of query response time and message traffic. This thesis proposes two scalable solutions for indexing and retrieving geotagged data based on location and time
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Le, Nhu Dinh. "Statistical analysis of the temporal-spatial structure of pH levels from the MAP3S/PCN monitoring network." Thesis, University of British Columbia, 1986. http://hdl.handle.net/2429/25884.
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The approach developed by Eynon-Switzer (1983) to analyze the spatial-temporal structure of a data set obtained from the EPRI monitoring network is applied to a data set obtained from the MAP3S/PCN monitoring network. In this approach, a spatio-temporal stochastic model, including deterministic components for seasonal variation and rainfall washout, is fitted to the data. The results indicate that the model fails to capture some of the features of the underlying structure.
In an effort to identify an appropriate model for the data, we examine the raw data in detail. An ANOVA model is fitted to the data. Different criteria such as Akaike, Schwarz, Mallows, etc, are used to identify the 'best' submodel (i.e. eliminate some terms in the full ANOVA model). The results indicate that it is possible to capture the deterministic component of the model with a much smaller model (i.e. fewer parameters). The normality of the residuals is also examined. The results indicate that the data from all stations except one can reasonably be approximated as coming from normal distributions.Science, Faculty of
Statistics, Department of
Graduate
Books on the topic "Temporary Network Structure"
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Yust, Jason. Structural Networks and the Experience of Musical Time. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780190696481.003.0005.
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The network model of temporal structure allows for many generalized concepts of musical time that can be applied across different modalities (rhythmic, tonal, and formal). This chapter defines network depths, distances, paths, centers, skew, and bias, and partially classifies network types such as piles, tortoises, and starfish. A splitting operation on networks is defined and applied to the problem of relating networks in different modalities and finding true disjunctions.
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Yust, Jason. Graph Theory for Temporal Structure. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780190696481.003.0014.
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This chapter introduces mathematical graph theory and develops graph-theory concepts that are useful for temporal networks. By generating chord progressions from networks, the potential musical and temporal meaning of graph-theory concepts, especially cycles, is emphasized. A number of concepts related to trees are introduced to show hierarchical aspects of temporal structure, and to allow for a comparison of Fred Lerdahl and Ray Jackendoff’s prolongational trees to temporal structures. This suggests an enrichment of MOPs through spanning trees, and is channelled into a discussion of graph-theoretic algebras, cycle and edge-cut algebras, as they apply to temporal structures.
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Rocha, Luis E. C., Fredrik Liljeros, and Petter Holme. Sexual and Communication Networks of Internet-Mediated Prostitution. Edited by Scott Cunningham and Manisha Shah. Oxford University Press, 2016. http://dx.doi.org/10.1093/oxfordhb/9780199915248.013.3.
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This chapter examines prostitution as a socioeconomic phenomenon and discusses its contribution to the spread of sexually transmitted infections. Using online network data from Internet-mediated prostitution in Brazil, it looks at the connectedness of individuals on a review website where clients record intimate details about encounters with sex workers. It begins with an overview of networks, including human sexual networks, along with network properties and measures and the dynamics and structure of a sexual network. It describes general models of disease spreading and introduces a specific methodology for temporal networks, where the infection coevolves with network structure. The chapter shows that the structure of the sexual network is highly clustered within cities but that minimal connections exist across cities. It also finds evidence for local bridges between cities: individual clients who frequent prostitutes nationally. Male tourists play important roles in a potential epidemic by linking otherwise distinct communities.
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Bianconi, Ginestra. Multilayer Networks. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780198753919.001.0001.
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Multilayer networks are formed by several networks that interact with each other and co-evolve. Multilayer networks include social networks, financial markets, transportation systems, infrastructures and molecular networks and the brain. The multilayer structure of these networks strongly affects the properties of dynamical and stochastic processes defined on them, which can display unexpected characteristics. For example, interdependencies between different networks of a multilayer structure can cause cascades of failure events that can dramatically increase the fragility of these systems; spreading of diseases, opinions and ideas might take advantage of multilayer network topology and spread even when its single layers cannot sustain an epidemic when taken in isolation; diffusion on multilayer transportation networks can significantly speed up with respect to diffusion on single layers; finally, the interplay between multiplexity and controllability of multilayer networks is a problem with major consequences in financial, transportation, molecular biology and brain networks. This field is one of the most prosperous recent developments of Network Science and Data Science. Multilayer networks include multiplex networks, multi-slice temporal networks, networks of networks, interdependent networks. Multilayer networks are characterized by having a highly correlated multilayer network structure, providing a significant advantage for extracting information from them using multilayer network measures and centralities and community detection methods. The multilayer network dynamics (including percolation, epidemic spreading, diffusion, synchronization, game theory and control) is strongly affected by the multilayer network topology. This book will present a comprehensive account of this emerging field.
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Bianconi, Ginestra. Epidemic Spreading. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780198753919.003.0013.
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Epidemic processes are relevant to studying the propagation of infectious diseases, but their current use extends also to the study of propagation of ideas in the society or memes and news in online social media. In most of the relevant applications epidemic spreading does not actually take place on a single network but propagates in a multilayer network where different types of interaction play different roles. This chapter provides a comprehensive view of the effect that multilayer network structures have on epidemic processes. The Susceptible–Infected–Susceptible (SIS) Model and the Susceptible–Infected–Removed (SIR) Model are characterized on multilayer networks. Additionally, it is shown that the multilayer networks framework can also allow us to study interacting Awareness and epidemic spreading, competing networks and epidemics in temporal networks.
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Yust, Jason. Rhythmic Hierarchy and the Network Model. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780190696481.003.0002.
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The idea of rhythmic hierarchy serves as an introduction to temporal structure in music and a network model (the “MOP” or maximal outerplanar graph) used to represent it. Rhythmic hierarchy relates to meter but is conceptually distinct from it. An argument may be made that rhythmic structure precedes meter (“meter as rhythm”) rather than vice versa. Slow movements from F.J. Haydn and C.P.E. Bach demonstrate the analytical utility of a concept of metricality.
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Yust, Jason. Organized Time. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780190696481.001.0001.
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This book presents a theory of temporal structure for music, making two main arguments. The first is that a single model of temporal structure, expressible in the form of a certain type of mathematical network, is common to all modalities, particularly rhythm, tonality, and form. As a result, we can develop tools to talk about the experience of musical time in abstraction from any particular modality, and make analogies from structural phenomena in one modality to another (e.g., formal counterpoint). The second argument is that each of these modalities is in principle independent: it has its own set of structuring criteria, and it may lead to structures that agree or disagree with each other. The resulting coordination or disjunction between modalities is of more direct aesthetic importance, typically, than anything that can be said about one isolated parameter alone. These claims have deep ramifications for theories of rhythm, tonality, and form: for instance, that it is possible to discuss formal structure without necessary reference to tonal features. Theories of harmony, key, formal function, hypermeter, and closure are developed in conjunction with analysis of a wide range of eighteenth- and nineteenth-century composers, surveys of classical repertoire, and observations about the history of musical styles. A number of mathematical tools for temporal structure are also proposed.
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Yust, Jason. Tonal Structure. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780190696481.003.0003.
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The concept of tonal structure is intimately associated with the person of Heinrich Schenker, but ultimately in order to enter dialogue with Schenker the theory of tonal structure must take the place of “Schenkerian analysis” in our discourse. A number of useful principles of tonal structure may be derived from Schenker’s theory: Schenkerian notation agrees with the network representation for temporal structure, and linear progressions are a good starting point for a tonal structure discovery procedure. The theory of the Ursatz, however, cannot be understood as an empirical claim but rather as a collection of grammatical norms. Also, Schenker’s dismissal of the concept of key is disputed, and a theory of tonal structure to which keys and modulation are integral is presented.
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Coolen, A. C. C., A. Annibale, and E. S. Roberts. Graphs on structured spaces. Oxford University Press, 2017. http://dx.doi.org/10.1093/oso/9780198709893.003.0010.
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This chapter moves beyond viewing nodes as homogeneous dots set on a plane. To introduce more complicated underlying space, multiplex networks (which are defined with layers of interaction on the same underlying node set) and temporal (time-dependent) networks are discussed. It shown that despite the much more complicated underlying space, many of the techniques developed in earlier chapters can be applied. Heterogeneous nodes are introduced as an extension of the stochastic block model for community structure, then extended using methods developed in earlier chapters to more general (continuous) node attributes such as fitness. The chapter closes with a discussion of the intersections and similarities between the many alternative models for capturing topological features that have been presented in the book.
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Inkson, Kerr. The Boundaryless Career. Edited by Susan Cartwright and Cary L. Cooper. Oxford University Press, 2009. http://dx.doi.org/10.1093/oxfordhb/9780199234738.003.0023.
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The boundaryless career type provides a model of career development that appears to have some advantages over traditional occupational or organizational models. In a changing environment, it encourages mobility, flexibility, the development of knowledge and networks, and the taking of responsibility for one's own career. The boundaryless career also resonates effectively with the temporary organization structures and “knowledge workers” becoming characteristic of the new century. It appears a particularly appropriate way of understanding careers in industries, such as film production and software development, that are based on temporary projects rather than permanent structures, but these industries may be merely extreme examples of a wider loosening and crossing of boundaries in the world of work. The organizational career is dead or dying, and boundaryless careers are representative not just of a creative elite of workers, but of the mainstream.
Book chapters on the topic "Temporary Network Structure"
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Belik, Vitaly, André Karch, Philipp Hövel, and Rafael Mikolajczyk. "Leveraging Topological and Temporal Structure of Hospital Referral Networks for Epidemic Control." In Temporal Network Epidemiology, 199–214. Singapore: Springer Singapore, 2017. http://dx.doi.org/10.1007/978-981-10-5287-3_9.
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Kiss, István Z., Luc Berthouze, Joel C. Miller, and Péter L. Simon. "Mapping Out Emerging Network Structures in Dynamic Network Models Coupled with Epidemics." In Temporal Network Epidemiology, 267–89. Singapore: Springer Singapore, 2017. http://dx.doi.org/10.1007/978-981-10-5287-3_12.
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Abeles, M., and Y. Prut. "Temporal structure of cortical activity." In Artificial Neural Networks — ICANN 96, 16. Berlin, Heidelberg: Springer Berlin Heidelberg, 1996. http://dx.doi.org/10.1007/3-540-61510-5_3.
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Kovács, György, and István Szekrényes. "Applying Neural Network Techniques for Topic Change Detection in the HuComTech Corpus." In The Temporal Structure of Multimodal Communication, 147–62. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-22895-8_8.
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Lehmann, Sune. "Fundamental Structures in Temporal Communication Networks." In Computational Social Sciences, 25–48. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-23495-9_2.
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Balkenius, Christian. "A Macro Architecture for Dynamic Processing of Temporal Structures." In International Neural Network Conference, 928. Dordrecht: Springer Netherlands, 1990. http://dx.doi.org/10.1007/978-94-009-0643-3_136.
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Uciński, Dariusz. "Sensor Network Design for Spatio–Temporal Prediction of Distributed Parameter Systems." In Advanced Structured Materials, 193–207. Berlin, Heidelberg: Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-05241-5_11.
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Li, Xiang, Peng Yao, and Yujian Pan. "Towards Structural Controllability of Temporal Complex Networks." In Complex Systems and Networks, 341–71. Berlin, Heidelberg: Springer Berlin Heidelberg, 2015. http://dx.doi.org/10.1007/978-3-662-47824-0_13.
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Qiao, Zhi, Wei Li, and Yunchun Li. "Temporal Network Embedding with Motif Structural Features." In Database Systems for Advanced Applications, 665–81. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-00123-9_53.
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Qiao, Zhi, Wei Li, and Yunchun Li. "Temporal Network Embedding with Motif Structural Features." In Database Systems for Advanced Applications, 665–81. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-00123-9_53.
Full textConference papers on the topic "Temporary Network Structure"
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Ninov, Plamen, and Tzviatka Karagiozova. "MONITORING AND INVESTIGATION OF INTERMITTENT RIVERS IN BULGARIA." In XXVII Conference of the Danubian Countries on Hydrological Forecasting and Hydrological Bases of Water Management. Nika-Tsentr, 2020. http://dx.doi.org/10.15407/uhmi.conference.01.01.
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River flows could be defined according to their surface hydrologic stream duration as either perennial or temporary. Normally perennial streams flow throughout the year, while temporary streams lack surface flow for some periods of the year. Temporary streams are classified as intermittent or ephemeral. Intermittent streams flow in some periods as result of snowmelt and eventually elevated groundwater tables during the periods of increased precipitations. Intermittent streams are poorly represented in existing river monitoring programs in Bulgaria and seldom are objects of regular monitoring. Only in several gauging stations exist hydrological time series. Furthermore, intermittent and ephemeral streams are not adequately protected by current legislation and management strategies in Bulgaria and generally are neglected. The authors discuss the climatic, hydrological and soil conditions in different part of the country as the major factors determining their origin and distribution. Covering the whole territory of Bulgaria the authors identify four main types of intermittent streams as: 1) intermittent flows as result of Mediterranean climatic impact located in the southern part of the country; 2) sinking intermittent flows as result of specific geological and soil characteristics, 3) intermittent flows in large karst and loess areas and finally 4) the sinking flows in alluvium depositions mainly along the large mainstreams. Nevertheless, the limited number of gauging stations built up at these rivers some hydrological information is collected and statistical results are presented as duration curves of temporal rivers, hydrographs with seasonal characteristics etc. Intermittent streams have a hydrologic flow regime with very specific characteristics that place them as interact between land and water. Unfortunately, in Bulgaria there are poorly mapped, recognized, and protected but they have a critical influence on the ecological health of networks. There exists a strong need for new approaches to scientifically study, the structure and function of temporal streams. The construction of monitoring network for the regular registration of their hydrological regime is surely the first required step for their future detailed ingestions, use and protection.
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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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Naciri, Mamoun, and Jean-Pierre Que´au. "The Soft Yoke Mooring and Offloading System for LNG Offloading Applications." In ASME 2003 22nd International Conference on Offshore Mechanics and Arctic Engineering. ASMEDC, 2003. http://dx.doi.org/10.1115/omae2003-37135.
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The ever-rising need for energy and environmental issues have propelled LNG as one of the most promising source of clean energy for the near future. LNG differs greatly from oil when it comes to loading and offloading in at least two respects. Firstly, owing to its temperature at atmospheric pressure (−162°C), Liquefied Natural Gas does not lend itself to offloading via the well-known floating hoses routinely used for oil. Instead, specially designed articulated steel structures are used in all jetty terminals around the world. Secondly, the very nature of long-term contracts negotiated with utility companies requires regular, uninterrupted LNG supply to their network. This requires extremely high availability figures for import/export terminals or floating, moored LNG producing facilities. A new concept based on the well-known soft yoke principle has been developed whereby the yoke structure has the dual function of mooring the LNG carrier to a fixed import terminal or to the stern of a permanently moored Floating LNG (FLNG) FPSO and of supporting the rigid pipe fluid transfer system. Whilst all soft yoke systems built to date permanently moor an oil FPSO to a fixed jacket structure, the new SYMO® system is designed as a temporary mooring for a fleet of dedicated LNG carriers. This paper addresses new engineering challenges associated with the SYMO® system.
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Gong, Jin, M. Hasnat Kabir, and Hidemitsu Furukawa. "Thermal-Mechanical ICN-SMG Gels for Smart Devices." In ASME 2014 Conference on Smart Materials, Adaptive Structures and Intelligent Systems. American Society of Mechanical Engineers, 2014. http://dx.doi.org/10.1115/smasis2014-7667.
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Transparent shape memory gels (SMGs) were developed in our group recently. They are smart materials having the ability to return from a deformed state (temporary shape) to their original (permanent) shapes upon application of a temperature change, which is named the shape memory. One of medical applications of SMGs is tried to use as a smart bandage material. The shape memory property of SMGs is good for fixing, removing and repeating, while their poor ductility is not good for wrapping. In order to improve the ductility of SMGs, a new network structure named as the inter-crosslinking network (ICN), which is composed of both flexible and easily broken chains and rod-like and durable chains, is introduced into the SMGs. Seven SMGs having ICN structure (ICN-SMGs) were synthesized by changing the ratio of monomers and the amount of crosslinker. The dependence of the mechanical properties on synthesis conditions and temperature changing of samples were investigated. The thermal-mechanical ICN-SMG showing the highest mechanical properties with the maximum stress of 4.6 MPa and the maximum strain of 7.4 (elongation 740%) was prepared. The Young’s modula of ICN-SMGs change quickly and reversibly between high temperature and low temperature from 0°C to 80°C. The water content was also discussed. The prepared ICN-SMGs in this paper have the water content in the range of 45∼72wt%. A trial medical bandage for treatment of broken finger was also made by the ICN-SMGs. It works well just by changing the temperature to wrap it around the finger and remove it after healing. The thermal-mechanical ICN-SMGs are supposed to be a very promising medical material for the future.
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Yu, Wenchao, Wei Cheng, Charu C. Aggarwal, Haifeng Chen, and Wei Wang. "Link Prediction with Spatial and Temporal Consistency in Dynamic Networks." 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.2017/467.
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Dynamic networks are ubiquitous. Link prediction in dynamic networks has attracted tremendous research interests. Many models have been developed to predict links that may emerge in the immediate future from the past evolution of the networks. There are two key factors: 1) a node is more likely to form a link in the near future with another node within its close proximity, rather than with a random node; 2) a dynamic network usually evolves smoothly. Existing approaches seldom unify these two factors to strive for the spatial and temporal consistency in a dynamic network. To address this limitation, in this paper, we propose a link prediction model with spatial and temporal consistency (LIST), to predict links in a sequence of networks over time. LIST characterizes the network dynamics as a function of time, which integrates the spatial topology of network at each timestamp and the temporal network evolution. Comparing to existing approaches, LIST has two advantages: 1) LIST uses a generic model to express the network structure as a function of time, which makes it also suitable for a wide variety of temporal network analysis problems beyond the focus of this paper; 2) by retaining the spatial and temporal consistency, LIST yields better prediction performance. Extensive experiments on four real datasets demonstrate the effectiveness of the LIST model.
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Pereira, Fabiola S. F., Gina M. B. Oliveira, and João Gama. "User Preference Dynamics on Evolving Social Networks - Learning, Modeling and Prediction." In XXV Simpósio Brasileiro de Sistemas Multimídia e Web. Sociedade Brasileira de Computação - SBC, 2019. http://dx.doi.org/10.5753/webmedia_estendido.2019.8129.
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The preferences adopted by individuals are constantly modified as these are driven by new experiences, natural life evolution and, mainly, influence from friends. Studying these temporal dynamics of user preferences has become increasingly important for personalization tasks. Online social networks contain rich information about social interactions and relations, becoming essential source of knowledge for the understanding of user preferences evolution. In this thesis, we investigate the interplay between user preferences and social networks over time. We use temporal networks to analyze the evolution of social relationships and propose strategies to detect changes in the network structure based on node centrality. Our findings show that we can predict user preference changes by just observing how her social network structure evolves over time.
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Fullerton, Anne M., Thomas C. Fu, and David E. Hess. "Investigation and Prediction of Wave Impact Loads on Ship Appendage Shapes." In ASME 2007 26th International Conference on Offshore Mechanics and Arctic Engineering. ASMEDC, 2007. http://dx.doi.org/10.1115/omae2007-29217.
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Navy fleet problems with damage to hatches and other appendages after operation in high sea states suggest that wave impact loads may be greater than the current design guidelines of 1000 pounds per square foot (48 kilopascal) (Ship Specification Section 100, General Requirements for Hull Structure and Guidance Manual for Temporary Alterations, NAVSEA S9070-AA-MME-010/SSN, SSBN). These large impact forces not only cause damage to ships and ship structures, they can also endanger the ship’s crew. To design robust marine structures, accurate estimates of all encountered loads are necessary, including the wave impact forces, which are complex and involve wave breaking, making them difficult to estimate numerically. An experiment to investigate wave impact loads was performed at the Naval Surface Warfare Center, Carderock Division in 2005. During this experiment, the horizontal and vertical loads of regular, non-breaking waves on a 12 inch (0.305 m) square plate and a 19.75 inch (0.5 m) diameter horizontal cylinder were measured while varying incident wave height, wavelength, wave steepness, plate angle and immersion level of the plate and cylinder. Wave heights of up to 1.5 feet (0.46 m) were tested, with wavelenghs of up to 30 feet (9.1 m). In all cases, the horizontal wave impact force increased with wave steepness. For some angles, the horizontal wave impact force increased with greater submergence. A feed-forward neural network (FFNN) developed by Applied Simulation Technologies was used to predict the horizontal forces measured during the experiment based on the values of wave height, wavelength, wave steepness, plate angle and immersion level of the plate and cyclinder. A FFNN is a computational method used to develop nonlinear equation systems that use input variables to predict output variables. Predictions of forces from the FFNN compare well with the experimental data, and may be useful in future design of ships and ship structures.
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Bhargava, Nikhil, and Brian C. Williams. "Complexity Bounds for the Controllability of Temporal Networks with Conditions, Disjunctions, and Uncertainty (Extended Abstract)." 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.2019/886.
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In temporal planning, many different temporal network formalisms are used to model real world situations. Each of these formalisms has different features which affect how easy it is to determine whether the underlying network of temporal constraints is consistent. While many of the simpler models have been well-studied from a computational complexity perspective, the algorithms developed for advanced models which combine features have very loose complexity bounds. In this work, we provide tight completeness bounds for strong, weak, and dynamic controllability checking of temporal networks that have conditions, disjunctions, and temporal uncertainty. Our work exposes some of the subtle differences between these different structures and, remarkably, establishes a guarantee that all of these problems are computable in PSPACE.
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Dal Col, Alcebiades, and Luis Gustavo Nonato. "Visual Analytics via Graph Signal Processing." In XXXII Conference on Graphics, Patterns and Images. Sociedade Brasileira de Computação - SBC, 2019. http://dx.doi.org/10.5753/sibgrapi.est.2019.8295.
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This dissertation presents an overview of the extension of the classical signal processing theory to graph domains. Furthermore, we introduce in this dissertation a novel method for visual analysis of dynamic networks, which relies on the graph wavelet theory. Our method enables the automatic analysis of a signal defined on the nodes of a network. We use a fast approximation of the graph wavelet transform to derive a set of wavelet coefficients, which are then used to identify activity patterns on large networks, including their temporal recurrence. The wavelet coefficients naturally encode spatial and temporal variations of the signal, leading to an efficient and meaningful representation. This method allows for the exploration of the structural evolution of the network and their patterns over time. The effectiveness of our approach is demonstrated using different scenarios and comparisons involving real dynamic networks.
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Huang, Hong, Ruize Shi, Wei Zhou, Xiao Wang, Hai Jin, and Xiaoming Fu. "Temporal Heterogeneous Information Network Embedding." 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.2021/203.
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Heterogeneous information network (HIN) embedding, learning the low-dimensional representation of multi-type nodes, has been applied widely and achieved excellent performance. However, most of the previous works focus more on static heterogeneous networks or learning node embedding within specific snapshots, and seldom attention has been paid to the whole evolution process and capturing all temporal dynamics. In order to fill the gap of obtaining multi-type node embeddings by considering all temporal dynamics during the evolution, we propose a novel temporal HIN embedding method (THINE). THINE not only uses attention mechanism and meta-path to preserve structures and semantics in HIN but also combines the Hawkes process to simulate the evolution of the temporal network. Our extensive evaluations with various real-world temporal HINs demonstrate that THINE achieves state-of-the-art performance in both static and dynamic tasks, including node classification, link prediction, and temporal link recommendation.
Reports on the topic "Temporary Network Structure"
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Leis, Sherry, Mike DeBacker, Lloyd Morrison, Gareth Rowell, and Jennifer Haack. Vegetation community monitoring protocol for the Heartland Inventory and Monitoring Network: Narrative, Version 4.0. Edited by Tani Hubbard. National Park Service, November 2022. http://dx.doi.org/10.36967/2294948.
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Native and restored plant communities are part of the foundation of park ecosystems and provide a natural context to cultural and historical events in parks throughout the Heartland Inventory and Monitoring Network (HTLN). Vegetation communities across the HTLN are primarily of three types: prairie, woodland, and forest. Park resource managers need an effective plant community monitoring protocol to guide the development and adaptation of management strategies for maintaining and/or restoring composition and structure of prairies, woodland, and forest communities. Our monitoring design attempts to balance the needs of managers for current information and the need for insight into the changes occurring in vegetation communities over time. This monitoring protocol consists of a protocol narrative (this document) and 18 standard operating procedures (SOPs) for monitoring plant communities in HTLN parks. The scientific objectives of HTLN plant community monitoring are to (1) describe the species composition, structure, and diversity of prairie, woodland, and forested communities; (2) determine temporal changes in the species composition, structure and diversity of prairie, woodland, and forested communities; and (3) determine the relationship between temporal and spatial changes and environmental variables, including specific management practices where possible. This protocol narrative describes the sampling design for plant communities, including the response design (data collection methods), spatial design (distribution of sampling sites within a park), and revisit design (timing and frequency of monitoring visits). Details can be found in the SOPs, which are listed in the Revision History section and available at the Integrated Resource Management Applications (IRMA) website (irma.nps.gov). Other aspects of the protocol summarized in the narrative include procedures for data management and reporting, personnel and operating requirements, and instructions for how to revise the protocol.
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Bornholdt, S., and D. Graudenz. General asymmetric neutral networks and structure design by genetic algorithms: A learning rule for temporal patterns. Office of Scientific and Technical Information (OSTI), July 1993. http://dx.doi.org/10.2172/10186812.
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Raymond, Kara, Laura Palacios, Cheryl McIntyre, and Evan Gwilliam. Status of climate and water resources at Chiricahua National Monument, Coronado National Memorial, and Fort Bowie National Historic Site: Water year 2019. National Park Service, May 2022. http://dx.doi.org/10.36967/nrr-2293370.
Full textAbstract:
Climate and hydrology are major drivers of ecosystems. They dramatically shape ecosystem structure and function, particularly in arid and semi-arid ecosystems. Understanding changes in climate, groundwater, and water quality and quantity is central to assessing the condition of park biota and key cultural resources. The Sonoran Desert Network collects data on climate, groundwater, and surface water at 11 National Park Service units in southern Arizona and New Mexico. This report provides an integrated look at climate, groundwater, and springs conditions at Chiricahua National Monument (NM), Coronado National Memorial (NMem), and Fort Bowie National Historic Site (NHS) during water year (WY) 2019 (October 2018–September 2019). Overall annual precipitation at Chiricahua NM and Coronado NMem in WY2019 was approximately the same as the normals for 1981–2010. (The weather station at Fort Bowie NHS had missing values on 275 days, so data were not presented for that park.) Fall and winter rains were greater than normal. The monsoon season was generally weaker than normal, but storm events related to Hurricane Lorena led to increased late-season rain in September. Mean monthly maximum temperatures were generally cooler than normal at Chiricahua, whereas mean monthly minimum temperatures were warmer than normal. Temperatures at Coronado were more variable relative to normal. The reconnaissance drought index (RDI) indicated that Chiricahua NM was slightly wetter than normal. (The WY2019 RDI could not be calculated for Coronado NMem due to missing data.) The five-year moving mean of annual precipitation showed both park units were experiencing a minor multi-year precipitation deficit relative to the 39-year average. Mean groundwater levels in WY2019 increased at Fort Bowie NHS, and at two of three wells monitored at Chiricahua NM, compared to WY2018. Levels in the third well at Chiricahua slightly decreased. By contrast, water levels declined in five of six wells at Coronado NMem over the same period, with the sixth well showing a slight increase over WY2018. Over the monitoring record (2007–present), groundwater levels at Chiricahua have been fairly stable, with seasonal variability likely caused by transpiration losses and recharge from runoff events in Bonita Creek. At Fort Bowie’s WSW-2, mean groundwater level was also relatively stable from 2004 to 2019, excluding temporary drops due to routine pumping. At Coronado, four of the six wells demonstrated increases (+0.30 to 11.65 ft) in water level compared to the earliest available measurements. Only WSW-2 and Baumkirchner #3 have shown net declines (-17.31 and -3.80 feet, respectively) at that park. Springs were monitored at nine sites in WY2019 (four sites at Chiricahua NM; three at Coronado NMem, and two at Fort Bowie NHS). Most springs had relatively few indications of anthropogenic or natural disturbance. Anthropogenic disturbance included modifications to flow, such as dams, berms, or spring boxes. Examples of natural disturbance included game trails, scat, or evidence of flooding. Crews observed 0–6 facultative/obligate wetland plant taxa and 0–3 invasive non-native species at each spring. Across the springs, crews observed six non-native plant species: common mullein (Verbascum thapsus), spiny sowthistle (Sonchus asper), common sowthistle (Sonchus oleraceus), Lehmann lovegrass (Eragrostis lehmanniana), rabbitsfoot grass (Polypogon monspeliensis), and red brome (Bromus rubens). Baseline data on water quality and water chemistry were collected at all nine sites. It is likely that that all nine springs had surface water for at least some part of WY2019, though temperature sensors failed at two sites. The seven sites with continuous sensor data had water present for most of the year. Discharge was measured at eight sites and ranged from < 1 L/minute to 16.5 L/minute.
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Financial Stability Report - Second Semester of 2020. Banco de la República de Colombia, March 2021. http://dx.doi.org/10.32468/rept-estab-fin.sem2.eng-2020.
Full textAbstract:
The Colombian financial system has not suffered major structural disruptions during these months of deep economic contraction and has continued to carry out its basic functions as usual, thus facilitating the economy's response to extreme conditions. This is the result of the soundness of financial institutions at the beginning of the crisis, which was reflected in high liquidity and capital adequacy indicators as well as in the timely response of various authorities. Banco de la República lowered its policy interest rates 250 points to 1.75%, the lowest level since the creation of the new independent bank in 1991, and provided ample temporary and permanent liquidity in both pesos and foreign currency. The Office of the Financial Superintendent of Colombia, in turn, adopted prudential measures to facilitate changes in the conditions for loans in effect and temporary rules for rating and loan-loss provisions. Finally, the national government expanded the transfers as well as the guaranteed credit programs for the economy. The supply of real credit (i.e. discounting inflation) in the economy is 4% higher today than it was 12 months ago with especially marked growth in the housing (5.6%) and commercial (4.7%) loan portfolios (2.3% in consumer and -0.1% in microloans), but there have been significant changes over time. During the first few months of the quarantine, firms increased their demands for liquidity sharply while consumers reduced theirs. Since then, the growth of credit to firms has tended to slow down, while consumer and housing credit has grown. The financial system has responded satisfactorily to the changes in the respective demands of each group or sector and loans may grow at high rates in 2021 if GDP grows at rates close to 4.6% as the technical staff at the Bank expects; but the forecasts are highly uncertain. After the strict quarantine implemented by authorities in Colombia, the turmoil seen in March and early April, which was evident in the sudden reddening of macroeconomic variables on the risk heatmap in Graph A,[1] and the drop in crude oil and coal prices (note the high volatility registered in market risk for the region on Graph A) the local financial markets stabilized relatively quickly. Banco de la República’s credible and sustained policy response played a decisive role in this stabilization in terms of liquidity provision through a sharp expansion of repo operations (and changes in amounts, terms, counterparties, and eligible instruments), the purchases of public and private debt, and the reduction in bank reserve requirements. In this respect, there is now abundant aggregate liquidity and significant improvements in the liquidity position of investment funds. In this context, the main vulnerability factor for financial stability in the short term is still the high degree of uncertainty surrounding loan quality. First, the future trajectory of the number of people infected and deceased by the virus and the possible need for additional health measures is uncertain. For that reason, there is also uncertainty about the path for economic recovery in the short and medium term. Second, the degree to which the current shock will be reflected in loan quality once the risk materializes in banks’ financial statements is uncertain. For the time being, the credit risk heatmap (Graph B) indicates that non-performing and risky loans have not shown major deterioration, but past experience indicates that periods of sharp economic slowdown eventually tend to coincide with rises in non-performing loans: the calculations included in this report suggest that the impact of the recession on credit quality could be significant in the short term. This is particularly worrying since the profitability of credit establishments has been declining in recent months, and this could affect their ability to provide credit to the real sector of the economy. In order to adopt a forward-looking approach to this vulnerability, this Report presents several stress tests that evaluate the resilience of the liquidity and capital adequacy of credit institutions and investment funds in the event of a hypothetical scenario that seeks to simulate an extreme version of current macroeconomic conditions. The results suggest that even though there could be strong impacts on the credit institutions’ volume of credit and profitability under such scenarios, aggregate indicators of total and core capital adequacy will probably remain at levels that are above the regulatory limits over the horizon of a year. At the same time, the exercises highlight the high capacity of the system's liquidity to face adverse scenarios. In compliance with its constitutional objectives and in coordination with the financial system's security network, Banco de la República will continue to closely monitor the outlook for financial stability at this juncture and will make the decisions that are necessary to ensure the proper functioning of the economy, facilitate the flow of sufficient credit and liquidity resources, and further the smooth operation of the payment systems. Juan José Echavarría Governor