Relevant bibliographies by topics / Multiparty models

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  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
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Academic literature on the topic 'Multiparty models'

Author: Grafiati
Published: 25 May 2024

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Journal articles on the topic "Multiparty models"

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Glasgow, Garrett. "Mixed Logit Models for Multiparty Elections." Political Analysis 9, no. 2 (2001): 116–36. http://dx.doi.org/10.1093/oxfordjournals.pan.a004867.

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Mixed logit (MXL) is a general discrete choice model thus far unexamined in the study of multicandidate and multiparty elections. Mixed logit assumes that the unobserved portions of utility are a mixture of an IID extreme value term and another multivariate distribution selected by the researcher. This general specification allows MXL to avoid imposing the independence of irrelevant alternatives (IIA) property on the choice probabilities. Further, MXL is a flexible tool for examining heterogeneity in voter behavior through random-coefficients specifications. MXL is a more general discrete choice model than multinomial probit (MNP) in several respects, and can be applied to a wider variety of questions about voting behavior than MNP. An empirical example using data from the 1987 British General Election demonstrates the utility of MXL in the study of multicandidate and multiparty elections.
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Alvarez, R. Michael, and Jonathan Nagler. "When Politics and Models Collide: Estimating Models of Multiparty Elections." American Journal of Political Science 42, no. 1 (January 1998): 55. http://dx.doi.org/10.2307/2991747.

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Stoetzer, Lukas F., Marcel Neunhoeffer, Thomas Gschwend, Simon Munzert, and Sebastian Sternberg. "Forecasting Elections in Multiparty Systems: A Bayesian Approach Combining Polls and Fundamentals." Political Analysis 27, no. 2 (November 8, 2018): 255–62. http://dx.doi.org/10.1017/pan.2018.49.

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We offer a dynamic Bayesian forecasting model for multiparty elections. It combines data from published pre-election public opinion polls with information from fundamentals-based forecasting models. The model takes care of the multiparty nature of the setting and allows making statements about the probability of other quantities of interest, such as the probability of a plurality of votes for a party or the majority for certain coalitions in parliament. We present results from two ex ante forecasts of elections that took place in 2017 and are able to show that the model outperforms fundamentals-based forecasting models in terms of accuracy and the calibration of uncertainty. Provided that historical and current polling data are available, the model can be applied to any multiparty setting.
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KAMALI, KAIVAN, XIAOCONG FAN, and JOHN YEN. "TOWARDS A THEORY FOR MULTIPARTY PROACTIVE COMMUNICATION IN AGENT TEAMS." International Journal of Cooperative Information Systems 16, no. 02 (June 2007): 271–98. http://dx.doi.org/10.1142/s0218843007001640.

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Helping behavior in effective teams is achieved via some overlapping "shared mental models" that are developed and maintained by members of the team. In this paper, we take the perspective that multiparty "proactive" communication is critical for establishing and maintaining such a shared mental model among teammates, which is the basis for agents to offer proactive help and to achieve coherent teamwork. We first provide formal semantics for multiparty proactive performatives within a team setting. We then examine how such performatives result in updates to mental model of teammates, and how such updates can trigger helpful behaviors from other teammates. We also provide conversation policies for multiparty proactive performatives.
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Zheng, Boyuan, Patrick Xia, Mahsa Yarmohammadi, and Benjamin Van Durme. "Multilingual Coreference Resolution in Multiparty Dialogue." Transactions of the Association for Computational Linguistics 11 (2023): 922–40. http://dx.doi.org/10.1162/tacl_a_00581.

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Abstract Existing multiparty dialogue datasets for entity coreference resolution are nascent, and many challenges are still unaddressed. We create a large-scale dataset, Multilingual Multiparty Coref (MMC), for this task based on TV transcripts. Due to the availability of gold-quality subtitles in multiple languages, we propose reusing the annotations to create silver coreference resolution data in other languages (Chinese and Farsi) via annotation projection. On the gold (English) data, off-the-shelf models perform relatively poorly on MMC, suggesting that MMC has broader coverage of multiparty coreference than prior datasets. On the silver data, we find success both using it for data augmentation and training from scratch, which effectively simulates the zero-shot cross-lingual setting.
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SCHOFIELD, NORMAN, and ITAI SENED. "Multiparty Competition in Israel, 1988–96." British Journal of Political Science 35, no. 4 (August 22, 2005): 635–63. http://dx.doi.org/10.1017/s0007123405000335.

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Formal models of voting usually assume that political agents, whether parties or candidates, attempt to maximize expected vote shares. ‘Stochastic’ models typically derive the ‘mean voter theorem’ that each agent will adopt a ‘convergent’ policy strategy at the mean of the electoral distribution. In this article, it is argued that this conclusion is contradicted by empirical evidence. Estimates of vote intentions require ‘valence’ terms. The valence of each party derives from the average weight, given by members of the electorate, in judging the overall competence or ‘quality’ of the particular party leader. In empirical models, a party's valence is independent of current policy declarations and can be shown to be statistically significant in the estimation. It is shown here that the addition of valence gives a very strong Bayes factor over an electoral model without valence. The formal model is analysed and shown to be classified by a ‘convergence’ coefficient, defined in terms of the parameters of the empirical model. This coefficient gives necessary and sufficient conditions for convergence. When the necessary condition fails, as it does in these empirical studies with valence, then the convergent equilibrium fails to exist. The empirical evidence is consistent with a formal stochastic model of voting in which there are multiple local Nash equilibria to the vote-maximizing electoral game. Simulation techniques based on the parameters of the empirical model have been used to obtain these local equilibria, which are determined by the principal component of the electoral distribution. Low valence parties, in equilibrium, will tend to adopt positions at the electoral periphery. High valence parties will contest the electoral centre, but will not, in fact, position themselves at the electoral mean. Survey data from Israel for the elections of 1988, 1992 and 1996 are used to compute the parameters of the empirical model and to illustrate the dependence of equilibria on the electoral principal components. The vote maximizing equilibria do not perfectly coincide with the actual party positions. This divergence may be accounted for by more refined models that either (i) include activism or (ii) consider strategic party considerations over post-election coalition bargaining.
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Zhu, Xiao Ming. "Research on Privacy Preserving Data Mining Association Rules Protocol." Advanced Materials Research 756-759 (September 2013): 1661–64. http://dx.doi.org/10.4028/www.scientific.net/amr.756-759.1661.

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Privacy preserving in data mining is a significant direction. There has been growing interests in private concerns for future data mining research. Privacy preserving data mining concentrates on developing accurate models without sharing precise individual data records. A privacy preserving association rule mining algorithm was introduced. This algorithm preserved privacy of individual values by computing scalar product. Then, the data mining and secure multiparty computation are briefly introduced. And proposes an implementation for privacy preserving mining protocol based secure multiparty computation protocol.
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Atanasov, Ivaylo I., Evelina N. Pencheva, Denitsa L. Velkova, and Ivaylo P. Asenov. "Multiparty Call Control at the Network Edge." Elektronika ir Elektrotechnika 26, no. 5 (October 27, 2020): 39–49. http://dx.doi.org/10.5755/j01.eie.26.5.26007.

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Network programmability is a key feature of fifth generation (5G) system which, in combination with cloud-based services, can support many use cases, including mission critical and healthcare communications. Programmability enables flexibility in customization of service connectivity. Multi-access Edge Computing (MEC) services and applications are enablers for network programmability. In this paper, MEC capabilities for programmability of multiparty multimedia call control at the network edge are studied. Multiparty video calls are one of the key applications of 5G, and are efficient way to exchange ideas, knowledge, expertise, information, and so on. The paper presents an approach to design MEC Application Programming Interfaces (APIs) which enable third party applications to create multiparty multimedia sessions and dynamically manage session participations. The API functionality is described by required information and message flows. The paper specifies the proposed MEC API with data model. Feasibility study includes modelling and formal validation of multiparty session state models supported by the network and mobile edge application. The latency injected by the API is evaluated by emulation.
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Song, Hyunjin, Dominic Nyhuis, and Hajo Boomgaarden. "A Network Model of Negative Campaigning: The Structure and Determinants of Negative Campaigning in Multiparty Systems." Communication Research 46, no. 2 (June 13, 2017): 273–94. http://dx.doi.org/10.1177/0093650217712596.

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Scholarly attention to the nature and extent of negative campaigning in nonmajoritarian multiparty systems is steadily growing. While prior studies have made commendable progress in outlining the conditions and consequences of negative campaigning, they have typically disregarded the complex interdependencies of multiactor communication environments. The present study focuses on network-structural determinants of negative campaigning. It does so by relying on unique data from the 2013 Austrian federal election and using exponential random graph models to investigate patterns of mediated negative campaigning. We find that—above and beyond common determinants of negative campaigning—indicators of network structure are important predictors of campaign communication. This suggests that network models are crucial for accurately representing campaign communication patterns in multiparty systems.
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Ma, Xu, Cunmei Ji, Xiaoyu Zhang, Jianfeng Wang, Jin Li, Kuan-Ching Li, and Xiaofeng Chen. "Secure multiparty learning from the aggregation of locally trained models." Journal of Network and Computer Applications 167 (October 2020): 102754. http://dx.doi.org/10.1016/j.jnca.2020.102754.

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Dissertations / Theses on the topic "Multiparty models"

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Dielmann, Alfred. "Automatic recognition of multiparty human interactions using dynamic Bayesian networks." Thesis, University of Edinburgh, 2009. http://hdl.handle.net/1842/4022.

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Relating statistical machine learning approaches to the automatic analysis of multiparty communicative events, such as meetings, is an ambitious research area. We have investigated automatic meeting segmentation both in terms of “Meeting Actions” and “Dialogue Acts”. Dialogue acts model the discourse structure at a fine grained level highlighting individual speaker intentions. Group meeting actions describe the same process at a coarse level, highlighting interactions between different meeting participants and showing overall group intentions. A framework based on probabilistic graphical models such as dynamic Bayesian networks (DBNs) has been investigated for both tasks. Our first set of experiments is concerned with the segmentation and structuring of meetings (recorded using multiple cameras and microphones) into sequences of group meeting actions such as monologue, discussion and presentation. We outline four families of multimodal features based on speaker turns, lexical transcription, prosody, and visual motion that are extracted from the raw audio and video recordings. We relate these lowlevel multimodal features to complex group behaviours proposing a multistreammodelling framework based on dynamic Bayesian networks. Later experiments are concerned with the automatic recognition of Dialogue Acts (DAs) in multiparty conversational speech. We present a joint generative approach based on a switching DBN for DA recognition in which segmentation and classification of DAs are carried out in parallel. This approach models a set of features, related to lexical content and prosody, and incorporates a weighted interpolated factored language model. In conjunction with this joint generative model, we have also investigated the use of a discriminative approach, based on conditional random fields, to perform a reclassification of the segmented DAs. The DBN based approach yielded significant improvements when applied both to the meeting action and the dialogue act recognition task. On both tasks, the DBN framework provided an effective factorisation of the state-space and a flexible infrastructure able to integrate a heterogeneous set of resources such as continuous and discrete multimodal features, and statistical language models. Although our experiments have been principally targeted on multiparty meetings; features, models, and methodologies developed in this thesis can be employed for a wide range of applications. Moreover both group meeting actions and DAs offer valuable insights about the current conversational context providing valuable cues and features for several related research areas such as speaker addressing and focus of attention modelling, automatic speech recognition and understanding, topic and decision detection.
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Bangalore, Kantharaju Reshmashree. "Modelling Cohesive Behaviours for Virtual Agents in Multiparty Interactions." Electronic Thesis or Diss., Sorbonne université, 2021. http://www.theses.fr/2021SORUS230.

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Les interactions de groupe sont une forme de communication couramment utilisée entre humains. Souvent, les membres d'un groupe sont impliqués dans la discussion, la prise de décisions et l'échange d'idées, dans différents contextes (par exemple, réunion, conférence, fête, etc.). La cohésion de groupe décrit le lien partagé qui pousse les membres à rester ensemble et à vouloir travailler ensemble pour atteindre les objectifs du groupe. Dans les interactions de groupe, les humains communiquent et se coordonnent via un certain nombre de comportements verbaux et non verbaux. Dans ce travail de recherche, dans un premier temps, nous reconnaissons la relation entre la cohésion de groupe et certains signaux sociaux d'intérêt non verbaux. Ensuite, nous présentons les résultats sur l'estimation automatique des niveaux de cohésion dans les groupes en utilisant différentes caractéristiques et techniques de représentation des caractéristiques pour les groupes. Les agents virtuels, un personnage animé généré par ordinateur avec des comportements non verbaux de type humain, ont été largement utilisés pour les interactions homme-machine dans diverses applications, par exemple des agents éducatifs, des entraîneurs de santé, des assistants de formation, etc. La plupart des applications jusqu'à présent se sont concentrées sur le développement d'agents pour des interactions dyadiques, c'est-à-dire un seul agent et utilisateur. Un groupe d'agents (multipartite) peut être potentiellement efficace pour persuader, motiver et éduquer les utilisateurs à travers des discussions interactives. Dans l'étape suivante, nous développons un modèle multipartite impliquant plusieurs agents autonomes capables d'afficher un comportement de groupe cohérent, c'est-à-dire un engagement partagé envers les tâches de groupe et une relation positive entre les agents. Compte tenu de l'augmentation du nombre d'applications utilisant des agents virtuels, il est important d'étudier les interactions entre plusieurs agents et l'utilisateur et de comprendre les effets de l'utilisation d'un tel système. Nous émettons l'hypothèse que l'utilisation d'un système multi-agents permettrait à l'utilisateur d'être plus engagé dans la discussion et fournirait différentes perspectives sur le même problème et faciliterait aux utilisateurs de prendre des décisions éclairées. Par conséquent, dans la dernière étape, nous menons plusieurs études d'évaluation des utilisateurs pour comprendre les effets des interactions multipartites sur l'utilisateur et ses perceptions, par exemple le niveau de confiance, la persuasion. Nous présentons des informations sur la forme d'interactions la plus efficace pour promouvoir un changement de comportement ou persuader l'utilisateur à l'aide de différents sujets de conversation de groupe. En résumé, dans cette thèse, nous reconnaissons l'association entre certains signaux sociaux non verbaux et la cohésion de groupe, présentons la précision de l'estimation à l'aide de caractéristiques extraites de ces signaux, développons un modèle multipartite pour simuler un groupe cohésif d'agents affichant des signaux sociaux importants et enfin évaluons l'efficacité d'un tel modèle dans un contexte de changement de comportement et ses effets sur les perceptions des utilisateurs
Group interactions are a commonly used form of communication among humans. Often the members of a group are involved in discussing, making decisions and exchanging ideas, under different settings (e.g., meeting, conference, party etc.). Group Cohesion describes the shared bond that drives the members to stay together and to want to work together to achieve group goals. In group interactions, humans communicate and coordinate with each other via a number of verbal and nonverbal behaviours. In this research work, as a first step we recognise the relation between group cohesion and certain non-verbal social signals of interest. Next, we present the results on automatic estimation of cohesion levels in groups using different features and feature representation techniques for groups. Virtual agents, a computer-generated animated character with human-like non-verbal behaviours, have been widely used for human-computer interactions in various applications e.g., educational agents, health coaches, training assistants etc. Most of the applications so far have focused on developing agents for dyadic interactions i.e., a single agent and user. A group of agents (multiparty) can be potentially effective in persuading, motivating and educating the users through interactive discussions. In the next step, we develop a multiparty model involving multiple autonomous agents that are capable of displaying cohesive group behaviour i.e., shared commitment to group tasks and positive relationship among the agents. Considering the surge in the range of applications using virtual agents, it is important to study the interactions between multiple agents and the user and understand the effects of using such a system. We hypothesise that the use of a multi-agent system would allow the user to be more engaged in the discussion and provide different perspectives on the same issue and facilitate the users to make informed decisions. Therefore, in the final step we conduct multiple user evaluation studies to understand the effects of multiparty interactions on the user and their perceptions e.g., the level of trust, persuasion. We present insights into the most effective form of interactions for promoting behaviour change or persuading the user using different group conversational topics. To summarise, in this thesis we recognise the association between certain non-verbal social signals and group cohesion, present the estimation accuracy using features extracted from these signals, develop a multiparty model to simulate a cohesive group of agents displaying prominent social signals and finally evaluate the effectiveness of such a model in the context of behaviour change and its effects on user’s perceptions
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Malik, Muhammad Usman. "Learning multimodal interaction models in mixed societies A novel focus encoding scheme for addressee detection in multiparty interaction using machine learning algorithms." Thesis, Normandie, 2020. http://www.theses.fr/2020NORMIR18.

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Les travaux de recherche proposés se situe au carrefour de deux domaines de recherche, l'interaction humain-agent et l'apprentissage automatique. L’interaction humain-agent fait référence aux techniques et concepts impliqués dans le développement des agents intelligents, tels que les robots et les agents virtuels, capables d'interagir avec les humains pour atteindre un objectif commun. L’apprentissage automatique, d'autre part, exploite des algorithmes statistiques pour apprendre des modèles de donnée. Les interactions humaines impliquent plusieurs modalités, qui peuvent être verbales comme la parole et le texte, ainsi que les comportements non-verbaux, c'est-à-dire les expressions faciales, le regard, les gestes de la tête et des mains, etc. Afin d'imiter l'interaction humain-humain en temps réel en interaction humain-agent, plusieurs modalités d'interaction peuvent être exploitées. Avec la disponibilité de corpus d'interaction multimodales humain-humain et humain-agent, les techniques d'apprentissage automatique peuvent alors être utilisées pour développer des modèles interdépendants participant à l'interaction humain-agent. À cet égard, nos travaux de recherche proposent des modèles originaux pour la détection de destinataires d'énoncés, le changement de tour de parole et la prédiction du prochain locuteur, et enfin la génération de comportement d'attention visuelle en interaction multipartie. Notre modèle de détection de destinataire prédit le destinataire d'un énoncé lors d'interactions impliquant plus de deux participant. Le problème de détection de destinataires a été traité comme un problème d'apprentissage automatique multiclasse supervisé. Plusieurs algorithmes d'apprentissage ont été entrainés pour développer des modèles de détection de destinataires. Les résultats obtenus montrent que ces propositions sont plus performants qu'un algorithme de référence. Le second modèle que nous proposons concerne le changement de tour de parole et la prédiction du prochain locuteur dans une interaction multipartie. La prédiction du changement de tour est modélisée comme un problème de classification binaire alors que le modèle de prédiction du prochain locuteur est considéré comme un problème de classification multiclasse. Des algorithmes d'apprentissage automatique sont entraînés pour résoudre ces deux problèmes interdépendants. Les résultats montrent que les modèles proposés sont plus performants que les modèles de référence. Enfin, le troisième modèle proposé concerne le problème de génération du comportement d'attention visuelle (CAV) pour les locuteurs et les auditeurs dans une interaction multipartie. Ce modèle est divisé en plusieurs sous-modèles qui sont entraînés par l'apprentissage machine ainsi que par des techniques heuristiques. Les résultats attestent que les systèmes que nous proposons sont plus performants que les modèles de référence développés par des approches aléatoires et à base de règles. Le modèle de génération de comportement CAV proposé est mis en œuvre sous la forme d’une série de quatre modules permettant de créer différents scénarios d’interaction entre plusieurs agents virtuels. Afin de l’évaluer, des vidéos enregistrées pour les modèles de génération de CAV pour les orateurs et les auditeurs, sont présentées à des évaluateurs humains qui évaluent les comportements de référence, le comportement réel issu du corpus et les modèles proposés de CAV sur plusieurs critères de naturalité du comportement. Les résultats montrent que le comportement de CAV généré via le modèle est perçu comme plus naturel que les bases de référence et aussi naturel que le comportement réel
Human -Agent Interaction and Machine learning are two different research domains. Human-agent interaction refers to techniques and concepts involved in developing smart agents, such as robots or virtual agents, capable of seamless interaction with humans, to achieve a common goal. Machine learning, on the other hand, exploits statistical algorithms to learn data patterns. The proposed research work lies at the crossroad of these two research areas. Human interactions involve multiple modalities, which can be verbal such as speech and text, as well as non-verbal i.e. facial expressions, gaze, head and hand gestures, etc. To mimic real-time human-human interaction within human-agent interaction,multiple interaction modalities can be exploited. With the availability of multimodal human-human and human-agent interaction corpora, machine learning techniques can be used to develop various interrelated human-agent interaction models. In this regard, our research work proposes original models for addressee detection, turn change and next speaker prediction, and finally visual focus of attention behaviour generation, in multiparty interaction. Our addressee detection model predicts the addressee of an utterance during interaction involving more than two participants. The addressee detection problem has been tackled as a supervised multiclass machine learning problem. Various machine learning algorithms have been trained to develop addressee detection models. The results achieved show that the proposed addressee detection algorithms outperform a baseline. The second model we propose concerns the turn change and next speaker prediction in multiparty interaction. Turn change prediction is modeled as a binary classification problem whereas the next speaker prediction model is considered as a multiclass classification problem. Machine learning algorithms are trained to solve these two interrelated problems. The results depict that the proposed models outperform baselines. Finally, the third proposed model concerns the visual focus of attention (VFOA) behaviour generation problem for both speakers and listeners in multiparty interaction. This model is divided into various sub-models that are trained via machine learning as well as heuristic techniques. The results testify that our proposed systems yield better performance than the baseline models developed via random and rule-based approaches. The proposed VFOA behavior generation model is currently implemented as a series of four modules to create different interaction scenarios between multiple virtual agents. For the purpose of evaluation, recorded videos for VFOA generation models for speakers and listeners, are presented to users who evaluate the baseline, real VFOA behaviour and proposed VFOA models on the various naturalness criteria. The results show that the VFOA behaviour generated via the proposed VFOA model is perceived more natural than the baselines and as equally natural as real VFOA behaviour
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Skowronek, Janto [Verfasser], Alexander [Akademischer Betreuer] Raake, Alexander [Gutachter] Raake, Sebastian [Gutachter] Möller, and Callet Patrick [Gutachter] Le. "Quality of experience of multiparty conferencing and telemeeting systems : methods and models for assessment and prediction / Janto Skowronek ; Gutachter: Alexander Raake, Sebastian Möller, Patrick Le Callet ; Betreuer: Alexander Raake." Berlin : Technische Universität Berlin, 2017. http://d-nb.info/1156176972/34.

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Menemenlis, Nickie. "Stochastic models for multipath fading channels." Thesis, McGill University, 2002. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=38505.

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The main contribution of this work is to extend the present multi-path fading channel (MFC) models in two directions.
First, the wireless communication system is viewed as a dynamical system where the channel constitutes the main plant of such a system. The random variables characterizing the magnitude of each multi-path component are generalized to random processes with time-varying statistics. It is claimed that the dynamics of both the log-normal shadowing and short-term fading channels is captured by the use of stochastic diffusion processes which emerge from mean-reverting Ornstein-Uhlenbeck processes, implying that signal envelope variations can be modeled using stochastic differential equations. Explicit expressions for signal envelope distributions and second order statistics of the received signal are derived.
Further, the short-term dynamical model is cast into a state-space representation and a nominal model is derived, based on which robust analysis and design can be performed in order to capture additional channel uncertainties.
The dynamical channel models introduced here are in accordance of the physical principles of electromagnetic wave propagation, they are parametric and able to describe diverse propagation environments.
Second, a unified statistical analysis framework is introduced in order to compute the various statistics, second-order properties and densities of the overall received signal of the MFC's. To this end, the MFC model is formulated as a general shot-noise process brought forward by Rice. By extending and adapting the shot-noise analysis to complex signals the statistics of the overall received signal are derived, with explicit computations of the various moments and second-order statistics. The analysis includes the case of moving scatters (i.e. rain droplets) which it is shown to affect the dynamical temporal characteristics of the channel. It is also shown here that samples of the received signal approach a jointly Gaussian density, as certain parameters tend to their limits. Further, when the density of the received signal does not approach the Gaussian density, the Edgeworth series expansion is employed to compute the non-Gaussian density. This analysis brings forward the parameters responsible for Gaussianity of the received signal, parameters which designers can use in order to tailor their transmitter/receiver design. (Abstract shortened by UMI.)
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Abbas, Syed Aun. "Multipath mobile wireless channel, models, interpretations and applications." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 1997. http://www.collectionscanada.ca/obj/s4/f2/dsk2/ftp03/NQ26842.pdf.

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Abbas, Syed A. (Syed Aun) Carleton University Dissertation Engineering Systems and Computer. "Multipath mobile wireless channel; models, interpretations and applications." Ottawa, 1997.

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Chalaça, João Pedro Gonçalves. "Multipath policy routing in packet switched networks." Master's thesis, Faculdade de Ciências e Tecnologia, 2013. http://hdl.handle.net/10362/10716.

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Dissertação apresentada para obtenção do Grau de Mestre em Engenharia Electrotécnica e de Computadores, pela Universidade Nova de Lisboa, Faculdade de Ciências e Tecnologia
Nowadays, the continuous operations of large networks, under multiple ownerships, are of tremendous importance and as a result, routing protocols have gained numerous extensions and accumulated complexity. Policy-based routing can be of signi cance for common networks when the cost of transporting a bit is no longer the biggest pressure point. The best path problem is a generalization of the shortest path problem that suits policy based routing. This means that preferences for the paths depend on semantically rich characteristics, in which two di erent paths may have the same preference. However, current policy-based routing models cannot take full advantage of the multiplicity of connections to a given destination and are single path in nature. Therefore multipath can bring several advantages in policy based routing. Designing multipath routing protocols based on policies seem to be a problem of interest. To model routing problems, algebraic structures and graph theory are used. Through variants of classical methods of linear algebra routing problems can be solved. The objective of this dissertation is to devise a multipath policy-based routing protocol using a simple destination-based hop-by-hop protocol with independent forwarding decisions. Networks featuring these characteristics can be more resilient to failures, provide better tra c distribution and maintain a simple forwarding paradigm. The dissertation concludes with the trade-o 's between the exibility of the proposed solution, the amount of multiple paths that can be used simultaneously and the network restrictions that must be applied.
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Rice, Michael, and Qiang Lei. "SHF MULTIPATH CHANNEL MODELING RESULTS." International Foundation for Telemetering, 2005. http://hdl.handle.net/10150/604799.

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ITC/USA 2005 Conference Proceedings / The Forty-First Annual International Telemetering Conference and Technical Exhibition / October 24-27, 2005 / Riviera Hotel & Convention Center, Las Vegas, Nevada
This paper presents the results of land-based SHF channel modeling experiments. Channel modeling data were collected at Edwards AFB, California at S-Band, X-Band and Ku-band. Frequency domain analysis techniques were used to evaluate candidate channel models. A graphical user interface (GUI) was developed to search for the optimum channel parameters. The model parameters corresponding to different frequencies were compared for multipath events captured at approximately the same locations. A general trend was observed where the magnitude of the first multipath reflection decreased as frequency increased and the delay remained relatively unchanged.
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EDWARDS, KARLA ROBERTA LISA. "Site-Specific Point Positioning and GPS Code Multipath Parameterization and Prediction." The Ohio State University, 2011. http://rave.ohiolink.edu/etdc/view?acc_num=osu1300860715.

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Books on the topic "Multiparty models"

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Shepsle, Kenneth A. Models of multiparty electoral competition. Chur: Harwood Academic Publishers, 1991.

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Greenberg, Joseph. Multiparty equilibria under proportional representation. Stanford, Calif: Institute for Mathematical Studies in the Social Sciences, Stanford University, 1985.

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Weber, Shlomo. On existence of a fixed-number equilibrium in a multiparty electoral system. Toronto: York University, Dept. of Economics, 1990.

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Kovalyov, I. P. SDMA for Multipath Wireless Channels: Limiting Characteristics and Stochastic Models. Berlin, Heidelberg: Springer Berlin Heidelberg, 2004.

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SDMA for multipath wireless channels: Limiting characteristics and stochastic models. Berlin: Springer·, 2003.

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Center, Langley Research, ed. Multipath analysis diffraction calculations. Hampton, Va: National Aeronautics and Space Administration, Langley Research Center, 1996.

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Shepsle, K. Models of Multiparty Electoral Competition. Taylor & Francis Group, 2012.

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Shepsle, K. Models of Multiparty Electoral Competition. Routledge, 2012. http://dx.doi.org/10.4324/9780203714966.

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Shepsle, K. Models of Multiparty Electoral Competition. Taylor & Francis Group, 2012.

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Models of Multiparty Electoral Competition. Routledge, 2012.

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Book chapters on the topic "Multiparty models"

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Lanese, Ivan, and Hernán Melgratti. "Synchronous Multiparty Synchronizations and Transactions." In Concurrency, Graphs and Models, 76–95. Berlin, Heidelberg: Springer Berlin Heidelberg, 2008. http://dx.doi.org/10.1007/978-3-540-68679-8_6.

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Castellani, Ilaria, Mariangiola Dezani-Ciancaglini, and Paola Giannini. "Event Structure Semantics for Multiparty Sessions." In Models, Languages, and Tools for Concurrent and Distributed Programming, 340–63. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-21485-2_19.

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Ng, Nicholas, Nobuko Yoshida, and Kohei Honda. "Multiparty Session C: Safe Parallel Programming with Message Optimisation." In Objects, Models, Components, Patterns, 202–18. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-30561-0_15.

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Beimel, Amos, Eyal Kushilevitz, and Pnina Nissim. "The Complexity of Multiparty PSM Protocols and Related Models." In Advances in Cryptology – EUROCRYPT 2018, 287–318. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-78375-8_10.

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Ma, Xu, Cunmei Ji, Xiaoyu Zhang, Jianfeng Wang, Jin Li, and Kuan-Ching Li. "Secure Multiparty Learning from Aggregation of Locally Trained Models." In Machine Learning for Cyber Security, 173–82. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-30619-9_13.

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Hulcelle, Marc, Giovanna Varni, Nicolas Rollet, and Chloé Clavel. "Computational Multimodal Models of Users’ Interactional Trust in Multiparty Human-Robot Interaction." In Pattern Recognition, Computer Vision, and Image Processing. ICPR 2022 International Workshops and Challenges, 225–39. Cham: Springer Nature Switzerland, 2023. http://dx.doi.org/10.1007/978-3-031-37660-3_16.

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Akshay, S., Blaise Genest, Loïc Hélouët, and Sharvik Mital. "Timed Negotiations." In Lecture Notes in Computer Science, 37–56. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-45231-5_3.

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AbstractNegotiations were introduced in [6] as a model for concurrent systems with multiparty decisions. What is very appealing with negotiations is that it is one of the very few non-trivial concurrent models where several interesting problems, such as soundness, i.e. absence of deadlocks, can be solved in PTIME [3]. In this paper, we introduce the model of timed negotiations and consider the problem of computing the minimum and the maximum execution times of a negotiation. The latter can be solved using the algorithm of [10] computing costs in negotiations, but surprisingly minimum execution time cannot.This paper proposes new algorithms to compute both minimum and maximum execution time, that work in much more general classes of negotiations than [10], that only considered sound and deterministic negotiations. Further, we uncover the precise complexities of these questions, ranging from PTIME to $$\varDelta _2^P$$ Δ 2 P -complete. In particular, we show that computing the minimum execution time is more complex than computing the maximum execution time in most classes of negotiations we consider.
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Kovalyov, Igor P. "Limit Capacity and Statistical Models of Wireless Channels." In SDMA for Multipath Wireless Channels, 11–26. Berlin, Heidelberg: Springer Berlin Heidelberg, 2004. http://dx.doi.org/10.1007/978-3-642-18863-3_2.

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Jamieson, Michael, Yulia Eskin, Afsaneh Fazly, Suzanne Stevenson, and Sven Dickinson. "Discovering Multipart Appearance Models from Captioned Images." In Computer Vision – ECCV 2010, 183–96. Berlin, Heidelberg: Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-15555-0_14.

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Li, Elaine, Felix Stutz, and Thomas Wies. "Deciding Subtyping for Asynchronous Multiparty Sessions." In Programming Languages and Systems, 176–205. Cham: Springer Nature Switzerland, 2024. http://dx.doi.org/10.1007/978-3-031-57262-3_8.

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AbstractMultiparty session types (MSTs) are a type-based approach to verifying communication protocols, represented as global types in the framework. We present a precise subtyping relation for asynchronous MSTs with communicating state machines (CSMs) as implementation model. We address two problems: when can a local implementation safely substitute another, and when does an arbitrary CSM implement a global type? We define safety with respect to a given global type, in terms of subprotocol fidelity and deadlock freedom. Our implementation model subsumes existing work which considers local types with restricted choice. We exploit the connection between MST subtyping and refinement to formulate concise conditions that are directly checkable on the candidate implementations, and use them to show that both problems are decidable in polynomial time.
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Conference papers on the topic "Multiparty models"

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Bohus, Dan, and Eric Horvitz. "Models for multiparty engagement in open-world dialog." In the SIGDIAL 2009 Conference. Morristown, NJ, USA: Association for Computational Linguistics, 2009. http://dx.doi.org/10.3115/1708376.1708409.

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Tang, Anke, Yong Luo, Han Hu, Fengxiang He, Kehua Su, Bo Du, Yixin Chen, and Dacheng Tao. "Improving Heterogeneous Model Reuse by Density Estimation." In Thirty-Second International Joint Conference on Artificial Intelligence {IJCAI-23}. California: International Joint Conferences on Artificial Intelligence Organization, 2023. http://dx.doi.org/10.24963/ijcai.2023/472.

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This paper studies multiparty learning, aiming to learn a model using the private data of different participants. Model reuse is a promising solution for multiparty learning, assuming that a local model has been trained for each party. Considering the potential sample selection bias among different parties, some heterogeneous model reuse approaches have been developed. However, although pre-trained local classifiers are utilized in these approaches, the characteristics of the local data are not well exploited. This motivates us to estimate the density of local data and design an auxiliary model together with the local classifiers for reuse. To address the scenarios where some local models are not well pre-trained, we further design a multiparty cross-entropy loss for calibration. Upon existing works, we address a challenging problem of heterogeneous model reuse from a decision theory perspective and take advantage of recent advances in density estimation. Experimental results on both synthetic and benchmark data demonstrate the superiority of the proposed method.
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Murali, Prasanth, Ian Steenstra, Hye Sun Yun, Ameneh Shamekhi, and Timothy Bickmore. "Improving Multiparty Interactions with a Robot Using Large Language Models." In CHI '23: CHI Conference on Human Factors in Computing Systems. New York, NY, USA: ACM, 2023. http://dx.doi.org/10.1145/3544549.3585602.

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Venkataraman, Vyas, Di Wang, Atabak Mahram, Wei Qin, Mrinal Bose, and Jayanta Bhadra. "Synthesis Oriented Scheduling of Multiparty Rendezvous in Transaction Level Models." In 2009 IEEE Computer Society Annual Symposium on VLSI. IEEE, 2009. http://dx.doi.org/10.1109/isvlsi.2009.8.

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Vishwamitra, Nishant, Yifang Li, Kevin Wang, Hongxin Hu, Kelly Caine, and Gail-Joon Ahn. "Towards PII-based Multiparty Access Control for Photo Sharing in Online Social Networks." In SACMAT'17: The 22nd ACM Symposium on Access Control Models and Technologies. New York, NY, USA: ACM, 2017. http://dx.doi.org/10.1145/3078861.3078875.

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Lee, Dong Won, Yubin Kim, Rosalind W. Picard, Cynthia Breazeal, and Hae Won Park. "MultiPar-T: Multiparty-Transformer for Capturing Contingent Behaviors in Group Conversations." In Thirty-Second International Joint Conference on Artificial Intelligence {IJCAI-23}. California: International Joint Conferences on Artificial Intelligence Organization, 2023. http://dx.doi.org/10.24963/ijcai.2023/433.

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As we move closer to real-world social AI systems, AI agents must be able to deal with multiparty (group) conversations. Recognizing and interpreting multiparty behaviors is challenging, as the system must recognize individual behavioral cues, deal with the complexity of multiple streams of data from multiple people, and recognize the subtle contingent social exchanges that take place amongst group members. To tackle this challenge, we propose the Multiparty-Transformer (Multipar- T), a transformer model for multiparty behavior modeling. The core component of our proposed approach is Crossperson Attention, which is specifically designed to detect contingent behavior between pairs of people. We verify the effectiveness of Multipar-T on a publicly available video-based group engagement detection benchmark, where it outperforms state-of-the-art approaches in average F-1 scores by 5.2% and individual class F-1 scores by up to 10.0%. Through qualitative analysis, we show that our Crossperson Attention module is able to discover contingent behaviors.
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Favre, Sarah, Alfred Dielmann, and Alessandro Vinciarelli. "Automatic role recognition in multiparty recordings using social networks and probabilistic sequential models." In the seventeen ACM international conference. New York, New York, USA: ACM Press, 2009. http://dx.doi.org/10.1145/1631272.1631362.

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Sapru, Ashtosh, and Hervé Bourlard. "Detecting speaker roles and topic changes in multiparty conversations using latent topic models." In Interspeech 2014. ISCA: ISCA, 2014. http://dx.doi.org/10.21437/interspeech.2014-598.

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Otsuka, Kazuhiro, Yoshinao Takemae, and Junji Yamato. "A probabilistic inference of multiparty-conversation structure based on Markov-switching models of gaze patterns, head directions, and utterances." In the 7th international conference. New York, New York, USA: ACM Press, 2005. http://dx.doi.org/10.1145/1088463.1088497.

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Kobayashi, Naohiro, Yasutomo Shimizu, Ryota Nagano, Simon Tupin, Makoto Ito, and Makoto Ohta. "Development and Evaluation of PVA-H 3D Printed Blood Vessel Biomodels With Several Stiffness." In ASME 2020 International Mechanical Engineering Congress and Exposition. American Society of Mechanical Engineers, 2020. http://dx.doi.org/10.1115/imece2020-23525.

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Abstract Biomodels, which are models of tissues such as blood vessels, have recently come into high demand for surgical training or medical device assessment use. Since the stiffness of blood vessels is not uniform, reproducing this nonuniformity would be advantageous to producing more realistic models, and to do this, we used a poly (vinyl alcohol) hydrogel (PVA-H) 3D printer. As a material, recently PVA-H has received increasing attention. This printing technique may be suitable for fabricating models composed of parts exhibiting different levels of stiffness (multipart models). However, the PVA-H 3D printer uses outer molds as supports. Outer mold removal as a post-process might affect the mechanical properties of the models or other post-processes such as ethanol substitution, and this requires investigation. Quality checks on the mechanical properties of the final product are also necessary. In this study, the effect of outer molds on the efficiency of ethanol substitution was estimated by measuring specimen weights. Additionally, the effect of the heat generated when molds were removed with an ultrasonic cleaner on the Young’s modulus of models was tested using tensile tests. Moreover, multipart pieces were fabricated, and their mechanical properties were measured. The findings were that ethanol substitution was able to be completed by conventional methods. Furthermore, the heat generation did not change the Young’s modulus of the models. Also, it was possible to fabricate multipart PVA-H models, and their level of stiffness followed the theoretical equation that assumes constant stiffness and independency of each part. The PVA-H 3D printer, therefore, has the potential to fabricate multipart models that will enable better surgical training and device assessments.
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Reports on the topic "Multiparty models"

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Fairlie, Alan. New challenges for the European Union's Multiparty Trade Agreement with Peru, Colombia and Ecuador. Fundación Carolina, February 2022. http://dx.doi.org/10.33960/issn-e.1885-9119.dtff02en.

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This document analyses the trade and cooperation relations between the European Union and the Andean countries with which the Multiparty Trade Agreement was signed (Peru, Ecuador and Colombia). It also examines the progress and challenges in terms of the sustainable development agenda, political dialogue and cooperation within the framework of the agreement. From there, it explores the different technical difficulties that have arisen in the implementation of the agreement and the role of the monitoring bodies. The aim is to study the strategic importance of the agreement in relations between the European Union and Peru, Ecuador and Colombia, and its contribution to the post-pandemic economic recovery and the promotion of new development models.
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Han, Yijie, and Armand M. Makowski. Resequencing Delays Under Multipath Routing - Asymptotics in a Simple Queueing Model. Fort Belvoir, VA: Defense Technical Information Center, January 2005. http://dx.doi.org/10.21236/ada438991.

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Fairlie, Alan. Nuevos retos para el Acuerdo Comercial Multipartes de la Unión Europea con Perú, Colombia y Ecuador. Fundación Carolina, February 2022. http://dx.doi.org/10.33960/issn-e.1885-9119.dtff02es.

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El presente documento analiza las relaciones comerciales y de cooperación entre la Unión Europea y los países andinos con los que se suscribió el Acuerdo Comercial Multipartes (Perú, Ecuador y Colombia). Asimismo, estudia los avances y desafíos en materia de la agenda de desarrollo sostenible, el diálogo político y la cooperación en el marco del acuerdo. A partir de ahí, explora las diferentes dificultades técnicas que se han presentado en la implementación del acuerdo y el rol de los órganos de seguimiento. Se trata de estudiar la importancia estratégica del acuerdo en las relaciones entre la Unión Europea con Perú, Ecuador y Colombia, y su contribución a la recuperación económica pospandemia y al impulso de nuevos modelos de desarrollo.
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Keskinen, Michael J., and Per A. Kullstam. Preliminary Composite Channel Model for the Mobile User Objective System Including Ionospheric Scintillation and Terrestrial Multipath Effects. Fort Belvoir, VA: Defense Technical Information Center, September 2004. http://dx.doi.org/10.21236/ada426698.

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