Готові списки джерел за темами / Multi-aspect networks

Добірка наукової літератури з теми "Multi-aspect networks"

Автор: Grafiati

Опубліковано: 10 грудня 2022

Оновлено: 28 січня 2023

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Статті в журналах з теми "Multi-aspect networks"

Zhang, Qiuyue, and Ran Lu. "A Multi-Attention Network for Aspect-Level Sentiment Analysis." Future Internet 11, no. 7 (July 16, 2019): 157. http://dx.doi.org/10.3390/fi11070157.

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Aspect-level sentiment analysis (ASA) aims at determining the sentiment polarity of specific aspect term with a given sentence. Recent advances in attention mechanisms suggest that attention models are useful in ASA tasks and can help identify focus words. Or combining attention mechanisms with neural networks are also common methods. However, according to the latest research, they often fail to extract text representations efficiently and to achieve interaction between aspect terms and contexts. In order to solve the complete task of ASA, this paper proposes a Multi-Attention Network (MAN) model which adopts several attention networks. This model not only preprocesses data by Bidirectional Encoder Representations from Transformers (BERT), but a number of measures have been taken. First, the MAN model utilizes the partial Transformer after transformation to obtain hidden sequence information. Second, because words in different location have different effects on aspect terms, we introduce location encoding to analyze the impact on distance from ASA tasks, then we obtain the influence of different words with aspect terms through the bidirectional attention network. From the experimental results of three datasets, we could find that the proposed model could achieve consistently superior results.

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Zhang, Qiuyue, Ran Lu, Qicai Wang, Zhenfang Zhu, and Peiyu Liu. "Interactive Multi-Head Attention Networks for Aspect-Level Sentiment Classification." IEEE Access 7 (2019): 160017–28. http://dx.doi.org/10.1109/access.2019.2951283.

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Брусков, А. А. "Failure propagation in interdependent multi-level networks." Informacionno-technologicheskij vestnik, no. 2(28) (June 17, 2021): 76–90. http://dx.doi.org/10.21499/2409-1650-2021-28-2-76-90.

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В этой работе разрабатываются новый подход и алгоритмические инструменты для моделирования и анализа живучести сетей с разнородными узлами, а также рассматривается их применение в космических сетях. Космические сети позволяют совместно использовать ресурсы космических аппаратов на орбите, такие как хранение, обработка и обмен данными. Каждый космический аппарат в сети может иметь различный состав и функциональность подсистем, что приводит к неоднородности узлов. Большинство традиционных анализов живучести сетей предполагают однородность узлов и в результате не подходят для анализа космических сетей. Эта работа предполагает, что гетерогенные сети могут быть смоделированы как взаимозависимые многоуровневые сети, что позволяет проводить анализ их живучести. Многоуровневый аспект фиксирует разбивку сети в соответствии с общими функциональными возможностями в различных узлах и позволяет создавать однородные подсети, в то время как аспект взаимозависимости ограничивает сеть для захвата физических характеристик каждого узла. In this paper, we develop a new approach and algorithmic tools for modeling and analyzing the survivability of networks with heterogeneous nodes, and also consider their application in space networks. Space networks allow the sharing of spacecraft resources in orbit, such as data storage, processing, and exchange. Each spacecraft in the network may have a different composition and functionality of subsystems, which leads to heterogeneity of nodes. Most traditional network survivability analyses assume node homogeneity and as a result are not suitable for space network analysis. This work suggests that heterogeneous networks can be modeled as interdependent multi-level networks, allowing analysis of their survivability. The multi-level aspect captures the network breakdown according to the common functionality in different nodes and allows for the creation of homogeneous subnets, while the interdependence aspect restricts the network to capture the physical characteristics of each node.

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Lan, Zhouxin, Qing He, and Liu Yang. "Dual-Channel Interactive Graph Convolutional Networks for Aspect-Level Sentiment Analysis." Mathematics 10, no. 18 (September 13, 2022): 3317. http://dx.doi.org/10.3390/math10183317.

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Aspect-level sentiment analysis aims to identify the sentiment polarity of one or more aspect terms in a sentence. At present, many researchers have applied dependency trees and graph neural networks (GNNs) to aspect-level sentiment analysis and achieved promising results. However, when a sentence contains multiple aspects, most methods model each aspect independently, ignoring the issue of sentiment connection between aspects. To address this problem, this paper proposes a dual-channel interactive graph convolutional network (DC-GCN) model for aspect-level sentiment analysis. The model considers both syntactic structure information and multi-aspect sentiment dependencies in sentences and employs graph convolutional networks (GCN) to learn its node information representation. Particularly, to better capture the representations of aspect and opinion words, we exploit the attention mechanism to interactively learn the syntactic information features and multi-aspect sentiment dependency features produced by the GCN. In addition, we construct the word embedding layer by the BERT pre-training model to better learn the contextual semantic information of sentences. The experimental results on the restaurant, laptop, and twitter datasets show that, compared with the state-of-the-art model, the accuracy is up to 1.86%, 2.50, 1.36%, and 0.38 and the Macro-F1 values are up to 1.93%, 0.61%, and 0.4%, respectively.

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Qiu, Heqian, Hongliang Li, Qingbo Wu, Fanman Meng, King Ngi Ngan, and Hengcan Shi. "A2RMNet: Adaptively Aspect Ratio Multi-Scale Network for Object Detection in Remote Sensing Images." Remote Sensing 11, no. 13 (July 4, 2019): 1594. http://dx.doi.org/10.3390/rs11131594.

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Object detection is a significant and challenging problem in the study area of remote sensing and image analysis. However, most existing methods are easy to miss or incorrectly locate objects due to the various sizes and aspect ratios of objects. In this paper, we propose a novel end-to-end Adaptively Aspect Ratio Multi-Scale Network (A 2 RMNet) to solve this problem. On the one hand, we design a multi-scale feature gate fusion network to adaptively integrate the multi-scale features of objects. This network is composed of gate fusion modules, refine blocks and region proposal networks. On the other hand, an aspect ratio attention network is leveraged to preserve the aspect ratios of objects, which alleviates the excessive shape distortions of objects caused by aspect ratio changes during training. Experiments show that the proposed A 2 RMNet significantly outperforms the previous state of the arts on the DOTA dataset, NWPU VHR-10 dataset, RSOD dataset and UCAS-AOD dataset by 5.73 % , 7.06 % , 3.27 % and 2.24 % , respectively.

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Robinson, M., M. R. Azimi-Sadjadi, and J. Salazar. "Multi-Aspect Target Discrimination Using Hidden Markov Models and Neural Networks." IEEE Transactions on Neural Networks 16, no. 2 (March 2005): 447–59. http://dx.doi.org/10.1109/tnn.2004.841805.

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Corchuelo, Rafael, José A. Pérez, and Antonio Ruiz-Cortés. "Aspect-oriented interaction in multi-organisational web-based systems." Computer Networks 41, no. 4 (March 2003): 385–406. http://dx.doi.org/10.1016/s1389-1286(02)00398-5.

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Xu, Nan, Wenji Mao, and Guandan Chen. "Multi-Interactive Memory Network for Aspect Based Multimodal Sentiment Analysis." Proceedings of the AAAI Conference on Artificial Intelligence 33 (July 17, 2019): 371–78. http://dx.doi.org/10.1609/aaai.v33i01.3301371.

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As a fundamental task of sentiment analysis, aspect-level sentiment analysis aims to identify the sentiment polarity of a specific aspect in the context. Previous work on aspect-level sentiment analysis is text-based. With the prevalence of multimodal user-generated content (e.g. text and image) on the Internet, multimodal sentiment analysis has attracted increasing research attention in recent years. In the context of aspect-level sentiment analysis, multimodal data are often more important than text-only data, and have various correlations including impacts that aspect brings to text and image as well as the interactions associated with text and image. However, there has not been any related work carried out so far at the intersection of aspect-level and multimodal sentiment analysis. To fill this gap, we are among the first to put forward the new task, aspect based multimodal sentiment analysis, and propose a novel Multi-Interactive Memory Network (MIMN) model for this task. Our model includes two interactive memory networks to supervise the textual and visual information with the given aspect, and learns not only the interactive influences between cross-modality data but also the self influences in single-modality data. We provide a new publicly available multimodal aspect-level sentiment dataset to evaluate our model, and the experimental results demonstrate the effectiveness of our proposed model for this new task.

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Singh, Omkar, and Vinay Rishiwal. "QoS Aware Multi-hop Multi-path Routing Approach in Wireless Sensor Networks." International Journal of Sensors, Wireless Communications and Control 9, no. 1 (July 15, 2019): 43–52. http://dx.doi.org/10.2174/2210327908666180703143435.

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Background & Objective: Wireless Sensor Network (WSN) consist of huge number of tiny senor nodes. WSN collects environmental data and sends to the base station through multi-hop wireless communication. QoS is the salient aspect in wireless sensor networks that satisfies end-to-end QoS requirement on different parameters such as energy, network lifetime, packets delivery ratio and delay. Among them Energy consumption is the most important and challenging factor in WSN, since the senor nodes are made by battery reserved that tends towards life time of sensor networks. Methods: In this work an Improve-Energy Aware Multi-hop Multi-path Hierarchy (I-EAMMH) QoS based routing approach has been proposed and evaluated that reduces energy consumption and delivers data packets within time by selecting optimum cost path among discovered routes which extends network life time. Results and Conclusion: Simulation has been done in MATLAB on varying number of rounds 400- 2000 to checked the performance of proposed approach. I-EAMMH is compared with existing routing protocols namely EAMMH and LEACH and performs better in terms of end-to-end-delay, packet delivery ratio, as well as reduces the energy consumption 13%-19% and prolongs network lifetime 9%- 14%.

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Xu, Guangtao, Peiyu Liu, Zhenfang Zhu, Jie Liu, and Fuyong Xu. "Attention-Enhanced Graph Convolutional Networks for Aspect-Based Sentiment Classification with Multi-Head Attention." Applied Sciences 11, no. 8 (April 18, 2021): 3640. http://dx.doi.org/10.3390/app11083640.

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The purpose of aspect-based sentiment classification is to identify the sentiment polarity of each aspect in a sentence. Recently, due to the introduction of Graph Convolutional Networks (GCN), more and more studies have used sentence structure information to establish the connection between aspects and opinion words. However, the accuracy of these methods is limited by noise information and dependency tree parsing performance. To solve this problem, we proposed an attention-enhanced graph convolutional network (AEGCN) for aspect-based sentiment classification with multi-head attention (MHA). Our proposed method can better combine semantic and syntactic information by introducing MHA and GCN. We also added an attention mechanism to GCN to enhance its performance. In order to verify the effectiveness of our proposed method, we conducted a lot of experiments on five benchmark datasets. The experimental results show that our proposed method can make more reasonable use of semantic and syntactic information, and further improve the performance of GCN.

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Більше джерел

Дисертації з теми "Multi-aspect networks"

Smoreda, Zbigniew. "Sociabilités ordinaires, réseaux sociaux et médiation des technologies de communication." Phd thesis, Université Paris-Est, 2008. http://tel.archives-ouvertes.fr/tel-00469439.

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La forte croissance des Technologies d'Information et de Communication (TIC) constitue un défi, tant pour les études qui portent sur la sociabilité que pour celles qui traitent des usages de ces technologies. Elle oblige en fait à réinterroger des méthodologies et des analyses sociologiques qui se sont jusqu'alors principalement fondées autour de la sociabilité en face-àface. Le travail présenté retrace l'historique des recherches conduites par l'auteur depuis dix ans sur les pratiques de communication outillées par les TIC. Il pose les hypothèses développées autour des liens entre la sociabilité et le téléphone fixe, puis il examine les effets de la popularisation des moyens de contact mobiles et individualisés tels que le téléphone cellulaire sur les pratiques de communication interpersonnelle. Il s'achève avec des questions méthodologiques et un regard sur des recherches plus récentes qui s'efforcent de saisir la sociabilité à travers l'ensemble des contextes et des moyens technologiques de communication largement diffusés ces dernières années. L'articulation entre médias de communication et sociabilités est modifiée par la transformation du paysage technologique actuel. Même s'ils ne les conditionnent ni ne les déterminent, les outils de communication posent les cadres d'interaction dans lesquels sont entretenus les liens sociaux. Les manières de construire, d'administrer et d'alimenter ces liens sont étroitement entrelacées avec l'outillage qui médiatise les contacts. Au même moment, une forte corrélation entre rencontres en face-à-face et appels échangés avec les proches est observée. Ce constat reste d'ailleurs valable pour l'ensemble des nouveaux outils de communication. Les recherches montrent que chaque nouveau service de communication adopté s'inscrit dans l'économie relationnelle globale, en augmentant le nombre des possibilités de tisser le lien. Il n'y a donc pas de substitution entre les différents outils de contact, mais des agencements continuels au fur et à mesure que les nouveaux instruments de communication apparaissent et sont insérés dans la partition qui fait vivre les liens interpersonnels. L'inscription des TIC dans les pratiques sociales est aujourd'hui si forte qu'il devient difficile de pouvoir analyser des interactions, des liens ou des réseaux sociaux, sans prendre en compte les outils techniques qui les épaulent, les orientent et les cadencent. En particulier, le passage vers les outils de communication mobiles et délocalisés, par rapport aux lieux habituels de présence outillée (maison, bureau.), transforme en partie notre accessibilité aux autres. Les nouveaux usages relationnels, lourdement instrumentés en outils de communication, favorisés par le recours aux dispositifs de communication portables, particulièrement adaptés à des enjeux de coordination, s'appuient sur le développement et le recours croissant aux messageries (email, SMS, IM). Même si ces technologies allègent les contraintes de disponibilité que les TIC font peser sur les acteurs en permettant une réponse différée aux sollicitations, la multiplication des échanges médiatisés fait croître la pression d'une nouvelle cadence relationnelle. Cette imbrication du " réel " et du " virtuel " dans la sociabilité de tous les jours risque de produire des formes de contrôle et des manières de gérer sa propre joignabilité inédites et à terme reconstruire les rythmes et les normes relationnels

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Malardé, Vincent. "Économie collaborative et régulation des plateformes numériques." Thesis, Rennes 1, 2019. http://www.theses.fr/2019REN1G006.

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Facilitée par les plateformes de pair à pair, l’économie collaborative s’est ancrée dans les habitudes des Français. Airbnb, Blablacar, Leboncoin... ces plateformes sont désormais bien connues des Français. Cette thèse a pour ambition d’apporter davantage d’éléments, théoriques et empiriques, afin d’éclairer les débats actuels autour de ces plateformes. Ce travail de thèse commence par exploiter des données d’enquête afin de mesurer l’importance de l’utilisation des plateformes collaboratives en France, et établir les caractéristiques socio-économiques des utilisateurs. Ensuite, cette thèse s’intéresse aux dynamiques de développement d’une plateforme collaborative, à travers l’exemple de la plateforme française de covoiturage domicile-travail, iDVROOM. L’objectif est d’étudier le rôle complémentaire des effets de réseau, des effets spatiaux et des effets de communauté sur le développement de la plateforme. La suite de cette thèse s’intéresse à la concurrence entre la plateforme de location Airbnb et les hôteliers, à Paris. L’effet de la densité de l’offre sur la plateforme collaborative sur le prix pratiqué par un hôtelier fait l’objet d’une première étude empirique, avant d’être modélisé de façon théorique afin de discuter des effets possibles de différents moyens de réguler de l’activité de la plateforme. Enfin la concurrence entre deux plateformes est analysée lorsque celles-ci ont la possibilité de mettre en place des stratégies de discrimination tarifaires destinées à encourager l’exclusivité côté offreurs. La conclusion revient sur les implications de ces résultats pour les décideurs publics, les plateformes et la recherche académique
Facilitated by peer-to-peer platforms, the sharing economy has become part of the French way of life. Airbnb, Blablacar, Leboncoin... these platforms are now well known in France. This thesis aims to provide more elements, both theoretical and empirical, to inform the current debates around these platforms. This thesis work begins by using survey data to measure the importance of the use of collaborative platforms in France, and to establish the socio-economic characteristics of users. Then this thesis focuses on the dynamics of developing a collaborative platform,through the example of the French home-to-work ride-sharing platform, iDVROOM. The objective is to study the complementary role of network effects, spatial effects and community effects on the development of the platform. The rest of this thesis focuses on the competition between the short-term rental platform Airbnb and the hotel industry in Paris. The effect of the density of hosts on the collaborative platform on the price charged by an hotel is the subject of a firstempirical study, before being modeled in a theoretical way to discuss the possible effects of a set of alternative regulations of the platform’s activity. Finally, competition between two platforms is analysed when they have the possibility of implementing tariff discrimination strategies designed to encourage supplier exclusivity. The conclusion develops the implications of these results forpolicy makers, platforms and academic research

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Частини книг з теми "Multi-aspect networks"

Yin, Chang, Qing Zhou, Liang Ge, and Jiaojiao Ou. "Multi-hop Syntactic Graph Convolutional Networks for Aspect-Based Sentiment Classification." In Knowledge Science, Engineering and Management, 213–24. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-55393-7_20.

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Wu, Lijuan, Guixian Zhang, Zhi Lei, Zhirong Huang, and Guangquan Lu. "Multi-View Gated Graph Convolutional Network for Aspect-Level Sentiment Classification." In Advanced Data Mining and Applications, 489–504. Cham: Springer Nature Switzerland, 2022. http://dx.doi.org/10.1007/978-3-031-22064-7_35.

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Gao, Yang, Jianxun Liu, Pei Li, Dong Zhou, and Peng Yuan. "Multitask Learning Based on Constrained Hierarchical Attention Network for Multi-aspect Sentiment Classification." In Communications in Computer and Information Science, 685–92. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-63820-7_78.

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Wu, Hanqian, Shangbin Zhang, Jingjing Wang, Mumu Liu, and Shoushan Li. "Multi-label Aspect Classification on Question-Answering Text with Contextualized Attention-Based Neural Network." In Lecture Notes in Computer Science, 479–91. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-32381-3_39.

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Ran, Xiangying, Yuanyuan Pan, Wei Sun, and Chongjun Wang. "Modeling More Globally: A Hierarchical Attention Network via Multi-Task Learning for Aspect-Based Sentiment Analysis." In Database Systems for Advanced Applications, 505–9. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-18590-9_76.

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Wijaya, I. Putu Krishna, Peeranan Towashiraporn, Anish Joshi, Susantha Jayasinghe, Anggraini Dewi, and Md Nurul Alam. "Climate Change-Induced Regional Landslide Hazard and Exposure Assessment for Aiding Climate Resilient Road Infrastructure Planning: A Case Study in Bagmati and Madhesh Provinces, Nepal." In Progress in Landslide Research and Technology, Volume 1 Issue 1, 2022, 175–84. Cham: Springer International Publishing, 2023. http://dx.doi.org/10.1007/978-3-031-16898-7_12.

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AbstractNepal’s hilly and mountainous regions are highly susceptible to landslides triggered by extreme precipitations. The prevalence of such landslides has increased due to climate change-induced extreme hydro-meteorological conditions. These recurring landslides have significantly impacted the road transport infrastructure, which is the economic lifeline for cities and socio-economic mobility of rural communities in the hilly and mountainous regions of the country. This study modelled extreme rainfall scenarios for the current 1976–2005 baseline and future horizons of 2030, 2050, and 2080 to develop high-resolution 1 km × 1 km mean precipitation datasets under RCP4.5 and RCP8.5. Based on these extreme precipitation scenarios, we developed high-resolution landslide hazard models adopting integrated weighted index by combining the Frequency Ratio (FR) and Analytical Hierarchical Process (AHP) methods using multi-variate factors. The multi-variate factors included three terrain parameters—slope, aspect, and elevation; two soil parameters—lithology and soil type; two Euclidean distance parameters from the likely sources—distance from the lineaments and distance from the stream/river; an anthropogenic parameter—land use; and the climate parameter—the mean annual rainfall for four-time horizons and two RCPs. These parameters were spatially modelled and combined using the weighted overlay method to generate a landslide hazard model. As demonstration case studies, the landslide hazard models were developed for Bagmati and Madhesh provinces. The models were validated using the Receiver Operating Characteristic curve (ROC) approach, which showed a satisfactory 81–86% accuracy in the study area. Spatial exposure analysis of the road network assets under the Strategic Road Network (SRN) was completed for seven landslide hazard scenarios. In both Bagmati and Madhesh provinces, the exposure analysis showed that the proportion of road sections exposed to landslide hazard significantly increases for the future climate change scenarios compared to the current baseline scenario.

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Orhanou, Ghizlane, Abdelmajid Lakbabi, Nabil Moukafih, and Said El Hajji. "Network Access Control and Collaborative Security Against APT and AET." In Security and Privacy in Smart Sensor Networks, 201–30. IGI Global, 2018. http://dx.doi.org/10.4018/978-1-5225-5736-4.ch010.

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Cybercrime is rising due to the appearance of a new generation of attacks, APT and AET, and the reactionary aspect of the protection systems implemented in the IP networks. In this chapter, the authors analyze the gap between the innovative aspect of those attacks and the reactive aspect of the security measures put in place inside victim networks. The challenge is to shift this security aspect from reactive to proactive by adopting a collaborative approach based on NAC technology as a multi-level protection and IF-MAP as a security standard exchange protocol. First, a brief overview of NAC and IF-MAP is given. Then, the authors analyze the anatomy of these chained exploits and their escape techniques in order to propose an approach able to counter such attacks through the convergence towards a security ecosystem having the correlative intelligence to respond to challenges in real time and in a proactive way.

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Guleria, Kalpna, Saira Banu Atham, and Ashok Kumar. "Data Fusion in Underwater Wireless Sensor Networks and Open Research Challenges." In Energy-Efficient Underwater Wireless Communications and Networking, 67–84. IGI Global, 2021. http://dx.doi.org/10.4018/978-1-7998-3640-7.ch005.

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Underwater wireless sensor networks consist of numerous devices such as vehicles and sensor nodes, which are positioned underwater, and these devices collaboratively perform data collection, monitoring, and control task. The most critical issues related to underwater wireless sensor networks include limited bandwidth, data aggregation, data fusion, data collection, routing, media access control, higher propagation delay, and higher power consumption. Underwater data fusion is one of the critical issues for underwater military surveillance applications. It is also considered an equally important and challenging aspect for underwater intelligent traffic control and underwater vehicle navigation systems. This chapter provides an insight into basic concepts about multi-sensor data fusion and detailed review of most popular data fusion architectural models available for underwater wireless sensor networks. Finally, the chapter also provides open research directions to researchers for multi-sensor data fusion.

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Crespo, Nuno, Nicole Palan, and Nadia Simoes. "Sectoral Trade Globalization." In Handbook of Research on the Empirical Aspects of Strategic Trade Negotiations and Management, 1–27. IGI Global, 2021. http://dx.doi.org/10.4018/978-1-7998-7568-0.ch001.

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This chapter aims to shed light on the trends of sectoral trade globalization. This component of trade globalization is often neglected. An accurate evaluation of sectoral trade requires the analysis of the interdependencies of countries and the consideration of distance as a central dimension of trade globalization. As such, sectoral trade globalization is one aspect of a more complex and multi-dimensional phenomenon. Data show that sectoral trade globalization has increased significantly over the last 50 years irrespective of the characteristics of individual sectors. One relevant insight is that the level of trade globalization is on average still different for high-tech sectors compared to low-tech and medium-low-tech sectors even though the former could increase their bilateral trade relationships over time. Even though protectionist tendencies as well as the COVID-19 pandemic have led to a vivid discussion about the return to more local or regional production schemes, digitalization processes could still have the potential to further integrate countries' trade networks.

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Shamsolmoali, Pourya, Masoumeh Zareapoor, and M. Afshar Alam. "Multi-Aspect DDOS Detection System for Securing Cloud Network." In Cloud Security, 1952–83. IGI Global, 2019. http://dx.doi.org/10.4018/978-1-5225-8176-5.ch096.

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Distributed Denial of Service (DDoS) attacks have become a serious attack for internet security and Cloud Computing environment. This kind of attacks is the most complex form of DoS (Denial of Service) attacks. This type of attack can simply duplicate its source address, such as spoofing attack, which defending methods do not able to disguises the real location of the attack. Therefore, DDoS attack is the most significant challenge for network. In this chapter we present different aspect of security in Cloud Computing, mostly we concentrated on DDOS Attacks. The Authors illustrated all types of Dos Attacks and discussed the most effective detection methods.

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Тези доповідей конференцій з теми "Multi-aspect networks"

Yang, Lingyu, Hongjia Li, Lei Li, Chun Yuan, and Shu-Tao Xia. "ACEs: Unsupervised Multi-label Aspect Detection with Aspect-category Experts." In 2022 International Joint Conference on Neural Networks (IJCNN). IEEE, 2022. http://dx.doi.org/10.1109/ijcnn55064.2022.9892431.

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Montanari, Mirko, and Roy Campbell. "Multi-Aspect Security Assessment of Airport Computer Networks." In AIAA Infotech@Aerospace 2010. Reston, Virigina: American Institute of Aeronautics and Astronautics, 2010. http://dx.doi.org/10.2514/6.2010-3312.

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Zhong, Ning, and Jianhui Chen. "Data-Brain driven multi-aspect mining process planning." In 2010 International Joint Conference on Neural Networks (IJCNN). IEEE, 2010. http://dx.doi.org/10.1109/ijcnn.2010.5596559.

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Li, Yuncong, Cunxiang Yin, Sheng-hua Zhong, and Xu Pan. "Multi-Instance Multi-Label Learning Networks for Aspect-Category Sentiment Analysis." In Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP). Stroudsburg, PA, USA: Association for Computational Linguistics, 2020. http://dx.doi.org/10.18653/v1/2020.emnlp-main.287.

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Hu, Mengting, Shiwan Zhao, Li Zhang, Keke Cai, Zhong Su, Renhong Cheng, and Xiaowei Shen. "CAN: Constrained Attention Networks for Multi-Aspect Sentiment Analysis." In Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP). Stroudsburg, PA, USA: Association for Computational Linguistics, 2019. http://dx.doi.org/10.18653/v1/d19-1467.

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Cartmill, Jered, Mahmood R. Azimi-Sadjadi, and Neil Wachowski. "Buried Underwater Object Classification Using a Collaborative Multi-Aspect Classifier." In 2007 International Joint Conference on Neural Networks. IEEE, 2007. http://dx.doi.org/10.1109/ijcnn.2007.4371232.

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Azimi-Sadjadi, Mahmood R., Qiang Huang, and Gerald J. Dobeck. "Underwater target classification using multi-aspect fusion and neural networks." In Aerospace/Defense Sensing and Controls, edited by Abinash C. Dubey, James F. Harvey, and J. Thomas Broach. SPIE, 1998. http://dx.doi.org/10.1117/12.324142.

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Zhao, Zefang, Yuyang Liu, Junruo Gao, Haibo Wu, Zhaojuan Yue, and Jun Li. "Multi-grained Syntactic Dependency-aware Graph Convolution for Aspect-based Sentiment Analysis." In 2022 International Joint Conference on Neural Networks (IJCNN). IEEE, 2022. http://dx.doi.org/10.1109/ijcnn55064.2022.9892472.

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Wang, Simin, Guiyun Zhang, and Jun Cao. "Aspect-Based Sentiment Analysis with Multi-aspects Heterogeneous Graph Convolutional Networks." In EITCE 2021: 2021 5th International Conference on Electronic Information Technology and Computer Engineering. New York, NY, USA: ACM, 2021. http://dx.doi.org/10.1145/3501409.3501574.

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Cui, Can, Luyuan Xu, Bo Liu, Jing Chen, Shuaiyu Yao, and Qi Kang. "Aspect-level Sentiment Classification with Multi-head-attention-based Multi-channel Graph Convolutional Networks." In 2022 IEEE International Conference on Networking, Sensing and Control (ICNSC). IEEE, 2022. http://dx.doi.org/10.1109/icnsc55942.2022.10004113.

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