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Journal of Applied Logics 2025年第3期12卷 251-294页

作者： Bikakis, Antonis Flouris, Giorgos Leite, Joao Patkos, Theodore Department of Information Studies University College London United Kingdom Institute of Computer Science FORTH Heraklion Greece NOVA LINCS NOVA University Lisbon Portugal

While a lot of research has been conducted on understanding and formalising the interplay of arguments within the context of Computational Argumentation, this research is not fully applicable to the types of arguments that populate the Social Web. In that context, arguments usually have the form of comments, opinions or reviews, and are the main ingredients of online discussion forums, social networks, online rating and review sites, debate portals and other online communities-the electronic version of word-of-mouth communication. As a result, voting and other forms of reaction to the provided comments or arguments (other than just "attacks") are allowed, features that are not normally considered in the classical literature on Computational Argumentation. In this chapter, we study extensions of argumentation frameworks that have been proposed to describe and understand the more complex types of interactions among arguments that can be found in the Social Web, and present the current state-of-the-art, as well as open problems. © 2025, College Publications. All rights reserved.

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Split-State Non-Malleable Codes and Secret Sharing Schemes for Quantum Messages

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IEEE Transactions on Information Theory 2025年第4期71卷 2838-2871页

作者： Boddu, Naresh Goud Goyal, Vipul Jain, Rahul Ribeiro, Joao NTT Research SunnyvaleCA94085 United States National University of Singapore and MajuLab UMI 3654 Singapore NOVA School of Science and Technology NOVA LINCS The Department of Computer Science Caparica2829-516 Portugal Centre for Quantum Technologies The School of Computing Singapore119077 Singapore

Non-malleable codes are fundamental objects at the intersection of cryptography and coding theory. These codes provide security guarantees even in settings where error correction and detection are impossible, and have found applications to several other cryptographic tasks. One of the strongest and most well-studied adversarial tampering models is 2-split-state tampering. Here, a codeword is split into two parts which are stored in physically distant servers, and the adversary can then independently tamper with each part using arbitrary functions. This model can be naturally extended to the secret sharing setting with several parties by having the adversary independently tamper with each share. Previous works on non-malleable coding and secret sharing in the split-state tampering model only considered the encoding of classical messages. Furthermore, until recent work by Aggarwal, Boddu, and Jain (IEEE Trans. Inf. Theory 2024 & arXiv 2022), adversaries with quantum capabilities and shared entanglement had not been considered, and it is a priori not clear whether previous schemes remain secure in this model. In this work, we introduce the notions of split-state nonmalleable codes and secret sharing schemes for quantum messages secure against quantum adversaries with shared entanglement. Then, we present explicit constructions of such schemes that achieve low-error non-malleability. More precisely, for some constant c > 0, we construct efficiently encodable and decodable split-state non-malleable codes and secret sharing schemes for quantum messages preserving entanglement with external systems and achieving security against quantum adversaries having shared entanglement with codeword length n, any message length at most nc, and error ϵ = 2-nc. In the easier setting of average-case non-malleability, we achieve efficient nonmalleable coding with rate close to 1/11. © 1963-2012 IEEE.

关键词： Quantum entanglement

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BI-Enabled Web Visualization of In-Place Inclinometer Data for Geotechnical Applications 23rd

BI-Enabled Web Visualization of In-Place Inclinometer Data ...

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23rd EPIA Conference on Artificial Intelligence, EPIA 2024

作者： Palma, João Marques, Nuno Santos, Ricardo NOVA LINCS NOVA School of Science and Technology Department of Computer Science Quinta da Torre - Campus FCT/UNL Caparica2829-516 Portugal Avenida do Brasil 101 Lisbon Portugal

ISBN: (纸本)9783031735028

IoT integration for continuous monitoring is essential for effective data interpretation, advanced visualization, and timely decision-making in Business Intelligence (BI). Current in-place inclinometer (IPI) systems suffer from outdated visualization tools and limited real-time capabilities. Our solution integrates a low-cost, wireless IPI prototype with a web-based application, providing efficient data preprocessing, intuitive visualization, and real-time monitoring to enhance decision-making and risk management. IPI involve the installation of multiple sensors at discrete depths along a tube casing and are useful when regular monitoring of ground movement is essential or when site accessibility is limited. This approach saves valuable time and labor that would otherwise be spent on manual measurements using the traditional inclinometer probe. Additionally, it enables the seamless collection of regular data through the utilization of automated data acquisition equipment, providing valuable information on the ground deformation vector and rate of movement. Our experiments present visualisations that illustrate the system’s effectiveness in diverse scenarios, highlighting its ability to accurately preprocess and visualize data, facilitate interactive analysis, and provide immediate insights into structural stability. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Risk management

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novaSearch at imageCLEFmed 2016 subfigure classification task

NovaSearch at imageCLEFmed 2016 subfigure classification tas...

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2016 Working Notes of Conference and Labs of the Evaluation Forum, CLEF 2016

作者： Semedo, David Magalhães, João NOVA LINCS Department of Computer Science Faculty of Science and Technology Portugal

This paper describes the novaSearch team participation in the ImageCLEF 2016 Medical Task in the subfigure classification subtask. Deep learning techniques have proved to be very effective in automatic representation learning and classification tasks with general data. More specifically, convolutional neural networks (CNNs) have surpassed humanlevel performance in the ImageNET classification task, making them a promising model for the task of medical modality *** assess how each model behave when dealing with medical images, by developing three different models, with different depths and components, and analyse the impact of these factors in the performance. One of the key ingredients for the effectiveness of CNNs (and deep learning in general) is the use of large amounts of data for training. This subtask scenario is completely different, due to the small size of the dataset, implying a significant risk of overfitting. We apply state-of-The-Art techniques developed to reduce overfitting in these networks to our models and evaluate their effectiveness. Our best model achieves 65:31% accuracy on the test set using only the training data provided.

关键词： Convolution

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Enabling the development of pervasive multi-device applications 17

Enabling the development of pervasive multi-device applicati...

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9th ACM SIGCHI Symposium on Engineering Interactive Computing Systems, EICS 2017

作者： Santos, Pedro Albuquerque NOVA LINCS Department of Computer Science Faculty of Science and Technology Universidade NOVA de Lisboa Portugal

ISBN: (纸本)9781450350839

Nowadays we are surrounded by many different computing devices, but applications running on them are still largely independent. It should be possible to address this shortcoming to provide a better user experience. There is a lack of tools to realize this vision, so we aim to develop a framework that allows third-party developers to build applications that run across multiple co-located devices. Three key related work areas have been identified: proxemics, indoor positioning and multi-device applications. The work is under way to define the framework's architecture and the design of core components, as well as to develop a supporting indoor positioning solution. We will also be developing prototypes in order to perform usability tests to assess if this approach is beneficial to potential users. © 2017 Association for Computing Machinery.

关键词： Indoor positioning systems

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novaSearch at TREC 2017 Real-Time Summarization Track 26

NOVASearch at TREC 2017 Real-Time Summarization Track

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26th Text REtrieval Conference, TREC 2017

作者： Gonçalves, Gustavo Martins, Flávio Magalhães, João NOVA LINCS Department of Computer Science Faculty of Science and Technology Universidade NOVA de Lisboa Caparica Portugal

The rise of large data streams introduces new challenges regarding the delivery of relevant content towards an information need. This information need can be seen as a broad topic of information. One possible strategy to tackle the delivery of the most relevant documents regarding this broader topic is summarization. TREC 2017 Real-Time Summarization (RTS) provides a testbed for the development of stream based real-time summarization systems. Leveraging on the social media network, Twitter, the participants are challenged to deliver the most relevant and diverse information in two main scenarios. The real-time push notifications scenario, or Scenario A, focuses on the identification and delivery of relevant information in near real-time. Whereas the daily-digest scenario, or scenario B, strives for the daily delivery of the most relevant and diverse documents. This paper presents the participation of the novaSearch group at TREC 2017 Real-Time Summarization (RTS). Our work was developed for tackling the scenario B, after an analysis of the proposed systems for the TREC RTS 2016. In our approach we explore document filtering methods;vocabulary expansions;and the identification of subtopics through the aggregation of documents based on their textual similarity. © 26th Text REtrieval Conference, TREC 2017 - Proceedings.

关键词： Information retrieval systems

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Gender Equality Through E-learning: A Machine Learning Approach to Measuring Impact

Gender Equality Through E-learning: A Machine Learning Appro...

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2024 International Conference on Innovation and Intelligence for Informatics, Computing, and Technologies, 3ICT 2024

作者： Lashgari, Farzaneh Pourvahab, Mehran Faraji, Aazaade Monteiro, Anilson Pais, Sebastiao Pombo, Nuno Department of Computer Science University of Beira Interior Covilhã Portugal NOVA LINCS NOVA University Lisbon Lisbon Portugal

ISBN: (纸本)9798331533137

In the contemporary digital era, e-learning has emerged as a transformative force in advancing women’s empowerment and promoting gender equality. This study investigates the significant impact of e-learning on women’s lives, illustrating how digital platforms can bridge gender divides and foster unprecedented opportunities for personal and professional development. By employing machine learning techniques, the research evaluates the advantages of e-learning, focusing on how online vocational and arts education can economically empower women and enhance their workforce participation. The study entailed an in-depth examination of 120 women from different age ranges, utilizing questionnaires and analytical techniques to evaluate the effectiveness of e-learning, as well as the mutual relationship between online education, improving women’s skill abilities and socio-economic development. The research highlights e-learning’s potential to overcome barriers such as financial constraints and the limitations of traditional in-person education. It underscores the importance of innovative teaching strategies and institutional support in maximizing e-learning benefits. This study advocates for a more equitable society where women are empowered with the knowledge and skills necessary to excel in the digital age. Our main goal of this study is to evaluate the effect of e-learning in facilitating financial independence and achieving social equality in the target society, and in addition to this research, we examine the achievements of other developing countries in this field. ©2024 IEEE.

关键词： Contrastive Learning

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Intelligent query answering with contextual knowledge for relational databases 10

Intelligent query answering with contextual knowledge for re...

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10th Symposium on Languages, Applications and Technologies, SLATE 2021

作者： Seipel, Dietmar Weidner, Daniel Abreu, Salvador Department of Computer Science Universität Würzburg Germany Nova-Lincs University of Évora Portugal

ISBN: (纸本)9783959772020

We are proposing a keyword-based query interface for knowledge bases - including relational or deductive databases - based on contextual background knowledge such as suitable join conditions or synonyms. Join conditions could be extracted from existing referential integrity (foreign key) constaints of the database schema. They could also be learned from other, previous database queries, if the database schema does not contain foreign key constraints. Given a textual representation - a word list - of a query to a relational database, one may parse the list into a structured term. The intelligent and cooperative part of our approach is to hypothesize the semantics of the word list and to find suitable links between the concepts mentioned in the query using contextual knowledge, more precisely join conditions between the database tables. We use a knowledge-based parser based on an extension of Definite Clause Grammars (Dcg) that are interweaved with calls to the database schema to suitably annotate the tokens as table names, table attributes, attribute values or relationships linking tables. Our tool DdQl yields the possible queries in a special domain specific rule language that extends Datalog, from which the user can choose one. © 2021 Schloss Dagstuhl- Leibniz-Zentrum fur Informatik GmbH, Dagstuhl Publishing. All rights reserved.

关键词： Logic programming

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PARAMETERIZED INAPPROXIMABILITY OF THE MINIMUM DISTANCE PROBLEM OVER ALL FIELDS AND THE SHORTEST VECTOR PROBLEM IN ALL p NORMS

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SIAM Journal on Computing 2024年第5期53卷 1439-1475页

作者： Bennett, Huck Cheraghchi, Mahdi Guruswami, Venkatesan Ribeiro, Joao Department of Computer Science University of Colorado BoulderCO80309 United States EECS Department University of Michigan Ann ArborMI48109 United States Department of EECS University of California Berkeley BerkeleyCA94720 United States NOVA LINCS Department of Computer Science NOVA School of Science and Technology Universidade Nova de Lisboa Caparica2829-516 Portugal

We prove that the minimum distance problem (MDP) on linear codes over any fixed finite field and parameterized by the input distance bound is \sansW [1]-hard to approximate within any constant factor. We also prove analogous results for the parameterized shortest vector problem (SVP) on integer lattices. Specifically, we prove that the SVP in the p norm is \sansW [1]-hard to approximate within any constant factor for any fixed p > 1 and \sansW [1]-hard to approximate within a factor approaching 2 for p = 1. (We show hardness under randomized reductions in each case.) These results answer the main questions left open (and explicitly posed) by Bhattacharyya et al. [J. ACM, 68 (2021), 16] on the complexity of the parameterized MDP and SVP. For the MDP, they established similar hardness for binary linear codes and left the case of general fields open. For the SVP in p norms with p >1, they showed inapproximability within some constant factor (depending on p) and left open showing such hardness for arbitrary constant factors. They also left open showing \sansW [1]-hardness even of the exact SVP in the 1 norm. © 2024 Society for Industrial and Applied Mathematics Publications. All rights reserved.

关键词： Brinell Hardness

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Querying Relational Databases with Speech-Recognition Driven by Contextual Knowledge 12

Querying Relational Databases with Speech-Recognition Driven...

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12th Symposium on Languages, Applications and Technologies, SLATE 2023

作者： Seipel, Dietmar Förster, Benjamin Liebl, Magnus Waleska, Marcel Abreu, Salvador Department of Computer Science Universität Würzburg Germany Nova–Lincs University of Évora Portugal

ISBN: (纸本)9783959772914

We are extending the keyword–based query interface DdQl for relational databases which is based on contextual background knowledge such as suitable join conditions and which was proposed in [10]. In the previous paper, join conditions were extracted from existing referential integrity (foreign key) constraints of the database schema, or they could be learned from other, previous database queries. In this paper, we describe a speech–to–text component for entering the query keywords based on the system Whisper. Keywords, which have been recognized wrongly by Whisper can be corrected to similarly sounding words. Again, the context of the database schema can help here. For users with a limited knowledge of the schema and the contents of the database, the approach of DdQl can help to provide useful suggestions for query implementations in Sql or Datalog, from which the user can choose one. Our tool DdQl can be run in a docker image;it yields the possible queries in Sql and a special domain specific rule language that extends Datalog. The Datalog variant allows for additional user-defined aggregation functions which are not possible in Sql. © Dietmar Seipel, Benjamin Förster, Magnus Liebl, Marcel Waleska, and Salvador Abreu

关键词： Logic programming

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