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1,749 results on '"Horváth, Gábor"'

105. Human Polarization Sensitivity

Author

McGregor, Juliette, Temple, Shelby, Horváth, Gábor, Marshall, N. Justin, Series editor, Collin, Shaun P, Series editor, and Horváth, Gábor, editor

Published
2014
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109. Efficient Implementations of the EM-Algorithm for Transient Markovian Arrival Processes

Author

Bražėnas, Mindaugas, Horváth, Gábor, Telek, Miklós, Hutchison, David, Series editor, Kanade, Takeo, Series editor, Kittler, Josef, Series editor, Kleinberg, Jon M., Series editor, Mattern, Friedemann, Series editor, Mitchell, John C., Series editor, Naor, Moni, Series editor, Pandu Rangan, C., Series editor, Steffen, Bernhard, Series editor, Terzopoulos, Demetri, Series editor, Tygar, Doug, Series editor, Weikum, Gerhard, Series editor, Wittevrongel, Sabine, editor, and Phung-Duc, Tuan, editor

Published
2016
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111. Blending citizen science with natural language processing and machine learning: Understanding the experience of living with multiple sclerosis

Author

Haag, Christina, primary, Steinemann, Nina, additional, Chiavi, Deborah, additional, Kamm, Christian P., additional, Sieber, Chloé, additional, Manjaly, Zina-Mary, additional, Horváth, Gábor, additional, Ajdacic-Gross, Vladeta, additional, Puhan, Milo Alan, additional, and von Wyl, Viktor, additional

Published
2023
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114. Efficacy and safety of elbasvir/grazoprevir and sofosbuvir/pegylated interferon/ribavirin: A phase III randomized controlled trial

Author

Sperl, Jan, Horvath, Gabor, Halota, Waldemar, Ruiz-Tapiador, Juan Arenas, Streinu-Cercel, Anca, Jancoriene, Ligita, Werling, Klara, Kileng, Hege, Koklu, Seyfettin, Gerstoft, Jan, Urbanek, Petr, Flisiak, Robert, Leiva, Rafael, Kazenaite, Edita, Prinzing, Renate, Patel, Sushma, Qiu, Jingjun, Asante-Appiah, Ernest, Wahl, Janice, Nguyen, Bach-Yen, Barr, Eliav, and Platt, Heather L.

Published
2016
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121. Measuring the Distance Between MAPs and Some Applications

Author

Horváth, Gábor, Hutchison, David, Series editor, Kanade, Takeo, Series editor, Kittler, Josef, Series editor, Kleinberg, Jon M., Series editor, Mattern, Friedemann, Series editor, Mitchell, John C., Series editor, Naor, Moni, Series editor, Pandu Rangan, C., Series editor, Steffen, Bernhard, Series editor, Terzopoulos, Demetri, Series editor, Tygar, Doug, Series editor, Weikum, Gerhard, Series editor, Gribaudo, Marco, editor, Manini, Daniele, editor, and Remke, Anne, editor

Published
2015
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125. Blending citizen science with natural language processing and machine learning: Understanding the experience of living with multiple sclerosis

Author

Haag, Christina; https://orcid.org/0000-0002-9662-5245, Steinemann, Nina, Chiavi, Deborah; https://orcid.org/0000-0003-0595-2054, Kamm, Christian P; https://orcid.org/0000-0002-3906-0161, Sieber, Chloé; https://orcid.org/0000-0002-6642-5082, Manjaly, Zina-Mary; https://orcid.org/0000-0002-9217-1688, Horváth, Gábor; https://orcid.org/0009-0003-4085-7770, Ajdacic-Gross, Vladeta, Puhan, Milo Alan; https://orcid.org/0000-0003-4721-1879, von Wyl, Viktor; https://orcid.org/0000-0002-8754-9797, Haag, Christina; https://orcid.org/0000-0002-9662-5245, Steinemann, Nina, Chiavi, Deborah; https://orcid.org/0000-0003-0595-2054, Kamm, Christian P; https://orcid.org/0000-0002-3906-0161, Sieber, Chloé; https://orcid.org/0000-0002-6642-5082, Manjaly, Zina-Mary; https://orcid.org/0000-0002-9217-1688, Horváth, Gábor; https://orcid.org/0009-0003-4085-7770, Ajdacic-Gross, Vladeta, Puhan, Milo Alan; https://orcid.org/0000-0003-4721-1879, and von Wyl, Viktor; https://orcid.org/0000-0002-8754-9797

Abstract

The emergence of new digital technologies has enabled a new way of doing research, including active collaboration with the public ('citizen science'). Innovation in machine learning (ML) and natural language processing (NLP) has made automatic analysis of large-scale text data accessible to study individual perspectives in a convenient and efficient fashion. Here we blend citizen science with innovation in NLP and ML to examine (1) which categories of life events persons with multiple sclerosis (MS) perceived as central for their MS; and (2) associated emotions. We subsequently relate our results to standardized individual-level measures. Participants (n = 1039) took part in the 'My Life with MS' study of the Swiss MS Registry which involved telling their story through self-selected life events using text descriptions and a semi-structured questionnaire. We performed topic modeling ('latent Dirichlet allocation') to identify high-level topics underlying the text descriptions. Using a pre-trained language model, we performed a fine-grained emotion analysis of the text descriptions. A topic modeling analysis of totally 4293 descriptions revealed eight underlying topics. Five topics are common in clinical research: 'diagnosis', 'medication/treatment', 'relapse/child', 'rehabilitation/wheelchair', and 'injection/symptoms'. However, three topics, 'work', 'birth/health', and 'partnership/MS' represent domains that are of great relevance for participants but are generally understudied in MS research. While emotions were predominantly negative (sadness, anxiety), emotions linked to the topics 'birth/health' and 'partnership/MS' was also positive (joy). Designed in close collaboration with persons with MS, the 'My Life with MS' project explores the experience of living with the chronic disease of MS using NLP and ML. Our study thus contributes to the body of research demonstrating the potential of integrating citizen science with ML-driven NLP methods to explore the experien

Published
2023

126. Uncovering Hidden Dependencies: Constructing Intelligible Path Witnesses using Dataflow Analyses.

Author

Umann, Kristóf, Horváth, Gábor, and Porkoláb, Zoltán

Subjects
ALGORITHMS, WITNESSES, DEFINITIONS, COST
Abstract

The lack of sound, concise and comprehensive error reports emitted by a static analysis tool can cause increased fixing cost, bottleneck at the availability of experts and even may undermine the trust in static analysis as a method. This paper presents novel techniques to improve the quality of bug reports for static analysis tools that employ symbolic execution. With the combination of data and control dependency analysis, we can identify the relevance of particular code snippets that were previously missing from the report. We demonstrated the benefits of our approach by implementing an improved bug report generator algorithm for the Clang Static Analyzer. After being tested by the open source community our solution became enabled by default in the tool. [ABSTRACT FROM AUTHOR]

Published
2024
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127. No Drone's Sky: Full Spectrum Drone Surveillance and Neutralisation Concept for Enhanced Counter-UAS Framework (Part 1, Surveillance).

Author

Horváth, Gábor

Subjects
DRONE surveillance, TECHNOLOGICAL innovations, TELECOMMUNICATION, COMPUTER engineering, RADIO frequency, RADAR interference
Abstract

Unmanned Aircraft Systems (UAS), commonly known as drones, have witnessed substantial global proliferation in the past decade. Their constructive applications hold the promise of being a useful, yet critical component in creating a more efficient society with the enhancement of safety, efficiency, and facilitating advancements in various domains, ultimately contributing to our modern daily lives. However, the escalating dependence on computer and communication technologies renders, especially small, UAS susceptible to various threats, posing risks to public safety, national security, and individual privacy. Addressing these concerns necessitates the development of innovative technologies designed to detect, track, identify, and eliminate UAS in a manner that upholds safety, security, and privacy. A Counter-Unmanned Aircraft System (C-UAS) is defined as a system or apparatus capable of legally and securely incapacitating, disrupting, or assuming control over an UAS. Recent years have witnessed significant research endeavours aimed at detecting and eliminate drone threats. Detection methodologies encompass acoustic, visual, passive radio frequency, radar, and data fusion techniques, while neutralisation strategies encompass physical capture and jamming approaches. This paper, delving into the realm of small drone surveillance, is the opening segment of a three-part series aims to envision a C-UAS framework; it provides an exhaustive review of existing literature in the domain of UAS surveillance, delineating the challenges associated with countering unauthorised or unsafe drone operations, and evaluating the trajectory of detection to prepare against UAS-induced threats. Therefore, the fundamental objective of this paper is to offer a comprehensive surveillance baseline for a structured vision to a C-UAS framework, thus fostering a research community dedicated to the secure integration of drones into the airspace system. [ABSTRACT FROM AUTHOR]

Published
2024
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