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检索条件"机构=Graduate Program in Informatics"

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Interacting with Cultural Heritage Through Shape Representation Techniques in 3D Modeling Environments 8th

Interacting with Cultural Heritage Through Shape Representat...

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8th European-Mediterranean Conference, EuroMed 2020

作者： Moralıoğlu, Begüm Aktaş, Begüm Architectural Design Computing Graduate Program Istanbul Technical University Institute of Informatics Istanbul Turkey Department of Architecture Altınbas University Istanbul Turkey

ISBN: (纸本)9783030730420

Three-dimensional (3D) representation of cultural heritage in a digital environment is coming into prominence for documentation of geometric and semantic details and the interpretation of shape representation from academic studies to commercial practices. To interpret cultural and historical shapes, the use of the computational medium is expanding with developing technologies. Advanced 3D design and development applications appear every day with distinct functions. However, not every technology provides designers a convenient medium to create, explore, and think naturally. In that sense, digital design mediums and tools become important to enhance the interactivity level with cultural heritage for designers through different interfaces. Particularly, the utilities of design interfaces are essential for preserving reconstructing ruined cultural heritage in the digital design mediums. In this study, we investigate the designers’ creative design process in the context of shape representation methods within the possibilities of two different 3D design interfaces as a computer and virtual reality (VR) interfaces. At first, we conducted a shape exploration exercise to generate the 3D model pieces of the Dark Church in Cappadocia. And then, we used the generated 3D model pieces in a shape representation exercise to observe the seeing, imagining, and acting abilities of designers in computer and VR environments. © 2021, Springer Nature Switzerland AG.

关键词： 3D modeling

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Use of Linked Data in the design of information infrastructure for collaborative emergency management system

Use of Linked Data in the design of information infrastructu...

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International Conference on Computer Supported Cooperative Work in Design

作者： Cordeiro, Kelli De Faria Marino, Tiago Campos, Maria Luiza M. Borges, Marcos R.S. Graduate Program in Informatics Instituto de Matemática and Ncleo de Computaçado Eletrnica Universidade Federal Do Rio de Janeiro Brazil

ISBN: (纸本)9781457703874

The evolution of communication channels and social networks proliferation through the web are inspiring and enabling the construction of collaborative environments. This article proposes an architecture of processes that aims to identify information responsibilities within a general emergency scenario, considering a new way of data provenance: citizens and government agencies. Citizens, who experience as victims a chaotic scenario, can also act as collaborators, providing relevant and useful information for the decision-making process. Today, they already do this informally, sharing public interest information through social networks, such as the Tweeter. The architecture also provides procedures for treating reliability and credibility of the information, provided by the so-called anonymous officials, subjecting it to a filtering and verification process. The heterogeneity of information formats is a well-known problem that affects organizations and communities that wants to access public data. The architecture includes a Linked Open Data (LOD) approach for acquisition and integration of data maintained by government agencies that adopt different publishing standards. A solution to this problem is of particular importance to emergency response organizations that need access to all information available to better respond to disasters and crisis. © 2011 IEEE.

关键词： Decision making

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Revealing a Country’s Government Discourse Through BERT-based Topic Modeling in the US Presidential Speeches 11

Revealing a Country’s Government Discourse Through BERT-bas...

引用

11th International Conference on Computer, Control, informatics and its Applications, IC3INA 2024

作者： Zain, Rafi Mahmud Anggai, Sajarwo Tukiyat Musyafa, Ahmad Waskita, A.A. Graduate Program of Informatics Engineering Universitas Pamulang Pamulang Indonesia Research Center for Data and Information Sciences National Research and Innovation Agency Bandung Indonesia

ISBN: (纸本)9798331542313

This paper analyzes presidential speeches from the United States, delivered by the current president, Joe Biden, from his inauguration until April 3, 2024, using BERT-based topic modeling techniques. Since the role and actions of the United States affect global affairs, inferring latent topics from these speeches are important for making informed decisions and also useful to researchers. We provide experiments combining different embedding methods and clustering algorithms for dimensionality reduction. Our experiment results demonstrated that using DistilBERT embeddings followed by HDBSCAN clustering and UMAP dimensionality reduction consistently produced meaningful and interpretable topics, and this paper introduces the UMASS and NPMI metrics for evaluating topic coherence, with the best values of these metrics among the other schemes investigated. Some of the dominant themes conveyed in the American president’s state of the union speech that were successfully revealed in this study include international cooperation, alongside significant attention to environmental, community, health, and economic issues. © 2024 IEEE.

关键词： Embeddings

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Using a Recurrent Neural Network Model for Classification of Tweets Conveyed Influenza-related Information 1

Using a Recurrent Neural Network Model for Classification of...

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1st International Workshop on Digital Disease Detection using Social Media, DDDSM 2017, co-located with the 8th International Joint Conference on Natural Language Processing, IJCNLP 2017

作者： Wang, Chen-Kai Singh, Onkar Tang, Zhao-Li Dai, Hong-Jie Graduate Institute of Biomedical Informatics Taipei Medical University Taipei Taiwan Bioinformatics Program Taiwan International Graduate Program Institute of Information Science Academia Sinica Taipei Taiwan Institute of Biomedical Informatics National Yang-Ming University Taipei Taiwan Department of Computer Science and Information Engineering National Taitung University Taitung Taiwan Interdisciplinary Program of Green and Information Technology National Taitung University Taitung Taiwan

ISBN: (纸本)9781948087070

Traditional disease surveillance systems depend on outpatient reporting and virological test results released by hospitals. These data have valid and accurate information about emerging outbreaks but it's often not timely. In recent years the exponential growth of users getting connected to social media provides immense knowledge about epidemics by sharing related information. Social media can now flag more immediate concerns related to outbreaks in real time. In this paper we apply the long short-term memory recurrent neural network (RNN) architecture to classify tweets conveyed influenza-related information and compare its performance with baseline algorithms including support vector machine (SVM), decision tree, naive Bayes, simple logistics, and naive Bayes multinomial. The developed RNN model achieved an F-score of 0.845 on the MedWeb task test set, which outperforms the F-score of SVM without applying the synthetic minority oversampling technique by 0.08. The F-score of the RNN model is within 1% of the highest score achieved by SVM with oversampling technique. © 2017 AFNLP

关键词： Support vector machines

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Semantic atomicity and multilinguality in the medical domain: Design considerations for the MORPHOSAURUS Subword Lexicon 5

Semantic atomicity and multilinguality in the medical domain...

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5th International Conference on Language Resources and Evaluation, LREC 2006

作者： Schulz, Stefan Markó, Kornél Daumke, Philipp Hahn, Udo Hanser, Susanne Nohama, Percy De Andrade, Roosewelt Leite Pacheco, Edson Romacker, Martin Department of Medical Informatics Freiburg University Hospital Freiburg Germany Health Informatics Laboratory Paraná Catholic University Curitiba Brazil Graduate Program in Electrical Engineering and Industrial Informatics CEFET-PR Curitiba Brazil Text Mining in Life Sciences Informatics Novartis Basel Switzerland Lab. Jena Germany

We present the lexico-semantic foundations underlying a multilingual lexicon the entries of which are constituted by so-called subwords. These subwords reflect semantic atomicity constraints in the medical domain which diverge from canonical lexicological understanding in NLP. We focus here on criteria to identify and delimit reasonable subword units, to group them into functionally adequate synonymy classes and to relate them by two types of lexical relations. The lexicon we implemented on the basis of these considerations forms the lexical backbone for MORPHOSAURUS, a cross-language document retrieval engine for the medical domain.

关键词： Semantics

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Abandonment of a Software Process Improvement program: Insights from Case Studies 20

Abandonment of a Software Process Improvement Program: Insig...

引用

Proceedings of the XIX Brazilian Symposium on Software Quality

作者： Regina Albuquerque Gleison Santos Andreia Malucelli Sheila Reinehr Graduate Program in Informatics – PUCPR Brazil Department of Applied Informatics - UNIRIO Brazil

ISBN: (纸本)9781450389235

Software processes improvement (SPI) based on maturity models is a well-researched theme regarding aspects such as adoption benefits, process definition, and automated support environments. However, few studies address the reasons that can lead an organization to abandon SPI. It is vital for organizations that seek to improve their processes to know what can negatively influence SPI and, thus, take actions to mitigate the risk of SPI failure, avoiding the loss of effort in the implementation stage. We present a study’s results to understand how abandonment occurs in software process improvement programs after successful assessments based on maturity models. We conducted case studies in four Brazilian software companies. The results show that SPI initiatives failed because of both internal factors (people, SPI project management, organizational aspects, and processes) and external factors (country economic crisis, outsourcing, and governmental political influence) to the organizational context.

关键词： Maturity Model Software Process Improvement Abandonment of SPI Continuity of SPI

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An observation model for the collaborative analysis of real workplaces

An observation model for the collaborative analysis of real ...

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11th International Conference on Computer Supported Cooperative Work in Design, CSCWD 2007

作者： Machado, Renata Guanaes Borges, Marcos R. S. Guerlain, Stephanie Gomes, Jose Orlando Graduate Program in Informatics Federal University of Rio de Janeiro Brazil Systems and Information Engineering Dept. University of Virginia Charlottesville VA United States

ISBN: (纸本)1424409632

Many approaches to work analysis have been proposed so as to enhance the requirements elicitation for systems design. However, systems delivered at dynamic, complex and socio-technical workplaces, have stillfailed at satisfying the needs of users successfully, mainly because they are unable to support activities entirely, especially those related with cognition and collaboration. This paper describes the Observation Conceptual Model, as a complementary approach, to elicit high-quality requirements through systematic field studies about organizations. We also include some ideas for the elaboration of a collaborative system that supports the conceptual model. ©2007 IEEE.

关键词： Groupware

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Lung cancer diseases diagnostic asistance using Gray color analysis

Lung cancer diseases diagnostic asistance using Gray color a...

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International Conference on Computational Intelligence, Modelling and Simulation

作者： Paulus Gaol, Ford Lumban Graduate Program in Informatics Engineering Department of Computer Science Bina Nusantara University Jakarta Indonesia Faculty of Computer Science Bina Nusantara University Jakarta Indonesia

ISBN: (纸本)9780769542621

Errors in diagnosing the disease is a critical risk that must be faced by any person giving treatment to the hospital. Medical treatment can not always be done with perfect accuracy. Lung cancer is one of the most deadly disease that prone to misdiagnose. In general, some practitioners tend to read cancer in x-ray rontgen image as tumor this could be fatal. To generate a diagnose, a general practitioner use three kind of examination i.e : patient History, Radiologic examination, phisical examination. In this paper, Gray color for image indexing and retrieval are investigated. The features are derived based on the statistical distribution of Harralick feature from image sample. By utilizing the proposed invariant features, the similarity measure between query and database images provides reliable retrieval results. © 2010 IEEE.

关键词： Diseases

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UC3M-PUCPR at SemEval-2022 Task 11: An Ensemble Method of Transformer-based Models for Complex Named Entity Recognition 16

UC3M-PUCPR at SemEval-2022 Task 11: An Ensemble Method of Tr...

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16th International Workshop on Semantic Evaluation, SemEval 2022

作者： Schneider, Elisa Terumi Rubel Rivera-Zavala, Renzo M. Martinez, Paloma Moro, Claudia Paraiso, Emerson Cabrera Graduate Program on Informatics Pontifícia Universidade Catolica do Paraná Brazil Computer Science and Engineering Department Universidad Carlos III de Madrid Spain

ISBN: (纸本)9781955917803

This study introduces the system submitted to the SemEval 2022 Task 11: MultiCoNER (Multilingual Complex Named Entity Recognition) by the UC3M-PUCPR team. We proposed an ensemble of transformer-based models for entity recognition in cross-domain texts. Our deep learning method benefits from the transformer architecture, which adopts the attention mechanism to handle the long-range dependencies of the input text. Also, the ensemble approach for named entity recognition (NER) improved the results over baselines based on individual models on two of the three tracks we participated in. The ensemble model for the code-mixed task achieves an overall performance of 76.36% F1-score, a 2.85 percentage point increase upon our individually best model for this task, XLM-RoBERTa-large (73.51%), outperforming the baseline provided for the shared task by 18.26 points. Our preliminary results suggest that contextualized language models ensembles can, even if modestly, improve the results in extracting information from unstructured data. © 2022 Association for Computational Linguistics.

关键词： Deep learning

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Introducing business process into legacy information systems

Introducing business process into legacy information systems

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3rd Internaional Conference on Business Process Management,BPM 2005

作者： Borges, Marcos R. S. Vincent, A.F. Penadés, M. Carmen Araujo, Renata M. Graduate Program in Informatics Federal University of Rio de Janeiro Brazil Technical University of Valencia Spain Department of Applied Informatics Federal University of the Rio de Janeiro State Brazil DSIC Technical University of Valencia Spain

The majority of legacy information systems running today were built without adopting a business process approach. In these systems, the control over the execution of the process activities is partial, leaving out all those activities that have not been automated. Moreover, the activities that constitute the process are not formally interconnected, causing loss of the overall business process context. This paper presents a method for gradually integrating the underlying business processes supported by these systems, without disrupting the automation they already support. The method is particularly attractive for legacy systems that are expected to last a long time and whose redevelopment costs are high. © Springer-Verlag Berlin Heidelberg 2005.

关键词： Legacy systems

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