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Quantum Software (QSW), IEEE International Conference on

作者： Shota Nagayama Toshihiko Sasaki Akihito Soeda Mercari R4D Mercari Inc Tokyo Japan Graduate School of Media and Governance Keio University Fujisawa Japan Department of Applied Physics Graduate School of Engineering The University of Tokyo Tokyo Japan Principles of Informatics Research Division National Institute of Informatics Tokyo Japan Informatics Program SOKENDAI (The Graduate University for Advanced Studies) Tokyo Japan Department of Physics Graduate School of Science The University of Tokyo Tokyo Japan

ISBN: (数字)9798350368475

ISBN: (纸本)9798350368482

A quantum internet is an emerging quantum information technology, possibly becoming a pinnacle of wide-area distributed system allowed under the laws of physics. The current expansion of quantum technologies would lead to innumerable types of quantum systems, composed of various kinds of quantum devices connected by a dedicated quantum network. However, the (inter)connectivity offered by a quantum internet should ideally be agnostic of the technologies used by each component system. Furthermore, concurrent progresses of the quantum technologies complicate the task of defining what a quantum internet is. In this paper, we adopt a backcasting approach to elucidate what a quantum internet should be. We begin by discussing what we believe to be the requirements of an ultimate distributed quantum system, from which we explain what role a quantum internet would play in achieving this ultimate system. We then lead to more practical requirements on a quantum internet, considering the known and expected constraints in designing a quantum internet. We also organize and categorize the relationship among known quantum network technologies and services relevant to a quantum internet. We hope this document to lay a common ground for all the key stakeholders of a quantum internet, including researchers, industrial enterprises, and policy makers and regulators.

关键词： Quantum system Protocols Quantum mechanics Transportation Logic gates Internet Quantum networks

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A task-oriented framework for generative AI in design

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Journal of Creativity 2024年第2期34卷

作者： Furtado, Lara Sucupira Soares, Jorge Barbosa Furtado, Vasco Department of Transportation Engineering Federal University of Ceará Brazil Applied Informatics Graduate Program University of Fortaleza Unifor Brazil ETICE State of Ceará Information Technology Company Brazil

The intersection of Artificial Intelligence and Design disciplines such as Architecture, Urban Planning, Engineering and Product Design has been a longstanding pursuit, with Generative AI (GAI) ushering in a new era of possibilities. The research presented here explores how GAI can enhance creativity and assist Design practitioners with tasks to create products such as, but not limited to, renderings, concepts, construction techniques, materials, data analytics or maps. We apply a framework of combinational, exploratory and transformational creativity to organize how recent advancements in GAI can support each creative category. We propose a conceptual framework of GAI towards transformational creativity, and identify real-world examples to demonstrate GAI's impact, such as transforming sketches into detailed renders, facilitating real-time 3D model generation, predicting trends through analytics and creating images or reports via text prompts. Our work envisions a future where GAI becomes a real-time collaborator to complete certain automated tasks while liberating Designers to focus on transformational innovation. © 2024

关键词： Creative computing Generative artificial intelligence Product Transformational Creativity

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

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

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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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Three-Dimensional Wound Reconstruction using Point Descriptors: A Comparative Study

Three-Dimensional Wound Reconstruction using Point Descripto...

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Annual IEEE Symposium on Computer-Based Medical Systems

作者： José R. A. Souto Fellipe M. C. Barbosa Bruno M. Carvalho Graduate Program in Systems and Computing Federal University of Rio Grande do Norte Natal Brazil Department of Informatics and Applied Mathematics Federal University of Rio Grande do Norte Natal Brazil

Precise measurements of chronic wound areas are very important for measuring the efficacy of different treatments, since it provides a clear picture of the chosen treatment evolution. The most used techniques still in use for measuring the wound areas involve manual measuring, paper scales and/or acetate tracing, with each health professional possibly measuring the wounds in slightly different ways, specially when dealing with the wound's depth. Thus, it is common to observe inconsistent wound area estimations by different health workers on the same wounds. Moreover, the measuring process requires direct contact with the wound, increasing the contamination and infection risks, besides possibly causing discomfort for the patient. An alternative that has already been proved successful is the use of Structure from Motion (SfM) to recover three-dimensional representations of a wound's surface and estimate that area. In this work, we analyze the effectiveness of several widely used point descriptors (BRIEF, DRINK, FREAK, ORB, SIFT and SURF) in the SfM wound reconstruction task when applied to real images of realistic synthetic wounds made of latex placed on different areas of the body. The results showed that SIFT, SURF and DRINK produced better area estimates. Since the execution time is a factor, we selected DRINK as the standard descriptor for our system, since it is approximately 9.3 and 4.9 times faster than SIFT and SURF, respectively.

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An Analysis of UX Based on Users’ Emotional Intention and Values, Both Expressed Through Twitter Posts 1

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8th Workshop of Human-Computer Interaction Aspects to the Social Web, WAIHCWS 2017 and the 9th Workshop of Human-Computer Interaction Aspects to the Social Web, WAIHCWS 2018

作者： Furtado, Elizabeth S. Mendes, Marilia S. Oliveira, Denilson C. Lima, Lanna Graduate Program in Applied Informatics University of Fortaleza FortalezaCE Brazil RussasCE Brazil

ISBN: (数字)9783030461300

ISBN: (纸本)9783030461294

Texts written by users are often used in investigations of their experiences using a system. When users write about texts based on their own decisions, the texts are a rich context for User eXperience (UX) evaluation of such systems due to the users’ spontaneity. Usually, UX goals are evaluated in users’ texts, including their perception about the usability of the system. An UX analysis from the perspective of the user’s emotional intent and the expression of their personal or social values in the posts has not yet been performed. In this chapter, we analyzed the UX reported on users’ Twitter posts relating to these two perspectives. We identified significant correlations calculated from posts that express a particular level of emotional intention of the user and a certain social or personal value. All levels of emotion had a significant relationship with at least 2 of the 12 values analyzed. Results showed that these relationships from texts written by users are useful to analyze the UX of the posts. © 2020, Springer Nature Switzerland AG.

关键词： Human computer interaction

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Machine Learning for Prediction of Adverse Drug Reactions: Application to Neonatal Intensive Care Units

SSRN

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SSRN 2023年

作者： do Nascimento, Amanda Roseane Farias Greati, Victor Rodrigues Leopoldino, Ramon Weyler Duarte Martins, Rand Randall Barbosa, Euzebio Guimarães Graduate Program in Pharmaceutical Sciences Health Sciences Center Federal University of Rio Grande do Norte Rio Grande do Norte Natal Brazil Graduate Program in Systems and Computing Department of Informatics and Applied Mathematics Federal University of Rio Grande do Norte Rio Grande do Norte Natal Brazil

Introduction: The intensive care of neonates is associated with the entry of a large volume of data in their medical records. The treatment of this data can be done through Machine Learning: a tool capable of assisting in the detection and decision-making of a wide range of medical conditions, including adverse drug reactions (ADR). Objective: To train a prediction model to assist in the detection of adverse drug reactions in neonates admitted to an ICU. Methodology: observational study developed in the Neonatal Intensive Care Unit of a teaching hospital in Brazil. Clinical data were collected from daily pharmacotherapeutic follow-up, processed and analyzed by machine learning through libraries written in Python language. Results: Eight hundred and three neonates were included in the study, with a mean gestational age of 32.2 ± 4.2 weeks and mean birth weight of 1807.2 ± 936.6g. The incidence of ADR was 10.8%. Antimicrobials, especially aminoglycosides, were the most prescribed drugs for this population. An algorithm was trained and tested to predict ADR in the NICU, in which the metrics were precision (0.35) and recall (0.823), with specificity (80%) and sensitivity (67%). Conclusion: There is a high potential in the machine learning method to predict ADR in neonates admitted to an ICU. © 2023, The Authors. All rights reserved.

关键词： Forecasting

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Incorporating teacher intelligence into digital games: An expert system-guided self-regulated learning approach to promoting EFL students' performance in digital gaming contexts

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British Journal of Educational Technology 2023年第2期54卷 534-553页

作者： Chu, Shih-Ting Hwang, Gwo-Jen Chien, Shu-Yun Chang, Shao-Chen Graduate Institute of Applied Science and Technology National Taiwan University of Science and Technology Taipei Taiwan Graduate Institute of Digital Learning and Education National Taiwan University of Science and Technology Taipei Taiwan International Bachelor Program in Informatics Department of Information Communication Yuan Ze University Taoyuan Taiwan

In recent years, several studies have reported the potential of employing digital games in EFL (English as Foreign Language) courses to promote students' learning motivation. However, scholars have pointed out that students generally lack self-learning ability, which is the key to the success of learning a foreign language. Therefore, it is crucial to foster students' self-learning ability during the game-based learning process. In this study, an expert system was developed to facilitate self-regulated learning in digital game-based learning contexts. To evaluate the effectiveness of the proposed approach, a quasi-experimental design was employed in a university English course. The experimental group students learned with the self-regulated English vocabulary game (SR-EVG) approach, while the control group students learned with the conventional English vocabulary game (C-EVG) approach. The experimental results indicated that the use of the SR-EVG approach could improve learners' English vocabulary achievement and self-regulation compared with the C-EVG approach without increasing students' English learning anxiety. Moreover, through qualitative interviews, it was found that students who used the SR-EVG approach would focus on their learning due to goal-setting in the game and would pay more attention to the learning strategies they used. Practitioner notes: What is already known about this topic Digital game-based learning situates students in a realistic situational environment, enabling students to learn by experiencing and interacting with the situations. Without appropriate scaffolding during digital game-based learning, students may become overly focused on the game, or perform many non-learning behaviors Self-regulated learning refers to students’ ability to learn on their own via goal setting, strategic planning, self-monitoring, and self-adjustment. What this paper adds An expert system-guided self-regulated learning approach was proposed to facilitate EFL s

关键词： Students

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A Fitness-Based Migration Policy for Biased Random-Key Genetic Algorithms 26th

A Fitness-Based Migration Policy for Biased Random-Key Gene...

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26th International Conference on Applications of Evolutionary Computation, EvoApplications 2023, held as part of EvoStar 2023

作者： Boiani, Mateus Parpinelli, Rafael Stubs Dorn, Márcio Institute of Informatics Federal University of Rio Grande do Sul Rio Grande do Sul Porto Alegre Brazil Graduate Program in Applied Computing Santa Catarina State University Santa Catarina Joinville Brazil Center for Biotechnology Federal University of Rio Grande do Sul Rio Grande do Sul Porto Alegre Brazil National Institute of Science and Technology - Forensic Science Rio Grande do Sul Porto Alegre Brazil

ISBN: (纸本)9783031302282

Population diversity management is crucial for the quality of solutions in Evolutionary Algorithms. Many techniques require assistance to handle diverse problem characteristics and may prematurely converge in local optima. Maintaining diversity enables the algorithm to search the space and produce better results effectively. Parallel models are a common approach to preserving diversity;however, design decisions affect optimization process characteristics. For example, the Island model’s migration policy affects convergence speed. This study proposes and evaluates a fitness-based migration policy for the Biased Random-Key Genetic Algorithm (BRKGA) and compares it to two traditional strategies. The results in continuous search spaces demonstrate that the proposed policy can enhance BRKGA optimization with appropriate parameters. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Genetic algorithms

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Retraction Note: Toward a novel method to support decision-making process in health and behavioral factors analysis for the composition of IT projects teams

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Neural Computing and Applications 2024年第24期36卷 15221-15221页

作者： Nunes, Luciano Comin Pinheiro, Plácido Rogério Pinheiro, Mirian Caliope Dantas Filho, Marum Simão Nunes, Rafael Espíndola Comin Graduate Program in Applied Informatics University of Fortaleza Fortaleza Brazil Federal University of Ceara Fortaleza Brazil

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MILPdM: A Predictive Maintenance Architecture for the Military Domain

MILPdM: A Predictive Maintenance Architecture for the Milita...

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International Conference on Machine Learning and Applications (ICMLA)

作者： Jovani Dalzochio Rafael Kunst Jorge Barbosa Edison Pignaton De Freitas Alécio Binotto Graduate Program in Applied Computing University of Vale do Rio dos Sinos São Leopoldo Brazil Institute of Informatics Federal University of Rio Grande do SuI Porto Alegre Brazil Asset and Edge Optimization IBM Consulting Munich Germany

Equipment monitoring for failure prediction is receiving attention from different sectors of society, such as industry, healthcare, and defense. In the defense domain, assets like military vehicles generate data that one can use to identify behavior changes and anticipate possible real-time failures, avoiding unnecessary maintenance interventions. Failure anticipation is crucial, as assets operated in the military domain perform critical tasks in which unexpected equipment failures result in high material and human costs. Approaches found in the literature typically deal with failure generation, aiming at analyzing the equipment's behavior. This paper proposes a broader approach called MILPdM. This proposal is a failure prediction architecture covering the whole failure prediction and predictive maintenance procedures. We evaluate MILPdM architecture by analyzing an engine-failure scenario where we train models to predict time series by collecting vibration data that describes the degradation of the vehicle's health. Considering the implementation of an LSTM-based neural network and Random Forest, the acquired results lead to a root mean square error of 0.15015 in the best case, which allows to predict the failure status two minutes in advance with only 3 hours of data history. This result shows that MILPdM is capable of anticipating failures with high assertiveness.

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