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UPB Scientific Bulletin, Series C: Electrical Engineering and Computer Science 2024年第2期86卷 61-72页

作者： Dorobăț, Ilie Cristian Posea, Vlad Boncea, Radu Dept. of Computer Science National University of Science and Technology POLITEHNICA Bucharest Romania National Institute for Research and Development in Informatics-ICI Bucharest Romania

The paper introduces the Cultural Leaf Semantic Portal whose aim is to provide a consolidated user-friendly solution for exploring the 36,132 Romanian artifacts and the 1,086 cultural entities that house them. Using the eCHO framework, the data collected from official sources are subjected to a transformation process through which they are sanitized, temporal expressions are normalized, thus reducing the number of forms in which the centuries and millennia are expressed from 1,733 to only 67, and then they are transformed into semantic structures. Finally, the resulting data is accessible via both a SPARQL endpoint and a semantic portal. © 2024, Politechnica University of Bucharest. All rights reserved.

关键词： Semantic Web

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A Study on the Topic of Crossing Minimisation 26

A Study on the Topic of Crossing Minimisation

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26th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing, SYNASC 2024

作者： Mateiu, Rares-Ioan Popa, Alexandru University of Bucharest ICI - National Institute for Research and Development in Informatics Bucharest Romania

ISBN: (纸本)9798331532833

In this article we undertake a rigorous study on several problems related to the topic of reordering the order of the leaves of a tree according to a specific function and we come up with our own discoveries on the topic. Our study has its roots in tanglegrams, which represent a pair of trees on the same set of leaves with the matching leaves in the two trees joined by an edge. The primary focus of our article is on two distinct approaches for transforming the initial leaf order to match the input order: One Tree Crossing Minimization (OTCM) and One Tree Drawing by Deleting Edges (OTDE). To be more precise, we get a specific order as input and the purpose is to match the initial order of the tree as much as possible with the input order. Both problems are NP Hard, and we present approximation algorithms for each. Moreover, we explore efficient solutions for the isolated case of binary trees. Our own results include providing 3 approximation algorithms for both OTDE and OTCM and displaying that OTDE is hard to approximate within a factor of 4/5 - . Last but not least, we compose a literature survey, studying related topics in the field of crossing minimisation as we compare the solutions and their efficiency with OTDE and OTCM. © 2024 IEEE.

关键词： Approximation algorithms

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Automation of student evaluation process through online educational platforms 11

Automation of student evaluation process through online educ...

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11th International Conference on Information Technology and Quantitative Management, ITQM 2024

作者： Zamfiroiu, Alin Vasile, Denisa National Institute for Research & Development in Informatics Bucharest University of Economic Studies Bucharest Romania

In the increasingly digital age, students' education and assessment have undergone significant transformations, and online educational platforms have become an essential tool in this process. The purpose of this article is to explore and highlight the crucial role these platforms play in optimizing the assessment process in higher education institutions. In the year 2020, the world of education has been challenged by the global pandemic of COVID-19, causing educational institutions to rapidly reconfigure teaching and assessment strategies. With the suspension of traditional courses, institutions have been forced to adopt distance teaching and assessment methods. In this context, the development and use of online learning platforms have become essential to ensure the continuity of the educational process. Focusing on universities, this article proposes to highlight the crucial importance of online educational platforms in optimizing students' assessment. The goal is to develop a university platform that facilitates both the student evaluation process and effective communication between students and teachers. Thus, this article aims to explore in depth how online educational platforms can influence and improve the process of student assessment in universities. This paper brings to the fore the essential role that technology plays in educating future generations and preparing them for the challenges of a world in continuous transformation. We present our proposed platform that can be used to evaluate the students in automatically way. © 2024 The Authors.

关键词： Students

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RecomMind: Movie Recommendation Dialogue with Seeker’s Internal State 2

RecomMind: Movie Recommendation Dialogue with Seeker’s Inte...

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2nd Workshop on Social Influence in Conversations, SICon 2024

作者： Kodama, Takashi Kiyomaru, Hirokazu Huang, Yin Jou Kurohashi, Sadao Research and Development Center for LLMs National Institute of Informatics Japan Kyoto University Japan

ISBN: (纸本)9798891761865

Humans pay careful attention to the interlocutor’s internal state in dialogues. For example, in recommendation dialogues, we make recommendations while estimating the seeker’s internal state, such as his/her level of knowledge and interest. Since there are no existing annotated resources for the analysis and experiment, we constructed RecomMind, a movie recommendation dialogue dataset with annotations of the seeker’s internal state at the entity level. Each entity has a first-person label annotated by the seeker and a second-person label annotated by the recommender. Our analysis based on RecomMind reveals that the success of recommendations is enhanced when recommenders mention entities that seekers do not know but are interested in. We also propose a response generation framework that explicitly considers the seeker’s internal state, utilizing the chain-of-thought prompting. The human evaluation results show that our proposed method outperforms the baseline method in both consistency and the success of recommendations. © 2024 Association for Computational Linguistics.

关键词： Computational linguistics

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Adaptive System for Monitoring the Patient's Environment Using Telemetric Data 28

Adaptive System for Monitoring the Patient's Environment Usi...

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2024 28th International Conference on Information Technology, IT 2024

作者： Rotuna, Carmen Ionela Floroiu, Iustin Paraschiv, Elena-Anca Bostan, Alexandru Radu National Institute for Research and Development in Informatics 8-10 Mareal Averescu Avenue Bucharest411515 Romania Politehnica University of Bucharest 313 Splaiul Independenţei Bucharest060042 Romania National Institute for Research and Development in Informatics Romania National Institute for Research and Development in Informatics Politehnica University of Bucharest 313 Splaiul Independenţei Bucharest060042 Romania

ISBN: (纸本)9798350369618

Currently, medical telemetry sensors data analysis in scientific research addresses patient monitoring, the digital recording, transmission and analysis of patient health information. This paper proposes an adaptive system for monitoring the patient's environment using telemetric data collected by sensors useful for optimal recovery conditions. The described system utilizes machine learning algorithms to analyze telemetric data, allowing it to identify patterns, adjust responses, and identify deviations from normal conditions. This adaptability enables the system to offer proactive and personalized patient care by providing information about potential health risks associated with room related parameters. © 2024 IEEE.

关键词： Machine learning

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Advancing Neurodegenerative Disease Management: The NeuroPredict Platform Integrating IoT, AI, and Cloud Technologies 15

Advancing Neurodegenerative Disease Management: The NeuroPre...

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15th International Conference on Communications, COMM 2024

作者： Ianculescu, Marilena Nicolau, Dragos Petrache, Cristian Vasilevschi, Ana National Institute for Research and Development in Informatics Communications Digital Applications and System Department Bucharest Romania

ISBN: (纸本)9798350355956

Worldwide healthcare systems face considerable challenges from neurodegenerative disorders including multiple sclerosis, Parkinson's disease, and Alzheimer's disease, especially as the population ages. For these complex conditions, traditional healthcare approaches tend to come inadequate in providing the comprehensive, real-time monitoring required. As a result, cutting-edge technologies like artificial intelligence and the Internet of Things have become critical resources for improving remote patient monitoring and healthcare outcomes. The NeuroPredict platform proposes an innovative approach to overcome these challenges. The NeuroPredict platform regularly gathers considerable health and environmental data required for customized healthcare management by integrating a wide range of IoT devices through a smart environment;then it analysis this data using AI algorithms to find patterns, predict whether the medical condition will change over time, and provide tailored insights for the patient. This paper focuses on some distinct features and functionalities of the NeuroPredict platform. It delves on the integration of IoT devices, making use of advanced AI for data analysis, while a reliable data recovery application is developed within the ICIPRO cloud environment. © 2024 IEEE.

关键词： Electronic health record

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BINARY PROGRAMMING MODELS FOR ENERGYEFFICIENT VIRTUAL MACHINES PLACEMENT IN DATA CENTERS

UPB Scientific Bulletin, Series C: Electrical Engineering an...

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UPB Scientific Bulletin, Series C: Electrical Engineering and Computer Science 2024年第3期86卷 335-346页

作者： Radulescu, Delia Mihaela Radulescu, Delia Mihaela Radulescu, Marius Radulescu, Constanţa Zoie Lazaroiu, Gheorghe National Institute for Research and Development in Informatics Bucharest Romania Faculty of Power Engineering National University of Science and Technology POLITEHNICA Bucharest Romania Dept. Statistical Inference Statistical Control and Optimization Gheorghe Mihoc-Caius Iacob Institute of Mathematical Statistics and Applied Mathematics Romanian Academy Bucharest Romania Senior research worker National Institute for Research and Development in Informatics Bucharest Romania Prof. Dept. of Energy Production and Use National University of Science and Technology POLITEHNICA Bucharest Romania

The aim of the paper is to present two virtual machines (VMs) placement models that minimize energy consumption in a data center. Both placement models use binary programming. The first model aims to find an allocation of VMs to a set of servers such that the energy consumption is minimized. The second model suppose that an allocation of VMs to a set of servers is given. Its aim is to find another allocation of VMs to servers that minimize the sum of two energies. The first energy is the energy consumption of VMs in the new allocation and second energy is the energy needed for migration between the two allocations. © 2024, Politechnica University of Bucharest. All rights reserved.

关键词： allocation binary programming model data center energy consumption minimization servers virtual machines

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A Machine Learning-based model with feature fusion for biometric data processing 15

A Machine Learning-based model with feature fusion for biome...

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15th International Conference on Communications, COMM 2024

作者： Soviany, Sorin Gheorghe, Cristina-Gabriela Sandulescu, Virginia Gheorghe-Moisii, Maria Nicolau, Dragos National Institute for Research and Development in Informatics ICI Communication Digital Applications and Systems Dept. Bucharest Romania

ISBN: (纸本)9798350355956

This paper presents a functional architecture for biometric data processing in m-Health applications to ensure a secured environment for these apps. The architecture specifies a Machine Learning model with data fusion to combine information extracted from different biometrics (fingerprint, face, iris, voice). The architecture addresses mobile users' biometric authentication by properly exploiting the biometric technologies integrated into their mobile devices. An application scenario is defined to show how the proposed model could be mapped onto a real use-case. Future developments include the model optimization and the software implementation based on the proposed architecture. © 2024 IEEE.

关键词： Electronic health record

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Emotion Detection from Face Images Using Deep Learning Techniques 12

Emotion Detection from Face Images Using Deep Learning Techn...

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12th E-Health and Bioengineering Conference, EHB 2024

作者： Petean, Corina Sandulescu, Virginia Bica, Ovidiu Communication Digital Applications and Systems Dept. National Institute for Research and Development in Informatics ICI Bucharest Bucharest Romania

ISBN: (纸本)9798331532147

Face Emotions Recognition (FER) systems are becoming increasingly performant, benefiting from developments in computer vision and deep learning techniques. In this paper, a deep convolutional neural network (DCNN) model is proposed for classifying facial expressions into three primary emotion categories: positive, neutral, and negative. The designed custom architecture integrates residual connections, which enhance the model’s ability to generalize by effectively retaining learned features across layers. The proposed model achieves an average accuracy of 92.16%, demonstrating good performances in discriminating between data from each targeted class. The FER2013 and its curated version, FER Plus, datasets were employed for training and testing different models. A new subset of FER Plus was created for model training and testing. Various preprocessing techniques were applied, including data normalization, augmentation and class balancing. © 2024 IEEE.

关键词： Convolutional neural networks

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Pose orientation analysis for fall detection using non-invasive technologies 24

Pose orientation analysis for fall detection using non-invas...

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24th International Conference on Control Systems and Computer Science, CSCS 2023

作者： Dutescu, Razvan-Alexandru Apostol, Mihai Digital Transformation and Governance National Institute for Research and Development in Informatics -ICI Bucharest Bucharest Romania

ISBN: (纸本)9798350313390

Older adults are more susceptible to falling which can cause serious health problems due to their frail bodies, dizziness, and other common health problems common for this age group. Fall detection systems can have a significant impact on this issue, potentially saving lives, mainly due to the underlying fall detection algorithm which is indispensable for the system's primary function. In this article, we propose a threshold-based fall detection algorithm that is the crux of a finite automaton intended for non-invasive sensor-based fall detection systems, especially radar-type sensors. Furthermore, we will be discussing similar algorithms to get a better understanding of the performance of our algorithm. © 2023 IEEE.

关键词： Fall detection

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