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4th International Conference on Novel and Intelligent Digital Systems, NiDS 2024

作者： Vonitsanos, Gerasimos Gounaridis, Ioannis Kanavos, Andreas Mylonas, Phivos Computer Engineering and Informatics Department University of Patras Patras Greece Department of Informatics Ionian University Corfu Greece Department of Informatics and Computer Engineering University of West Attica Athens Greece

ISBN: (纸本)9783031733437

Flight delays pose significant challenges to the aviation industry, leading to increased operational costs and passenger dissatisfaction. This paper explores the use of machine learning (ML) and big data analytics to enhance the accuracy and efficiency of flight delay predictions. Utilizing data from the Federal Aviation Administration (FAA) covering the period from 2018 to 2022, we analyze critical factors influencing delays and develop predictive models employing techniques such as Random Forest, Gradient Boosting Machines, Decision Trees, and k-Nearest Neighbors. Our analysis demonstrates that these ML techniques significantly outperform traditional models, improving the accuracy of delay predictions and thereby supporting airlines in optimizing operational efficiency and enhancing passenger satisfaction. The paper also discusses the practical implementation of these findings in real-time airline operations and outlines future research directions to further improve predictive accuracy. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.

关键词： Adversarial machine learning

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Evaluating Machine Learning Techniques for Enhanced Prediction of Building Energy Consumption 9

Evaluating Machine Learning Techniques for Enhanced Predicti...

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9th South-East Europe Design Automation, computer engineering, computer Networks and Social Media Conference, SEEDA-CECNSM 2024

作者： Vonitsanos, Gerasimos Kanavos, Andreas Mylonas, Phivos University of Patras Computer Engineering and Informatics Department Patras Greece Ionian University Department of Informatics Corfu Greece University of West Attica Department of Informatics and Computer Engineering Athens Greece

ISBN: (纸本)9798350342482

Accurate prediction of energy usage is crucial for optimizing resource allocation, enhancing energy efficiency, and reducing environmental impact, pivotal for sustainable development. This study examines electricity consumption in three Cornell University buildings, utilizing advanced machine learning techniques to tackle the challenges of sustainable energy management effectively. We specifically evaluated the performance of Support Vector Machine (SVM), Random Forest, Decision Tree, and K-Nearest Neighbors (KNN) in forecasting electricity usage. Our findings reveal that SVM consistently outperforms the other models across various performance metrics, including accuracy and efficiency. These results provide vital insights into the efficacy of these algorithms in predicting energy consumption, thereby supporting strategic energy management decisions in educational institutions and potentially other similar settings. © 2024 IEEE.

关键词： Sustainable building

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Social Media Insights into Climate Change: Sentiment Analysis Using VADER and RoBERTa 19

Social Media Insights into Climate Change: Sentiment Analysi...

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19th International Workshop on Semantic and Social Media Adaptation and Personalization, SMAP 2024

作者： Vonitsanos, Gerasimos Kanavos, Andreas Bardis, Georgios Mylonas, Phivos University of Patras Computer Engineering and Informatics Department Patras Greece Ionian University Department of Informatics Corfu Greece University of West Attica Department of Informatics and Computer Engineering Athens Greece

ISBN: (纸本)9798331504502

Sentiment analysis, a critical branch of Natural Language Processing (NLP), is pivotal for uncovering the emotional undertones within textual data, thereby revealing public sentiments on diverse topics. This study conducts a comparative analysis of two prominent sentiment analysis tools - VADER, a lexicon and rule-based approach, and RoBERTa, a transformer-based deep learning model. It focuses on their efficacy in analyzing tweets related to climate change, a topic of global significance that elicits a wide range of public opinions. The nuanced and dynamic nature of social media language poses unique challenges, particularly in contexts such as climate change discussions. We assess how effectively each model discerns positive, neutral, and negative sentiments across different categories of climate change-related tweets, delineated into Pro, Neutral, News, and Anti stances. Our findings indicate that RoBERTa outperforms VADER in capturing contextual nuances and providing detailed sentiment classifications. This detailed capability allows RoBERTa to better reflect the complex public opinions on climate change, offering invaluable insights to policymakers, researchers, and environmental advocates. This study not only aids in better understanding and engaging with public discourse on social media but also highlights the potential of advanced NLP tools in shaping environmental communication and policy formulation. © 2024 IEEE.

关键词： Tweets

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Variable-Sized Tiling and Rate Allocation for 360° Video Streaming

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IEEE Transactions on Vehicular Technology 2024年第5期74卷 6979-6990页

作者： Su, Qichen Huang, Jiawei Li, Weihe Zhong, Ping Gao, Feng Li, Zhaoyi Liu, Jingling Zhou, Shengwen Lu, Bo Song, Zhiming Wang, Jianxin Central South University School of Computer Science and Engineering China University of Edinburgh School of Informatics United Kingdom

In recent years, the quality of 360° video over bandwidth-constrained networks has received a lot of attention. To reduce the bandwidth cost, some tile-based 360 ° video streaming systems split video spatially into variable-sized coarse-grained tiles by grouping areas with the similar quality levels. However, these approaches do not minimize the number of tiles, resulting in considerable overhead in re-encoding the boundaries between small tiles. To improve the coding efficiency of 360° video, we propose a new video tiling scheme called TRAS, by using the convex decomposition of concave polygon. Meanwhile, to maximize user's quality of experience (QoE), we propose a greedy bitrate selection algorithm by considering the tile size and coding efficiency. The experiment results demonstrate that, compared with the state-of-the-art approaches, TRAS reduces the coding overhead by about 18% and significantly improves the video quality by about 5 dB. © 1967-2012 IEEE.

关键词： Bandwidth

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Muli-Quay Combined Berth and Quay Crane Allocation Using the Cuckoo Search Algorithm 10

Muli-Quay Combined Berth and Quay Crane Allocation Using the...

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10th International Conference on Vehicle Technology and Intelligent Transport Systems, VEHITS 2024

作者： Aslam, Sheraz Michaelides, Michalis P. Herodotou, Herodotos Department of Electrical Engineering Computer Engineering and Informatics Cyprus University of Technology Cyprus

ISBN: (纸本)9789897587030

This study investigates the combined berth allocation problem (BAP) and quay crane allocation problem (QCAP) while considering a multi-quay setting. First, a mixed integer linear programming mathematical model is developed based on various constraints and real port settings. Then, the multi-quay combined BAP and QCAP is solved using both the exact method and a metaheuristic optimization method, namely, the cuckoo search algorithm (CSA). This analysis pertains to a one-week planning scenario, utilizing data from a real port. The results of the comparative analysis show that the proposed CSA can provide a near-optimal solution ( Copyright © 2024 by SCITEPRESS - Science and Technology Publications, Lda.

关键词： Integer programming

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Towards LLM-Generated Affective Phrase Sets for Text Entry Evaluation 24

Towards LLM-Generated Affective Phrase Sets for Text Entry E...

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23rd International Conference on Mobile and Ubiquitous Multimedia, MUM 2024

作者： Komninos, Andreas Simou, Ioulia Fotopoulos, Angelos Michanetzi, Eleftheria Lito Xenos, Michalis Computer Engineering & Informatics Department University of Patras Rio Greece

ISBN: (纸本)9798400712838

We present a novel method to generate affective phrase sets using Large Language Models (LLMs), for use in text entry study transcription tasks. These phrases could be used to adjust participant emotions, and enable performance assessment under various affective conditions. We found that the affective phrases impacted participants' valence, but not arousal or text entry performance. Though partially succesful, our work provides a foundation for exploring the relationship between emotion and text entry performance in lab studies. © 2024 Copyright held by the owner/author(s).

关键词： Text Entry

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Comparison of Elbow, Silhouette and DBI Methods for Clustering Nutritional Status of Toddlers Using K-Means Clustering 12

Comparison of Elbow, Silhouette and DBI Methods for Clusteri...

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12th International Conference on Cyber and IT Service Management, CITSM 2024

作者： Muharram, Asep Taufik Nalawati, Rizki Elisa Warsuta, Bambang Malik Matin, Iik Muhamad Pradiptyas, Ayres Natanael, Michael Politeknik Negeri Jakarta Informatics and Computer Engineering Depok Indonesia

ISBN: (纸本)9798331528799

Nutritional status is a measure of a person's health condition as seen from the food consumed. The implementation of nutritional monitoring or nutritional surveillance at the Community Health Center begins with data collection and reporting of toddler nutritional status with the Electronic Community-Based Nutrition Recording and Reporting System (E-PPGBM), the recording process must input toddler data from each integrated health post so that the process takes a long time until each integrated health post has measured each toddler. Furthermore, the data is processed and analyzed with Excel to produce a health information report in the form of toddler nutritional status data from each integrated health post which is reported to the health office. In the final process, namely dissemination, namely decision making for follow-up actions to carry out nutritional improvement programs. The nutritional surveillance process still has motivational constraints and performance becomes less than optimal, such as late reporting and coaching because all implementation processes are only carried out by one health center nutrition officer. The health center needs a data clustering system for the nutritional status of toddlers at each integrated health post to facilitate the decision-making process and monitoring of the nutritional health of each integrated health post so that information can be obtained to help nutrition officers prioritize integrated health posts for nutritional improvement service programs in order to achieve improvements in the nutritional health of toddlers at the Abadijaya Health Center. Evaluation of the number of optimal clusters using the Elbow, Silhouette, and Davies Bouldin Index (DBI) methods. The Elbow method obtained 4 optimal clusters, while the Silhouette method obtained 2 optimal clusters and the Davies Bouldin Index (DBI) obtained 2 clusters. © 2024 IEEE.

关键词： Electronic health record

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Design of an AI-Assisted Platform that will Facilitate Educators in Creating Minecraft Education Courses 6

Design of an AI-Assisted Platform that will Facilitate Educa...

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6th International Workshop on Artificial Intelligence and Education, WAIE 2024

作者： Roumpas, Konstantinos Xenos, Michalis University of Patras Computer Engineering and Informatics Department Patras Greece

ISBN: (纸本)9798350378894

The potential of Education Technology has reached a point where teachers cannot keep up with the latest trends, nor they can spend the time to get accustomed to innovative technologies that might become obsolete in a few years. With the rise in the popularity of Minecraft Education, an educational platform based on the engine of the world-famous video-game: Minecraft, as well as the benefits of gamification in classrooms for all student ages, it seems that an application that would help teachers create educational video games that are run on Minecraft Education, without any code and with artificial intelligence assistance, could be just the thing that they need to update their teaching techniques. We propose the creation of a platform like that, and we present its potential design, after being consulted by the available research that has been done to this day regarding instructional design, user interface and applications that utilize large language models. © 2024 IEEE.

关键词： Gamification

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Use Technology to Help Medical Staff Treat "New Health Problems" Arising Constantly

Use Technology to Help Medical Staff Treat "New Health Probl...

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2024 European Federation for Medical informatics Special Topic Conference, EFMI STC 2024

作者： Karanikolas, Nikitas N. Department of Informatics and Computer Engineering University of West Attica Greece

ISBN: (纸本)9781643685540

The development of medical science allows the treatment of more and more health problems that in the past were not a factor of consumption of health resources, because at that time medical science did not have protocols for their treatment. Health problems that are now treatable, hereafter referred as 'new health problems', often affect large population groups and require increased consumption of health resources. It therefore becomes necessary to increase the number of staff providing health services (doctors, nurses, etc.) and other resources. This raises the question: is it feasible to manage the 'new health problems' by the existing medical staff? If not, are there other solutions? Could technology help the existing Medical Staff to sufficiently manage the 'new health problems'? We will examine a pilot system 'Recording and visualizing of outpatient monitoring data with smart mobile phones', which seeks to ensure the competence of existing medical staff in the effective treatment of the ever-increasing volume of transplant patients. © 2024 The Authors.

关键词： Electronic health record

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Content Creation for Touristic Portals Using ChatGPT 15

Content Creation for Touristic Portals Using ChatGPT

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15th International Conference on Information, Intelligence, Systems and Applications, IISA 2024

作者： Lampros, Papantoniou Eleni, Voyiatzaki Ioannis, Hatzilygeroudis University of Patras Computer Engineering and Informatics Dept Patras Greece

ISBN: (纸本)9798350368833

Our research presents the development of an innovative web-based application designed to assist hoteliers in creating and managing multilingual content for their tourist accommodations for tourism portals. To address this need, our application leverages the advanced capabilities of OpenAI's ChatGPT for automated content generation and DeepL's API for high-quality translations, integrated within a user-friendly interface. Through an integrated development process, we leveraged the capabilities of combining natural language processing with artificial intelligence to meet the specific needs of the tourism and hospitality industry. Our findings indicate that the application significantly streamlines the content creation and translation process, offering hoteliers a competitive edge in a globally connected marketplace. By automating these tasks, the system not only saves time and resources but also ensures consistency and quality in accommodation listings across different languages. The application's impact is further evidenced by its adaptability to various accommodation types and the potential for enhancing guest satisfaction through improved information accessibility. The benefits of our application are supported by a medium scale evaluation. © 2024 IEEE.

关键词： Tourism

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