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IEEE Communications Standards Magazine 2025年

作者： Saleh, Sharief Zheng, Pinjun Liu, Xing Chen, Hui Keskin, Musa Furkan Priyanto, Basuki Beale, Martin Ettefagh, Yasaman Seco-Granados, Gonzalo Al-Naffouri, Tareq Y. Wymeersch, Henk Chalmers University of Technology Department of Electrical Engineering Sweden King Abdullah University of Science and Technology (KAUST) Electrical and Computer Engineering Program Division of Computer Electrical and Mathematical Sciences and Engineering (CEMSE) Saudi Arabia Sony Europe BV United Kingdom Universitat Autònoma de Barcelona Department of Telecommunications and Systems Engineering Spain

The rapid evolution of cellular networks has introduced groundbreaking technologies, including large and distributed antenna arrays and reconfigurable intelligent surfaces in terrestrial networks (TNs), as well as aerial and space-based nodes in non-terrestrial networks (NTNs). These advancements enable applications beyond traditional communication, such as high-precision localization and sensing. While integrating TN and NTN enablers will lead to unparalleled opportunities for seamless global localization, such integration attempts are expected to face several challenges. To understand these opportunities and challenges, we first examine the distinctive characteristics of the key 6G enablers, evaluating their roles in localization from both technical and practical perspectives. Next, to identify developments driving TN-NTN localization, we review the latest standardization and industrial innovation progress. Finally, we discuss the opportunities and challenges of TN-NTN integration, illustrating its potential through two numerical case studies. © 2017 IEEE.

关键词： 6G localization low-Earth-orbit (LEO) satellites non-terrestrial network (NTN) reconfigurable intelligent surface (RIS) terrestrial network (TN)

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A model of service-oriented architecture of e-certification system to support boat registration and site visit inspection to support maritime safety and crew health inspection

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Marine Systems and Ocean technology 2023年第1-2期18卷 45-63页

作者： Saputra, Diaz Gaol, Ford Lumban Abdurachman, Edi Sensuse, Dana Indra Matsuo, Tokuro Department of Computer Science BINUS Graduate Program - Doctor of Computer Science Bina Nusantara University Jakarta11480 Indonesia Department of Computer Science Binus Graduate Program - Master in Information System Bina Nusantara University Jakarta11480 Indonesia Department of Research in Management Bina Nusantara University Jakarta Indonesia Faculty of Computer Science University of Indonesia Jakarta Indonesia Advanced Institute of Industrial Technology Tokyo Japan City University of Macau China Asia University Taichung Taiwan

This article describes the architecture of software services that provide registration of small boat data to build maritime safety. The proposed system architecture which so-called SIMKAPEL aims to support small boat registration for maritime safety. It is developed from a conventional service-oriented architecture (SOA) with an open standard for data interoperability between elements. The goal of this research is to implement and evaluate the proposed architecture to support small boat registration and e-certification. Several parts of the architecture have been implemented as a platform that provides core services and data sources to be used by Ministry of Transportation, Directorate General of Sea Transportation, and other government agencies. Finally, the proposed SIMKAPEL platform with the SOA architecture is evaluated for its benefits to users through the expert opinion survey to measure its efficiency. The analysis results showed that SOA-based SIMKAPEL is feasible to use as a boat e-certification system. Furthermore, experiment results provide three parameters (e.g., maritime safety, namely, cargo/passengers, boat safety facilities, and maritime safety systems) with efficiency values of 42%, 46%, and 42%, respectively. The parameter with the highest efficiency shows a big effect on the level of safety of the boat and passengers. Thus, the parameters that need to be prioritized and need boat owners’ attention are cargo/passenger, boat safety equipment, and maritime safety system. © 2023, The Author(s).

关键词： Boat e-certification Boat online certification Cloud-based service Integrated system SOA architecture

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Addressing the role and opportunities of machine learning utilization in brain tumor detection 9th

Addressing the role and opportunities of machine learning ut...

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9th International Conference on computer science and Computational Intelligence, ICCSCI 2024

作者： Lesmana, Vallerie Delia Agustine, Holly Wairooy, Irma Kartika Makalew, Brilly Andro Computer Science Department School of Computer Science Binus University Jakarta11480 Indonesia Mobile Application & Technology Program Computer Science Department Binus University Jakarta11480 Indonesia

This research aims to develop a brain tumor detection model by utilizing the machine learning techniques and Convolutional Neural Network (CNN). A significant matter to address is revolving around early detection and the proper handling regarding the brain tumor. This research's methodology consists of collecting the dataset, identifying the tools and language to use, prepare and preprocessing the data, data augmentation, splitting and label encoding, building the model architecture, compiling the model, training, and evaluating the model, predicting the model, and comparing it with other models. Dataset consists of 7022 MRI images, divided into training and testing subsets;and four classes: glioma, meningioma, pituitary, and no tumor. There are four different CNN models that have been built and evaluated, namely VGG16, InceptionV3, ResNet50, and DenseNet121. The result gained shows VGG16 with the best performance achieving an accuracy rate of 96.43%, followed by DenseNet121 (94,96%), InceptionV3 (92,40%), and ResNet50 (78,69%). Although there is still room for improvement regarding overfitting and increasing the models' overall performance, this result is promising enough to enhance early diagnosis and offer an appropriate and effective treatment for patients. © 2024 The Authors.

关键词： Convolutional neural networks

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False alarm reduction in continuous cardiac monitoring using 3D Accélération signals

False alarm reduction in continuous cardiac monitoring using...

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International computer science and Engineering Conference, ICSEC 2014

作者： Tanantong, Tanatorn Nantajeewarawat, Ekawrt Thiemjarus, Surapa Computer Science Program Sirindhorn International Institute of Technology Thammasat University Pathumthani Thailand National Electronics and Computer Technology Center Pathumthani Thailand

ISBN: (纸本)9781479949632

In continuous cardiac monitoring through wireless Body Sensor Networks (BSNs) using ECG signals, signal quality can be deteriorated due to several factors, including, noise, low battery power and network transmission problems. Body movements occurring when a subject performs activities of daily living (ADLs) are also major causes of high false alarm rates. This paper presents a hybrid framework for false alarm reduction in continuous cardiac monitoring, where classification models constructed using machine learning algorithms are used for labeling input signals and a rule-based expert system is used for combining the classification results into make a final decision. From their extracted low-level features, ECG signal portions are labeled with heartbeat types and also signal quality levels. Meanwhile, low-level features from 3D acceleration signals are used for predicting types of activities. Taking signal quality levels and activity types into considerations, the rule-based expert system then determines whether abnormal ECG portions should trigger alarms or should be ignored. The proposed framework is validated using two datasets: one is obtained from the MIT-BIH arrhythmia database and the other is acquired from 10 subjects while they are performing ADLs. The results of the experiments demonstrate that our proposed framework can reduce false alarm rates in continuous cardiac monitoring and potentially assist physicians in diagnosing a vast amount of data acquired from wireless sensors. © 2014 IEEE.

关键词： Errors

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Sentiment Analysis of Makeup Alley Website Cosmetic Reviews Using SVM and TF-IDF 9

Sentiment Analysis of Makeup Alley Website Cosmetic Reviews ...

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9th International Conference on Information Management and technology, ICIMTech 2024

作者： Putri, Christine Salim, Claudya Veronica Dwiyanti, W.K. Achmad, Said Moniaga, Jurike V School of Computer Science Bina Nusantara University Mobile Application & Technology Program Computer Science Department Jakarta11480 Indonesia School of Computer Science Bina Nusantara University Computer Science Department Jakarta11480 Indonesia

ISBN: (纸本)9798350390025

This paper focuses on performing sentiment analysis of cosmetic reviews using a machine learning algorithm. The study aims to classify reviews into positive, neutral, and negative opinions using aspect-based sentiment analysis with TF-IDF and SVM algorithms. The research questions include understanding user opinions on cosmetic products and identifying the most common positive and negative sentiments in reviews. Data cleaning, tokenization, stopwords removal, normalization, and lemmatization techniques are employed to achieve these goals. The study uses the Makeup Alley website as a data source and employs web scraping to obtain the data. The Natural Language Toolkit (NLTK) is used to simplify the removal of stopwords. The research seeks to document the step-by-step process of developing a sentiment analysis application tailored to cosmetic product reviews. © 2024 IEEE.

关键词： Support vector machines

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GAN Generated Portraits Detection Using Modified VGG-16 and EfficientNet 7

GAN Generated Portraits Detection Using Modified VGG-16 and ...

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7th NAFOSTED Conference on Information and computer science, NICS 2020

作者： Pham, Kha-Luan Dang, Khanh-Mai Tang, Loi-Phat Nguyen, Thanh-Nhan Advanced Program in Computer Science Faculty of Information Technology University of Science Ho Chi Minh City Viet Nam Advanced Program in Computer Science Faculty of Information Technology Vietnam National University Ho Chi Minh City Viet Nam

ISBN: (纸本)9780738105536

Generative Adversarial Networks can generate deceptive portraits of people who do not exist. The misuse of this technology leads to severe security issues such as fake identities and credentials. Since 2017, many works on Deep Learning have focused on detecting GAN synthesized images to prevent the threat against credibility in media. In this work, the authors propose a lightweight VGG-like model to detect state-of-the-art StyleGAN generated portraits. The authors also adopt EfficientNet-B0 to train a classifier on the same StyleGAN architecture. The VGG-like model and EfficientNet-based model achieve 98.9% and 100%, respectively, on the StyleGAN dataset published by Nvidia in 2019. Both models show the potential in generalizing to other GAN architectures and synthetic technologies. © 2020 IEEE.

关键词： Generative adversarial networks

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User Experience Metric for Augmented Reality Application: A Review 3

User Experience Metric for Augmented Reality Application: A ...

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3rd International Conference on computer science and Computational Intelligence, ICCSCI 2018

作者： Arifin, Yulyani Sastria, Thomas Galih Barlian, Edo Computer Science Department School of Computer Science Bina Nusantara University Jakarta11480 Indonesia Game Application and Technology Program Computer Science Department School of Computer Science Bina Nusantara University Jakarta11480 Indonesia

Augmented Reality technology is developing rapidly and has been widely used in the field of education. Due to the ease of developing AR by non-professionals, User Experience (UX) is often not considered in the application. Currently, there are no standard measurements of UX for AR applications especially in Education. The authors reviewed previous research to obtain UX references and the existing measurement standards. From the results of the review, the metrics were analyzed based on the characteristics of AR, especially in the field of education. The metrics will be recommended for the UX measurement of an AR application. The available standard metrics can be used to determine the UX quality of an AR application and contribute to the improvement of UX in AR applications, especially in the field of Education. © 2018 The Authors. Published by Elsevier Ltd.

关键词： Natural language processing systems

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AI-Powered Mobile Application for Image-Based Food Ingredient Detection and Recipe Generation 9

AI-Powered Mobile Application for Image-Based Food Ingredien...

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9th International Conference on Information Management and technology, ICIMTech 2024

作者： Rosaline, Thessalonica Maria Luisse Suciawan, Calvin Anacia Ng, William Achmad, Said Moniaga, Jurike V School of Computer Science Bina Nusantara University Mobile Application & Technology Program Computer Science Department Jakarta11480 Indonesia School of Computer Science Bina Nusantara University Computer Science Department Jakarta11480 Indonesia

ISBN: (纸本)9798350390025

This research explores the critical impact of dietary habits on health, addressing the lack of awareness regarding nutritional content that leads to issues such as malnutrition. The proposed mobile application utilizes the YOLOv8 algorithm with a deep convolutional neural network (CNN) architecture, deployed on the Roboflow server, a local MySQL database server, and ChatGPT. The architectural framework of this application is integrated through the NodeJs server via an API system embedded within the Android application. Despite this approach, the study highlights the need for further refinement in the accuracy of the ingredients' object detection model. The refined YOLOv8 model, trained on an extensive dataset of 24,583 images across 13 food ingredient classes, outperforms the initial YOLOv8 model trained on 9,867 images. Improvements are notable, particularly in addressing misclassifications of ingredients such as beef, pork, onion, and egg in the initial model. However, the YOLOv8 model can still be improved by introducing more ingredient variations and expanding the training dataset. This application can detect multiple food ingredients from an image and evaluate their nutritional value, specifically in calorie count. It also provides tailored recipes to help users meet their daily nutritional requirements, offering a practical solution for users to achieve their dietary goals. This research connects computer vision and nutrition, providing insights for developing practical solutions in this domain. © 2024 IEEE.

关键词： Convolutional neural networks

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Mental illness detection using sentiment analysis in social media 9th

Mental illness detection using sentiment analysis in social ...

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9th International Conference on computer science and Computational Intelligence, ICCSCI 2024

作者： Odja, Kasimirus Derryl Widiarta, Jasson Purwanto, Eko Setyo Ario, Muhamad Keenan Computer Science Department School of Computer Science Bina Nusantara University Jakarta11480 Indonesia Mobile Application & Technology Program Computer Science Department School of Computer Science Bina Nusantara University Jakarta11480 Indonesia

This research tries to detect mental illness using sentiment analysis on Reddit data, as well as comparing the performance of the k-Nearest Neighbors (k-NN), Random Forest, and Neural Network models. Using text post data from the pre-pandemic and post-pandemic periods, we concluded that the Random Forest model had the highest overall performance with an F1 Score, accuracy, recall and precision of 80.6%, making it quite effective in detecting depression. Even though the Neural Network model shows slightly lower accuracy, namely 79%, in fact this model has the lowest error rate, namely 0.06496. The k-NN model showed the lowest accuracy and higher error rate. These findings highlight the potential of sentiment analysis and machine learning in identifying mental health issues on social media and suggest that better models can improve early detection and intervention efforts. © 2024 The Authors.

关键词： Neural network models

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Through the Lens: Unveiling the Power and Promise of Google's Visual Search technology 9

Through the Lens: Unveiling the Power and Promise of Google'...

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9th International Conference on Information Management and technology, ICIMTech 2024

作者： Salim, Devano Hofker Susanto, Jose Juan Manalu, Sonya R. Shiddiqi, Hafizh Ash School of Computer Science Bina Nusantara University Computer Science Department Jakarta11480 Indonesia School of Computer Science Bina Nusantara University Mobile Application & Technology Program Computer Science Department Jakarta11480 Indonesia

ISBN: (纸本)9798350390025

The digital landscape is undergoing profound changes, with visual search technology like Google Lens emerging as a pivotal force shaping our interaction with information. This research paper delves into Google Lens, a cutting-edge tool redefining how we engage with visual data. We comprehensively examine its functionalities, underlying principles, and real-world applications, particularly in education and library services. Through meticulous analysis, we evaluate its efficacy in addressing practical challenges and assess its accuracy, efficiency, and breadth of capabilities compared to other visual search technologies. By exploring existing research and the intricacies of Google Lens, this paper aims to provide a holistic understanding of this technology and its potential impact on how we access and interact with information in the real world. Finally, we explore the future of technology by contemplating the prospective roles of Google Lens across various industries and its potential for shaping the future of information access. © 2024 IEEE.

关键词： future of technology google lens visual search technology

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