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Prediabetes detection in unconstrained conditions using wearable sensors

Clinical Nutrition Open Science 2024年 58卷 163-174页

作者： Tatli, Dimitra Papapanagiotou, Vasileios Liakos, Aris Tsapas, Apostolos Delopoulos, Anastasios Multimedia Understanding Group Dpt. of Electrical and Computer Engineering Faculty of Engineering AUTH Greece Embedded Systems Laboratory Institute of Electrical and Micro Engineering EPFL Lausanne Switzerland IMPACT Research Group Dpt. of Medicine Karolinska Institutet Huddinge Sweden Diabetes Centre Second Medical Department at Ippokratio General Hospital Thessaloniki Greece

Prediabetes is a common health condition that often goes undetected until it progresses to type 2 diabetes. Early identification of prediabetes is essential for timely intervention and prevention of complications. This research explores the feasibility of using wearable continuous glucose monitoring along with smartwatches with embedded inertial sensors to collect glucose measurements and acceleration signals respectively, for the early detection of prediabetes. We propose a methodology based on signal processing and machine learning techniques. Two feature sets are extracted from the collected signals, based both on a dynamic modeling of the human glucose-homeostasis system and on the Glucose curve, inspired by three major glucose related blood tests. Features are aggregated per individual using bootstrap. Support Vector Machines are used to classify normoglycemic vs. prediabetic individuals. We collected data from 22 participants for evaluation. The results are highly encouraging, demonstrating high sensitivity and precision. This work is a proof of concept, highlighting the potential of wearable devices in prediabetes assessment. Future directions involve expanding the study to a larger, more diverse population and exploring the integration of CGM and smartwatch functionalities into a unified device. Automated eating detecting algorithms can also be used. © 2024 The Authors

关键词： Continuous glucose monitors Machine learning Prediabetes Signal processing

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Digitization and Secure Process of Forensic Data Management Using Blockchain

Digitization and Secure Process of Forensic Data Management ...

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2023 International Conference on System, Computation, Automation and Networking, ICSCAN 2023

作者： Indhumathi, R. Mathivanan, P. Mahalakshmi, K. Subha, K. Krishna, Nanda S. Manakula Vinayagar Institute of Technology Department of Computer Science and Engineering Puducherry India Kit - Kalaignarkarunanidhi Institute of Technology Department of Computer Science and Business Systems Coimbatore India Surya Group of Institutions Department of Computer Science and Engineering Villuppuram India

ISBN: (纸本)9798350315127

Cyber threats and data manipulation are the main concerns in this technological society. The investigator finds it challenging to submit evidence to the court because of the information breach as continuity documentation of records is very critical for safeguarding against criminal events. Blockchain-based digital forensic data management systems have been developed to deal with this issue of Privacy preservation for evidence items. Blockchain technology provides authentication, immutability, traceability, resilience, and distributed trust for forensic data. In order to ensure security and ease of use, the system utilizes onion architecture. Data can be stored and analysed whenever required. They provide trust between the examiners and the system. The system is a multi-platform system that provides effective usage where it can be accessed and used from anywhere. The honest information is make sure to follow the crime investigator of the steps. if we use the propose system of block chain, it is can't be altered the evidence during the submission of court. The storing data of each block is verify and added to the blockchian. The creation of safe database was implemented by a decentralised network with bitcoin and networks of cryptocurrency. In proposed system, the blockchain technology helps in can't able to access and altered the data during the investigation periods. This system is used to implements the easily accessed and used in anywhere. © 2023 IEEE.

关键词： Blockchain

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Sensitivity of DC Network Representation for GIC Analysis

Sensitivity of DC Network Representation for GIC Analysis

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2025 IEEE Texas Power and Energy Conference, TPEC 2025

作者： Mishra, Aniruddh Barnes, Arthur K. Tabarez, Jose E. Mate, Adam University of Texas at Austin Department of Electrical and Computer Engineering AustinTX United States Information Systems and Modeling Group Los Alamos National Laboratory Los AlamosNM United States

ISBN: (纸本)9798331541125

Geomagnetic disturbances are a threat to the reliability and security of our national critical energy infrastructures. These events specifically result in geomagnetically induced currents, which can cause damage to transformers due to magnetic saturation. In order to mitigate these effects, blocker devices must be placed in optimal locations. Finding this placement requires a dc representation of the ac transmission lines, which this paper discusses. Different decisions in this process, including the method of representing the blocking devices, result in significant variations to the power loss calculations. To analyze these effects, we conclude the paper by comparing the losses on a sample network with different modeling implementations. © 2025 IEEE.

关键词： Transformer windings

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Scalable Data Profiling for Quality Analytics Extraction 13th

Scalable Data Profiling for Quality Analytics Extraction

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13th Mining Humanistic Data Workshop, MHDW 2024, 9th Workshop on 5G-Putting Intelligence to the Network Edge, 5G-PINE 2024 and 1st Workshop on AI in Applications for Achieving the Green Deal Targets, AI4GD 2024 held as parallel events of the IFIP WG 12.5 International Workshops on Artificial Intelligence Applications and Innovations, AIAI 2024

作者： Nikolakopoulos, Anastasios Chondrogiannis, Efthymios Karanastasis, Efstathios Osa, María José López Aroca, Jordi Arjona Kefalogiannis, Michalis Apostolopoulou, Vasiliki Deligeorgi, Efstathia Siopidis, Vasileios Varvarigou, Theodora School of Electrical and Computer Engineering Institute of Communication and Computer Systems National Technical University of Athens Athens Greece Bilbao Spain Valencia Spain OTE Group of Companies Athens Greece Centre for Research and Technology Hellas Marousi Greece

ISBN: (纸本)9783031632266

In today’s modern society, data play an integral role in the development global industry, since they have become a valuable asset for companies, institutions, governments, and others. At the same time, data generated daily, at a global scale, require significant resources to pre-process, filter and store. When it comes to acquiring such stored data, it is essential to understand which dataset fits to the needs of the user beforehand. One particularly important factor is the quality of a dataset, which could be determined based on a series of quality related attributes generated by it. Such attributes constitute "Profiling", the process of obtaining information from a data sample, related to the complete dataset’s quality. However, in the era of Big Data, the ability to apply profiling techniques in complete large datasets should also be considered, in order to obtain complete quality insights. This paper attempts to provide a solution for this consideration by presenting "DaQuE", a scalable framework for efficient profiling and quality analytics extraction in complete datasets of all volumes. © IFIP International Federation for Information Processing 2024.

关键词： Extraction

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"Hi, My Name is Robin" – Remotely Co-designing an Embodied Conversational Agent for Empathy with Older Adults 9th

"Hi, My Name is Robin" – Remotely Co-designing an Embodied ...

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9th International Conference on Human Aspects of IT for the Aged Population, ITAP 2023, held as part of the 25th International Conference on Human-computer Interaction, HCII 2023

作者： Tunc, Sefora Nijboer, Femke Tinga, Angelica M. Tabak, Monique Biomedical Signals and Systems Group Faculty of Electrical Engineering Mathematics and Computer Science University of Twente Enschede Netherlands Roessingh Research and Development Enschede Netherlands

ISBN: (纸本)9783031348655

Embodied conversational agents (ECAs) have the potential to facilitate empathic relationships between older adults and eHealth coaches, but little research has been conducted on how to effectively include appearance and personality in the design of ECAs such that older adults can empathize with the agent. In this study, we aimed first to develop design requirements for ECAs that induce empathy in older adults. Second, we developed and reflected upon a remote (online), iterative co-design methodology which can be used as an alternative when traditional physical methods cannot take place (e.g. during COVID-19). Over the course of three months, five older adults (mean age 68 years) 1) received a paper booklet, 2) were invited to an Q&A session, 3) after which they were asked develop their own ECAs at home using the booklet, 4) and came back to discuss their designs online in a group setting to determine design requirements, 5) which were used to develop an interactive ECA, 6) that was individually evaluated in an online meeting. The final ECA, called Robin, was positively perceived in terms of appearance, but the participants expected the conversation with Robin to be more flexible and deeper. Overall, the current study demonstrated the feasibility of remote co-design activities for this population and presents recommendations for researchers and practitioners interested in or in need for a remote approach. Moreover, the current findings are translated in lessons learnt to inform design and development of future ECAs for older adults. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Design

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Feature Correlation Aggregation: on the Path to Better Graph Neural Networks

Feature Correlation Aggregation: on the Path to Better Graph...

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2023 International Conference on Digital Image Computing: Techniques and Applications, DICTA 2023

作者： Zhou, Jieming Zhang, Tong Fang, Pengfei Petersson, Lars Harandi, Mehrtash Australian National University College of Engineering and Computer Science Canberra Australia Image and Visual Representation Laboratory Epfl Lausanne Switzerland Imaging and Computer Vision Group Csiro Canberra Australia Monash University Department of Electrical and Computer Systems Engineering Melbourne Australia

ISBN: (纸本)9798350382204

Prior to the introduction of Graph Neural Networks (GNNs), modelling and analyzing irregular data, particularly graphs, was thought to be the Achilles' heel of deep learning. The core concept of GNNs is to find a representation by recursively aggregating the representations of a central node and those of its neighbor, and many GNNs' designs have demonstrated its success. However, most only focus on using the first-order information between a node and its neighbors. In this paper, we introduce a central node permutation variant function through a frustratingly simple and innocent-looking modification to the core operation of a GNN, namely the Feature cOrrelation aGgregation (FOG) module, which learns the second-order information from feature correlation between a node and its neighbors in the pipeline. By adding FOG into existing variants of GNNs, we empirically verify this second-order information complements the features generated by original GNNs across a broad set of benchmarks. A tangible boost in the model's performance is observed where the model surpasses previous state-of-the-art results by a significant margin while employing fewer parameters. e.g., 26.202% improvement on a real-world molecular dataset using graph convolutional networks. © 2023 IEEE.

关键词： Graph neural networks

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Towards new realities: Implications of personalized online layers in our daily lives

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i-com 2024年第2期23卷 221-229页

作者： Herder, Eelco Stojko, Laura Strecker, Jannis Neumayr, Thomas Yigitbas, Enes Augstein, Mirjam Department of Information and Computing Sciences Utrecht University Utrecht Netherlands Department of Computer Science University of the Bundeswehr Munich Neubiberg Germany Institute of Computer Science University of St. Gallen St. Gallen Switzerland Research Group Personalized Environments and Collaborative Systems University of Applied Sciences Upper Austria Hagenberg Austria Faculty of Electrical Engineering Computer Science and Mathematics Paderborn University Paderborn Germany

We are currently in a period of upheaval, as many new technologies are emerging that open up new possibilities to shape our everyday lives. Particularly, within the field of Personalized Human-computer Interaction we observe high potential, but also challenges. In this article, we explore how an increasing amount of online services and tools not only further facilitates our lives, but also shapes our lives and how we perceive our environments. For this purpose, we adopt the metaphor of personalized 'online layers' and show how these layers are and will be interwoven with the lives that we live in the 'human layer' of the real world. © 2024 the author(s), published by De Gruyter, Berlin/Boston.

关键词： Human computer interaction

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Go Together: Bridging the Gap between Learners and Teachers 7

Go Together: Bridging the Gap between Learners and Teachers

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7th International Multi-Topic ICT Conference: IMTIC 2023

作者： Irfan, Asim Nawaz, Atif Turab, Muhammad Azeem, Muhmmad Adnan, Mashal Mehmood, Ahsan Ahmed, Sarfaraz Ashraf, Adnan Mehran University of Engineering and Technology Computer Systems Engineering Pakistan Design Internee UI/UX UnifiedCrest R&d Group Ethiopia Muet Faculty Cs Jamshoro Pakistan

ISBN: (纸本)9798350338461

After the pandemic, humanity has been facing different types of challenges. Social relationships, societal values, and academic and professional behavior have been hit the most. People are shifting their routines to social media, and gadgets and getting addicted to their isolation [5]. This sudden change in their lives has caused an unusual social breakdown and endangered their mental health. In mid of 2021, Pakistan's 1st Human Library was established under HelpingMind® to overcome these effects [9]. Despite online sessions and webinars, HelpingMind® needs technology to reach the masses. In this work, we customized the UI/UX of a Go-Together Mobile Application (GTMA) to meet the requirements of the client organization. A very interesting concept of the book (expert listener/ psychologist) and the reader is introduced in GTMA. It offers separate dashboards, separate reviews or rating systems, booking, and venue information to engage the human-reader with his/ her favorite human book. The loyalty program enables the members to avail discounts through a mobile application and its membership is global where both the human-reader and human-books can register under the platform. The minimum viable product has been approved by our client organization. © 2023 IEEE.

关键词： Application programs

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Discovering Structural Errors From Business Process Event Logs (Extended Abstract) 39

Discovering Structural Errors From Business Process Event Lo...

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39th IEEE International Conference on Data engineering, ICDE 2023

作者： Song, Wei Chang, Zhen Jacobsen, Hans-Arno Zhang, Pengcheng Nanjing University of Science and Technology School of Computer Science and Engineering Nanjing China University of Toronto Middleware Systems Research Group Toronto Canada Hohai University College of Computer and Information Nanjing China

ISBN: (纸本)9798350322279

While process mining has gained much attention in the past decade, surprisingly, discovering structural errors (i.e., deadlock and lack of synchronization) from event logs has seldom been studied. Since event logs may involve erroneous event occurrences caused by unsynchronized activities, discovering deadlocks and lack of synchronization errors may influence each other. To this end, we first extract from the original event log two independent event logs which are employed to discover deadlocks and lack of synchronization errors, respectively. We then discard the erroneous event occurrences in the two event logs, from which our event relation based mining rules can discover the corresponding structural errors. We have implemented our approach, and the experimental results corroborate that our approach can effectively and efficiently discover process structural errors from the event logs involving sufficient event sequences. © 2023 IEEE.

关键词： Synchronization

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Proactive Frequency Stability Scheme via Bayesian Filters and Synchrophasors 4

Proactive Frequency Stability Scheme via Bayesian Filters an...

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4th Annual IEEE Kansas Power and Energy Conference, KPEC 2023

作者： Paramo, Gian Bretas, Arturo University of Florida Electrical and Computer Engineering GainesvilleFL United States Pacifc Northwest National Laboratory Distributed Systems Group RichlandWA United States

ISBN: (纸本)9798350335408

Underfrequency load shedding (UFLS) schemes are traditionally implemented in two ways. One approach is based on manual load shedding implemented by system operators. The second approach is automatic load shedding, implemented through underfrequency relays. The main limitation of traditional load shedding schemes is that they are reactive and leave little room for optimized corrective actions. This work presents a proactive and automatic underfrequency load shedding framework for power systems. Measurements are captured via phasor measurement units (PMUs) at relatively low rates of 30 fps. These measurements are then processed by a particle filter which predicts the future state of frequency. Based on these predictions excess loading is determined and shed. Comparative case studies are performed via simulations. Easy-to-implement models, without hard-to-derive parameters, highlight the potential for real-life implementation. © 2023 IEEE.

关键词： Phasor measurement units

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