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"I Am There But...": Remote Students’ Experiences of Inclusion through Telepresence Robots

"I Am There But...": Remote Students’ Experiences of Inclus...

引用

2025 CHI Conference on Human Factors in Computing Systems, CHI EA 2025

作者： Elmimouni, Houda Sabanovic, Selma Department of Computer Science University of Manitoba WinnipegMB Canada University of Siegen Siegen Germany Luddy School of Informatics Computing and Engineering Indiana University BloomingtonIN United States

ISBN: (纸本)9798400713958

The use of telepresence robots in educational settings offers a promising solution for students who are unable to attend classes in person due to illness, disability, or other barriers. However, the extent to which these technologies facilitate the perceived inclusion of remote students remains underexplored. This study investigates the experiences of remote students using telepresence robots to attend university classes, focusing on factors that mediate their sense of inclusion. Through an inductive analysis of interviews and observations from 22 remote students, we identify technological and socio-pedagogical factors that influence inclusion. Our findings reveal that while telepresence robots enhance physical presence and agency compared to traditional video conferencing tools, challenges such as technological limitations, social norms, and pedagogical practices can hinder full integration. We offer recommendations for educators and institutions to better support remote students and suggest design improvements for telepresence technologies to foster inclusivity in classroom settings. © 2025 Copyright held by the owner/author(s).

关键词： Teaching

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Overview of Image Detection Algorithms: Performance Analysis and Technology Trends

Overview of Image Detection Algorithms: Performance Analysis...

引用

International Conference on informatics and Computing (ICIC)

作者： Nurul Hidayat R. Rizal Isnanto Department of Informatics Jenderal Soedirman University Purwokerto Indonesia Department of Computer Engineering Diponegoro University Semarang Indonesia

ISBN: (数字)9798331517601

ISBN: (纸本)9798331517618

Image detection plays a vital role in digital image processing and artificial intelligence, with applications ranging from security surveillance to autonomous vehicles and medical image analysis. This study employs a qualitative approach to review the performance of image detection algorithms, focusing on deep learning methods such as YOLO, SSD, and CNN. Through computational experiments using quantitative data, this research provides performance comparisons based on accuracy, precision, recall, and computational efficiency. The results highlight YOLO’s superior performance in terms of both accuracy ($\mathbf{9 2} .5 \%$) and inference speed (75.2 fps), making it suitable for real-time applications. This study contributes by addressing the gap in balancing computational efficiency and adaptability for real-world applications.

关键词： YOLO Deep learning Machine learning algorithms Accuracy Computational modeling Real-time systems Inference algorithms Computational efficiency Detection algorithms Edge computing

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Assessing the effect of human factors in healthcare cyber security practice: An empirical study 25

Assessing the effect of human factors in healthcare cyber se...

引用

25th Pan-Hellenic Conference on informatics, PCI 2021

作者： Karvounidis, Theodoros Kallergis, Dimitrios Garofalaki, Zacharenia Douligeris, Christos Department of Informatics University of Piraeus Greece Department of Informatics and Computer Engineering University of West Attika Greece

ISBN: (纸本)9781450395557

Healthcare organizations are bound to face a multitude of challenges;quite special demands are directed to the data processing. This paper proposes a methodology for adopting security management principles in health sector environments, based on the guidelines of the ISO/IEC 27005:2018 standard. The purpose of this methodology is to identify and to assess the risks to which the information environment and the resources that make it up are exposed. A process is defined that identifies and evaluates the risks and the threats within a healthcare information system, with: (i) the identification, (ii) the documentation, (iii) the categorization, and finally (iv) the prioritization of risks arising from the handling, management, and storage of healthcare information. Based on the aforementioned targets, a risk management strategy is developed against the identified risks, while implementing the appropriate controls. The work is carried out in three steps: (i) Identification and Valuation of the Assets that are the subject of a Health Care Information System, (ii) Risk Analysis, and (iii) Risk Management. The outcome of this study can be used to determine the appropriate security controls (administrative, physical, technical, and operational) so as to minimize the risks together with the implementation of the appropriate information security controls. © 2021 ACM.

关键词： Risk analysis

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Area-Delay Efficient Security Scheme for Smart Hospital Systems

Area-Delay Efficient Security Scheme for Smart Hospital Syst...

引用

Cyber Security and Resilience (CSR), IEEE International Conference on

作者： Kyriaki Tsantikidou Dimitrios Boufeas Nicolas Sklavos Computer Engineering and Informatics Department SCYTALE Group University of Patras Hellas Electrical and Computer Engineering Department University of Patras Hellas

In recent years, traditional Hospital facilities are adopting new technologies. Smart Hospitals mostly utilize the Internet of Things (loT) technology due to its vast capabilities in connectivity. This loT network requires specific protocols for proper functionality. Message Queuing Telemetry Transport (MQTT) protocol is suitable for managing the communication and routing procedures of the resource constrained loT environment. Nevertheless, both MQTT and loT have various vulnerabilities and threats that must first be addressed. In this paper, a lightweight key management procedure is analyzed, an end-to-end payload encryption method is followed, and a processor with different cryptographic mechanisms is implemented. This combination of processes best complements the E-Health-based Hospital architecture, requiring minimum resources and complete security. The proposed crypto processor efficiently implements three different cryptographic primitives in a RISC- V architecture, providing flexibility. It achieves the best area-delay compared to other hardware-based security schemes, with 61.3% resource reduction and minimum added computation overhead. This is accomplished due to proper formatting of specific instructions and a function, operation and register sharing methodology.

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Integrating Multimodal Contrastive Learning and Cross-Modal Attention for Alzheimer's Disease Prediction in Brain Imaging Genetics

Integrating Multimodal Contrastive Learning and Cross-Modal ...

引用

2023 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2023

作者： Zhou, Rong Zhou, Houliang Shen, Li Chen, Brian Y. Zhang, Yu He, Lifang Lehigh University Department of Computer Science and Engineering BethlehemPA United States University of Pennsylvania Department of Biostatistics Epidemiology and Informatics PhiladelphiaPA United States Lehigh University Department of Bioengineering BethlehemPA United States

ISBN: (纸本)9798350337488

High annotation costs serve as a significant hurdle in deploying modern deep learning architectures for clinically relevant medical applications, especially when dealing with the inherent heterogeneity of multimodal data, proving the critical need for innovative algorithms that can effectively utilize unlabeled data. In this paper, we propose a model named MCLCA, which integrates multimodal contrastive learning and cross-modal attention to diagnose Alzheimer's Disease (AD) and identify biomarkers using both labeled and unlabeled multimodal brain imaging genetics data. Through multimodal contrastive learning, MCLCA can effectively learn representations even in the absence of sufficient labels. By utilizing cross-modal attention blocks, the model captures deep connections between different modalities, providing a more comprehensive view of diagnosis. Our proposed MCLCA model is evaluated using the ADNI database with three imaging modalities (VBM-MRI, FDG-PET, and AV45-PET) and genetic SNP data. The results demonstrate that MCLCA can identify important biomarkers with better prediction accuracy compared to the existing methods. The source code is available at https://***/MCLCA. © 2023 IEEE.

关键词： Alzheimer's disease Brain imaging genetics contrastive learning cross-modal attention

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Full Duplex Holographic MIMO for Near-Field Integrated Sensing and Communications 31

Full Duplex Holographic MIMO for Near-Field Integrated Sensi...

引用

31st European Signal Processing Conference, EUSIPCO 2023

作者： Gavras, Ioannis Islam, Md Atiqul Smida, Besma Alexandropoulos, George C. Department of Informatics and Telecommunications National and Kapodistrian University of Athens Greece Qualcomm Technologies Inc. Santa ClaraCA United States Department of Electrical and Computer Engineering University of Illinois Chicago United States

ISBN: (纸本)9789464593600

This paper presents an in-band Full Duplex (FD) integrated sensing and communications system comprising a holographic Multiple-Input Multiple-Output (MIMO) base station, which is capable to simultaneously communicate with multiple users in the downlink direction, while sensing targets being randomly distributed within its coverage area. Considering near-field wireless operation at THz frequencies, the FD node adopts dynamic metasurface antenna panels for both transmission and reception, which consist of massive numbers of sub-wavelength-spaced metamaterials, enabling reduced cost and power consumption analog precoding and combining. We devise an optimization framework for the FD node's reconfigurable parameters with the dual objective of maximizing the targets' parameters estimation accuracy and the downlink communication performance. Our simulation results verify the integrated sensing and communications capability of the proposed FD holographic MIMO system, showcasing the interplays among its various design parameters. © 2023 European Signal Processing Conference, EUSIPCO. All rights reserved.

关键词： Antennas

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Global Graph Clustering and Local Graph Exploration for Community Detection in Twitter 7

Global Graph Clustering and Local Graph Exploration for Comm...

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7th South-East Europe Design Automation, computer engineering, computer Networks and Social Media Conference, SEEDA-CECNSM 2022

作者： Karras, Christos Karras, Aristeidis Giannoukou, Ioanna Giotopoulos, Konstantinos C. Tsolis, Dimitrios Sioutas, Spyros University of Patras Decentralized Systems Computing Group Computer Engineering and Informatics Department Greece University of Patras Department of Management Science and Technology Greece

ISBN: (数字)9798350398588

ISBN: (纸本)9798350398588

In this paper, the concepts and techniques for global graph clustering are examined, or the process of locating related clusters of vertices within a graph. We introduce the construction of a graph clustering technique based on an eigenvector embedding and a local graph clustering method based on stochastic exploration of the graph. Then, the developed implementations of both methods are presented and assessed in terms of performance. In addition, the difficulties associated with assessing clusterings and benchmarking cluster algorithms are explored where PageRank and EigEmbed algorithms are utilized. The experiments show that the EigEmbed outperformed PageRank across all experiments as it detected more communities with the same number of clusters. Ultimately, we apply both algorithms to a real-world graph representing Twitter network and the followers and tweets therein. © 2022 IEEE.

关键词： Random processes

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Implementing a Digital Repository for the Cultural and Natural Heritage of the Island of Zakynthos

Implementing a Digital Repository for the Cultural and Natur...

引用

International Workshop on Semantic Media Adaptation and Personalization (SMAP)

作者： Stergios Palamas Yorghos Voutos Katerina Kabassi Phivos Mylonas Department of Informatics Ionian University Corfu Greece Department of Informatics and Computer Engineering University of West Attica Athens Greece Department of Environment Ionian University Zakynthos Greece

ISBN: (数字)9798331504502

ISBN: (纸本)9798331504519

The present study discusses the development of a digital repository (ANTETI) for the preservation and dissemination of the Cultural and Natural Heritage of Zakynthos Island. The platform is based on a popular Content Management System (CMS) to provide the core functionality, extended with the use of the CMS’s API, to provide additional personalisation functionality for the end-users. Additionally, the system features a web application, oriented mainly on users visiting the island of Zakynthos and developed exclusively with open web technologies and JavaScript frameworks. The web application is an alternative, map-centered, mobile optimised front-end, for the platform’s content featured in the CMS. The system also provides a RESTful API, allowing integration with 3 rd party systems and web applications, thereby expanding the repository's reach and capabilities. Content delivery is personalized based on user profiles, location, and preferences, enhancing engagement and usability. By integrating these features, the repository effectively preserves and makes accessible the unique cultural and natural heritage of Zakynthos to both local and global audiences.

关键词： Content management Restful API Cultural differences Usability

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Designing a Digital Repository for the Cultural and Natural Heritage of the Island of Zakynthos

Designing a Digital Repository for the Cultural and Natural ...

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South Eastern European Design Automation, computer engineering, computer Networks and Social Media Conference (SEEDA-CECNSM)

作者： Stergios Palamas Katerina Kabassi Phivos Mylonas Department of Informatics Ionian University Corfu Greece Department of Environment Ionian University Zakynthos Greece Department of Informatics and Computer Engineering University of West Attica Athens Greece

ISBN: (数字)9798331504489

ISBN: (纸本)9798331504496

The present study discusses the design of a digital archive for the preservation and dissemination of the Cultural and Natural Heritage of Zakynthos Island. The proposed architecture suggests a Content Management System (CMS) to provide the core functionality, while a web application, interacting with the CMS through a RESTFul API, will provide an alternative front-end targeting mainly on-site end-users using mobile devices. Authors and contributors can submit multimedia content to the repository, which is reviewed and approved by system administrators before publishing, ensuring this way the information quality and *** system will also provide a RESTful API, allowing integration with 3 rd party systems and web applications, thereby expanding the repository's reach and capabilities. Content delivery is personalized based on user profiles, location, and preferences, enhancing engagement and usability. By integrating these features, the repository effectively preserves and makes accessible the unique cultural and natural heritage of Zakynthos to both local and global audiences.

关键词： Social networking (online) Restful API computer architecture Service-oriented architecture Cultural differences Global communication Biodiversity Usability Sustainable development Standards

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In Image Classification of Skin Cancer Sufferers: Modification of K-Nearest Neighbor with Histogram of Oriented Gradients Approach 1

In Image Classification of Skin Cancer Sufferers: Modificati...

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1st International Conference on Information System and Information Technology, ICISIT 2022

作者： Lubis, Arif Ridho Prayudani, Santi Fatmi, Yulia Lase, Yuyun Yusnida Al-Khowarizmi Politeknik Negeri Medan Department of Computer Engineering and Informatics Medan Indonesia Universitas Muhammadiyah Sumatera Utara Department of Information Technology Medan Indonesia

ISBN: (数字)9781665402002

ISBN: (纸本)9781665402002

Classification in data mining is one technique in recognizing all types of data. Where data can be in the form of text, numeric, images and others. One of the superior classification techniques is the KNN algorithm. The KNN algorithm is a distance search using Euclidean distance. image data classification using the HOG process is needed to modify the KNN. The purpose of this paper is to classify patients with classifying skin cancer patients using the KNN method where the Histogram of Oriented Gradients (HOG) process is used to assist in extracting data for skin cancer patients, which consists of benign and malignant cancers. However, in this paper, the images included in this article are pictures of skin cancer sufferers, which consist of malignant and benign. The data obtained were 660 datasets of which 630 were used as training data and 30 were used as test data. The training and testing went well, this was shown by getting a MAPE of O.06705477%. So that the classification process can be accepted because it shows a small validity. © 2022 IEEE.

关键词： Data mining

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