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IEEE Southeastcon

作者： Ali Abdelmoniem Frank Feng Eric Huang P. L. Carro M. Angeles Losada Alicia Lopez J. Mateo A. Ortega D. Ribas E. Lleida N. Antoniades D. Richards Xin J. Jiang Yi Wang Department of Engineering and Environmental Science College of Staten Island CUNY Staten Island NY Communications Networks and Information Technologies (CeNIT) Aragón Institute of Engineering Research (i3A) Universidad de Zaragoza Zaragoza Spain Photonic Technologies Group (GTF) Aragón Institute of Engineering Research (i3A) Universidad de Zaragoza Zaragoza Spain Voice Input Voice Output Laboratory (ViVoLab) Aragón Institute of Engineering Research (i3A) Universidad de Zaragoza Zaragoza Spain Department of Electrical and Computer Engineering Manhattan College Bronx NY

This study investigates the impact of under-filled and over-filled launching configurations on the transmission properties of Plastic Optical Fiber (POF). Experimental analyses on step and graded index fibers reveal differences in spatial and frequency properties under these launching conditions. Results show that the under-filled configuration leads to narrower radial profiles and Encircled Angular Flux (EAF) compared to the over-filled configuration. Additionally, under-filled launching produces better frequency response and larger bandwidth, particularly notable in shorter fibers. Results show that the under-filled launching significantly improves transmission properties, offering potential improvements in POF applications.

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Privacy engineering in the Wild: Understanding the Practitioners’ Mindset, Organisational Aspects, and Current Practices

arXiv

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arXiv 2022年

作者： Iwaya, Leonardo Horn Ali Babar, Muhammad Rashid, Awais Centre for Research on Engineering Software Technologies The University of Adelaide AdelaideSA5005 Australia Australia research group Department of Mathematics and Computer Science Karlstad University Sweden Bristol Cyber Security Group Department of Computer Science University of Bristol United Kingdom REPHRAIN: National Research Centre on Privacy Harm Reduction and Adversarial Influence Online United Kingdom

Privacy engineering, as an emerging field of research and practice, comprises the technical capabilities and management processes needed to implement, deploy, and operate privacy features and controls in working systems. For that, software practitioners and other stakeholders in software companies need to work cooperatively toward building privacy-preserving businesses and engineering solutions. Significant research has been done to understand the software practitioners’ perceptions of information privacy, but more emphasis should be given to the uptake of concrete privacy engineering components. This research delves into the software practitioners’ perspectives and mindset, organisational aspects, and current practices on privacy and its engineering processes. A total of 30 practitioners from nine countries and backgrounds were interviewed, sharing their experiences and voicing their opinions on a broad range of privacy topics. The thematic analysis methodology was adopted to code the interview data qualitatively and construct a rich and nuanced thematic framework. As a result, we identified three critical interconnected themes that compose our thematic framework for privacy engineering "in the wild": (1) personal privacy mindset and stance, categorised into practitioners’ privacy knowledge, attitudes and behaviours;(2) organisational privacy aspects, such as decision-power and positive and negative examples of privacy climate;and, (3) privacy engineering practices, such as procedures and controls concretely used in the industry. Among the main findings, this study provides many insights about the state-of-the-practice of privacy engineering, pointing to a positive influence of privacy laws (e.g., EU General Data Protection Regulation) on practitioners’ behaviours and organisations’ cultures. Aspects such as organisational privacy culture and climate were also confirmed to have a powerful influence on the practitioners’ privacy behaviours. A conducive environment f

关键词： Data privacy

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Full-Coverage Mapping of Daily High-Resolution XCO2 across China from 2015 to 2020 by Deep Learning-Based Spatio-Temporal Fusion

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IEEE Transactions on Geoscience and Remote Sensing 2025年

作者： Li, Yi Yan, Jining Zhong, Liheng Bao, De Sun, Leigang Li, Guangyu China University of Geosciences School of Computer Science Wuhan430074 China Ministry of Education Engineering Research Center of Natural Resource Information Management and Digital Twin Engineering Software Wuhan430074 China Ant Group World Financial Center Beijing100020 China Hebei Academy of Sciences Institute of Geographical Sciences Shijiazhuang050011 China Hebei Technology Innovation Center for Geographic Information Application Shijiazhuang050011 China Environmental Development Center of the Ministry of Ecology and Environment China

Carbon neutrality has become a global priority, and high spatio-temporal resolution data on the column-average dry-air mole fraction carbon dioxide (XCO2) is essential for tracking progress and guiding policy adjustments. However, satellite-derived XCO2 exhibits significant temporal and spatial gaps due to influences such as orbital dynamics and cloud cover. Additionally, the low spatial resolution of CarbonTracker (CT) is insufficient to meet the current demands for fine-scale monitoring. Current XCO2 assessment methods often rely solely on single-pixel data, overlooking the spatio-temporal correlations. In this article, we introduce a deep learning-based spatio-temporal model (DSTM) that extracts features from multiple data sources related to atmospheric transport, carbon emissions, and carbon sinks, enabling fine-scale XCO2 assessments. Additionally, XCO2 data from the Orbiting Carbon Observatory-2 (OCO-2) and CT were fused at a 0.1° spatial resolution to generate training labels with broader coverage and more samples, serving as fitting labels. Our approach produced daily, full-coverage 0.1° resolution XCO2 maps for China from 2015 to 2020, and analyzed changes in XCO2 growth trends over this period. Numerical results show that our model outperforms traditional deep learning methods. Model validation using data from four ground-based observation sites of the Total Carbon Column Observing Network (TCCON) achieved an average R2 of 0.86 and an RMSE of 2.67 ppm. The extraction and fusion of spatio-temporal features from multiple data sources provide a novel approach for reconstructing missing XCO2 data. © 1980-2012 IEEE.

关键词： Atmospheric movements

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On the Privacy of Mental Health Apps: An Empirical Investigation and its Implications for Apps Development

arXiv

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arXiv 2022年

作者： Iwaya, Leonardo Horn Ali Babar, M. Rashid, Awais Wijayarathna, Chamila Centre for Research on Engineering Software Technologies The University of Adelaide AdelaideSA5005 Australia Australia Department of Mathematics and Computer Science Karlstad University Karlstad Sweden Bristol Cyber Security Group Department of Computer Science University of Bristol United Kingdom

An increasing number of mental health services are offered through mobile systems, a paradigm called mHealth. Although there is an unprecedented growth in the adoption of mHealth systems, partly due to the COVID-19 pandemic, concerns about data privacy risks due to security breaches are also increasing. Whilst some studies have analyzed mHealth apps from different angles, including security, there is relatively little evidence for data privacy issues that may exist in mHealth apps used for mental health services, whose recipients can be particularly vulnerable. This paper reports an empirical study aimed at systematically identifying and understanding data privacy incorporated in mental health apps. We analyzed 27 top-ranked mental health apps from Google Play Store. Our methodology enabled us to perform an in-depth privacy analysis of the apps, covering static and dynamic analysis, data sharing behaviour, server-side tests, privacy impact assessment requests, and privacy policy evaluation. Furthermore, we mapped the findings to the LINDDUN threat taxonomy, describing how threats manifest on the studied apps. The findings reveal important data privacy issues such as unnecessary permissions, insecure cryptography implementations, and leaks of personal data and credentials in logs and web requests. There is also a high risk of user profiling as the apps' development do not provide foolproof mechanisms against linkability, detectability and identifiability. Data sharing among third parties and advertisers in the current apps' ecosystem aggravates this situation. Based on the empirical findings of this study, we provide recommendations to be considered by different stakeholders of mHealth apps in general and apps developers in particular. We conclude that while developers ought to be more knowledgeable in considering and addressing privacy issues, users and health professionals can also play a role by demanding privacy-friendly apps. Copyright © 2022, The Authors. All r

关键词： Data privacy

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SMedBERT: A knowledge-enhanced pre-trained language model with structured semantics for medical text mining 59

SMedBERT: A knowledge-enhanced pre-trained language model wi...

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Joint Conference of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing, ACL-IJCNLP 2021

作者： Zhang, Taolin Cai, Zerui Wang, Chengyu Qiu, Minghui Yang, Bite He, Xiaofeng School of Software Engineering East China Normal University China Alibaba Group Shanghai Key Laboratory of Trsustworthy Computing China School of Computer Science and Technology East China Normal University China DXY Shanghai Research Institute for Intelligent Autonomous Systems China

ISBN: (纸本)9781954085527

Recently, the performance of Pre-trained Language Models (PLMs) has been significantly improved by injecting knowledge facts to enhance their abilities of language understanding. For medical domains, the background knowledge sources are especially useful, due to the massive medical terms and their complicated relations are difficult to understand in text. In this work, we introduce SMedBERT, a medical PLM trained on large-scale medical corpora, incorporating deep structured semantics knowledge from neighbours of linked-entity. In SMedBERT, the mention-neighbour hybrid attention is proposed to learn heterogeneous-entity information, which infuses the semantic representations of entity types into the homogeneous neighbouring entity structure. Apart from knowledge integration as external features, we propose to employ the neighbors of linked-entities in the knowledge graph as additional global contexts of text mentions, allowing them to communicate via shared neighbors, thus enrich their semantic representations. Experiments demonstrate that SMedBERT significantly outperforms strong baselines in various knowledge-intensive Chinese medical tasks. It also improves the performance of other tasks such as question answering, question matching and natural language inference. © 2021 Association for Computational Linguistics

关键词： Knowledge graph

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DECIDO Portal for evidence-Based Policy-Making

DECIDO Portal for evidence-Based Policy-Making

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International Conference on Information, Intelligence, Systems and Applications (IISA)

作者： Konstantinos Alexakis Jabier Martinez Panagiotis Kokkinakos Antonio Filograna Yury Glikman Xabier Uriarte Dimitris Askounis Decision Support Systems Laboratory School of Electrical and Computer Engineering National Technical University of Athens Athens Greece Software Technologies Tecnalia Basque Research and Technology Alliance (BRTA) Derio Spain Open Public Service Innovation Engineering Ingegneria Informatica S.p.A. Rome Italy Open Service Engineering Group Fraunhofer FOKUS Berlin Germany

Public policy-making has a strong impact on our daily lives and on most of the aspects of our society including its relation with the environment. Sustainability as a global goal cannot be achieved without effective policies supporting it. The current trend in policy-making has two main pillars, policies are a) co-created with citizens and other relevant stakeholders and b) data-based to take informed decisions. Information technologies are needed to support these pillars and facilitate evidence-based policy-making. We present the DECIDO Portal that acts as a catalyst towards putting these general principles into practice gathering the technical components to be used within the whole policy life cycle. Notably, the portal lays its foundations on a well-defined co-creation methodology that can be seamlessly followed from a unique portal and provides best-practices for participatory processes and data-driven analyses. A set of real-world experimental policies in different countries serves as case studies to showcase and discuss the usage of the portal.

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Describing Brachiopods Shape Based on Fusion of Curvature and Fourier Descriptors 12th

Describing Brachiopods Shape Based on Fusion of Curvature an...

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12th International Conference on Soft Computing and Pattern Recognition, SoCPaR 2020 and 16th International Conference on Information Assurance and Security, IAS 2020

作者： Khouya, Youssef Ait Oussous, Mohammed Ait Ghorbel, Faouzi Software Engineering and Information Systems Engineering Team Faculty of Sciences and Techniques Errachidia Moulay Ismail University Meknes Morocco Qualifying High School Ibn Albana Ministry of National Education Rabat Morocco GRIFT Research Group CRISTAL Laboratory National School of Computer Sciences University of Manouba Manouba Tunisia

ISBN: (纸本)9783030736880

The fossils classification has a great importance in palaeontological studies. They make it possible to understand the biodiversity in its morphological dimension and they show the morphological transformations suffered during the biological evolution. In this paper, we propose a descriptor for fossils classification and particularly Brachiopods. The proposed descriptor is a fusion between the curvature and Fourier descriptors. The curvature properties provide an apparently powerful cue to the underlying structure of the curve and captures completely the structure of planar curve. In addition, it is stable and complete. Fourier descriptors are powerful features for the recognition of two-dimensional connected shapes and is supported by the well-developed and well-understood Fourier theory. We used the Fourier descriptors proposed by Ghorbel, this set of invariants is also stable and complete. Experimental results are performed to illustrate the performance of the proposed descriptor. © 2021, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Biodiversity

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The Role of Generative AI in Strengthening Secure software Coding Practices: A Systematic Perspective

arXiv

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arXiv 2025年

作者： Alwageed, Hathal S. Khan, Rafiq Ahmad College of Computer and Information Sciences Jouf University Sakaka42421 Saudi Arabia Software Engineering Research Group Department of Computer Science and IT University of Malakand Pakistan

As software security threats continue to evolve, the demand for innovative ways of securing coding has tremendously grown. The integration of Generative AI (GenAI) into software development holds significant potential for improving secure coding practices. This paper aims at systematically studying the impact of GenAI in enhancing secure coding practices from improving software security, setting forth its potential benefits, challenges, and implications. To outline the contribution of AI driven code generation tools, we analyze via a structured review of recent literature, application to the industry, and empirical studies on how these tools help to mitigate security risks, comply with the secure coding standards, and make software development efficient. We hope that our findings will benefit researchers, software engineers and cybersecurity professionals alike in integrating GenAI into a secure development workflow without losing the advantages GenAI provides. Finally, the state of the art advances and future directions of AI assisted in secure software engineering discussed in this study can contribute to the ongoing discourse on AI assisted in secure software engineering. © 2025, CC BY.

关键词： software design

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Comparative Study of Quantum and Classical Error Correction for Future Quantum-6G networks

TechRxiv

引用

TechRxiv 2023年

作者： Das, Siddharth Bassoli, Riccardo Ferrara, Roberto Nötzel, Janis Deppe, Christian Fitzek, Frank H.P. Boche, Holger The Deutsche Telekom Chair of Communication Networks Institute of Communication Technology Faculty of Electrical and Computer Engineering Technische Universität Dresden Dresden Germany Cluster of Excellence Dresden Germany research group Technische Universität Dresden Dresden Germany The Department of Electrical and Computer Engineering Technische Universität München München Germany München Germany Ruhr University Bochum Bochum44801 Germany

The research on 6G communication networks has started. Currently, the proposed architectures envision the realisation of a fully softwarized network continuum, with in-network intelligence for network management and operations. Moreover, more stringent requirements than 5G have been set in order to support new use cases like telepresence and massive twinning. However, these requirements implies some critical tradeoffs, which are going to limit the promises of 6G. In order to go beyond the intrinsic limitations of 6G, new resources and technologies should be found. That is why, some research groups are now investigating how quantum technologies can be integrated into 6G. This works deals with the scenario of sending classical information via a quantum channel, using the so-called dense coding protocol. If this channel is not ideal, quantum errors can affect the reliability of the communication. Nevertheless, quantum error-correcting codes are still very demanding in terms of resources and redundancy. Then, this work investigates how classical error-correcting codes (in particular, Reed-Solomon codes and turbo codes) can be applied to make reliable classical communications via quantum channels. The preliminary results of this paper show that the employment of classical forward error correction in future hybrid 6G-quantum networks can be very promising. © 2023, CC BY.

关键词： Reed-Solomon codes

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An analysis of machine learning algorithms in rotating machines maintenance

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IFAC-PapersOnLine 2022年第2期55卷 252-257页

作者： Alexandre S. Roque Vinicius W. Krebs Iuri Castro Figueiro Nasser Jazdi Alexandre S. Roque Vinicius W. Krebs and Iuri C. Figueiro are members of the Research Group on Electronics and Power Systems (GPESP) of the Computer Science and Engineering Department Regional Integrated University of High Uruguay and Missions Brazil Institute of Industrial Automation and Software Engineering (IAS) University of Stuttgart Germany

The industrial maintenance activities represent an increase in production costs, mainly caused by unnecessary production stops. Recent technologies approaches are handling the continuous monitoring of industrial machines, storing sensors data, and also maintenance history. More data analysis is necessary specifically for rotating machines presenting methodologies to reduce the maintenance. In order to handle this problem, a comparative analysis of machine learning methods is presented. The strategy aims to predict failures and then indicates the maintenance necessity before a break occurs. Thus, it is applied and analyzed the specific machine learning algorithms, Gradient Boosting and Random Forest, using a dataset of rotation machines. The results show that both methods have an excellent performance (metrics accuracy, precision, and recall), with slightly better results in Gradient Boosting (hit rate of 99.93%) indicating the prominent application of these algorithms in this industrial scenario.

关键词： Maintenance Rotation machines Machine learning Intelligent inspection

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