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8th International Conference on the Development of Biomedical engineering, BME8 2020

作者： Ho, Thi Kieu Khanh Kim, Minhee Garg, Harish Kim, Byeong C. Lee, Jang Jae Choi, Kyu Yeong Kim, Jae Gwan Lee, Kun Ho Song, Jong-In Gwak, Jeonghwan School of Electrical Engineering and Computer Science Gwangju Institute of Science and Technology Gwangju61005 Korea Republic of Department of Biomedical Science and Engineering Institute of Science and Technology Gwangju61005 Korea Republic of School of Mathematics Thapar Institute of Engineering and Technology Deemed University Patiala Punjab147004 India Department of Neurology Chonnam National University Medical School Gwangju61469 Korea Republic of Cohort Research Center Chosun University Gwangju61452 Korea Republic of Department of Biomedical Science Chosun University Gwangju61452 Korea Republic of Aging Neuroscience Research Group Korea Brain Research Institute Daegu41062 Korea Republic of Department of Software Korea National University of Transportation Chungju27469 Korea Republic of

ISBN: (纸本)9783030755058

Early and accurate diagnosis of Alzheimer’s disease (AD) is especially important for neurodegenerative disorders allowing patients, who exhibit different patterns of severity and progression risks, to take prevention and treatments before brain damages are shaped. Functional Near-Infrared Spectroscopy (fNIRS), as a clinical test, can be employed in an ecological setting to support AD diagnosis at early stages. In this study, we aimed to comprehensively study the hemodynamic response patterns among four subject groups from 140 participants by visualizing the 4-class distributions based on t-SNE visualization techniques and showing the fNIRS topographic mapping to have a pictorial representation on the surface of the prefrontal cortex region. We demonstrated that the changes in hemodynamic concentrations of oxygenated hemoglobin (HbO) and deoxygenated hemoglobin (Hb) from healthy controls to three stages of AD did exist during four stages of our experimental protocols. Results also revealed that various machine learning techniques were capable of both analyzing AD patterns and its related features and classifying multiple pathophysiologic mechanisms with the highest accuracies of 74.39 ± 4.7% and 84.91 ± 4.01% corresponding to raw and SMOTE-based features, respectively. These findings demonstrate the feasibility of fNIRS-based approaches to investigate the stages of AD progression. © 2022, Springer Nature Switzerland AG.

关键词： Machine learning

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Game-Oriented Security Strategy Against Hotspot Attacks for Internet of Vehicles

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computers, Materials & Continua 2021年第8期68卷 2145-2157页

作者： Juan Guo Yanzhu Liu Shan Li Zhi Li Sonia Kherbachi Guilin University of Electronic Technology Beihai536000GuangxiChina Great Wall Computer Software and Systems Inc. Beijing100083China Department of Electronics and Communication Engineering Beijing Electronic Science and Technology InstituteBeijing100070China State Grid Information&Telecommunication Group Co. Ltd.Beijing100031China Department of Management University of BejaiaBejaia06000Algeria

With the rapid development of mobile communication technology,the application of internet of vehicles(IoV)services,such as for information services,driving safety,and traffic efficiency,is growing *** businesses with low transmission delay,high data processing capacity and large storage capacity,by deploying edge computing in the IoV,data processing,encryption and decision-making can be completed at the local end,thus providing real-time and highly reliable communication *** roadside unit(RSU),as an important part of edge computing in the IoV,fulfils an important data forwarding function and provides an interactive communication channel for vehicles and server *** computing resources can be configured to accommodate the computing requirements of *** this study,a virtual traffic defense strategy based on a differential game is proposed to solve the security problem of user-sensitive information leakage when an RSU is *** incentive mechanism encourages service vehicles within the hot range to send virtual traffic to another *** attracting the attention of attackers,it covers the target RSU and protects the system from *** results show that the scheme provides the optimal strategy for intelligent vehicles to transmit virtual data,and ensures the maximization of users’interests.

关键词： Edge computing internet of vehicles differential games security defense

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QuIP: A P4 Quantum Internet Protocol Prototyping Framework

arXiv

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arXiv 2024年

作者： Kozlowski, Wojciech Kuipers, Fernando A. Smets, Rob Turkovic, Belma QuTech Delft University of Technology Delft2628 CD Netherlands The Networked Systems Group Department of Software Technology Faculty of Electrical Engineering Mathematics and Computer Science Delft University of Technology Delft2628 CD Netherlands SURF Utrecht3511 EP Netherlands TNO The Hague2595 DA Netherlands

Quantum entanglement is so fundamentally different from a network packet that several quantum network stacks have been proposed;one of which has even been experimentally demonstrated. Several simulators have also been developed to make up for limited hardware availability, and which facilitate the design and evaluation of quantum network protocols. However, the lack of shared tooling and community-agreed node architectures has resulted in protocol implementations that are tightly coupled to their simulators. Besides limiting their reusability between different simulators, it also makes building upon prior results and simulations difficult. To address this problem, we have developed QuIP: a P4-based Quantum Internet Protocol prototyping framework for quantum network protocol design. QuIP is a framework for designing and implementing quantum network protocols in a platform-agnostic fashion. It achieves this by providing the means to flexibly, but rigorously, define device architectures against which quantum network protocols can be implemented in the network programming language P416. QuIP also comes with the necessary tooling to enable their execution in existing quantum network simulators. We demonstrate its use by showcasing V1Quantum, a completely new device architecture, implementing a link- and network-layer protocol, and simulating it in the existing simulator NetSquid. © 2024, CC BY.

关键词： Network architecture

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A cooperative heterogeneous vehicular clustering framework for

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Frontiers of Information Technology & Electronic engineering 2021年第9期22卷 1247-1259页

作者： Iftikhar AHMAD Rafidah Md NOOR Zaheed AHMED Umm-e-HABIBA Naveed AKRAM Fausto Pedro GARCIA MARQUEZ Department of Computer Science and Information Technology MirpurUniversity of Science and TechnologyMirpur-10250(AJK)Pakistan Facultyof Computer Science and Information Technology University of MalayaKualaLumpur 50603Malaysia Departmentof Software Engineering University of KotliAJK 11100Pakistan Department of Mechanical Engineering Mirpur University of Science andTechnologyMirpur-10250(AJK)Pakistan Department of MechanicalEngineering Faculty of Mechanical EngineeringUniversity of MalayaKualaLumpur 50603Malaysia Ingenium Research Group University of Castilla-LaManchaSpain

Heterogeneous vehicular clustering integrates multiple types of communication networks to work efficiently for various vehicular *** popular form of heterogeneous network is the integration of long-term evolution(LTE)and dedicated short-range *** heterogeneity of such a network infrastructure and the non-cooperation involved in sharing cost/data are potential problems to solve.A vehicular clustering framework is one solution to these problems,but the framework should be formally verified and validated before being deployed in the real *** solve these issues,first,we present a het-erogeneous framework,named destination and interest-aware clustering,for vehicular clustering that integrates vehicular ad hoc networks with the LTE network for improving road traffic ***,we specify a model system of the proposed *** model is formally verified to evaluate its performance at the functional level using a model checking *** evaluate the performance of the proposed framework at the micro-level,a heterogeneous simulation environment is created by integrating state-of-the-art *** comparison of the simulation results with those of other known approaches shows that our proposed framework performs better.

关键词： Vehicular cluster Heterogeneity Cooperation Formal verification System model

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EasyNER: A Customizable Easy-to-Use Pipeline for Deep Learning- and Dictionary-based Named Entity Recognition from Medical Text

arXiv

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arXiv 2023年

作者： Ahmed, Rafsan Berntsson, Petter Skafte, Alexander Rashed, Salma Kazemi Klang, Marcus Barvesten, Adam Olde, Ola Lindholm, William Arrizabalaga, Antton Lamarca Nugues, Pierre Aits, Sonja Cell Death Lysosomes and Artificial Intelligence Group Department of Experimental Medical Science Faculty of Medicine Lund Sweden Lund University Profile Area Nature-Based Future Solutions Sweden Lund University Profile Area Artificial and Natural Cognition Sweden Sweden Department of Computer Science Faculty of Engineering Lund University Lund Sweden

Background Medical research generates millions of publications and it is a great challenge for researchers to utilize this information in full since its scale and complexity greatly surpasses human reading capabilities. Automated text mining can help extract and connect information spread across this large body of literature but this technology is not easily accessible to life scientists. Results Here, we developed an easy-to-use end-to-end pipeline for deep learning- and dictionary-based named entity recognition (NER) of typical entities found in medical research articles, including diseases, cells, chemicals, genes/proteins, and species. The pipeline can access and process large medical research article collections (PubMed, CORD-19) or raw text and incorporates a series of deep learning models fine-tuned on the HUNER corpora collection. In addition, the pipeline can perform dictionary-based NER related to COVID-19 and other medical topics. Users can also load their own NER models and dictionaries to include additional entities. The output consists of publication-ready ranked lists and graphs of detected entities and files containing the annotated texts. An associated script allows rapid inspection of the results for specific entities of interest. As model use cases, the pipeline was deployed on two collections of autophagy-related abstracts from PubMed and on the CORD19 dataset, a collection of 764 398 research article abstracts related to COVID-19. Conclusions The NER pipeline we present is applicable in a variety of medical research settings and makes customizable text mining accessible to life *** Codes 92-04, 92-08, 68T50 © 2023, CC BY-NC-ND.

关键词： Pipelines

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Human Factors in Model-Driven engineering: Future Research Goals and Initiatives for MDE

arXiv

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arXiv 2024年

作者： Liebel, Grischa Klünder, Jil Hebig, Regina Lazik, Christopher Nunes, Inês Graßl, Isabella Steghöfer, Jan-Philipp Exelmans, Joeri Oertel, Julian Marquardt, Kai Juhnke, Katharina Schneider, Kurt Gren, Lucas Happe, Lucia Herrmann, Marc Wyrich, Marvin Tichy, Matthias Goulão, Miguel Wohlrab, Rebekka Kalantari, Reyhaneh Heinrich, Robert Greiner, Sandra Rukmono, Satrio Adi Chakraborty, Shalini Abrahão, Silvia Amaral, Vasco Department of Computer Science Reykjavik University Menntavegur 1 Reykjavik102 Iceland Software Engineering Group Leibniz University Hannover Welfengarten 1 Hannover30167 Germany Department of Software Engineering University of Rostock Albert-Einstein-Straße Rostock18057 Germany Department of Software Engineering Humboldt-Universität zu Berlin Unter den Linden 6 Berlin10099 Germany Frankfurt Germany Department of Software Engineering II University of Passau Innstraße 33 Passau94032 Germany XITASO GmbH Austraße 35 Augsburg86153 Germany Department of Computer Science University of Antwerp Middelheimlaan 1 Antwerp2020 Belgium Department of Informatics Karlsruhe Institute of Technology Am Fasanengarten 5 Karlsruhe75131 Germany SMT-EMI6 Carl Zeiss SMT GmbH Rudolf-Eber-Straße 2 Oberkochen73447 Germany Department of Computer Science and Engineering Chalmers | University of Gothenburg Gothenburg41127 Sweden Department of Interdisciplinary Didactics Karlsruhe Institute of Technology Engesserstr. 2 Karlsruhe75131 Germany Department of Computer Science Saarland University Saarland Informatics Campus Saarbrücken66123 Germany Institute of Software Engineering and Languages Ulm University James-Franck-Ring Ulm89081 Germany Department of Computer Science NOVA School of Science & Technology Campus de Caparica Caparica2829-516 Portugal Department of Engineering Design and Teaching Innovation University of Ottawa 800 King Edward Avenue OttawaK1N6N5 Canada KASTEL - Institute of Information Security and Dependability Karlsruhe Institute of Technology Am Fasanengarten 5 Karlsruhe75131 Germany Department of Computer Science University of Bern Bern3012 Switzerland Department of Mathematics and Computer Science Eindhoven University of Technology De Zaale Eindhoven5600 MB Netherlands Instituto Universitario Mixto de Tecnología Informática Universitat Politècnica de València Camino de Vera s/n Valencia46022 Spain

Purpose: software modelling and Model-Driven engineering (MDE) is traditionally studied from a technical perspective. However, one of the core motivations behind the use of software models is inherently human-centred. Models aim to enable practitioners to communicate about software designs, make software understandable, or make software easier to write through domain-specific modelling languages. Several recent studies challenge the idea that these aims can always be reached and indicate that human factors play a role in the success of MDE. However, there is an under-representation of research focusing on human factors in modelling. Methods: During a GI-Dagstuhl seminar, topics related to human factors in modelling were discussed by 26 expert participants from research and industry. Results: In breakout groups, five topics were covered in depth, namely modelling human aspects, factors of modeller experience, diversity and inclusion in MDE, collaboration and MDE, and teaching human-aware MDE. Conclusion: We summarise our insights gained during the discussions on the five topics. We formulate research goals, questions, and propositions that support directing future initiatives towards an MDE community that is aware of and supportive of human factors and values. © 2024, CC BY.

关键词： software design

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Breamy: An augmented reality mHealth prototype for surgical decision-making in breast cancer

arXiv

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arXiv 2023年

作者： Najafi, Niki Addie, Miranda Meterissian, Sarkis Kersten-Oertel, Marta Applied Perception Lab Department of Computer Science and Software Engineering Concordia University Québec Canada Experimental Surgery Mcgill University Québec Canada Breast Center McGill University Health Centre Québec Canada Department of Surgery Faculty of Medicine McGill University Québec Canada

In 2020, according to WHO, breast cancer affected 2.3 million women worldwide, resulting in 685,000 fatalities. By the end of the year, approximately 7.8 million women worldwide had survived their breast cancer making it the most widespread form of cancer globally. Surgical treatment decisions, including choosing between oncoplastic options, often require quick decision-making within an 8-week time frame. However, many women lack the necessary knowledge and preparation for making such complex informed decisions. Anxiety and unsatisfactory outcomes can result from inadequate decision-making processes, leading to complications and the need for revision surgeries. Shared decision-making and personalized decision aids have shown positive effects on patient satisfaction and treatment outcomes. This paper introduces Breamy, a prototype mobile health (mHealth) application that utilizes augmented reality (AR) technology to assist breast cancer patients in making informed decisions. The app provides 3D visualizations of different oncoplastic procedures, aiming to improve confidence in surgical decision-making, reduce decisional regret, and enhance patient well-being after surgery. To determine the perception of the usefulness of Breamy, we collected data from 166 participants through an online survey. The results suggest that Breamy has the potential to reduce patient's anxiety levels and assist them during the decision-making process. Copyright © 2023, The Authors. All rights reserved.

关键词： Visualization

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SUMMER: Bias-aware Prediction of Graduate Employment Based on Educational Big Data

引用

ACM/IMS Transactions on Data science 2021年第4期2卷 1–24页

作者： Xia, Feng Guo, Teng Bai, Xiaomei Shatte, Adrian Liu, Zitao Tang, Jiliang School of Engineering It and Physical Sciences Federation University Australia Ballarat3353 Australia School of Software Dalian University of Technology Dalian116620 China Computing Center Anshan Normal University Anshan114007 China Tal Education Group Beijing100080 China Department of Computer Science and Engineering Michigan State University East LansingMI48824 United States

The failure of obtaining employment could lead to serious psychosocial outcomes such as depression and substance abuse, especially for college students who may be less cognitively and emotionally mature. In addition to academic performance, employers' unconscious biases are a potential obstacle to graduating students in becoming employed. Thus, it is necessary to understand the nature of such unconscious biases to assist students at an early stage with personalized intervention. In this paper, we analyze the existing bias in college graduate employment through a large-scale education dataset and develop a framework called SUMMER (biaS-aware gradUate eMployMEnt pRediction) to predict students' employment status and employment preference while considering biases. The framework consists of four major components. Firstly, we resolve the heterogeneity of student courses by embedding academic performance into a unified space. Next, we apply a Wasserstein generative adversarial network with gradient penalty (WGAN-GP) to overcome the label imbalance problem of employment data. Thirdly, we adopt a temporal convolutional network to comprehensively capture sequential information of academic performance across semesters. Finally, we design a bias-based regularization to smooth the job market biases. We conduct extensive experiments on a large-scale educational dataset and the results demonstrate the effectiveness of our prediction framework. © 2022 Association for Computing Machinery.

关键词： Forecasting

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Federated Learning for Recognizing Private Handwritten Numbers

Federated Learning for Recognizing Private Handwritten Numbe...

引用

2021 IEEE International Conference on Data science and computer Application, ICDSCA 2021

作者： Wang, Di Jiang, Yuchen Zhao, Yibo Chen, Panyang Li, Ang Pan, Kun Institution of Information Engineering Chinese Academy of Sciences State Key Laboratory of Information Security Beijing China School of Cyber Security University of Chinese Academy of Sciences Beijing China Computer Science and Technology College of Computer Science Chongqing University Chongqing China Zibo Shiyan High School International Division Zibo Shandong China Computer Science Department of Computer Science and Software Engineering Auburn University Auburn United States Shanghai Shangde Experimental School Shanghai China School of Computing University of Leeds Leeds United Kingdom

ISBN: (纸本)9781665440530

Federated learning (FL) is a new technology in the field of machine learning, which trains an algorithm across multiple decentralized edge devices or servers holding data samples, without exchanging their data samples. Horizontal Federated Learning (HFL) is a FL method focusing on using the same feature space across all users, which is suitable for situations where users' data feature dimensions overlap more. Because FL has the advantage of privacy protection in the field of manufacturing, we propose an HFL-based deep learning method named FedCNN, which realizes the digits handwritten recognition without violating the privacy or data sharing. Three different methods (local model, centralized model, and HFL-based FedCNN) are used on a public data set (MINIST) to compare the pros and cons of the solutions. The experimental results demonstrate that FedCNN scheme can simultaneously achieve practical privacy preservation and good model generalization performance with Homomorphic Encryption. © 2021 IEEE.

关键词： Data privacy

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Detection of brain tumor and identification of tumor region using deep neural network on FMRI images 19

Detection of brain tumor and identification of tumor region ...

引用

19th International Conference on Machine Learning and Cybernetics, ICMLC 2020

作者： Mashiat, Afsara Akhlaque, Reza Rifat Fariha, Fahmeda Hasan Reza, Tanzim Rahman, Md Anisur Parvez, Mohammad Zavid Brac University Software Engineering and HCI Research Group Department of Computer Science and Engineering Bangladesh Charles Sturt University School of Computing and Mathematics Australia

ISBN: (纸本)9780738124261

As brain is the most vital organ of the human body, the affects of brain related diseases can be severe. One of the most harmful diseases is brain tumor, which results in a very short life expectancy of the affected patient. Detection of brain tumor is a challenging task in the early stages. Still, with the help of modern technology and machine learning algorithms, it has become a matter of great interest for research. While detecting the brain tumor of an affected person, we are considering the fMRI data of the patient. Our aim is to identify whether the tumor is present in the patient's brain or not. We use a Convolutional Neural Network(CNN) that is good enough to generate high accuracy. We have used some deeper architecture design VGG16, VGG19, and Inception v3 for better accuracy. Three classification techniques are used namely binary classification, lobe based classification, and position based classification. The main contribution of our proposed work is that we have identified the specific region of the brain where the tumor is located. The region-based classification distinguishes our work from others that are applied on the same dataset. For binary classification, we found approximately 95% accuracy from all the three architectures. Furthermore, we found approximately 78% accuracy for lobe based classification and approximately 97% accuracy for position based classification. The experimental results indicate the superiority of our proposed method in terms of identifying the brain tumor. © 2020 IEEE.

关键词： Brain

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