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38th Conference on Neural Information Processing Systems, NeurIPS 2024

作者： Yao, Wenfang Liu, Chen Yin, Kejing Cheung, William K. Qin, Jing School of Nursing The Hong Kong Polytechnic University Hong Kong Department of Computer Science Hong Kong Baptist University Hong Kong School of Software Engineering South China University of Technology China

Integrating multi-modal clinical data, such as electronic health records (EHR) and chest X-ray images (CXR), is particularly beneficial for clinical prediction tasks. However, in a temporal setting, multi-modal data are often inherently asynchronous. EHR can be continuously collected but CXR is generally taken with a much longer interval due to its high cost and radiation dose. When clinical prediction is needed, the last available CXR image might have been outdated, leading to suboptimal predictions. To address this challenge, we propose DDL-CXR, a method that dynamically generates an up-to-date latent representation of the individualized CXR images. Our approach leverages latent diffusion models for patient-specific generation strategically conditioned on a previous CXR image and EHR time series, providing information regarding anatomical structures and disease progressions, respectively. In this way, the interaction across modalities could be better captured by the latent CXR generation process, ultimately improving the prediction performance. Experiments using MIMIC datasets show that the proposed model could effectively address asynchronicity in multimodal fusion and consistently outperform existing methods. © 2024 Neural information processing systems foundation. All rights reserved.

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Novel Algorithm for Mobile Robot Path Planning in Constrained Environment

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computers, Materials & Continua 2022年第5期71卷 2697-2719页

作者： Aisha Muhammad Mohammed A.H.Ali Sherzod Turaev Ibrahim Haruna Shanono Fadhl Hujainah Mohd Nashrul Mohd Zubir Muhammad Khairi Faiz Erma Rahayu Mohd Faizal Rawad Abdulghafor Faculty of Manufacturing Engineering Universiti Malaysia Pahang(UMP)Pekan26600Malaysia Department of Mechanical Engineering Faculty of EngineeringUniversity of Malaya50603Kuala LumpurMalaysia Department of Computer Science and Software Engineering College of Information TechnologyUnited Arab Emirates UniversityAl AinUnited Arab Emirates Faculty of Electrical and Electronics Engineering Universiti Malaysia Pahang(UMP)Pekan26600Malaysia Department of Mechatronics Engineering Faculty of TechnologyBayero UniversityKano(BUK)700241Nigeria Computer Science and Engineering Department Chalmers and University of Gothenburg41296GothenburgSweden Department of Artificial Intelligence Faculty of Computer Science and Information TechnologyUniversity of Malaya50603Kuala LumpurMalaysia Department of Computer Science Faculty of Information and Communication TechnologyInternational Islamic University Malaysia53100Kuala LumpurMalaysia

This paper presents a development of a novel path planning algorithm, called Generalized Laser simulator (GLS), for solving the mobilerobot path planning problem in a two-dimensional map with the presence ofconstraints. This approach gives the possibility to find the path for a wheelmobile robot considering some constraints during the robot movement inboth known and unknown environments. The feasible path is determinedbetween the start and goal positions by generating wave of points in alldirection towards the goal point with adhering to constraints. In simulation,the proposed method has been tested in several working environments withdifferent degrees of complexity. The results demonstrated that the proposedmethod is able to generate efficiently an optimal collision-free path. Moreover,the performance of the proposed method was compared with the A-star andlaser simulator (LS) algorithms in terms of path length, computational timeand path smoothness. The results revealed that the proposed method hasshortest path length, less computational time and the best smooth path. Asan average, GLS is faster than A∗ and LS by 7.8 and 5.5 times, respectivelyand presents a path shorter than A∗ and LS by 1.2 and 1.5 times. In orderto verify the performance of the developed method in dealing with constraints, an experimental study was carried out using a Wheeled Mobile Robot(WMR) platform in labs and roads. The experimental work investigates acomplete autonomous WMR path planning in the lab and road environmentsusing a live video streaming. Local maps were built using data from a live video streaming with real-time image processing to detect segments of theanalogous-road in lab or real-road environments. The study shows that theproposed method is able to generate shortest path and best smooth trajectoryfrom start to goal points in comparison with laser simulator.

关键词： Path planning generalized laser simulator wheeled mobile robot global path panning local path planning

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Kororā: A secure live virtual machine job migration framework for cloud systems integrity

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Array 2023年 19卷

作者： Deylami, Hanif Gutierrez, Jairo Sinha, Roopak Department of Computer Science and Software Engineering Auckland University of Technology New Zealand

The article introduces an innovative framework called Kororā, which aims to enhance the security and integrity of live virtual machine migration in a public cloud computing environment. The framework incorporates a trusted platform module to ensure the integrity of the migration process. It offers a new approach for virtual machine migration and has been specifically designed and implemented on a public infrastructure-as-a-service cloud platform. The primary research problem identified is the vulnerability of virtual machine instances to attacks during the live migration procedure. The evaluation used involves running the framework simultaneously on the same hardware components (such as I/O, CPU, and memory) and utilizing the same hypervisor's platform (Xen's open-source hypervisor). In addition, the security aspect of live migration is a crucial consideration due to the possibility of security threats across different area: data plane, control plane, and migration plane. Potential attackers may employ both passive and active attack techniques, putting the live migration at risk and resulting in a decline in performance. This poses a significant and alarming risk to the overall platform. To address the research gap, the Kororā framework emerged as a successful approach for achieving control-flow integrity by incorporating the Clark-Wilson security model proved effective in bridging the research gaps while maintaining system integrity. The primary achievement of this research is the introduction of the Kororā framework, which consists of seven agents operating within the Xen-privileged dom0 and establishing communication with the hypervisor. Overall, the finding indicate that the suggested framework offers an effective defence mechanism for moving a virtual machine from one host to another host with minimal disruption to normal operation with enhanced integrity. © 2023 The Authors

关键词： Virtual machine

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Dependency Practices for Vulnerability Mitigation

arXiv

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arXiv 2023年

作者： Jafari, Abbas Javan Costa, Diego Elias Abdellatif, Ahmad Shihab, Emad Lab The Department of Computer Science and Software Engineering Concordia University Montreal Canada Department of Computer Science and Software Engineering Concordia University Montreal Canada

Relying on dependency packages accelerates software development, but it also increases the exposure to security vulnerabilities that may be present in dependencies. While developers have full control over which dependency packages (and which version) they use, they have no control over the dependencies of their dependencies. Such transitive dependencies, which often amount to a greater number than direct dependencies, can become infected with vulnerabilities and put software projects at risk. To mitigate this risk, Practitioners need to select dependencies that respond quickly to vulnerabilities to prevent the propagation of vulnerable code to their project. To identify such dependencies, we analyze more than 450 vulnerabilities in the npm ecosystem to understand why dependent packages remain vulnerable. We identify over 200,000 npm packages that are infected through their dependencies and use 9 features to build a prediction model that identifies packages that quickly adopt the vulnerability fix and prevent further propagation of vulnerabilities. We also study the relationship between these features and the response speed of vulnerable packages. We complement our work with a practitioner survey to understand the applicability of our findings. Developers can incorporate our findings into their dependency management practices to mitigate the impact of vulnerabilities from their dependency supply chain. Copyright © 2023, The Authors. All rights reserved.

关键词： Ecosystems

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Virtual Laboratory Learning Experience in engineering: An Extended Technology Acceptance Model (TAM) 3

Virtual Laboratory Learning Experience in Engineering: An Ex...

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3rd IEEE International Maghreb Meeting of the Conference on sciences and Techniques of Automatic Control and computer engineering, MI-STA 2023

作者： Ahmed Alnagrat, Ahmed Jamah Ahmed, Khamiss M. S. Alkhallas, Muhannad Ismail Almakhzoom, Osama Abulaqasim Ibrahim Syed Idrus, Syed Zulkarnain Che Ismail, Rizalafande Higher Institute of Science and Technology Wadi Al-Shati Department of Computer Science and Information Technology Wadi al-Shati Fezzan Libya Sebha University Faculty of Information Technology Department of Computer Science Sebha Libya Faculty of Engineering Technology in Zuwarah Department of Software Engineering Zuwarah Libya Department of Communication Perlis Kangar01000 Malaysia Arau02600 Malaysia

ISBN: (纸本)9798350319897

This research presents an enhanced version of the Technology Acceptance Model (TAM), which integrates usability and learning objectives to evaluate the effect of adopting virtual laboratories on student performance. Data from 97 participants, gathered via a survey, was used to examine the correlation between perceived usefulness (PU), perceived ease of use (PEOU), and intention to use (IU) concerning their experiences and outcomes with a simulation-based virtual laboratory. A custom questionnaire was designed to assess TAM components, namely PU, PEOU, and IU, specifically in the context of virtual laboratory learning environments. Findings indicate that the integration of specific laboratory learning objectives fosters the creation of a more credible and authentic simulation tool. This, in turn, optimizes the learning process and enhances students' learning outcomes. The refined TAM model provides valuable insights into the determinants of user acceptance of virtual laboratories and offers practical guidance for educators and instructional designers to construct more effective and efficient virtual laboratory environments in educational contexts. © 2023 IEEE.

关键词： Virtual reality

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PMMVar: Leveraging Multi-level Protein Structures for Enhanced Coding Variant Pathogenicity Prediction

PMMVar: Leveraging Multi-level Protein Structures for Enhanc...

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2023 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2023

作者： Chen, Yijia Chen, Yiwen Nie, Shanling Yang, Hai East China University of Science and Technology Department of Computer Science and Engineering Shanghai China Shanghai Key Laboratory of Computer Software Evaluating and Testing Shanghai China National University of Singapore Center for Continuing and Lifelong Education Singapore The University of Sydney Faculty of Engineering Australia

ISBN: (纸本)9798350337488

Genomic variants, which can disrupt cellular functions, present a challenge in distinguishing deleterious from benign instances. While assessing genome-wide functional impacts, many current algorithms neglect protein tertiary structure of coding region variants due to limitations in protein structural prediction. This study introduces PMMVar, an advanced multimodal deep convolutional network, which adeptly integrates protein tertiary structures with conservation properties from ESM-2, supplemented by other protein structural sequences. PMMVar achieves outstanding performance on the latest clinical variant datasets, NCBI ClinVar (2023), and the Mendelian variant dataset, surpassing existing benchmarks. Ablation analyses validate the significance of protein multi-level structures in enhancing the model's accuracy. Overall, our findings spotlight the essential role of multi-level protein structures in pathogenicity predictions and their potential to discern deleterious genomic variants effectively. © 2023 IEEE.

关键词： deep learning multimodal pathogenicity protein structure variant

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Using Equivalent Gold Sequences for Parallel Data Transmission with Non-orthogonal Code Division 8

Using Equivalent Gold Sequences for Parallel Data Transmissi...

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8th International Conference on Information, Control, and Communication Technologies, ICCT 2024

作者： Kukunin, Dmitry Berezkin, Alexander Kirichek, Ruslan Bonch-Bruevich Saint-Petersburg University of Telecommunications Communication Networks and Data Transmission Department Saint-Petersburg Russia Bonch-Bruevich Saint-Petersburg University of Telecommunications Software Engineering and Computer Science Department Saint-Petersburg Russia

ISBN: (纸本)9798331517564

This article describes a new technology for the formation of compacted code structures based on maximum length sequences. The most important distinguishing feature of the code division method presented here is the absence of requirements for the orthogonality of sequences that can be used as address combinations when organizing parallel data transmission. Thus, the identification of information recipients is carried out at the physical level using special signal-code structures. At the same time, it is possible to implement a system with anonymous recipients, when any of the recipient nodes does not have information about what data was transferred to other nodes. The communication system model built in accordance with such principles allows the use of the most noise-resistant type of modulation, for example, binary phase-shift keying. This, in turn, ensures the minimum peak factor of the signal. It is also worth noting that the main tool for processing the resulting compacted code structures are dual bases of Galois fields. © 2024 IEEE.

关键词： Code division multiple access

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The Future of Differentiated Thyroid Cancer Recurrence Prediction Using a Machine Learning Framework Advancements, Challenges, and Prospects 4

The Future of Differentiated Thyroid Cancer Recurrence Predi...

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4th International Conference on Emerging Trends in Networks and computer Communications, ETNCC 2024

作者： Imtiaz, Irsa Rehman, Attique Ur Javaid, Sabeen Ali, Tahir Mohammad Mir, Azka Masud, Mehedi Nirsanametla, Yadaiah University of Sialkot Department of Software Engineering Sialkot Pakistan GULF University for Sciences and Technology Department of Software Engineering Mubarak Al-Abdullah Kuwait Taif University Department of Computer Science Taif Saudi Arabia Lovely Professional University Division of Research and Development Phagwara144411 India KKR and KSR institute of technology and sciences Andhra Pradesh Guntur India

ISBN: (纸本)9798350353266

Differentiated thyroid cancer originates in the thyroid gland, which is positioned in the front of the neck. The thyroid gland generates hormones that control metabolism, heart rate, and other bodily functions. Differentiated thyroid carcinoma (DTC) recurrence is a major challenge in clinical therapy. Early detection and treatment play an important role in reducing the impact of thyroid cancer recurrence. The development of precise prediction algorithms is demanding. The prognosis, diagnosis, and treatment of differentiated thyroid carcinoma have been the subject of extensive investigation. Scholars have investigated diverse methodologies to forecast the likelihood of getting thyroid cancer, refine early identification techniques, and augment therapeutic results. Machine learning (ML) frameworks have emerged as useful tools in this setting, with the potential to improve prediction accuracy and patient outcomes. This paper provides a detailed evaluation of the current state and future directions of DTC recurrence prediction using machine learning. We examine current advances in machine learning techniques, data sources, and feature selection approaches used in DTC recurrence prediction models. Several machine-learning algorithms have been applied. We have suggested the model containing the classifier with the highest accuracy after comparing the accuracy percentage of the various classifiers that were produced. Our suggested model has a 98.17% accuracy rate with Bagging. Finally, we propose solutions to these difficulties and emphasize ML's potential to revolutionize the landscape of DTC recurrence prediction. We hope that this analysis will provide insights into the developing role of machine learning in DTC management and motivate more research in this crucial area. © 2024 IEEE.

关键词： Diseases

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Digitalisation of MFIs with HCI Intervention for Low Income and Limited Literacy Individuals

Digitalisation of MFIs with HCI Intervention for Low Income ...

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International Conference on computer and Information Technology (ICCIT)

作者： Aisha Chowdhury Prapti Roy Mushfiqur Rahman Department of Computer Science & Engineering Shahjalal University of Science & Technology Sylhet Bangladesh Department of Software Engineering Shahjalal University of Science & Technology Sylhet Bangladesh Department of Computer Science & Engineering Sylhet Engineering College Sylhet Bangladesh

ISBN: (数字)9798331519094

ISBN: (纸本)9798331519100

Human-computer Interaction (HCI) is a multidisciplinary field that studies how people use, design, and evaluate digital technologies. HCI can have significant implications for the digitalization of microfinance, which is the provision of financial services to low-income individuals and groups through digital platforms. In this research, we aim to explore how HCI can affect the digitalization of microfinance in Bangladesh, a developing country with a large population of microfinance clients. We will use a qualitative approach, comprising semi-structured interviews, and observations, to assess the current state of digital microfinance in Bangladesh. The challenges and opportunities for HCI design and evaluation, and the impact of HCI on the financial inclusion and empowerment of microfinance clients. We aspire to construct an innovative application tailored specifically for low-literate individuals. By melding the conceptual underpinnings of HCI with the unique needs of this demographic, our endeavor seeks to foster a technological solution that bridges the digital divide and empowers those traditionally excluded from the digital revolution. We expect that this research will contribute to the literature on HCI for development, as well as provide insights and recommendations for practitioners and policymakers in the microfinance sector.

关键词： Human computer interaction Bridges Pain Digital transformation Developing countries Digital divide Interviews Information technology Financial services Logistics

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AI-Enhanced Multi-Cloud Security Management: Ensuring Robust Cybersecurity in Hybrid Cloud Environments

AI-Enhanced Multi-Cloud Security Management: Ensuring Robust...

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2023 International Conference on Innovative Computing, Intelligent Communication and Smart Electrical Systems, ICSES 2023

作者： Srimathi, J. Kanagasabapathi, K. Mahajan, Kirti Ahamad, Shahanawaj Soumya, E. Barthwal, Shivangi KPR College of Arts Science and Research Department of Information Technology Covai Arasur641407 India Karpagam College of Engineering Computer Science and Technology Coimbatore India Bharati Vidyapeeth Deemed University Institute of Management & Entrepreneurship Development Department of Information Technology Pune411030 India University of Hail College of Computer Science and Engineering Department of Software Engineering Hail City Saudi Arabia St. Martins Engineering College Department of Computer Science and Engineering Telangana Secunderabad India Graphic Era Deemed to Be University Department of Electronics & Communication Engineering Uttarakhand Dehradun248002 India

ISBN: (纸本)9798350319200

The complex landscape of multi-cloud settings is the result of the fast growth of cloud computing and the ever-changing needs of contemporary organizations. Strong cyber defenses are of fundamental importance in this setting. In this study, we investigate the use of AI in hybrid cloud settings for the purpose of multi-cloud security management. To help businesses improve their productivity and resilience, we provide a mathematical model for optimal resource allocation. Our methodology streamlines dynamic threat assessments, making it easier for security teams to efficiently priorities vulnerabilities. The advent of a new age of real-time threat response is heralded by the incorporation of AI-driven security tactics. The technique we use has real-world implications that may help businesses stay ahead of constantly changing threats. In the future, scientists will focus on autonomous security systems, interoperability, ethics, interoperability, and cutting-edge AI models that have been validated in the real world. This study provides a detailed road map for businesses to follow as they navigate the complex cybersecurity landscape of multi-cloud settings, therefore promoting resilience and agility in this era of digital transformation. © 2023 IEEE.

关键词： Adaptive Security Systems Artificial Intelligence Autonomous Security Cybersecurity Hybrid Cloud Multi-Cloud Security Quantum Computing Real-Time Threat Response Threat Assessment

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