信息工程最新文献

{"title":"Multi-task learning for PBFT optimisation in permissioned blockchains","authors":"","doi":"10.1016/j.bcra.2024.100206","DOIUrl":"10.1016/j.bcra.2024.100206","url":null,"abstract":"<div><div>Finance, supply chains, healthcare, and energy have an increasing demand for secure transactions and data exchange. Permissioned blockchains fulfilled this need thanks to the consensus protocol that ensures that participants agree on a common value. One of the most widely used protocols in private blockchains is the Practical Byzantine Fault Tolerance (PBFT), which tolerates up to one-third of Byzantine nodes, performs within partially synchronous systems, and has superior throughput compared to other protocols. It has, however, an important bandwidth consumption: <span><math><mn>2</mn><mi>N</mi><mo>(</mo><mi>N</mi><mo>−</mo><mn>1</mn><mo>)</mo></math></span> messages are exchanged in a system composed of <em>N</em> nodes to validate only one block.</div><div>It is possible to reduce the number of consensus participants by restricting the validation process to nodes that have demonstrated high levels of security, rapidity, and availability. In this paper, we propose the first database that traces the behavior of nodes within a system that performs PBFT consensus. It reflects their level of security, rapidity, and availability throughout the consensus. We first investigate different Single-Task Learning (STL) techniques to classify the nodes within our dataset. Then, using Multi-Task Learning (MTL) techniques, the results are much more interesting, with classification accuracies over 98%. Integrating node classification as a preliminary step to the PBFT protocol optimizes the consensus. In the best cases, it is able to reduce the latency by up to 94% and the communication traffic by up to 99%.</div></div>","PeriodicalId":53141,"journal":{"name":"Blockchain-Research and Applications","volume":null,"pages":null},"PeriodicalIF":6.9,"publicationDate":"2024-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2096720924000198/pdfft?md5=e11c2d536c1985f173948098606e4b4b&pid=1-s2.0-S2096720924000198-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141051117","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Genetic diversity, virulence profiles, and antimicrobial resistance of Salmonella enterica serovar Typhi isolated from typhoid fever patients in Baghdad, Iraq","authors":"","doi":"10.1016/j.jobb.2024.08.001","DOIUrl":"10.1016/j.jobb.2024.08.001","url":null,"abstract":"<div><p>Typhoid fever is an important health issue in developing countries, and the pathogenicity of <em>Salmonella enterica</em> serovar Typhi (<em>S.</em> ser. Typhi) depends on the presence of different virulence factors. Therefore, this study aimed to investigate the spread of virulence genes among <em>S.</em> Typhi isolates from patients with typhoid fever in Baghdad, Iraq. Sixty <em>S.</em> Typhi isolates were collected from several hospitals in Baghdad and identified using VITEK-II and confirmed by polymerase chain reaction <strong>(</strong>PCR) to detect the <em>16S rRNA</em> gene. After testing their susceptibility to different antimicrobials (via the disk diffusion method), we found the highest resistance rates (100 %) were to ampicillin, piperacillin, cefotaxime, and ceftriaxone. The highest sensitivity rates (100 %) were to ertapenem, imipenem, meropenem, and sulfamethoxazole/trimethoprim. The presence of genes encoding for virulence in <em>S.</em> Typhi isolates was tested by conventional PCR. The results showed that out of 60 isolates, 59 (98.3 %), 59 (98.3 %), 58 (96.7 %), and 60 (100 %) were positive for <em>viaB, staA, cdtB,</em> and <em>orfL</em> genes, respectively. The sequencing of PCR products (<em>viaB, staA, cdtB,</em> and <em>orfL</em> genes) was carried out at the Macrogen Company (Seoul, Korea). The sequences were compared with nucleotide sequences in the BLAST GenBank database, and data obtained from the sequencing of these virulence genes were submitted to GenBank under different accession numbers. A phylogenetic analysis of the <em>16S rRNA</em> gene sequence found a high similarity between local sequences and the closely related sequences of genes in GenBank. The presence of the <em>viaB, staA, cdtB,</em> and <em>orfL</em> virulence genes in nearly all of the isolates under examination suggests that they play an important role in the pathogenicity of local isolates.</p></div>","PeriodicalId":52875,"journal":{"name":"Journal of Biosafety and Biosecurity","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-08-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2588933824000396/pdfft?md5=29e047c9e195776b3f4303349920534c&pid=1-s2.0-S2588933824000396-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142083192","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Pseudovirus technology in global health: A critical need for robust biosecurity measures","authors":"","doi":"10.1016/j.jobb.2024.07.002","DOIUrl":"10.1016/j.jobb.2024.07.002","url":null,"abstract":"","PeriodicalId":52875,"journal":{"name":"Journal of Biosafety and Biosecurity","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-08-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2588933824000384/pdfft?md5=e08b2d7d323a451bf516682ba068e063&pid=1-s2.0-S2588933824000384-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142050451","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Narrow windows of opportunity: the limited utility of cyber operations in war","authors":"Frederik A H Pedersen, Jeppe T Jacobsen","doi":"10.1093/cybsec/tyae014","DOIUrl":"https://doi.org/10.1093/cybsec/tyae014","url":null,"abstract":"The use of offensive cyber operations in war is no longer theoretical conjecture. Still, as we witness their use, important questions remain. How are offensive cyber operations employed in conventional warfighting, and what is their utility for the warfighting? This article answers these questions by analyzing new empirical evidence from the Russo–Ukrainian War, drawing on the novel TECI-model built for systematically analyzing and understanding offensive cyber operations in war through the model’s four constituent variables: target, effect, complexity, and integration. The article finds the utility of cyber operations in war is limited owing to an unsuitability for physical destruction, high risks of failure, high costs of complex operations that are more likely to attain successful and destructive effects, and a dichotomy between the tempi of conventional and cyber operations leading to cross-domain integration difficulties. Still, two narrow windows for achieving utility exist. Cumulative strategic utility is achievable by targeting critical infrastructure and governments in a persistent barrage of less complex cyber operations. Operational and tactical utility is achievable in the beginning of warfighting where the temporal dichotomy is less pronounced because cross-domain integration can be planned before warfighting commences. Filling a gap in the literature, TECI provides a common and operationalized model for future research systematically analyzing cyber operations, allowing for comparisons on the evolving role of cyberspace in war.","PeriodicalId":44310,"journal":{"name":"Journal of Cybersecurity","volume":null,"pages":null},"PeriodicalIF":3.9,"publicationDate":"2024-08-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141940833","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Computational modeling and inhibition of SARS-COV-2 Papain-like protease enzyme: A potential therapeutic approach for COVID-19","authors":"","doi":"10.1016/j.jobb.2024.07.001","DOIUrl":"10.1016/j.jobb.2024.07.001","url":null,"abstract":"<div><p>This study aims to investigate the potential impact of inhibitors targeting the papain-like protease (PLpro) of SARS-CoV-2 on viral replication and the host immune response. A mathematical model was developed to simulate the interaction among susceptible cells, infected cells, PLpro, and immune cells, incorporating data on PLpro inhibition. Through numerical simulations using MATLAB, the model parameters were estimated based on available statistical data. The results indicate that strategically positioned inhibitors could impede the virus’s access to host cellular machinery, thereby enhancing the immune response and gradually reducing susceptible and infected cells over time. The dynamics of the viral enzyme PLpro showed reduced activity with the introduction of the inhibitor, leading to a decline in viral replication. Moreover, the immune cell population exhibited functional recovery as the inhibitor suppressed PLpro activity. These findings suggest that inhibitors targeting PLpro may serve as therapeutic interventions against SARS-CoV-2 by inhibiting viral replication and bolstering the immune response.</p></div>","PeriodicalId":52875,"journal":{"name":"Journal of Biosafety and Biosecurity","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-08-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2588933824000372/pdfft?md5=fdbf876165b0e2e2b70466ae5d584222&pid=1-s2.0-S2588933824000372-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141978304","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Multi-scale context-aware network for continuous sign language recognition","authors":"","doi":"10.1016/j.vrih.2023.06.011","DOIUrl":"10.1016/j.vrih.2023.06.011","url":null,"abstract":"<div><p>The hands and face are the most important parts for expressing sign language morphemes in sign language videos. However, we find that existing Continuous Sign Language Recognition (CSLR) methods lack the mining of hand and face information in visual backbones or use expensive and time-consuming external extractors to explore this information. In addition, the signs have different lengths, whereas previous CSLR methods typically use a fixed-length window to segment the video to capture sequential features and then perform global temporal modeling, which disturbs the perception of complete signs. In this study, we propose a Multi-Scale Context-Aware network (MSCA-Net) to solve the aforementioned problems. Our MSCA-Net contains two main modules: <strong>(</strong>1) Multi-Scale Motion Attention (MSMA), which uses the differences among frames to perceive information of the hands and face in multiple spatial scales, replacing the heavy feature extractors; and <strong>(</strong>2) Multi-Scale Temporal Modeling (MSTM), which explores crucial temporal information in the sign language video from different temporal scales. We conduct extensive experiments using three widely used sign language datasets, i.e., RWTH-PHOENIX-Weather-2014, RWTH-PHOENIX-Weather-2014T, and CSL-Daily. The proposed MSCA-Net achieve state-of-the-art performance, demonstrating the effectiveness of our approach.</p></div>","PeriodicalId":33538,"journal":{"name":"Virtual Reality Intelligent Hardware","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2096579623000414/pdfft?md5=d9cac344d105f6ddc495c1cb1e50a67a&pid=1-s2.0-S2096579623000414-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142039960","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"MKEAH： Multimodal knowledge extraction and accumulation based on hyperplane embedding for knowledge-based visual question answering","authors":"","doi":"10.1016/j.vrih.2023.06.002","DOIUrl":"10.1016/j.vrih.2023.06.002","url":null,"abstract":"<div><h3>Background</h3><p>External knowledge representations play an essential role in knowledge-based visual question and answering to better understand complex scenarios in the open world. Recent entity-relationship embedding approaches are deficient in representing some complex relations, resulting in a lack of topic-related knowledge and redundancy in topic-irrelevant information.</p></div><div><h3>Methods</h3><p>To this end, we propose MKEAH: Multimodal Knowledge Extraction and Accumulation on Hyperplanes. To ensure that the lengths of the feature vectors projected onto the hyperplane compare equally and to filter out sufficient topic-irrelevant information, two losses are proposed to learn the triplet representations from the complementary views: range loss and orthogonal loss. To interpret the capability of extracting topic-related knowledge, we present the Topic Similarity (TS) between topic and entity-relations.</p></div><div><h3>Results</h3><p>Experimental results demonstrate the effectiveness of hyperplane embedding for knowledge representation in knowledge-based visual question answering. Our model outperformed state-of-the-art methods by 2.12% and 3.24% on two challenging knowledge-request datasets: OK-VQA and KRVQA, respectively.</p></div><div><h3>Conclusions</h3><p>The obvious advantages of our model in TS show that using hyperplane embedding to represent multimodal knowledge can improve its ability to extract topic-related knowledge.</p></div>","PeriodicalId":33538,"journal":{"name":"Virtual Reality Intelligent Hardware","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2096579623000268/pdfft?md5=74ea90656cf281de7a0e35aa5b55705b&pid=1-s2.0-S2096579623000268-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142039957","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Robust blind image watermarking based on interest points","authors":"","doi":"10.1016/j.vrih.2023.06.012","DOIUrl":"10.1016/j.vrih.2023.06.012","url":null,"abstract":"<div><p>Digital watermarking technology plays an essential role in the work of anti-counterfeiting and traceability. However, image watermarking algorithms are weak against hybrid attacks, especially geometric at-tacks, such as cropping attacks, rotation attacks, etc. We propose a robust blind image watermarking algorithm that combines stable interest points and deep learning networks to improve the robustness of the watermarking algorithm further. First, to extract more sparse and stable interest points, we use the Superpoint algorithm for generation and design two steps to perform the screening procedure. We first keep the points with the highest possibility in a given region to ensure the sparsity of the points and then filter the robust interest points by hybrid attacks to ensure high stability. The message is embedded in sub-blocks centered on stable interest points using a deep learning-based framework. Different kinds of attacks and simulated noise are added to the adversarial training to guarantee the robustness of embedded blocks. We use the ConvNext network for watermark extraction and determine the division threshold based on the decoded values of the unembedded sub-blocks. Through extensive experimental results, we demonstrate that our proposed algorithm can improve the accuracy of the network in extracting information while ensuring high invisibility between the embedded image and the original cover image. Comparison with previous SOTA work reveals that our algorithm can achieve better visual and numerical results on hybrid and geometric attacks.</p></div>","PeriodicalId":33538,"journal":{"name":"Virtual Reality Intelligent Hardware","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2096579623000426/pdfft?md5=0d46d851b07db92670b0c63431ec427e&pid=1-s2.0-S2096579623000426-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142039959","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Generating animatable 3D cartoon faces from single portraits","authors":"","doi":"10.1016/j.vrih.2023.06.010","DOIUrl":"10.1016/j.vrih.2023.06.010","url":null,"abstract":"<div><h3>Background</h3><p>With the development of virtual reality (VR) technology, there is a growing need for customized 3D avatars. However, traditional methods for 3D avatar modeling are either time-consuming or fail to retain the similarity to the person being modeled. This study presents a novel framework for generating animatable 3D cartoon faces from a single portrait image.</p></div><div><h3>Methods</h3><p>First, we transferred an input real-world portrait to a stylized cartoon image using StyleGAN. We then proposed a two-stage reconstruction method to recover a 3D cartoon face with detailed texture. Our two-stage strategy initially performs coarse estimation based on template models and subsequently refines the model by nonrigid deformation under landmark supervision. Finally, we proposed a semantic-preserving face-rigging method based on manually created templates and deformation transfer.</p></div><div><h3>Conclusions</h3><p>Compared with prior arts, the qualitative and quantitative results show that our method achieves better accuracy, aesthetics, and similarity criteria. Furthermore, we demonstrated the capability of the proposed 3D model for real-time facial animation.</p></div>","PeriodicalId":33538,"journal":{"name":"Virtual Reality Intelligent Hardware","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2096579623000359/pdfft?md5=e0641053e4314662ffe5dca1c167d86b&pid=1-s2.0-S2096579623000359-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142039958","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"S2ANet: Combining local spectral and spatial point grouping for point cloud processing","authors":"","doi":"10.1016/j.vrih.2023.06.005","DOIUrl":"10.1016/j.vrih.2023.06.005","url":null,"abstract":"<div><h3>Background</h3><p>Despite the recent progress in 3D point cloud processing using deep convolutional neural networks, the inability to extract local features remains a challenging problem. In addition, existing methods consider only the spatial domain in the feature extraction process.</p></div><div><h3>Methods</h3><p>In this paper, we propose a spectral and spatial aggregation convolutional network (S²ANet), which combines spectral and spatial features for point cloud processing. First, we calculate the local frequency of the point cloud in the spectral domain. Then, we use the local frequency to group points and provide a spectral aggregation convolution module to extract the features of the points grouped by the local frequency. We simultaneously extract the local features in the spatial domain to supplement the final features.</p></div><div><h3>Results</h3><p>S²ANet was applied in several point cloud analysis tasks; it achieved state-of-the-art classification accuracies of 93.8%, 88.0%, and 83.1% on the ModelNet40, ShapeNetCore, and ScanObjectNN datasets, respectively. For indoor scene segmentation, training and testing were performed on the S3DIS dataset, and the mean intersection over union was 62.4%.</p></div><div><h3>Conclusions</h3><p>The proposed S²ANet can effectively capture the local geometric information of point clouds, thereby improving accuracy on various tasks.</p></div>","PeriodicalId":33538,"journal":{"name":"Virtual Reality Intelligent Hardware","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2096579623000360/pdfft?md5=718a7d943dc6468abf44b38521bcc2cb&pid=1-s2.0-S2096579623000360-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142039956","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}