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28th International Conference on Database systems for Advanced Applications, DASFAA 2023

作者： Li, Dong Wang, Pancheng He, Liangliang Pang, Kunyuan Li, Shasha Tang, Jintao Wang, Ting College of Computer Science and Technology National University of Defense Technology Changsha China Key Laboratory of Software Engineering for Complex Systems Changsha China

ISBN: (纸本)9783031306747

The Winograd Schema Challenge (WSC) is a popular benchmark for commonsense reasoning. Each WSC instance has a component that corresponds to the mention of the correct answer option of the two options in the context. We observe that the answers of many instances are insensitive to the options. In this paper, based on this observation, we propose an approach based on fine-tuning the pre-trained language model for WSC by distinguishing sensitive and insensitive options. First, we split WSC instances into option-sensitive and insensitive categories, and use option expanding and option masking strategies to weaken the options so that the model does not pay attention to options when they are insensitive during fine-tuning. Second, we treat the two categories as intermediate-task of each other, and use transfer learning to improve the performance. We fine-tune BERT-Large and T5-XXL with our approach on WINOGRANDE, a new dataset of WSC, and the experiment shows our method outperforms baselines by a large margin, achieving state-of-the-art, which indicates the effectiveness of our instance-distinguishing strategy. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Large dataset

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Fiber Optic Devices for High-Resolution Refractive Index Sensing

Fiber Optic Devices for High-Resolution Refractive Index Sen...

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2023 Photonics and Electromagnetics Research Symposium, PIERS 2023

作者： Pevec, S. Njegovec, M. Javornik, J. Donlagic, D. University of Maribor Laboratory for Electro Optics and Sensor Systems Faculty of Electrical Engineering and Computer Science Koroska cesta 46 Maribor2000 Slovenia

ISBN: (纸本)9798350312843

The paper describes a fiber optic Fabry-Perot (FP) refractive index (RI) sensors that provide performances required in gas sensing applications. Presented high-resolution FabryPerot Interferometer (FPI) sensors are based on open-path cells that can be integrated with the optical fiber in different ways. They can be fabricated as microcells on the fiber tip or along the optical fiber, or as external/extrinsic gas cells connected to the fiber. All presented configurations are based on low-finesse FPI as they allow for a simple and cost-efficient designs. © 2023 IEEE.

关键词： Optical fibers

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The Role of Generative AI in Deepfake Detection: A Systematic Literature Review

The Role of Generative AI in Deepfake Detection: A Systemati...

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International Conference on Smart Business and technology, ICSBT 2024

作者： Acim, Btissam Kharmoum, Nassim Lagmiri, Souad Najoua Ziti, Soumia Department of Computer Science Intelligent Processing & Security of Systems Faculty of Sciences Mohammed V University in Rabat Rabat Morocco Rabat Morocco IT Networking Security and Management Laboratory Higher Institute of Management Administration and Computer Engineering Rabat Morocco

ISBN: (纸本)9783031866975

There is a possibility that deepfakes will increase a great deal of false information in a very realistic way, but it seems that today such technology appears to be extremely dangerous. While generative Artificial Intelligence (AI) does expand possibilities and give an opportunity to achieve terrific outcomes and has innumerable potential uses. This systematic literature review focuses on the role of generative AI in the improvement of deepfake detection technologies, providing a comparison between different methods and assessing their effectiveness. By analyzing recent studies, it depicts the techniques employed most frequently in deepfake detection, such as the ones concentrating on the intricacies between the visual and auditory elements, the temporal domains, as well as any minor signs of alteration. Due to the fact that generative AI is rapidly improving, the methods that are used to detect its use are often inadequate, which calls for more studies on the subject matter. Besides, by combining audio and visual elements when performing the analysis, calling it as a method that can be useful in focusing the detection growth potential with diverse and unstructured data. Also, this study evaluates the advantages and limitations of the techniques existing today and demonstrates their relative effectiveness in controlled and real conditions. Clarifying that measures aimed at detecting AI generated content should be preoccupied with a technique that is able to keep pace with changes in generative AI. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Generative adversarial networks

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Training Graph Neural Networks on Growing Stochastic Graphs 48

Training Graph Neural Networks on Growing Stochastic Graphs

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48th IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2023

作者： Cerviño, Juan Ruiz, Luana Ribeiro, Alejandro University of Pennsylvania Department of Electrical and Systems Engineering Philadelphia United States Mit Computer Science & Artificial Intelligence Laboratory Cambridge United States

ISBN: (纸本)9781728163277

Graph Neural Networks (GNNs) rely on graph convolutions to exploit meaningful patterns in networked data. Based on matrix multiplications, convolutions incur in high computational costs leading to scalability limitations in practice. To overcome these limitations, proposed methods rely on training GNNs in smaller number of nodes, and then transferring the GNN to larger graphs. Even though these methods are able to bound the difference between the output of the GNN with different number of nodes, they do not provide guarantees against the optimal GNN on the very large graph. In this paper, we propose to learn GNNs on very large graphs by leveraging the limit object of a sequence of growing graphs, the graphon. We propose to grow the size of the graph as we train, and we show that our proposed methodology - learning by transference - converges to a neighborhood of a first order stationary point on the graphon data. A numerical experiment validates our proposed approach. © 2023 IEEE.

关键词： Graph Neural Networks Graphons

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Parallelism or Fairness? How to Be Friendly for SSDs in Cloud Environments

Parallelism or Fairness? How to Be Friendly for SSDs in Clou...

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2024 IEEE International Conference on Cluster Computing, CLUSTER 2024

作者： Zhou, Yang Wang, Fang Shi, Zhan Feng, Dan Engineering Research Center of Data Storage Systems and Technology Ministry of Education of China Wuhan National Laboratory for Optoelectronics Key Laboratory of Information Storage System Wuhan China School of Computer Science and Technology Huazhong University of Science and Technology Wuhan China

ISBN: (纸本)9798350358711

Modern SSDs achieve low latency and high throughput by utilizing multiple levels of SSD parallelism. Fairness is also a critical design consideration in cloud environments and has inspired great interest in recent years to study it. However, we find that excessive striving for SSD parallelism can inadvertently harm the SSD fairness due to the striped data layout. We observe from our experimental analysis that some common access patterns in cloud loads (e.g., high-intensity I/O) are not addressed by SSD parallelism, which can affect both SSD parallelism and fairness. In this paper, we analyze two address mapping policies with orthogonal characteristics from SSD parallelism and fairness perspectives. Based on extensive experiments and observations, we schedule a hybrid address mapping policy to achieve fairness of SSDs in cloud environments by distinguishing different I/O access modes and cold/hot data, while ensuring SSD performance. Experimental results on the latest block-level I/O traces show that our approach significantly improves performance and fairness by up to 77.3% and 62.8%, respectively, over the previous schemes with negligible cost. Meanwhile, it can also reduce the write amplification by 23.5% to 33.5%. © 2024 IEEE.

关键词： Cloud platforms

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Disentangling Spatio-Temporal Knowledge for Weakly Supervised Object Detection and Segmentation in Surgical Video

Disentangling Spatio-Temporal Knowledge for Weakly Supervise...

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2025 IEEE/CVF Winter Conference on Applications of computer Vision, WACV 2025

作者： Liao, Guiqiu Jogan, Matjaz Koushik, Sai Eaton, Eric Hashimoto, Daniel A. University of Pennsylvania Pcaso Laboratory Department of Surgery United States University of Pennsylvania Department of Electrical and Systems Engineering United States University of Pennsylvania Department of Computer and Information Science United States

ISBN: (纸本)9798331510831

Weakly supervised video object segmentation (WSVOS) enables the identification of segmentation maps without requiring extensive annotations of object masks, relying instead on coarse video labels indicating object presence. WSVOS in surgical videos is, however, more challenging due to the complex interaction of multiple transient objects, such as surgical tools moving in and out of the surgical field. In this scenario, state-of-the-art WSVOS methods struggle to learn accurate segmentation maps. We address this problem by introducing ViDeo Spatio-Temporal disentanglement Networks (VDST-Net), a framework to disentangle complex spatio-temporal object interactions using semi-decoupled knowledge distillation to predict high-quality class activation maps (CAMs). A teacher network is designed to help a temporal-reasoning student network resolve activation conflicts, as the student leverages temporal dependencies when specifics about object location and timing in the video are not provided. We demonstrate the efficacy of our framework on a challenging surgical video dataset where objects are, on average, present in less than 60% of annotated frames, and compare our method to state-of-the-art methods on surgical data and on a public dataset commonly used to benchmark WSVOS. Our method outperforms state-of-the-art techniques and generates accurate segmentation masks under video-level weak supervision. Our code is available at: https://***/PCASOlab/VDST-net. © 2025 IEEE.

关键词： Image segmentation

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A Monadic Second-Order Temporal Logic framework for hypergraphs

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Neural Computing and Applications 2024年第35期36卷 22081-22118页

作者： Bhuyan, Bikram Pratim Singh, T.P. Tomar, Ravi Meraihi, Yassine Ramdane-Cherif, Amar LISV Laboratory University of Paris Saclay 10-12 Avenue of Europe Velizy78140 France School of Computer Science University of Petroleum and Energy Studies Uttarakhand Bidholi Dehra Dun248006 India School of Computer Science Engineering and Technology Bennett University Greater Noida201306 India Persistent Systems Mumbai Pune411016 India LIST Laboratory University of M’Hamed Bougara Boumerdes Avenue of Independence Boumerdes35000 Algeria

This study introduces a novel computational framework integrating monadic second-order temporal logic (MSOTL) with hypergraph models to enhance the predictive analysis and prediction of complex systems, with a specific focus on urban agriculture. Traditional graph-based models often fail to capture the intricate, high-order temporal dynamics inherent in such systems. By leveraging the expressive power of MSOTL within a hypergraph context, our approach enables a more nuanced representation of temporal and relational data, leading to improved predictive accuracy and deeper analytical insights. The framework was applied to a comprehensive dataset of urban agricultural practices, incorporating data from diverse farming sites across multiple countries. Our results demonstrate the model’s capability to outperform existing methods in predicting agricultural outcomes by effectively capturing both the spatial and temporal complexities of urban farming data. The study not only advances the theoretical understanding of hypergraph-based temporal logic modeling but also offers an application for urban agricultural planning and management. © The Author(s), under exclusive licence to Springer-Verlag London Ltd., part of Springer Nature 2024.

关键词： Temporal logic

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Movable surface acoustic wave tweezers: a versatile toolbox for micromanipulation

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Microsystems & Nanoengineering 2024年第5期10卷 367-380页

作者： Xianming Qin Xianglian Liu Shuo Liu Chuanyu Zhang Ningning Bai Xue Li Weidong Wang Dan Liu Qiqi Yang Ruiguo Yang Yajing Shen Xueyong Wei School of Mechano-Electronic Engineering Xidian UniversityXi'an 710071China State Key Laboratory for Manufacturing Systems Engineering Xi'an Jiaotong UniversityXi'an 710049China State Key Laboratory of Electromechanical Integrated Manufacturing of High-Performance Electronic Equipment Xidian UniversityXian 710071China State Key Laboratory of Holistic Integrative Management of Gastrointestinal Cancers and National Clinical Research Center for Digestive Diseases Xijing Hospital of Digestive DiseasesFourth Military Medical UniversityXi'an 710032China Department of Biomedical Engineering and Institute for Quantitative Health Science and Engineering(IQ)Michigan State UniversityEast LansingMI 48824USA Department of Electronic and Computer Engineering The Hong Kong University of Science and TechnologyClear Water BayKowloonHong KongChina

Surface acoustic wave(SAW)tweezers are a promising multifunctional micromanipulation method that controls microscale targets via patterned acoustic *** to their device structure and bonding process,most SAW tweezers have limitations in terms of controlling the position and motion of the acoustic traps,as they generate an acoustic field with a fixed region and adjust the manipulation effects via signal *** address this challenge,we propose movable SAW tweezers with a multilayer structure,achieving dynamic control of their wave field and acoustic trap positions;we demonstrate their precise manipulation functions,such as translation,in-plane rotation,out-of-plane rotation,and cluster formation,on a wide spectrum of samples,including particles,bubbles,droplets,cells,and *** method not only improves the degree of freedom and working range of SAW tweezers but also allows for precise and selective manipulation of microtargets via microtools and localized *** to their flexibility,versatility,and biocompatibility,the movable SAW tweezers can be a practical platform for achieving arbitrary manipulation of microscale targets and have the potential to play significant roles in biomedical microrobotics.

关键词： wave precise rotation

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MSEs Credit Risk Assessment Model Based on Federated Learning and Feature Selection

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computers, Materials & Continua 2023年第6期75卷 5573-5595页

作者： Zhanyang Xu Jianchun Cheng Luofei Cheng Xiaolong Xu Muhammad Bilal School of Computer and Software Nanjing University of Information Science&TechnologyNanjing210044China State Key Laboratory Novel Software Technology Nanjing UniversityNanjing210023China Department of Computer and Electronics Systems Engineering Hankuk University of Foreign StudiesYongin-siGyeonggi-do17035Korea

Federated learning has been used extensively in business inno-vation scenarios in various *** research adopts the federated learning approach for the first time to address the issue of bank-enterprise information asymmetry in the credit assessment ***,this research designs a credit risk assessment model based on federated learning and feature selection for micro and small enterprises(MSEs)using multi-dimensional enterprise data and multi-perspective enterprise *** proposed model includes four main processes:namely encrypted entity alignment,hybrid feature selection,secure multi-party computation,and global model ***,a two-step feature selection algorithm based on wrapper and filter is designed to construct the optimal feature set in multi-source heterogeneous data,which can provide excellent accuracy and *** addition,a local update screening strategy is proposed to select trustworthy model parameters for aggregation each time to ensure the quality of the global *** results of the study show that the model error rate is reduced by 6.22%and the recall rate is improved by 11.03%compared to the algorithms commonly used in credit risk research,significantly improving the ability to identify ***,the business operations of commercial banks are used to confirm the potential of the proposed model for real-world implementation.

关键词： Federated learning feature selection credit risk assessment MSEs

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Improving the stockpiling sites for inbound, outbound containers by timing the place of stacking

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International Journal of Information Technology (Singapore) 2023年第6期15卷 3071-3077页

作者： Saleh, Mohammed Ahmed Moqbel Hicham, Attariuas Ben Maâti, M.L. Taha, Hatem Admeur, Smail Computer Science and Systems Engineering Laboratory Faculty of Science University of Abdelmalek Essaadi Tetouan Morocco Research Operational and Statistic Applied (LAROSA) Faculty of Sciences Abdelmalek Essaâdi University Tetouan Morocco

Seaports face rising pressure in container stacking. Nations are endeavoring to get the most advantage from it, increase their portion of this area’s assets, and achieve their aspirations. Because of this increment, the ports experience the bad effects of numerous issues, including how to make the proper choice to store and extract different containers. In this paper, The method for stacking containers in a suitable location has been proposed in the maritime terminal in light of the speculation of time’s elements for choosing the ideal position for the container in the yard in light of the speculation of time’s elements for choosing the ideal position for the container in the yard. This method gives ideal capacity areas to organize containers by time to stay away from random scattering. The scattering of containers is not a solution to stacking because it causes retrieval issues. As well as to give more flexibility during work with the option of reorganizing containers that should be put away in the terminal to permit the arrangement of new stockpiling places that decrease time and working expenses. This work contributes to the decision about organizing the stacking of containers. We propose to apply artificial intelligence techniques to take an optimal decision for stacking the containers that have various departure dates in light of the fact that artificial intelligence algorithms read the data styles in the historical data and predict the optimal solution for new inputs. © 2023, The Author(s), under exclusive licence to Bharati Vidyapeeth's Institute of computer Applications and Management.

关键词： Artificial intelligence Container terminal Container time Improve container stacking Real-time stacking

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