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arXiv 2022年

作者： Jmal, Sohail Ait Balli, Sohail Ait Bouhani, Hamza Mounkachi, Omar AMEEC Team LERMA International University of Rabat Parc Technopolis Rocade de Rabat- Salé 11100 Morocco Complex Systems and Interactions Ecole Centrale Casablanca Morocco Laboratory of Condensed Matter and Interdisciplinary Sciences Department of Physics Faculty of Sciences Mohammed V University in Rabat PO Box 1014 Rabat Morocco Modeling Simulation & Data Analysis Program Mohammed VI Polytechnic University Ben Guerir43150 Morocco

In this paper, we investigate the influence of the rare earth element (R) on the physical properties of RVO3 (R = Er, Ho, Y, Lu). For this purpose, a theoretical work is reported in this study using ab initio method with the intent of enhancing our knowledge of the electronic, and magnetic properties of RVO3 (R = Er, Ho, Y, Lu) compounds. The electronic properties of these materials show the presence of Jahn-Teller effect, with a band gap of approximately 0.58eV, 1.57eV, 1.12eV, 1.28eV, for ErVO3, HoVO3, YVO3, LuVO3, respectively. The magnetic contribution of Ho, Er, and V atoms in HoVO3, and ErVO3 compounds was disentangled using X-ray magnetic circular dichroism (XMCD). The magnetic anisotropies of RVO3 with (R = Er, Ho, Y, Lu) are studied and analyzed using spin orbit coupling. We noticed an easy axis of magnetization along the c-direction with strong magneto-crystalline anisotropy energies for the non-magnetic rare earth elements (R = Lu, Y)VO3. For the magnetic rare earth elements, the easy and hard magnetization direction were found to be along b-axis and c-axis, and a- axis and c-axis for HoVO3, and ErVO3, respectively. This means that instead of the standard magnetization demagnetization process, large thermal effects can be obtained by spinning their single crystals in constant magnetic fields. The exchange coupling between (Ho-V) is also found to be greater than the other exchange interactions in HoVO3. Accordingly, a large conventional magnetocaloric effect could be created in HoVO3, since the Ho Ising moments experience a metamagnetic transition. However, the magnetocaloric effect (MCE) is expected to be lower in ErVO3 due to the weak (Er-V) exchange coupling. © 2022, CC BY.

关键词： Holmium compounds

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Multi-task Paired Masking with Alignment modeling for Medical Vision-Language Pre-training

arXiv

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arXiv 2023年

作者： Zhang, Ke Yang, Yan Yu, Jun Jiang, Hanliang Fan, Jianping Huang, Qingming Han, Weidong The Key Laboratory of Complex Systems Modeling and Simulation School of Computer Science and Technology Hangzhou Dianzi University Hangzhou310018 China Regional Medical Center for National Institute of Respiratory Diseases Sir Run Run Shaw Hospital College of Medicine Zhejiang University Hangzhou310016 China AI Lab at Lenovo Research 100094 China The School of Computer Science and Technology University of Chinese Academy of Sciences Beijing101408 China The Department of Medical Oncology at Sir Run Run Shaw Hospital College of Medicine Zhejiang University Hangzhou China The College of Mathematical Medicine Zhejiang Normal University Jinhua China

In recent years, the growing demand for medical imaging diagnosis has placed a significant burden on radiologists. As a solution, Medical Vision-Language Pre-training (Med-VLP) methods have been proposed to learn universal representations from medical images and reports, benefiting downstream tasks without requiring fine-grained annotations. However, existing methods have overlooked the importance of cross-modal alignment in joint image-text reconstruction, resulting in insufficient cross-modal interaction. To address this limitation, we propose a unified Med-VLP framework based on Multi-task Paired Masking with Alignment (MPMA) to integrate the cross-modal alignment task into the joint image-text reconstruction framework to achieve more comprehensive cross-modal interaction, while a Global and Local Alignment (GLA) module is designed to assist self-supervised paradigm in obtaining semantic representations with rich domain knowledge. Furthermore, we introduce a Memory-Augmented Cross-Modal Fusion (MA-CMF) module to fully integrate visual information to assist report reconstruction and fuse the multi-modal representations adequately. Experimental results demonstrate that the proposed unified approach outperforms previous methods in all downstream tasks, including uni-modal, cross-modal, and multimodal tasks. Copyright © 2023, The Authors. All rights reserved.

关键词： Alignment

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PARDA: A dataset for scholarly PDF document metadata extraction evaluation 14th

PARDA: A dataset for scholarly PDF document metadata extract...

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14th EAI International Conference on Collaborative Computing: Networking, Applications and Worksharing, CollaborateCom 2018

作者： Fan, Tiantian Liu, Junming Qiu, Yeliang Jiang, Congfeng Zhang, Jilin Zhang, Wei Wan, Jian School of Computer Science and Technology Hangzhou Dianzi University Hangzhou310018 China Key Laboratory of Complex Systems Modeling and Simulation Ministry of Education Hangzhou310018 China School of Information and Electronic Engineering Zhejiang University of Science and Technology Hangzhou310023 China

ISBN: (纸本)9783030129804

Metadata extraction from scholarly PDF documents is the fundamental work of publishing, archiving, digital library construction, bibliometrics, and scientific competitiveness analysis and evaluations. However, different scholarly PDF documents have different layout and document elements, which make it impossible to compare different extract approaches since testers use different source of test documents even if the documents are from the same journal or conference. Therefore, standard datasets based performance evaluation of various extraction approaches can setup a fair and reproducible comparison. In this paper we present a dataset, namely, PARDA(Pdf Analysis and Recognition DAtaset), for performance evaluation and analysis of scholarly documents, especially on metadata extraction, such as title, authors, affiliation, author-affiliation-email matching, year, date, etc. The dataset covers computer science, physics, life science, management, mathematics, and humanities from various publishers including ACM, IEEE, Springer, Elsevier, arXiv, etc. And each document has distinct layouts and appearance in terms of formatting of metadata. We also construct the ground truth metadata in Dublin Core XML format and BibTex format file associated this dataset. © 2019, ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering.

关键词： Metadata

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Energy aware edge computing: a survey 2nd

Energy aware edge computing: a survey

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2nd International Workshop on High Performance Computing for Advanced modeling and simulation in Nuclear Energy and Environmental Science, HPCMS 2018, and 1st International Workshop on HPC Supported Data Analytics for Edge Computing, HiDEC 2018 held at the 32nd ACM International Conference on Supercomputing, ACM ICS 2018

作者： Fan, Tiantian Qiu, Yeliang Jiang, Congfeng Wan, Jian Key Laboratory of Complex Systems Modeling and Simulation Hangzhou Dianzi University Hangzhou310018 China School of Computer Science and Technology Hangzhou Dianzi University Hangzhou310018 China School of Information and Electronic Engineering Zhejiang University of Science and Technology Hangzhou310023 China

ISBN: (纸本)9789813299863

Edge computing is an emerging paradigm to meet the ever-increasing computation demands from pervasive devices such as sensors, actuators, and smart things. Though the edge devices can execute complex applications, it is necessary for some applications to migrate to centralized servers. By offloading the computation from the edge nodes to the edge servers or cloud servers, the quality of computation experience could be greatly improved. However, it may cause delay and increase network overheads, and energy consumption eventually. Therefore, an optimal offloading strategy should take into account what task should be offloaded, when to offload and where to offload to avoid the overheads. Thus, it is important to tradeoff between energy consumption, computation delay and throughput when the system makes the computation offloading to achieve high energy efficiency. In this paper, we conduct a survey of energy aware edge computing, including the existing work on computation offloading frameworks and strategies in edge computing. Specifically, we describe the strategies from the perspective of energy aware offloading, energy optimization offloading and offloading algorithms. © Springer Nature Singapore Pte Ltd 2019.

关键词： Energy efficiency

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An edge computing platform for intelligent internet data center operational monitoring 2nd

An edge computing platform for intelligent internet data cen...

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作者： Qiu, Yeliang Jiang, Congfeng Fan, Tiantian Wan, Jian Key Laboratory of Complex Systems Modeling and Simulation Hangzhou Dianzi University Hangzhou310018 China School of Computer Science and Technology Hangzhou Dianzi University Hangzhou310018 China School of Information and Electronic Engineering Zhejiang University of Science and Technology Hangzhou310023 China

ISBN: (纸本)9789813299863

The explosive growth in cloud-based services, big data analytics, and artificial intelligence related services provisioning leads to the rapid growth of construction of large scale Internet data centers (IDCs). Modern IDCs are equipped with various sensors to monitor its healthy operation and maintenance states, such as temperature, thermal distribution, air flow, etc. However, fine-grained, single-node level and even mainboard level monitoring including server resource consumption and power consumption is still needed for more progressive resource multiplexing and job scheduling in IDCs. In this paper, we propose an edge computing platform for intelligent Internet data center operational monitoring, which integrates wireless sensors and on-board built-in sensors to sense and collect the data of data center operation and maintenance. The edge computing based solution reduces the latency for data transportation to central clouds and reduces the amount of data and enhances the real time resource capping decisions in data centers. © Springer Nature Singapore Pte Ltd 2019.

关键词： Energy efficiency

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Towards computation offloading in edge computing: A survey 2nd

Towards computation offloading in edge computing: A survey

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作者： Cheng, Xiaolan Zhou, Xin Jiang, Congfeng Wan, Jian Key Laboratory of Complex Systems Modeling and Simulation Hangzhou Dianzi University Hangzhou310018 China School of Computer Science and Technology Hangzhou Dianzi University Hangzhou310018 China School of Information and Electronic Engineering Zhejiang University of Science and Technology Hangzhou310023 China

ISBN: (纸本)9789813299863

The explosive growth of massive data generation from Internet of Things in industrial, agricultural and scientific communities has led to a rapid increase in cloud data centers for data analytics. The ubiquitous and pervasive demand for near-data processing urges the edge computing paradigm in recent years. Edge computing is promising for less network backbone bandwidth usage and thus less data center side processing, as well as enhanced service responsiveness and data privacy protection. Computation offloading plays a crucial role in network packets transmission and system responsiveness through dynamic task partitioning between cloud data centers and edge servers and edge devices. In this paper a thorough literature review is conduct to reveal the state-of-the-art of computation offloading in edge computing. Various aspects of computation offloading, including energy consumption minimization, Quality of Services (QoS), and Quality of Experiences (QoE) are surveyed. Resource scheduling approaches, gaming and tradeoffing among system performance and system overheads for offloading decision making are also reviewed. © Springer Nature Singapore Pte Ltd 2019.

关键词： computation offloading

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Query modeling for click data based image recognition using graph based propagation and sparse coding

Query modeling for click data based image recognition using ...

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9th International Conference on Internet Multimedia Computing and Service, ICIMCS 2017

作者： Wu, Weichen Tan, Min Zheng, Guangjian Yu, Jun Key Laboratory of Complex Systems Modeling and Simulation School of Computer Science and Technology Hangzhou Dianzi University Hangzhou310018 China

ISBN: (纸本)9789811085291

We address the fine-grained image recognition problem using user click data, wherein each image is represented as a semantical query-click feature vector. Usually, the query set obtained from search engines is large-scale and redundant. We propose a novel query modeling approach to merge semantically similar queries and construct a compact click feature. We represent each query as a click feature, and design a graph based propagation approach to predict the zero-clicks, ensuring similar images have similar clicks. Afterwards, using this feature, we formulate the problem as a sparse coding based recognition task, wherein the dictionary is discriminatively trained. We evaluate our method for fine-grained image recognition on the public Clickture-Dog dataset. It is shown that, the propagated click feature performs much better than the original one. Also, sparse coding performs better than K-means in query merging. © Springer Nature Singapore Pte Ltd. 2018.

关键词： Image recognition

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On Exploring Undetermined Relationships for Visual Relationship Detection

On Exploring Undetermined Relationships for Visual Relations...

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IEEE/CVF Conference on Computer Vision and Pattern Recognition

作者： Yibing Zhan Jun Yu Ting Yu Dacheng Tao Key Laboratory of Complex Systems Modeling and Simulation School of Computer Science and Technology Hangzhou Dianzi University UBTECH Sydney AI Centre School of Computer Science FEIT University of Sydney

ISBN: (纸本)9781728132945

In visual relationship detection, human-notated relationships can be regarded as determinate relationships. However, there are still large amount of unlabeled data, such as object pairs with less significant relationships or even with no relationships. We refer to these unlabeled but potentially useful data as undetermined relationships. Although a vast body of literature exists, few methods exploit these undetermined relationships for visual relationship detection. In this paper, we explore the beneficial effect of undetermined relationships on visual relationship detection. We propose a novel multi-modal feature based undetermined relationship learning network (MF-URLN) and achieve great improvements in relationship detection. In detail, our MF-URLN automatically generates undetermined relationships by comparing object pairs with human-notated data according to a designed criterion. Then, the MF-URLN extracts and fuses features of object pairs from three complementary modals: visual, spatial, and linguistic modals. Further, the MF-URLN proposes two correlated subnetworks: one subnetwork decides the determinate confidence, and the other predicts the relationships. We evaluate the MF-URLN on two datasets: the Visual Relationship Detection (VRD) and the Visual Genome (VG) datasets. The experimental results compared with state-of-the-art methods verify the significant improvements made by the undetermined relationships, e.g., the top-50 relation detection recall improves from 19.5% to 23.9% on the VRD dataset.

关键词： Visualization Fuses Dataset

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Deep Point Convolutional Approach for 3D Model Retrieval

Deep Point Convolutional Approach for 3D Model Retrieval

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IEEE International Conference on Multimedia and Expo (ICME)

作者： Zhenzhong Kuang Jun Yu Jianping Fan Min Tan Key Laboratory of Complex Systems Modeling and Simulation Hangzhou Dianzi University

With the increasing popularity of 3D models, retrieving deformable 3D objects is becoming a crucial task. The state-of-the-art methods use complex deep neural networks to address this problem, which require lots of computational resources. In this paper, we develop a more effective solution by using point convolution. Our algorithm takes local point descriptors as the input and produces a global vector for shape retrieval. To save the efforts of designing complex deep convolutional neural network (CNN), we first use intrinsic point descriptors to describe the shape deformations. Then, a simple but effective point CNN network is developed to integrate the local shape information by performing subspace compression and fusion, which depends on an end-to-end learning process to link the local and global information for discriminative shape representation. The experimental results on popular benchmarks have verified that our algorithm is able to outperform the state-of-the-art methods.

关键词： Shape Three-dimensional displays Solid modeling Heating systems Strain Machine learning Feature extraction

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Deep Modular Co-Attention Networks for Visual Question Answering

Deep Modular Co-Attention Networks for Visual Question Answe...

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IEEE/CVF Conference on Computer Vision and Pattern Recognition

作者： Zhou Yu Jun Yu Yuhao Cui Dacheng Tao Qi Tian Key Laboratory of Complex Systems Modeling and Simulation School of Computer Science and Technology Hangzhou Dianzi University UBTECH Sydney AI Centre School of Computer Science FEIT University of Sydney Noah's Ark Lab

ISBN: (纸本)9781728132945

Visual Question Answering (VQA) requires a finegrained and simultaneous understanding of both the visual content of images and the textual content of questions. Therefore, designing an effective 'co-attention' model to associate key words in questions with key objects in images is central to VQA performance. So far, most successful attempts at co-attention learning have been achieved by using shallow models, and deep co-attention models show little improvement over their shallow counterparts. In this paper, we propose a deep Modular Co-Attention Network (MCAN) that consists of Modular Co-Attention (MCA) layers cascaded in depth. Each MCA layer models the self-attention of questions and images, as well as the question-guided-attention of images jointly using a modular composition of two basic attention units. We quantitatively and qualitatively evaluate MCAN on the benchmark VQA-v2 dataset and conduct extensive ablation studies to explore the reasons behind MCAN's effectiveness. Experimental results demonstrate that MCAN significantly outperforms the previous state-of-the-art. Our best single model delivers 70.63% overall accuracy on the test-dev set.

关键词： Modularity images Visualization system buses compensatory amounts Maximum credible accidents Layer models

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