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Unsupervised feature selection via adaptive embedding and sparse learning for Parkinson’s disease diagnosis 1

3rd International Workshop on Connectomics in NeuroImaging, CNI 2019 held in conjunction with the 22nd International Conference on Medical Image computing and Computer Assisted Intervention, MICCAI 2019

作者： Huang, Zhongwei Lei, Haijun Chen, Guoliang Li, Shiqi Li, Hancong Elazab, Ahmed Lei, Baiying Key Laboratory of Service Computing and Applications Guangdong Province Key Laboratory of Popular High Performance Computers College of Computer Science and Software Engineering Shenzhen University Shenzhen518060 China National-Regional Key Technology Engineering Laboratory for Medical Ultrasound Guangdong Key Laboratory for Biomedical Measurements and Ultrasound Imaging School of Biomedical Engineering Health Science Center Shenzhen University Shenzhen518060 China

ISBN: (数字)9783030323912

ISBN: (纸本)9783030323905

Parkinson’s disease (PD) is known as a progressive neurodegenerative disease in elderly people. Apart from decelerating the disease exacerbation, early and accurate diagnosis also alleviates mental and physical sufferings and provides timely and appropriate medication. In this paper, we propose an unsupervised feature selection method via adaptive manifold embedding and sparse learning exploiting longitudinal multimodal neuroimaging data for classification and regression prediction. Specifically, the proposed method simultaneously carries out feature selection and dynamic local structure learning to obtain the structural information inherent in the neuroimaging data. We conduct extensive experiments on the publicly available Parkinson’s progression markers initiative (PPMI) dataset to validate the proposed method. Our proposed method outperforms other state-of-the-art methods in terms of classification and regression prediction performance. © Springer Nature Switzerland AG 2019.

关键词： Neuroimaging

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VMScan: an out-of-VM malware scanner

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The Journal of China Universities of Posts and Telecommunications 2020年第4期27卷 59-68页

作者： Lin Jie Liu Chuanyi Fang Binxing School of Computer Science and Technology Harbin Institute of TechnologyShenzhenShenzhen 518055China Key Laboratory of Trustworthy Distributed Computing and Service Beijing University of Posts and TelecommunicationsBeijing 100876China Department of Information and Electronic Engineering Chinese Academy of EngineeringBeijing 100088China

The harm caused by malware in cloud computing environment is more and more serious. Traditional anti-virus software is in danger of being attacked when it is deployed in virtual machine on a large scale, and it tends not to be accepted by tenants in terms of performance. In this paper, a method of scanning malicious programs outside the virtual machine is proposed, and the prototype is implemented. This method transforms the memory of the virtual machine to the host machine so that the latter can access it. The user space and kernel space of virtual machine memory are analyzed via semantics, and suspicious processes are scanned by signature database. Experimental results show that malicious programs can be effectively scanned outside the virtual machine, and the performance impact on the virtual machine is low, meeting the needs of tenants.

关键词： security virtualization cloud malware virus detection signature scanning

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Incorporating language patterns and domain knowledge into feature-opinion extraction

Incorporating language patterns and domain knowledge into fe...

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17th International Conference on Text, Speech, and Dialogue, TSD 2014

作者： Zhou, Erqiang Luo, Xi Qin, Zhiguang School of Computer Science and Engineering University of Electronic Science and Technology of China No.2006 Xiyuan Ave Chengdu 611731 Sichuan China Guangdong Key Laboratory of Popular High Performance Computers Shenzhen Key Laboratory of Service Computing and Applications No. 3688 Nanhai Ave Shenzhen 518060 Guangdong China

ISBN: (纸本)9783319108155

We present a hybrid method for aspect-based sentiment analysis of Chinese restaurant reviews. Two main components are employed so as to extract feature-opinion pairs in the proposed method: domain independent language patterns found in Chinese and a lexical base built for restaurant reviews. The language patterns focus on the general knowledge which is implicit contained in Chinese, thus can be used directly by other domains without any modification. The lexical base, on the other hand, targets for particular characteristics of a given domain and acts as a plug-in part in our prototype system, thus does not affect the portability when applying the proposed approach in practice. Empirical evaluation shows that our method performs well and it can gain a progressive result when each component takes into effective. © 2014 Springer International Publishing.

关键词： Sentiment analysis

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Parallel Identifying Motifs in Biological Network on Multicore System

Parallel Identifying Motifs in Biological Network on Multico...

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2015全国理论计算机科学学术年会

作者： Cheng ZHONG Jing ZHAO Feng YANG Mengxiao YIN School of Computer and Electronics and Information Guangxi UniversityNanningChinaGuangdong Key Laboratory of Popular High Performance ComputersShenzhen Key Laboratory of Service Computing and ApplicationsShenzhenChina

The required time to indentify the motifs in biological networks will be sharply increased with increase of the scale of the original network or the size of motifs in the *** is very necessary to develop the fast algorithms to indentify larger motifs in large-scale biological networks.A thread-level parallel indentifying motifs algorithm is proposed on multicore machine, in which the local hash tables are used to store the subgraph SIKs mined by parallel threads and a task queue is used to dlistribute the data blocks to parallel threads to balance their loads.A dynamic task scheduling strategy is used to balance the loads among nodes on multi-core cluster, and an efficient parallel algorithn is designed to identify the motifs in biological *** experiment results in undirected network YeastPPI and directed network yeast show that compared with the existing parallel indentifying motifs algorithm, the presented parallel algorithms are faster and obtain good speedup, and it can identify larger motifs in the biological networks.

关键词： biological network motif identification multicore architecture parallel algorithms subgraph enumeration subgraph isomorphism task scheduling

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M2Trans: Multi-Modal Regularized Coarse-to-Fine Transformer for Ultrasound Image Super-Resolution

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IEEE Journal of Biomedical and Health Informatics 2024年第5期29卷 3112-3123页

作者： Ni, Zhangkai Xiao, Runyu Yang, Wenhan Wang, Hanli Wang, Zhihua Xiang, Lihua Sun, Liping Tongji University Department of Computer Science and Technology The Key Laboratory of Embedded System and Service Computing Ministry of Education Shanghai200092 China Pengcheng Laboratory Shenzhen518066 China Shenzhen MSU-BIT University Guangdong Laboratory of Machine Perception and Intelligent Computing Shenzhen518115 China Tongji University Shanghai Engineering Research Center of Ultrasound Diagnosis and Treatment Department of Medical Ultrasound Center of Tumor Minimally Invasive Treatment Shanghai Tenth Peoples Hospital Ultrasound Research and Education Institute Clinical Research Center for Interventional Medicine School of Medicine Shanghai200072 China

Ultrasound image super-resolution (SR) aims to transform low-resolution images into high-resolution ones, thereby restoring intricate details crucial for improved diagnostic accuracy. However, prevailing methods relying solely on image modality guidance and pixel-wise loss functions struggle to capture the distinct characteristics of medical images, such as unique texture patterns and specific colors harboring critical diagnostic information. To overcome these challenges, this paper introduces the Multi-Modal Regularized Coarse-to-fine Transformer (M2Trans) for Ultrasound Image SR. By integrating the text modality, we establish joint image-text guidance during training, leveraging the medical CLIP model to incorporate richer priors from text descriptions into the SR optimization process, enhancing detail, structure, and semantic recovery. Furthermore, we propose a novel coarse-to-fine transformer comprising multiple branches infused with self-attention and frequency transforms to efficiently capture signal dependencies across different scales. Extensive experimental results demonstrate significant improvements over state-of-the-art methods on benchmark datasets, including CCA-US, US-CASE, and our newly created dataset MMUS1K, with a minimum improvement of 0.17dB, 0.30dB, and 0.28dB in terms of PSNR. Our code and dataset will be available at: https://***/eezkni/M2Trans © 2013 IEEE.

关键词： Ultrasonic imaging

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Color transfer based on multiscale gradient-aware decomposition and color distribution mapping

Color transfer based on multiscale gradient-aware decomposit...

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20th ACM International Conference on Multimedia, MM 2012

作者： Su, Zhuo Deng, Daiguo Yang, Xue Luo, Xiaonan National Engineering Research Center of Digital Life State-Province Joint Laboratory of Digital Home Interactive Applications School of Information Science & Technology Sun Yat-sen University Shenzhen China Digital Home Key Technology Engineering Laboratory Shenzhen Key Laboratory of Digital Living Network and Content Service Research Institute of Sun Yat-sen University in Shenzhen China

ISBN: (纸本)9781450310895

Automatic global color transfer is a challenging problem in image editing. In this paper, we propose a novel color transfer method, which is based on the gradient-aware decomposition and the color distribution mapping. Firstly, a gradient-aware decomposition model is established to separate the target image into the base and detail layers. Then, the colors of each separated base layer are enforced to match those of a given reference image by Pitie's multi-dimensional probability density function transfer method. After that, all mapped base layers are combined with corresponding boosted detail layers to produce the final output. The experiments demonstrate that our method can achieve a visual satisfied result without post-processing gradient correction. © 2012 ACM.

关键词： Mapping

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Design model execution engine based on web services for distributed geography modeling environment

Design model execution engine based on web services for dist...

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IEEE International Symposium on Geoscience and Remote Sensing (IGARSS)

作者： Xiaolin Wang Hongqiang Mao Yingwei Luo The Shenzhen Key Laboratory for Cloud Computing Technology and Applications Peking University Shenzhen Graduate School Guangdong China

The design of execution engine based on web services for distributed geography modeling environment relies on model contract, model management environment, execution node, data center and control node. The execution procedure of geography model execution engine would be like this: first, geographers construct model contract according to the rule of model contract, and then submit the model contract into control node; Second, the control node parsers the model contract, queries the geography model deployment information, entry point and model input/output information from model management environment, keeps them in memory; Third, control node prepares model data and calls the models which distributed on each execution node for simulation; Finally, the environment returns the result to geographers. The model execution engine adopts multi-thread technology, and could handle multi-job submitted by geographers.

关键词： Computational modeling Biological system modeling Data models Geography Contracts Engines Web services

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Reply to Comments on 'Direct-Splitting-Based CN-FDTD for Modeling 2D Material Nanostructure Problems'

IEEE Open Journal of Antennas and Propagation

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IEEE Open Journal of Antennas and Propagation 2021年 2卷 676-678页

作者： Feng, Naixing Zhang, Yuxian Zeng, Qingsheng Tong, Mei Song Joines, William T. Wang, Guo Ping Institute of Microscale Optoelectronics Shenzhen University Shenzhen China College of Astronautics Nanjing University of Aeronautics and Astronautics Nanjing China Key Laboratory of Embedded System and Service Computing of the Ministry of Education College of Electronics and Information Engineering Tongji University Shanghai China Department of Electrical and Computer Engineering Duke University DurhamNC United States

In this response letter, we focus on addressing Yu Hang Yang's comments so that the correctness and validity of the proposed auxiliary-differential-equation-based (ADE) Crank-Nicolson finite-difference time-domain method with direct-splitting technique (CNDS-FDTD) are demonstrated. Moreover, related applications in modeling 2D material nanostructure problems are shown. © 2020 IEEE.

关键词： Finite difference time domain method

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Model semantic network for massive spatial information

Model semantic network for massive spatial information

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IEEE International Symposium on Geoscience and Remote Sensing (IGARSS)

作者： Xiaolin Wang Yingwei Luo The Shenzhen Key Laboratory for Cloud Computing Technology and Applications (SPCCTA) Peking University Shenzhen Graduate School Shenzhen Guangdong China

Spatial information is now increasing continuously and is available via the Internet. But facing the abundant spatial information, people recognize many agonizing problems, such as how can spatial information cooperate with each other to solve users' task and how do users know where spatial information is located, what kinds of spatial information can be used, and the way of how to use them. The only way to remedy those problems is to use spatial metadata. Spatial metadata is the description of spatial information and its associated information, which give a semantic expatiation for spatial information. Spatial metadata is now developed as an indispensable and powerful tool for data finding, data exchanging, data managing and data utilization. Currently, there are some standards for spatial metadata such as FGDC and ISO/TC211. But the existing spatial metadata is largely for people to use, and only describes spatial information itself. In this paper, spatial metadata is extended to describe the relations among different spatial information and the distribution of spatial information on the Internet. Based on the extensive spatial metadata, a semantic network model for massive spatial information is presented to support the collaboration among spatial information and make the navigation of spatial information more fast and exact. At last, XML technology is adopted to represent the semantic network for spatial information.

关键词： Semantics XML Spatial databases Resource description framework Educational institutions ISO standards

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Managing and integrating geography models in distributed environment

Managing and integrating geography models in distributed env...

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IEEE International Symposium on Geoscience and Remote Sensing (IGARSS)

作者： Xiaolin Wang Hui Li Hao Deng Yingwei Luo The Shenzhen Key Laboratory for Cloud Computing Technology and Applications (SPCCTA) Peking University Shenzhen Graduate School Shenzhen Guangdong China

For the current "Model islands" problems which occur in the process of the geography modeling and model sharing, we propose an idea of geography model sharing and reusing method which based on the metadata standard in distributed environment. This article mainly solves how to describe and manage the geography model to achieve the model sharing and reuse. We work on the design of the metadata standard, the integrating standard and the managing environment of the geography model. It is expected to provide a convenient platform for the geographers, so that they can easily reuse any model, which means the heterogeneous models can be well shared.

关键词： Geography Computational modeling Contracts Data models Databases Sea surface Semantics

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