检索结果-内蒙古大学图书馆

International Symposium on Biomedical Imaging

作者： Lin Yuan Tianming Liu Dewen Hu College of Mechanotrics and Automation National University of Defense Technology Changsha Hunan 410073 China Cortical Architecture Imaging and Discovery Lab Department of Computer Science The University of Georgia Athens United States of America

ISBN: (纸本)9781509011735

Resting-state functional magnetic resonance imaging (rs-fMRI) has become a powerful technique for analyzing cognitive function and its disruption in mental diseases, including schizophrenia. It has played an important role in analyzing and diagnosing mental diseases. In this paper, we present a novel machine learning approach called group-wise sparse representation of rs-fMRI signals to find differences between schizophrenia patients and healthy controls. Firstly, we extract the fMRI signals from all subjects that are registered into the MNI atlas space in the pre-processing step to build a large input signal matrix. Secondly, we use online dictionary learning and sparse coding methods to derive the coefficient matrix. Thirdly, we use two-sample t-test to analyze the regions of increased and decreased activity in schizophrenia patients compared to healthy controls. Finally, by using the AAL atlas the distributions of the detected regions are obtained. We test our approach on the COBRE dataset and the experimental results show that the schizophrenia patients have increased activities mainly at the fronto-parietal network. All other networks excluding the fronto-parietal network show decreased phenomenon. These results provide novel insights into better understanding of schizophrenia.

关键词： resting-state fMRI group-wise sparse representation schizophrenia research

来源：评论

学校读者我要写书评

暂无评论

Multi-tenant cross-slice resource orchestration: A deep reinforcement learning approach

arXiv

引用

arXiv 2018年

作者： Chen, Xianfu Zhao, Zhifeng Wu, Celimuge Bennis, Mehdi Liu, Hang Ji, Yusheng Zhang, Honggang VTT Technical Research Centre of Finland Oulu Finland Zhejiang Lab College of Information Science and Electronic Engineering Zhejiang University Hangzhou China Graduate School of Informatics and Engineering University of Electro-Communications Tokyo Japan Centre for Wireless Communications University of Oulu Finland Department of Electrical Engineering and Computer Science Catholic University of America United States Information Systems Architecture Research Division National Institute of Informatics Tokyo Japan College of Information Science and Electronic Engineering Zhejiang University Hangzhou China

With the cellular networks becoming increasingly agile, a major challenge lies in how to support diverse services for mobile users (MUs) over a common physical network infrastructure. Network slicing is a promising solution to tailor the network to match such service requests. This paper considers a system with radio access network (RAN)-only slicing, where the physical infrastructure is split into slices providing computation and communication functionalities. A limited number of channels are auctioned across scheduling slots to MUs of multiple service providers (SPs) (i.e., the tenants). Each SP behaves selfishly to maximize the expected long-term payoff from the competition with other SPs for the orchestration of channels, which provides its MUs with the opportunities to access the computation and communication slices. This problem is modelled as a stochastic game, in which the decision makings of a SP depend on the global network dynamics as well as the joint control policy of all SPs. To approximate the Nash equilibrium solutions, we first construct an abstract stochastic game with the local conjectures of channel auction among the SPs. We then linearly decompose the per-SP Markov decision process to simplify the decision makings at a SP and derive an online scheme based on deep reinforcement learning to approach the optimal abstract control policies. Numerical experiments show significant performance gains from our scheme. Copyright © 2018, The Authors. All rights reserved.

关键词： Deep learning

来源：评论

学校读者我要写书评

暂无评论

3-D Functional Brain Network Classification using Convolutional Neural Networks

3-D Functional Brain Network Classification using Convolutio...

引用

International Symposium on Biomedical Imaging

作者： Dehua Ren Yu Zhao Hanbo Chen Qinglin Dong Jinglei Lv Tianming Liu College of Computer Science and Information Engineering Tianjin University of Science and Technology 300222 China Cortical Architecture Imaging and Discovery Lab Department of Computer Science and Bioimaging Research Center the University of Georgia Athens 30605 USA Queensland Institute of Medical Research (QIMR) Berghofer Herston Australia

ISBN: (纸本)9781509011735

Several recent studies have shown that dictionary learning and sparse representation can effectively reconstruct hundreds of interacting functional brain networks simultaneously from whole-brain fMRI data. However, accurate classification and recognition of those hundreds of functional networks from an individual or a population of many subjects is still a challenging and open problem due to the intrinsic variability of functional networks and other noise sources. To tackle this problem, this paper presents an effective deep learning framework to train convolutional neural networks from a large dataset of hundreds of thousands of available brain network volume maps, which was then applied on testing samples for network classification and recognition. We effectively applied computer-labeled data as training set so the whole process can be automated. Experimental results showed that the proposed method is quite robust in handling noisy patterns in the dataset, which suggests that our work offers a new computational framework for modeling functional connectomes from fMRI big data in the future.

关键词： deep learning 3D convolutional neural networks functional brain networks classification

来源：评论

学校读者我要写书评

暂无评论

Managing deadline-constrained bag-of-tasks jobs on hybrid clouds

Managing deadline-constrained bag-of-tasks jobs on hybrid cl...

引用

24th High Performance Computing Symposium, HPC 2016, Part of the 2016 Spring Simulation Multi-Conference, SpringSim 2016

作者： Wang, Bo Song, Ying Sun, Yuzhong Liu, Jun Department of Computer Science and Technology Xi'an Jiaotong University Xi'an710049 China SKL Computer Architecture ICT CAS China SPKLSTN Lab Department of Computer Science and Technology Xi'an Jiaotong University Xi'an710049 China

ISBN: (纸本)9781510824256

Outsourcing jobs to a public cloud is a cost-effective way to address the problem of satisfying the peak resource demand when the local cloud has insufficient resources. In this paper, we study on managing deadline-constrained bag-of-tasks jobs on hybrid clouds. We present a binary nonlinear programming (BNP) problem to model the hybrid cloud management where the utilization of physical machines (PMs) in the local cloud/cluster is maximized when the local resources are enough to satisfy the deadline constraints of jobs, while when not, the rent cost from the public cloud is minimized. To solve the BNP problem in polynomial time, we propose the heuristic algorithm whose main idea is assigning a task to a core of a used PM (in local cloud) or a rented virtual machine (VM) (in public cloud) such that the difference between the finish time of the task and its deadline is minimal in all of assignments. If none of unassigned tasks can be completed within its deadline, the algorithm adds an available PM with most capacity or rents a new VM with highest cost-performance ratio and assigns tasks to the new PM/VM as previous step. Extensive experimental results show that our heuristic algorithm saves 16.2%-76% cost and improves 47.3%-182.8% resource utilizations for finishing jobs within their respective deadlines with comparable overheads, compared with first fit decreasing algorithm. © 2016 Society for Modeling & Simulation International (SCS).

关键词： Heuristic algorithms

来源：评论

学校读者我要写书评

暂无评论

Music, Computing, and Health: A Roadmap for the Current and Future Roles of Music Technology for Health Care and Well-Being

引用

Music and Science 2021年 4卷

作者： Agres, Kat R. Schaefer, Rebecca S. Volk, Anja van Hooren, Susan Holzapfel, Andre Dalla Bella, Simone Müller, Meinard de Witte, Martina Herremans, Dorien Ramirez Melendez, Rafael Neerincx, Mark Ruiz, Sebastian Meredith, David Dimitriadis, Theo Magee, Wendy L. Yong Siew Toh Conservatory of Music National University of Singapore Singapore Social and Cognitive Computing Department Institute of High Performance Computing A*STAR Singapore Institute for Psychology Health Medical Neuropsychology Unit Leiden University Leiden Netherlands Leiden Institute for Brain and Cognition Leiden University Leiden Netherlands Academy of Creative and Performing Arts Leiden University Leiden Netherlands Department of Information and Computing Sciences Utrecht University Utrecht Netherlands Faculty of Health care Department of Arts Therapies Zuyd University of Applied Sciences Heerlen Netherlands KenVaK Research Centre for the Arts Therapies and Psychomotricity Heerlen Netherlands Faculty of Psychology Open University of The Netherlands Heerlen Netherlands Division of Media Technology and Interaction Design KTH Royal Institute of Technology Stockholm Sweden International Laboratory for Brain Music and Sound Research (BRAMS) Outremont QC Canada Department of Psychology University of Montreal Montreal QC Canada Centre for Research on Brain Language and Music (CRBLM) Montreal QC Canada University of Economics and Human Sciences in Warsaw Warsaw Poland International Audio Laboratories Erlangen Friedrich-Alexander Universität Erlangen-Nürnberg Erlangen Germany HAN University of Applied Sciences Department of Arts Therapies and Psychological Studies Nijmegen Netherlands University of Amsterdam Research Institute of Child Development and Education Amsterdam Netherlands Treatment Centre for People with Mild Intellectual Disabilities and Psychiatric and Behavioral Disorders Gennep Netherlands Information Systems Technology and Design Singapore University of Technology and Design Singapore Music and Machine Learning Lab Music Technology Group Universitat Pompeu Fabra Barcelona Spain Faculty of EEMCS Interactive Intelligence Group Delft University of Technology Delft Netherlands Centre for Digital Music School of Electronic Engineerin

The fields of music, health, and technology have seen significant interactions in recent years in developing music technology for health care and well-being. In an effort to strengthen the collaboration between the involved disciplines, the workshop “Music, Computing, and Health” was held to discuss best practices and state-of-the-art at the intersection of these areas with researchers from music psychology and neuroscience, music therapy, music information retrieval, music technology, medical technology (medtech), and robotics. Following the discussions at the workshop, this article provides an overview of the different methods of the involved disciplines and their potential contributions to developing music technology for health and well-being. Furthermore, the article summarizes the state of the art in music technology that can be applied in various health scenarios and provides a perspective on challenges and opportunities for developing music technology that (1) supports person-centered care and evidence-based treatments, and (2) contributes to developing standardized, large-scale research on music-based interventions in an interdisciplinary manner. The article provides a resource for those seeking to engage in interdisciplinary research using music-based computational methods to develop technology for health care, and aims to inspire future research directions by evaluating the state of the art with respect to the challenges facing each field. © The Author(s) 2021.

关键词： health care interdisciplinarity MedTech music information retrieval (MIR) music neuroscience Music psychology music technology music therapy well-being

来源：评论

学校读者我要写书评

暂无评论

Server consolidation for Internet applications in virtualized data centers

Server consolidation for Internet applications in virtualize...

引用

24th High Performance Computing Symposium, HPC 2016, Part of the 2016 Spring Simulation Multi-Conference, SpringSim 2016

作者： Wang, Bo Song, Ying Sun, Yuzhong Liu, Jun Department of Computer Science and Technology Xi'an Jiaotong University Xi'an710049 China SKL Computer Architecture ICT CAS Beijing100190 China SPKLSTN Lab Department of Computer Science and Technology Xi'an Jiaotong University Xi'an710049 China

ISBN: (纸本)9781510824256

Server consolidation based on virtualization technology simplifies system administration and improves energy efficiency by improving resource utilizations and reducing the physical machine (PM) number in contemporary service-oriented data centers. The elasticity of Internet applications changes the consolidation technologies from addressing virtual machines (VMs) to PMs mapping schemes which must know the VMs statuses, i.e. the number of VMs and the profiling data of each VM, into providing the application-to-VM-to-PM mapping. In this paper, we study on the consolidation of multiple Internet applications, minimizing the number of PMs with required performance. We first model the consolidation providing the application-to-VM-to-PM mapping to minimize the number of PMs as an integer linear programming problem, and then present a heuristic algorithm to solve the problem in polynomial time. Extensive experimental results show that our heuristic algorithm consumes less than 4.3% more resources than the optimal amounts with few overheads. Existing consolidation technologies using the input of the VM statuses output by our heuristic algorithm consume 1.06% more PMs. © 2016 Society for Modeling & Simulation International (SCS).

关键词： Elasticity

来源：评论

学校读者我要写书评

暂无评论

MDFS: A mimic defense theory based architecture for distributed file system

MDFS: A mimic defense theory based architecture for distribu...

引用

IEEE International Conference on Big Data

作者： Zhili Lin Kedan Li Hanxu Hou Xin Yang Hui Li Shenzhen Key Lab of Information Theory & Future Internet Architecture Shenzhen Graduate School.Peking University Shenzhen China Dept. of Computer Science UIUC USA School of Electrical Engineering & Intelligentization Dongguan University of Technology Dongguan China

As the Internet and the big data system evolve rapidly, the deployment of distributed applications becomes widespread, promoting the development of Distributed File System (DFS). The existing defense technologies for DFS, such as detection or patching, mainly aim to protect the system from known attacks and vulnerabilities. However, it is difficult for those systems to solve the growing security issues from the unknown threats due to their passiveness and hysteresis. In this paper, we propose MDFS, a mimic defense theory based architecture for DFS with the capability to improve the data security. Mimic Defense (MD), a proactive defense embedded in MDFS, emphasizes dynamism, heterogeneity and redundancy. The key benefits of MD are transferring the attack surface as well as increasing the cost of modification.

关键词： File systems Servers Metadata Redundancy computer architecture Authentication

来源：评论

学校读者我要写书评

暂无评论

Modeling functional dynamics of cortical gyri and sulci 1

引用

1st International Workshop on Simulation and Synthesis in Medical Imaging, SASHIMI 2016 held in conjunction with 19th International Conference on Medical Image Computing and computer-Assisted Intervention, MICCAI 2016

作者： Jiang, Xi Li, Xiang Lv, Jinglei Zhao, Shijie Zhang, Shu Zhang, Wei Zhang, Tuo Liu, Tianming Cortical Architecture Imaging and Discovery Lab Department of Computer Science and Bioimaging Research Center The University of Georgia AthensGA United States School of Automation Northwestern Polytechnical University Xi’an China

ISBN: (数字)9783319467207

ISBN: (纸本)9783319467191

Cortical gyrification is one of the most prominent features of human brain. A variety of studies in the brain mapping field have demonstrated the specific structural and functional differences between gyral and sulcal regions. However,previous studies of gyri/sulci function analysis based on the fMRI data assume the temporal stationarity over the entire fMRI scan,while the possible temporal dynamics of gyri/sulci function is largely unknown. We present a computational framework to model the functional dynamics of cortical gyri and sulci based on task fMRI data. Specifically,the whole-brain fMRI signals’ temporal segments are derived via the sliding time window approach. The spatial overlap patterns among functional networks (SOPFNs),which are crucial for characterizing brain functions,are then measured within each time window via a group-wise sparse representation approach. Finally,the temporal dynamics of SOPFNs distribution on gyral/sulcal regions across all time windows are assessed. Experimental results based on the publicly released Human Connectome Project task fMRI data demonstrated that the proposed framework identified meaningful temporal dynamics difference of the SOPFNs distribution between gyral and sulcal regions which are reproducible across different subjects and task fMRI datasets. Our results provide novel understanding of functional dynamics mechanisms of human cerebral cortex. © Springer International Publishing AG 2016.

关键词： Dynamics

来源：评论

学校读者我要写书评

暂无评论

REMO: Redundant execution with minimum area, power, performance overhead fault tolerant architecture

REMO: Redundant execution with minimum area, power, performa...

引用

IEEE Symposium on On-Line Testing (IOLTS)

作者： Shoba Gopalakrishnan Virendra Singh Computer Architecture & Dependable Systems Lab Indian Institute of Technology Bombay India

ISBN: (纸本)9781509015085

Relentless scaling in CMOS fabrication technology has made contemporary integrated circuits continue to evolve and grow in functionality with high clock frequencies and exponentially increasing transistor counts. However, it also makes them more susceptible to transient faults effectively decreasing their reliability. Therefore, ensuring correct and reliable operation of these microprocessors at low cost has become a challenging task. This paper proposes a light weight error detection method called REMO which aims to incorporate simple fault tolerance mechanisms as part of the basic architecture. It dynamically verifies the execution results of the instructions by exploiting spatial and temporal redundancy and detects soft errors. REMO shows that with minimal area, power and performance overhead, and a very low detection latency, a very high degree of fault coverage can be achieved. Our simulation results shows an increase in area is about 0.4%, power overhead near to 9% and a negligible performance penalty during fault free run.

关键词： Redundancy Out of order Pipelines Hardware Fault tolerant systems

来源：评论

学校读者我要写书评

暂无评论

Unveiling difficult bugs in address translation caching arrays for effective post-silicon validation

Unveiling difficult bugs in address translation caching arra...

引用

IEEE International Conference on computer Design: VLSI in computers and Processors, (ICCD)

作者： George Papadimitriou Dimitris Gizopoulos Athanasios Chatzidimitriou Tom Kolan Anatoly Koyfman Ronny Morad Vitali Sokhin University of Athens Computer Architecture Lab Greece IBM Research Haifa Israel

Post-silicon validation is one of the most important parts of the microprocessor prototype chip lifecycle. It is the last chance for debug engineers to detect defects and bugs that escaped pre-silicon verification, before the chip is released to the market. Effective solutions are required to harness the peak performance of the hardware prototype and evaluate whether the microprocessor chip is fully compliant with the instruction set and other specifications. We perform a comprehensive experimental study on a state-of-the-art microarchitecture to assess and identify the most difficult bugs in address translation caching arrays (multi-level TLBs and MMU Caches), and explain why these bugs persist across generations. We also categorize them into distinct bug scenarios. We then propose a novel methodology for generating random self-checking stimuli programs, which expose and detect such bug scenarios. Our experimental results show that the proposed method can detect difficult bugs that are likely to be missed by traditional post-silicon validation techniques.

关键词： computer bugs Microprocessors Silicon Benchmark testing Prototypes Hardware Microarchitecture

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：