检索结果-内蒙古大学图书馆

2024 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2024

作者： Liu, Yawen Chen, Yiwen Nie, Shanling Yang, Hai East China University of Science and Technology Department of Computer Science and Engineering Shanghai China Shanghai Key Laboratory of Computer Software Evaluating and Testing Shanghai China National University of Singapore Center for Continuing and Lifelong Education Singapore University of Sydney Faculty of Engineering Australia

ISBN: (纸本)9798350386226

With the ongoing advancements in science and technology and the increasing research focus on cancer-related issues, there has been a proliferation of omics-related resources for in-depth analysis and exploration. This burgeoning volume and complexity of biological data have fostered the integration of machine-learning techniques into biology. As a result, numerous machine-learning strategies have been established to identify driver mutations. Yet, many of these strategies produce complex models, complicating comprehension and thereby clouding the impact of input features on the resulting predictions. Our analysis presented the CIXG framework, which integrates a driver gene prediction module using XGBoost with a causality interpretation module anchored on CXPlain. This architecture enables quantifying each input feature's contribution to the prediction outcome and ensures precise predictions of driver genes. When benchmarked against the state-of-the-art (SOTA) method, CIXG demonstrated superior accuracy in pinpointing driver genes across pan-cancer studies and within the 32 specific cancer types. Importantly, our results underscored that mutation features chiefly influence CIXG's predictive prowess, with additional support from other omics features. © 2024 IEEE.

关键词： Adversarial machine learning

来源：评论

学校读者我要写书评

暂无评论

A multi-source fusion method to identify biomarkers for breast cancer prognosis based on dual-layer heterogeneous network

A multi-source fusion method to identify biomarkers for brea...

引用

2022 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2022

作者： Li, Xingyi Zhao, Zhelin Xiang, Ju Hu, Jialu Shang, Xuequn Northwestern Polytechnical University School of Computer Science Xi'an710072 China Northwestern Polytechnical University School of Software Xi'an710072 China Changsha University of Science and Technology School of Computer and Communication Engineering Changsha410000 China

ISBN: (纸本)9781665468190

The prognosis of breast cancer is challenging, which is an urgent problem to be solved. The prognostic biomarkers for breast cancer can help us predict the clinical outcomes of patients, and network-based methods are widely introduced to find prognostic biomarkers. According to the difference of input biological data, existing network-based biomarker prediction methods are mainly classified into two types: integrating single-source network or multi-source networks. However, the interactome of single-source network remains incomplete, and biological networks are noisy, which will hamper the network-based identification accuracy of biomarkers. In this study, we introduce a multi-source fusion method, DualMarker, which integrates multiple biological information sources and constructs a dual-layer heterogeneous network by fast network embedding. Next, we introduce a network enhancement method to denoise the constructed dual-layer heterogeneous network, and we implement network propagation algorithm on the constructed dual-layer heterogeneous network to rank the features. After comparing with competitive methods, we find that DualMarker substantially outperforms these methods. In addition, we verify that the biomarkers identified by DualMarker are closely related to the prognosis of breast cancer patients. © 2022 IEEE.

关键词： Heterogeneous networks

来源：评论

学校读者我要写书评

暂无评论

Vehicle kinematics modeling and design of vehicle trajectory generator system

引用

Journal of Central South University 2012年第10期19卷 2860-2865页

作者：李昭蔡自兴任孝平陈爱斌薛志超 School of Information Science and Engineering Central South University Institute of Intelligent System and Software Central South University Department of Intelligence Science and Technology Central South University National Institute of Metrology College of Computer Science and Information Technology Central South University of Forestry and Technology Faculty of Health Science University of Copenhagen

A trajectory generator based on vehicle kinematics model was presented and an integrated navigation simulation system was *** that the tight relation between vehicle motion and topography,a new trajectory generator for vehicle was proposed for more actual ***,a vehicle kinematics model was built based on conversion of attitude vector in different coordinate ***,the principle of common trajectory generators was ***,combining the vehicle kinematics model with the principle of dead reckoning,a new vehicle trajectory generator was presented,which can provide process parameters of carrier anytime and achieve simulation of typical actions of running ***,IMU(inertial measurement unit) elements were simulated,including accelerometer and *** setting up the simulation conditions,the integrated navigation simulation system was verified by final performance *** result proves the validity and flexibility of this design.

关键词： vehicle kinematics model integrated navigation system track generator IMU element system simulation

来源：评论

学校读者我要写书评

暂无评论

SWRR:The Link Scheduling Algorithm Based on Weighted Round-Robin

引用

computers, Materials & Continua 2019年第6期59卷 965-982页

作者： Tianbo Lu Ru Yan Chao Li Lihua Yin Hao Chen Xieyu Zou School of Software Engineering Beijing University of Posts and TelecommunicationsBeijing100876China Key Laboratory of Trustworthy Distributed Computing and Service(Beijing University of Posts and Telecommunications) Ministry of EducationBeijing100876China Cyberspace Institute of Advanced Technology Guangzhou UniversityGuangzhou510006China Department Computer Science and Engineering The University of Texas at ArlingtonArlington76091USA

With the rapid development of the Internet,people pay more and more attention to the protection of *** second-generation onion routing system Tor is the most commonly used among anonymous communication systems,which can be used to protect user privacy *** recent years,Tor’s congestion problem has become the focus of attention,and it can affect Tor’s performance even user ***,we investigate the causes of Tor network congestion and summarize some link scheduling algorithms proposed in recent *** we propose the link scheduling algorithm SWRR based on WRR(Weighted Round Robin).In this process,we design multiple weight functions and compare the performance of these weight functions under different congestion conditions,and the appropriate weight function is selected to be used in our algorithms based on the experiment ***,we also compare the performance of SWRR with other link scheduling algorithms under different congestion conditions by experiments,and verify the effectiveness of the algorithm SWRR.

关键词： Weighted Round-Robin Tor congestion control link scheduling anonymous communication

来源：评论

学校读者我要写书评

暂无评论

A novel image retrieval method with saliency feature vector

引用

International Journal of Performability engineering 2018年第2期14卷 223-231页

作者： Wu, Junfeng Qu, Wenyu Li, Zhiyang Ji, Changqing School of Computer Science and Technology Tianjin University Tianjin300072 China School of Information Engineering Dalian Ocean University Dalian116023 China School of Software Tianjin University Tianjin300072 China School of Information Science and Technology Dalian Maritime University Dalian116026 China School of Physical Science and Technology Dalian University Dalian116023 China

In the past few years, image retrieval has been one of the research focuses in the field of computer vision. For most retrieval methods, the accuracy of the retrieval results mainly depends on the extracted feature vectors. But, the foreground and the background in the images are not distinguished for most methods. It is obvious that these methods are not in accordance with the visual characteristics of the human eye. In this paper, salient objects are extracted from images in order to improve the pertinence of feature vector extraction. The paper utilizes a spatial pyramid model to divide the image into different parts with different scales. The feature vectors extracted in different scale are connected. Then, the saliency map and saliency score are used to rebuild the joint vector. Each feature vector is assigned different weighted values according to its different location in the image and scale. Finally, the newly constructed feature vectors are used to measure the similarity between images. In order to test the effectiveness of the algorithm, we evaluate our method on the SIMPLIcity dataset and Stanford dataset. Experimental results show that the proposed method has a great improvement in both accuracy and efficiency. © 2018 Totem Publisher, Inc. All rights reserved.

关键词： Image retrieval

来源：评论

学校读者我要写书评

暂无评论

Video2Reward: Generating Reward Function from Videos for Legged Robot Behavior Learning 27

Video2Reward: Generating Reward Function from Videos for Leg...

引用

27th European Conference on Artificial Intelligence, ECAI 2024

作者： Zeng, Runhao Zhou, Dingjie Liang, Qiwei Liu, Junlin Li, Hui Huang, Changxin Li, Jianqiang Hu, Xiping Sun, Fuchun Artificial Intelligence Research Institute Shenzhen MSU-BIT University China College of Mechatronics and Control Engineering Shenzhen University China College of Computer Science and Software Engineering Shenzhen University China National Engineering Laboratory for Big Data System Computing Technology Shenzhen University China Department of Computer Science and Technology Tsinghua University China

ISBN: (纸本)9781643685489

Learning behavior in legged robots presents a significant challenge due to its inherent instability and complex constraints. Recent research has proposed the use of a large language model (LLM) to generate reward functions in reinforcement learning, thereby replacing the need for manually designed rewards by experts. However, this approach, which relies on textual descriptions to define learning objectives, fails to achieve controllable and precise behavior learning with clear directionality. In this paper, we introduce a new video2reward method, which directly generates reward functions from videos depicting the behaviors to be mimicked and learned. Specifically, we first process videos containing the target behaviors, converting the motion information of individuals in the videos into keypoint trajectories represented as coordinates through a video2text transforming module. These trajectories are then fed into an LLM to generate the reward function, which in turn is used to train the policy. To enhance the quality of the reward function, we develop a video-assisted iterative reward refinement scheme that visually assesses the learned behaviors and provides textual feedback to the LLM. This feedback guides the LLM to continually refine the reward function, ultimately facilitating more efficient behavior learning. Experimental results on tasks involving bipedal and quadrupedal robot motion control demonstrate that our method surpasses the performance of state-of-the-art LLM-based reward generation methods by over 37.6% in terms of human normalized score. More importantly, by switching video inputs, we find our method can rapidly learn diverse motion behaviors such as walking and running. © 2024 The Authors.

关键词： Robots

来源：评论

学校读者我要写书评

暂无评论

The Complexity of Finding a Broadcast Center 15th

The Complexity of Finding a Broadcast Center

引用

15th International Conference on Algorithmic Aspects in Information and Management, AAIM 2021

作者： Harutyunyan, Hovhannes A. Li, Zhiyuan Department of Computer Science and Software Engineering Concordia University MontrealQCH3G 1M8 Canada Computer Science and Technology United International College Zhuhai0086-519000 China

ISBN: (纸本)9783030931759

Broadcasting in networks is one of the most important information dissemination processes. It is known that finding the optimal (minimum) broadcast time is NP-hard. Some of the follow-up researches focus on approximations/heuristics to find the broadcast center, a set of nodes from which the broadcast time in the network is minimum, in a given network by assuming the problem is hard without an actual proof. In this paper, we show that answering the questions "is a set of vertices a broadcast center to the given graph", and "does the given graph has a broadcast center of size smaller than k" are both NP-hard under Turing reductions. © 2021, Springer Nature Switzerland AG.

关键词： Information dissemination

来源：评论

学校读者我要写书评

暂无评论

Performance evaluation of energy-efficient parallel I/O systems with write buffer disks

Performance evaluation of energy-efficient parallel I/O syst...

引用

38th International Conference on Parallel Processing, ICPP-2009

作者： Ruan, Xiaojun Manzanares, Adam Yin, Shu Zong, Ziliang Qin, Xiao Department of Computer Science and Software Engineering Auburn University Auburn AL 36849-5347 United States Department of Mathematics and Computer Science South Dakota School of Mines and Technology Rapid City SD 57701 United States

ISBN: (纸本)9780769538020

In the past decade, parallel disk systems have been developed to address the problem of I/O performance. A critical challenge with modern parallel I/O systems is that parallel disks consume a significant amount of energy in servers and highperformance computers. To conserve energy consumption in parallel I/O systems, one can immediately spin down disks when disk are idle;however, spinning down disks might not be able to produce energy savings due to penalties of spinning operations. Unlike powering up CPUs, spinning down and up disks need physical movements. Therefore, energy savings provided by spinning down operations must offset energy penalties of the disk spinning operations. To substantially reduce the penalties incurred by disk spinning operations, we developed a novel approach to conserving energy of parallel I/O systems with write buffer disks, which are used to accumulate small writes using a log file system. Data sets buffered in the log file system can be transferred to target data disks in a batch way. Thus, buffer disks aim to serve a majority of incoming write requests, attempting to reduce the large number of disk spinning operations by keeping data disks in standby for long period times. Interestingly, the write buffer disks not only can achieve high energy efficiency in parallel I/O systems, but also can shorten response times of write requests. To evaluate the performance and energy efficiency of our parallel I/O systems with buffer disks, we implemented a prototype using a cluster storage system as a testbed. Experimental results show that under light and moderate I/O load, buffer disks can be employed to significantly reduce energy dissipation in parallel I/O systems without adverse impacts on I/O performance. © 2009 IEEE.

关键词： Energy dissipation

来源：评论

学校读者我要写书评

暂无评论

Deep stochastic weight assignment network of Chinese chess machine game

Deep stochastic weight assignment network of Chinese chess m...

引用

2016 International Conference on Machine Learning and Cybernetics, ICMLC 2016

作者： Wang, Zhi Zhai, Junhai Wang, Xizhao College of Computer Science and Technology Hebei University Baoding071002 China College of Mathematics and Information Science Hebei University Baoding071002 China College of Computer Science and Software Engineering Shenzhen University Shenzhen518060 China

ISBN: (纸本)9781509003891

Man-machine game is an important component in the field of artificial intelligence. Game tree search algorithms and chess situation evaluation functions are mostly applied in the traditional chess game system. When the game tree method is used, the response time will be extended as the depth of tree. This paper proposes to use the stochastic weight assignment neural network (SWAN), trained by Extreme Learning Machine (ELM), to solve this problem. ELM is a fast learning algorithm in which all of the weights and biases between the input layer and hidden layer are randomized and the weights of output layer are analytically computed through solving a generalized inverse of matrix. Since the learning process does not include iteration, the learning speed is significantly accelerated and generalization capacity is improved greatly. Moreover, considering the complexity of Chinese chess situation features, feature learning and classification of chess samples cannot be efficiently accomplished by the shallow network. A deep stochastic weight assignment network (DSWAN) is developed to settle this difficulty. © 2016 IEEE.

关键词： Learning algorithms

来源：评论

学校读者我要写书评

暂无评论

Stellar Spectral Classification Based on Capsule Network

引用

Chinese Astronomy and Astrophysics 2021年第3期45卷 352-363页

作者： Li-ting, D.U. Li-hua, H.O.N.G. Jin-tao, Y.A.N.G. Ting-ting, X.U. Jing-min, ZHANG Lin-pin, A.I. Wei-hong, Z.H.O.U. School of Mathematics and Computer Science Yunnan Minzu University Kunming 650500 School of Software Engineering Xiamen Institute of Software Technology Xiamen 361000 Center for Astrophysics Guangzhou University Guangzhou 510006 Key Laboratory of the Structure and Evolution of Celestial Objects Chinese Academy of Sciences Kunming 650011

The rapid development of large-scale sky survey project has produced a large amount of stellar spectral data, which make the automatic classification of stellar spectral data a challenging task. In this paper, we have proposed a stellar spectral classification method based on a capsule network. At first, by using the one-dimensional convolutional network and short-time Fourier transform (STFT), the one-dimensional spectra of the F5, G5, and K5 types selected from the LAMOST Data Release 5 (DR5) are converted into the two-dimensional Fourier spectrum images. Then, the two-dimensional Fourier spectrum images are classified automatically by the capsule network. Because the capsule network can preserve the hierarchical pose relationships among the entities in the image, and it does not need any pooling layers, the experimental results show that the capsule network has a better classification performance, for the classifications of the F5, G5, and K5-type stellar spectra, its classification accuracy is superior to other classification methods. © 2021

关键词： methods: data analysis Stars: fundamental parameters techniques: spectral analysis

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：