检索结果-内蒙古大学图书馆

DSPE: An End-to-End Drug Synergy Combination Prediction Algorithm for Echinococcosis

Current Bioinformatics 2025年

作者： Li, Haitao Jiang, Liyuan Chu, Yuanyuan Liu, Yuansheng Zheng, Chunhou Su, Yansen Key Laboratory of Intelligent Computing and Signal Processing School of Artificial Intelligence Anhui University 111 Jiulong Road Hefei230601 China Institute of Artificial Intelligence Hefei Comprehensive National Science Center 5089 Wangjiang West Road Anhui Hefei230088 China College of Computer Science and Electronic Engineering Hunan University China

Background: Echinococcosis, a parasitic disease caused by the larvae of the Echinococcus parasite, poses a serious threat to human health. Medication is an indispensable means of treatment for Echinococcosis;however, due to the less satisfactory efficacy of single drugs, identifying effective drug combinations for the treatment of Echinococcosis is essential. Yet, current predictive models for drug synergy in Echinococcosis face accuracy challenges due to data scarcity, method limitations, and insufficient feature representation. Objective: This work aims to design an end-to-end method to predict drug synergistic combinations, which enables efficient and accurate identification of drug combinations against Echinococcosis. Methods: In this work, an end-to-end method, named DSPE, is proposed for predicting anti-Echinococcosis drug synergistic combinations. In DSPE, a dataset of Echinococcosis drug synergistic combinations is constructed by retrieving and extracting information from related scientific articles. Further, DSPE employs a residual graph attention network to deeply analyze drug characteristics and their interactions, thereby enhancing the performance of deep learning models. It also explores the protein-protein interaction network related to Echinococcosis, using node2vec combined with an attention mechanism to efficiently encode disease features. Finally, it predicts the synergy of drug combinations based on the Bliss score by integrating drug combinations and disease features. Results: Experimental evidence shows that DSPE outperforms five state-of-the-art algorithms in predicting drug combination effects by leveraging disease-target information and single-agents for the treatment. Conclusion: DSPE improves prediction accuracy and addresses the issue of data scarcity for new diseases, offering new insights and methods for the development of treatment plans for parasitic diseases in the future. © 2025 Bentham Science Publishers.

关键词： Diseases

来源：评论

学校读者我要写书评

暂无评论

Tomographic imaging method of GB-ArcSAR with arc-shaped interferometric baseline

Tomographic imaging method of GB-ArcSAR with arc-shaped inte...

引用

signal, information and Data processing (ICSIDP), IEEE International Conference on

作者： Hanpu Zhou Kai Yan Jian Wang Xiaoxiao Li Weiming Tian Yunkai Deng Radar Technology Research Institute Bejing Institute of Technology Beijing China Beijing Key Laboratory of Embedded Real-Time Information Processing Technology Beijing Institute of Technology Beijing China Beijing Building Research Institute Corporation Limited of CSCEC Beijing China Advanced Technology Research Institute Beijing Institute of Technology Jinan China Chongqing Innovation Center Beijing Institute of Technology China

ISBN: (数字)9798331515669

ISBN: (纸本)9798331515676

When observing building scenarios, there exists the layover problem. Synthetic aperture radar (SAR) tomography can use multiple two-dimensional (2D) SAR images acquired from different heights to inverse the range-azimuth-height 3D information of the targets. Ground-based arc-scanning synthetic aperture radar (GB-ArcSAR) can obtain a series of SAR images at different heights by performing azimuthal scanning on horizontal planes with different pitch angles, which makes it has tomography capabilities. However, the baseline of GB-ArcSAR is arc-shaped, which makes the existing tomographic imaging methods suitable for linear tomographic baselines cannot be directly applied to GB-ArcSAR. This paper proposes a tomographic imaging method of GB-ArcSAR with arc-shaped interferometric baseline. Through Taylor expansion of the distance between the target and the sampling position, a mapping relationship between the target pitch angle and interferometric phase was established. Based on the mapping relationship, the measurement matrix was constructed. Validation of the proposed method is achieved through simulations and measured data.

关键词： Point cloud compression Three-dimensional displays Two-dimensional displays Superresolution Tomography Apertures radar imaging Taylor series radar polarimetry Synthetic aperture radar

来源：评论

学校读者我要写书评

暂无评论

intelligent ultrasonic distance measurer system with temperature compensation algorithm

Intelligent ultrasonic distance measurer system with tempera...

引用

2022 International Applied Computational Electromagnetics Society Symposium, ACES-China 2022

作者： Wu, Yuwen Yang, Qiang Tang, Kai Zou, Jianhang Zhuo, Jianming Feng, Naixing Cai, Yijun Xiamen University of Technology Smart Sensing Integrated Circuit Engineering Research Center of Universities in Fujian Province Xiamen361024 China Xiamen Wish Information Technology Co. Ltd Xiamen361006 China Xiamen Blue Ocean Technology Co. Ltd Xiamen361022 China Anhui University Key Laboratory of Intelligent Computing & Signal Processing Ministry of Education Hefei China

ISBN: (纸本)9781665452366

With regard to distance measurement in daily life, the traditional way is to measure the distance between objects through rulers. Nowadays, ultrasonic ranging, laser ranging, radar ranging, sonar ranging and other technologies have enriched the way of distance measurement. At the same time, it is possible to choose a suitable solution according to different actual environments. This paper design an intelligent ultrasonic ranging system through the research of ultrasonic characteristics and the application of existing ultrasonic ranging. The paper introduces the design ideas and process of the intelligent ultrasonic ranging system. Through the design of independent buttons, the normal mode ranging and the high-precision mode ranging are generated to achieve the division of the measurement range and accuracy. When the distance between the measured object and the intelligent ultrasonic ranging system is less than the preset value or exceeds the range of this mode, the buzzer will sound an alarm, so that the system can be used in more fields. The system detects the current ambient temperature in real time, so that the distance measurement can be compensated and modified by the temperature compensation algorithm in the system to achieve self-adaptation and reduce measurement errors. © 2022 IEEE.

关键词： Range finding

来源：评论

学校读者我要写书评

暂无评论

A Wideband Circularly Polarized Folded Transmitarray Antenna With Linearly Polarized Feed

A Wideband Circularly Polarized Folded Transmitarray Antenna...

引用

IEEE International Conference on Electronic information and Communication Technology (ICEICT)

作者： Xiangdong Sun Xulong Guo Yin Li Yongliang Zhang Yingsong Li School of Electronic Information Engineering Inner Mongolia University Hohhot China Inner Mongolia Branch of National Computer Network Emergency Response Technical Team/Coordination Center of China Inner Mongolia University Hohhot China Peng Cheng Laboratory Shenzhen China School of Transportation Institute Inner Mongolia University Hohhot China Key Laboratory of Intelligent Computing and Signal Processing Ministry of Education Anhui University China

ISBN: (数字)9798350384437

ISBN: (纸本)9798350384444

A low-profile, high-gain, wideband circularly polarized folded transmitarray antenna (CPFTA) is proposed, and a polarization-selective linear-to-circular polarization (LP-CP) conversion element is introduced. The CPFTA consists of a linearly polarized (LP) magnetoelectric dipole antenna and a circularly polarized (CP) helical patch antenna. The CPFTA demonstrates excellent performance with a 3dB gain bandwidth of 29.5% and a 3dB axial ratio (AR) bandwidth of 40.9%.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Optimal Sequential False Data Injection Attack Scheme: Finite-Time Inverse Convergence

Optimal Sequential False Data Injection Attack Scheme: Finit...

引用

IEEE Conference on Decision and Control

作者： Xiaoyu Luo Chongrong Fang Chengcheng Zhao Peng Cheng Jianping He The Department of Automation Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai Jiao Tong University Shanghai Engineering Research Center of Intelligent Control and Management Shanghai China The State Key Laboratory of Industrial Control Technology Institute of Cyberspace Research Zhejiang University China

In this paper, we explore the relationship between the injected attack signal and the attack selection strategy in networked control systems where the adversary desires to steer the system state to the expected malicious one. We construct a sequential attack framework, i.e., the injected false data varies with the sampling time in discrete-time systems, and then derive an optimal sequential FDI attack strategy. The optimal sequential FDI attack strategy reveals the strongly coupled relationship between the injected attack signal and the attack selection strategy. Furthermore, we prove the finite-time inverse convergence of the critical parameters in the injected optimal attack signal by discrete-time Lyapunov analysis, which enables the efficient off-line design of the attack strategy and saves computing sources. Extensive simulations are conducted to show the effectiveness of the injected optimal sequential attack and the relationship between the attack signal and the attack selection strategy.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Image Compression for Wireless Sensor Network: A Model Segmentation-Based Compressive Autoencoder

引用

Wireless Communications and Mobile Computing 2023年第1期2023卷

作者： Bao, Xuecai Ye, Chen Han, Longzhe Xu, Xiaohua Jiangxi Province Key Laboratory of Water Information Cooperative Sensing and Intelligent Processing Nanchang Institute of Technology Jiangxi Nanchang330099 China School of Information Engineering Nanchang Institute of Technology Jiangxi Nanchang330099 China Jiangxi Academy of Water Science and Engineering Jiangxi Nanchang330029 China

Aiming at the problems of image quality, compression performance, and transmission efficiency of image compression in wireless sensor networks (WSN), a model segmentation-based compressive autoencoder (MS-CAE) is proposed. In the proposed algorithm, we first divide each image in the dataset into pixel blocks and design a novel deep image compression network with a compressive autoencoder to form a compressed feature map by encoding pixel blocks. Then, the reconstructed image is obtained by using the quantized coefficients of the quantizer and splicing the decoded feature maps in order. Finally, the deep network model is segmented into two parts: the encoding network and the decoding network. The weight parameters of the encoding network are deployed to the edge device for the compressed image in the sensor network. For high-quality reconstructed images, the weight parameters of the decoding network are deployed to the cloud system. Experimental results demonstrate that the proposed MS-CAE obtains a high signal-to-noise ratio (PSNR) for the details of the image, and the compression ratio at the same bit per pixel (bpp) is significantly higher than that of the compared image compression algorithms. It also indicates that the MS-CAE not only greatly relieves the pressure of the hardware system in sensor network but also effectively improves image transmission efficiency and solves the deployment problem of image monitoring in remote and energy-poor areas. © 2023 Xuecai Bao et al.

关键词： Image compression

来源：评论

学校读者我要写书评

暂无评论

Evaluating the Performance to Detecting Topic Shift of Large Language Models: A Study

Evaluating the Performance to Detecting Topic Shift of Large...

引用

6th International Conference on intelligent Computing and signal processing (ICSP)

作者： Pingfang Tian Deting Liu Department of Computer Science and Technology Wuhan University of Science and Technology Wuhan China The Key Laboratory of the Rich Media Knowledge Organisation and Service of Digital Publishing Content Institute of Scientific and Technical Information of China Beijing China Hubei Province Key Laboratory of Intelligent Information Processing and Real-time Industrial System Wuhan China Big Data Science and Engineering Research Institute Wuhan University of Science and Technology Wuhan China

ISBN: (数字)9798350376548

ISBN: (纸本)9798350376555

Topic shift detection aims to identify whether there is a change in the current topic of conversation or if a change is needed. The study found previous work did not evaluate the performance of large language models like ChatGPT on the task of topic shift. Therefore, this paper's main task and innovation lie in analyzing ChatGPT's performance on topic shift detection. To provide a more comprehensive evaluation, we conducted topic shift detection tasks on ChatGPT from three aspects: single utterances, adjacent utterances, and contextual levels. Additionally, to gauge the performance of large language models, we conducted experiments on multiple small-scale models and compared the results of the two models. Experimental results on the publicly available English TIAGE dataset showed that small-scale models exhibited lower recall in all three aspects, while ChatGPT performed better in the recall. This suggests that compared to small-scale models, large models are more capable of accurately detecting topic shifts. However, large models also exhibited lower precision, indicating that while ChatGPT can recognize content differences in utterances, its judgment on whether these different contents belong to the same topic is poor.

关键词： Technological innovation Large language models Oral communication signal processing Chatbots Context modeling

来源：评论

学校读者我要写书评

暂无评论

Inter-pulse carrier frequency agile design for cognitive radar

Inter-pulse carrier frequency agile design for cognitive rad...

引用

IET International radar Conference (IRC 2023)

作者： Yin Li Tao Fan Xianxiang Yu Lan Lan Huai Ding Guolong Cui School of Information and Communication Engineering University of Electronic Science and Technology of China Chengdu People's Republic of China National Key Laboratory of Radar Signal Processing Xidian University Xi'an People's Republic of China The 29th Research Institute of China Electronics Technology Group Corporation Chengdu People's Republic of China

ISBN: (数字)9781837240982

This paper deals with the joint design of inter-pulse frequency and receive filter to reduce the Doppler sidelobe for cognitive Frequency Agile radar (FAR) working in search and confirmation modes. At first, we introduce an inter-pulse coherent processing method that integrates phase compensation with Weighted Non-Uniform Discrete Fourier Transform (W-NUDFT). Then, a multi-parameter non-convex optimization model is established based on the issue of high Doppler sidelobes caused by inter-pulse non-uniform accumulation. Subsequently, we develop an alternating iterative optimization algorithm that combines Coordinate Descent with Alternating Direction Method of Multipliers (CD-ADMM) to tackle the resulting non-convex optimization problem. Finally, through numerical simulations, the effectiveness of the waveform via the application on weak targets detection accompanied by strong targets is demonstrated.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Precise segmentation of offshore farms in high-resolution SAR Images based on improved UNet++

Precise segmentation of offshore farms in high-resolution SA...

引用

2021 International Conference on Computer Application and information Security, ICCAIS 2021

作者： Yu, Chuang Liu, Yunpeng Xia, Xin Key Laboratory of Opto-Electronic Information Processing Chinese Academy of Sciences Shenyang110016 China Shenyang Institute of Automation Chinese Academy of Sciences Shenyang110016 China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang110169 China School of Computer Science and Technology University of Chinese Academy of Sciences Beijing100049 China

ISBN: (纸本)9781510655218

The segmentation of the offshore farm area in the high-resolution SAR image is of great significance for the statistics of the farming area and the analysis of the rationality of the farming layout. However, the SAR images have the characteristics of a lot of noise and inconspicuous features. It is difficult to achieve precise segmentation by directly using non-learning image segmentation methods. Therefore, we propose a precise segmentation scheme for offshore farms in high-resolution SAR images based on improved UNet++. We first adopt a simulated annealing strategy for the update of the learning rate during the network training. By initializing the learning rate multiple times, we avoid the network from falling into a local optimum. Secondly, for the data set studied, we verify that the segmentation performance of resizing the image to 256×256 pixels is better than that of 512×512 pixels. Finally, we propose an improved UNet++, which uses SE-Net as the feature extraction network to enhance the feature learning ability. Extensive experimental results show that, compared to some state-of-the-art methods, the proposed scheme achieves superior performance with a Frequency Weighted Intersection over Union (FWIoU) of 0.9853 on the high-resolution SAR offshore farm data set. © The Authors.

关键词： Synthetic aperture radar

来源：评论

学校读者我要写书评

暂无评论

Coherence Analysis and Interferometric Measurement of P-Band Repeat Pass UAV InSAR

Coherence Analysis and Interferometric Measurement of P-Band...

引用

IEEE International Symposium on Geoscience and Remote Sensing (IGARSS)

作者： Xin Xie Yunkai Deng Zihang Jiang Xiaoxiao Li Weiming Tian Radar Technology Research Institute Beijing Institute of Technology Beijing China Chongqing Innovation Center Beijing Institute of Technology Chongqing China Beijing Key Laboratory of Embedded Real-Time Information Processing Technology Beijing China Beijing Building Research Institute Co. Ltd. of CSCEC Beijing China Advanced Technology Research Institute Beijing Institute of Technology Jinan China

ISBN: (数字)9798350360325

ISBN: (纸本)9798350360332

Miniaturized and lightweight unmanned aerial vehicles (UAV) provide a flexible platform for synthetic aperture radar (SAR). The application of UAV interferometric SAR (InSAR) is gradually increasing in interferometric measurement fields. Leveraging the P-band signal and the capability to penetrate leaf clusters, these UAV InSAR systems demonstrate significant potential for topographic mapping and deformation monitoring, even in challenging surface conditions. This paper introduces the primary challenges associated with UAV InSAR, with a specific focus on analyzing the coherence of UAV InSAR. Additionally, we present interferometric measurement results obtained by our self-developed P-band UAV InSAR system and the processing flow we proposed. These results effectively address key challenges and validate the feasibility of the system for repeat pass interferometric measurements.

关键词： Optical interferometry Deformation Geoscience and remote sensing Coherence Gain measurement Autonomous aerial vehicles Surface topography

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：