检索结果-内蒙古大学图书馆

arXiv 2024年

作者： Zhou, Shuang Xu, Zidu Zhang, Mian Xu, Chunpu Guo, Yawen Zhan, Zaifu Ding, Sirui Wang, Jiashuo Xu, Kaishuai Fang, Yi Xia, Liqiao Yeung, Jeremy Zha, Daochen Lin, Mingquan Zhang, Rui Division of Computational Health Sciences Department of Surgery University of Minnesota MinneapolisMN United States School of Nursing Columbia University New YorkNY United States Erik Jonsson School of Engineering and Computer Science University of Texas at Dallas RichardsonTX United States Department of Computing The Hong Kong Polytechnic University Hong Kong Department of Informatics University of California Irvine IrvineCA United States Department of Electrical and Computer Engineering University of Minnesota MinneapolisMN United States Bakar Computational Health Sciences Institute University of California San Francisco San FranciscoCA United States Shanghai China Department of Industrial and Systems Engineering The Hong Kong Polytechnic University Hong Kong Department of Computer Science Rice University HoustonTX United States

Automatic disease diagnosis has become increasingly valuable in clinical practice. The advent of large language models (LLMs) has catalyzed a paradigm shift in artificial intelligence, with growing evidence supporting the efficacy of LLMs in diagnostic tasks. Despite the growing attention in this field, many critical research questions remain under-explored. For instance, what diseases and LLM techniques have been investigated for diagnostic tasks? How can suitable LLM techniques and evaluation methods be selected for clinical decision-making? To answer these questions, we performed a comprehensive analysis of LLM-based methods for disease diagnosis. This scoping review examined the types of diseases, associated organ systems, relevant clinical data, LLM techniques, and evaluation methods reported in existing studies. Furthermore, we offered guidelines for data preprocessing and the selection of appropriate LLM techniques and evaluation strategies for diagnostic tasks. We also assessed the limitations of current research and delineated the challenges and future directions in this research field. In summary, our review outlined a blueprint for LLM-based disease diagnosis, helping to streamline and guide future research endeavors. Copyright © 2024, The Authors. All rights reserved.

关键词： Diseases

来源：评论

学校读者我要写书评

暂无评论

Generative AI for Unmanned Vehicle Swarms: Challenges, Applications and Opportunities

arXiv

引用

arXiv 2024年

作者： Liu, Guangyuan Van Huynh, Nguyen Du, Hongyang Hoang, Dinh Thai Niyato, Dusit Zhu, Kun Kang, Jiawen Xiong, Zehui Jamalipour, Abbas In Kim, Dong The School of Computer Science and Engineering The Energy Research Institute @ NTU Interdisciplinary Graduate Program Nanyang Technological University Singapore The Department of Electrical Engineering and Electronics University of Liverpool Liverpool L69 3GJ United Kingdom The School of Electrical and Data Engineering University of Technology Sydney Australia The School of Computer Science and Engineering Nanyang Technological University Singapore College of Computer Science and Technology Nanjing University of Aeronautics and Astronautics Nanjing China The School of Automation Guangdong University of Technology China The Pillar of Information Systems Technology and Design Singapore University of Technology and Design Singapore The School of Electrical and Information Engineering University of Sydney Australia The College of Information and Communication Engineering Sungkyunkwan University Korea Republic of

With recent advances in artificial intelligence (AI) and robotics, unmanned vehicle swarms have received great attention from both academia and industry due to their potential to provide services that are difficult and dangerous to perform by humans. However, learning and coordinating movements and actions for a large number of unmanned vehicles in complex and dynamic environments introduce significant challenges to conventional AI methods. Generative AI (GAI), with its capabilities in complex data feature extraction, transformation, and enhancement, offers great potential in solving these challenges of unmanned vehicle swarms. For that, this paper aims to provide a comprehensive survey on applications, challenges, and opportunities of GAI in unmanned vehicle swarms. Specifically, we first present an overview of unmanned vehicles and unmanned vehicle swarms as well as their use cases and existing issues. Then, an in-depth background of various GAI techniques together with their capabilities in enhancing unmanned vehicle swarms are provided. After that, we present a comprehensive review on the applications and challenges of GAI in unmanned vehicle swarms with various insights and discussions. Finally, we highlight open issues of GAI in unmanned vehicle swarms and discuss potential research directions. © 2024, CC BY.

关键词： Metadata

来源：评论

学校读者我要写书评

暂无评论

Pay Self-Attention to Audio-Visual Navigation

arXiv

引用

arXiv 2022年

作者： Yu, Yinfeng Cao, Lele Sun, Fuchun Liu, Xiaohong Wang, Liejun Department of Computer Science and Technology State Key Lab on Intelligent Technology and Systems Tsinghua University Beijing China Motherbrain EQT Stockholm Sweden College of Information Science and Engineering Xinjiang University Urumqi China

Audio-visual embodied navigation, as a hot research topic, aims training a robot to reach an audio target using egocentric visual (from the sensors mounted on the robot) and audio (emitted from the target) input. The audio-visual information fusion strategy is naturally important to the navigation performance, but the state-of-the-art methods still simply concatenate the visual and audio features, potentially ignoring the direct impact of context. Moreover, the existing approaches requires either phase-wise training or additional aid (e.g. topology graph and sound semantics). Up till this date, the work that deals with the more challenging setup with moving target(s) is still rare. As a result, we propose an end-to-end framework FSAAVN (feature self-attention audio-visual navigation) to learn chasing after a moving audio target using a context-aware audio-visual fusion strategy implemented as a self-attention module. Our thorough experiments validate the superior performance (both quantitatively and qualitatively) of FSAAVN in comparison with the state-of-the-arts, and also provide unique insights about the choice of visual modalities, visual/audio encoder backbones and fusion patterns. © 2022, CC BY-NC-ND.

关键词： Topology

来源：评论

学校读者我要写书评

暂无评论

Evaluation of machine learning algorithms in a human-computer hybrid record linkage system

Evaluation of machine learning algorithms in a human-compute...

引用

2021 AAAI Spring Symposium on Combining Machine Learning and Knowledge Engineering, AAAI-MAKE 2021

作者： Ramezani, Mahin Ilangovan, Guru Kum, Hye-Chung Department of Computer Science Texas A&M University 400 Bizzell St College StationTX77843 United States Population Informatics Lab Department of Health Policy and Management Texas A&M University School of Public Health 212 Adriance Lab Rd College StationTX77843 United States

Record linkage, often called entity resolution or de-duplication, refers to identifying the same entities across one or more databases. As the amount of data that is generated grows at an exponential rate, it becomes increasingly important to be able to integrate data from several sources to perform richer analysis. In this paper, we present an open source comprehensive end to end hybrid record linkage framework that combines the automatic and manual review process. Using this framework, we train several models based on different machine learning algorithms such as random forests, linear SVM, Radial SVM, and Dense Neural Networks and compare the effectiveness and efficiency of these models for record linkage in different settings. We evaluate model performance based on Recall, F1-score (quality of linkages) and number of uncertain pairs which is the number of pairs that need manual review. We also test our trained models in a new dataset to test how different trained models transfer to a new setting. The RF, linear SVM and radial SVM models transfer much better compared to the DNN. Finally, we study the effect of name2vec (n2v) feature, a letter embedding in names, on model performance. Using n2v results in smaller manual review set with slightly less F1-score. Overall the SVM models performed best in all experiments. © 2021 Copyright for this paper by its authors. Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0). CEUR Workshop Proceedings (***)

关键词： Decision trees

来源：评论

学校读者我要写书评

暂无评论

The stratified K-folds cross-validation and class-balancing methods with high-performance ensemble classifiers for breast cancer classification

引用

Healthcare Analytics 2023年 4卷 100247-100247页

作者： T R, Mahesh V, Vinoth Kumar V, Dhilip Kumar Geman, Oana Margala, Martin Guduri, Manisha Department of Computer Science and Engineering Faculty of Engineering and Technology JAIN (Deemed-to-be University) Bangalore 562112 India School of Computer Science Engineering & Information Systems (SCORE) Vellore Institute of Technology (VIT) 632014 India School of Computing Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology Chennai 600062 India Department of Computers Electronics and Automation Faculty of Electrical Engineering and Computer Science Stefan cel Mare University of Suceava Suceava 720229 Romania School of Computing and Informatics University of Louisiana at Lafayette United States

Breast cancer is one of the most common causes of death among women, and early diagnosis is vital for reducing the fatality rate. This study evaluates the most widely used machine-learning breast cancer prediction and diagnosis methods. We use synthetic minority over-sampling to handle imbalanced data in the breast cancer diagnosis dataset obtained from the Wisconsin Machine Learning Repository. We use a variety of machine learning algorithms, including Logistic Regression (LR), Support Vector Machine (SVM), K-Nearest Neighbours (KNN), Classification and Regression Tree (CART), Naive Bayes (NB), and well-known ensembles methods like Majority-Voting, eXtreme Gradient Boosting algorithm (XGBoost), and Random Forest (RF) for the breast cancer classification. The findings show that the Majority-Voting ensemble method, built on the top three classifiers (LR, SVM, and CART), outperforms all other individual classifiers and offers the highest accuracy of 99.3%. © 2023 The Author(s)

关键词： Breast cancer Class-balancing Cross-validation Diagnostic analytics Ensemble method Machine learning

来源：评论

学校读者我要写书评

暂无评论

Measurement of Absorption Current of Polyester Coated Enameled Wires with Q(t) Meter

Measurement of Absorption Current of Polyester Coated Enamel...

引用

International Symposium on Electrical Insulating Materials

作者： Akinao Watanabe Masumi Fukuma Yoitsu Sekiguchi Advanced Electronic and Information Systems Course National Institute of Technology Matsue College Matsue Japan Department of Electrical Engineering and Computer Science National Institute of Technology Matsue College Matsue Japan Energy and Electronics Materials R&D Laboratories Sumitomo Electric Industries Osaka Japan

A Q(t) meter is used to measure electrical properties in insulating materials. Here, Q(t) is the integral value of circuit current with time t. It is possible to measure the Q(t) of the insulation material of a capacitor and a cable by using Q(t) meter. The current through an insulating material is divided into an instantaneous charging current, an absorption current and an equilibrium leakage current. It is considered that the absorption current is related to charge accumulation in the insulating materials. In this paper, an enameled wire (1.6 PEW) is used to prepare a cable sample, the Q(t) of the coated polyester (PEs) is measured, and extraction of absorption current components from measured Q(t) are reported.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Proposed New Framework Scheme for Path Loss in Wireless Body Area Network

Iraqi Journal for Computer Science and Mathematics

引用

Iraqi Journal for computer science and Mathematics 2022年第1期3卷 11-21页

作者： Al-Barazanchi, Israa Niu, Yitong Abdulshaheed, Haider Rasheed Hashim, Wahidah Alkahtani, Ammar Ahmed Daghighi, Elika Jaaz, Zahraa A. Shawkat, Shihab A. Rauf, Hafiz Tayyab College of Computing and Informatics Universiti Tenaga Nasional Malaysia Belarusian-Russian University Mira Avenue 43 Mogilev212000 Belarus Computer Engineering Techniques Department Baghdad College of Economic Sciences University Baghdad Iraq Institute of Sustainable Energy Universiti Tenga Nasional Selangor Kajang43000 Malaysia Technical and Vocational University Tehran Iran College of Science Computer Department AlNahrain University Baghdad Iraq University of Samarra Samarra Iraq Centre for Smart Systems AI and Cybersecurity Staffordshire University Stoke-on-Trent United Kingdom

Recent technical developments in wi-fi networking, microelectronic integration and programming, sensors and the Internet have enabled us to create and enforce a range of new framework schemes to fulfil the necessities of healthcare-related wireless body area network (WBAN). WBAN sensors continually screen and measure patients' indispensable signs and symptoms, and relay them to scientific monitoring for diagnosis. WBAN has a range of applications, the most necessary of which is to help patients suffering diseases to stay alive. The quality instance is the coronary heart implant sensor, whose video display unit monitors coronary heart sign and continuously transmits it. This setup eliminates the need for patients to visit the medical doctor frequently. Instead, they can take a seat at home and acquire an analysis and prescription for the disease. Today, a sizable effort is being made to increase low-power sensors and gadgets for utility in WBAN. A new framework scheme that addresses route loss in WBAN and discusses its penalties in depth is endorsed in this paper. The new framework scheme is applied to three case scenarios to obtain parameters by measuring vital information about the human body. On-body and intrabody conversation simulations are conducted. On-body conversation findings show that the route loss between transmitter and receiver rises with growing distance and frequency. © 2022 college of Education, Al-Iraqia University. All Rights Reserved.

关键词： Heart

来源：评论

学校读者我要写书评

暂无评论

The Implementation of a Network Log System Using RNN on Cyberattack Detection with Data Visualization 9th

The Implementation of a Network Log System Using RNN on Cybe...

引用

9th International Conference on Frontier Computing, FC 2019

作者： Yang, Chao-Tung Jiang, Wei-Je Kristiani, Endah Chan, Yu-Wei Liu, Jung-Chun Department of Computer Science Tunghai University Taichung City Taiwan Department of Industrial Engineering and Enterprise Information Tunghai University Taichung City Taiwan Department of Informatics Faculty of Engineering and Computer Science Krida Wacana Christian University Jakarta Indonesia College of Computing and Informatics Providence University Taichung City Taiwan

ISBN: (纸本)9789811532498

Network log data is essential to web administrator, which provides information such as, system error, cyberattack warning, mobile data gigabytes, message sending status, and so on. Managing the massive volume of log data give a challenge and an opportunity. It would be a challenge for administering large amounts of log data, and an opportunity to prevent future cyberattacks. In this paper, we aim to provide a network log data management, which can do visualization analyzing using Elasticsearch, Logstash, and Kibana (ELK Stack). In the ELK Stack technology, we can create filter, screen and analyze network log database on different purpose, and apply visualization effects on the web browser. Also, we propose a deep learning model using RNN for advanced network attack detection. From the model, we can learn the characteristics of each cyberattack by knowing network attack features and then cross-validation with the analysis information on the log system. Finally, we do the performance metric test using Grafana. © 2020, Springer Nature Singapore Pte Ltd.

关键词： Visualization

来源：评论

学校读者我要写书评

暂无评论

Prompting Disentangled Embeddings for Knowledge Graph Completion with Pre-trained Language Model

arXiv

引用

arXiv 2023年

作者： Geng, Yuxia Chen, Jiaoyan Zeng, Yuhang Chen, Zhuo Zhang, Wen Pan, Jeff Z. Wang, Yuxiang Xu, Xiaoliang Powerchina Huadong Engineering Corporation Limited Hangzhou311112 China School of Computer Science Hangzhou Dianzi University Hangzhou310018 China Department of Computer Science The University of Manchester ManchesterM13 9PL United Kingdom HDU-ITMO Joint Institute Hangzhou Dianzi University Hangzhou310018 China College of Computer Science and Technology Zhejiang University Hangzhou310028 China School of Software Technology Zhejiang University Ningbo315048 China School of Informatics The University of Edinburgh EdinburghEH8 9AB United Kingdom

Both graph structures and textual information play a critical role in Knowledge Graph Completion (KGC). With the success of Pre-trained Language Models (PLMs) such as BERT, they have been applied for text encoding for KGC. However, the current methods mostly prefer to fine-tune PLMs, leading to huge training costs and limited scalability to larger PLMs. In contrast, we propose to utilize prompts and perform KGC on a frozen PLM with only the prompts trained. Accordingly, we propose a new KGC method named PDKGC with two prompts — a hard task prompt which is to adapt the KGC task to the PLM pre-training task of token prediction, and a disentangled structure prompt which learns disentangled graph representation so as to enable the PLM to combine more relevant structure knowledge with the text information. With the two prompts, PDKGC builds a textual predictor and a structural predictor, respectively, and their combination leads to more comprehensive entity prediction. Solid evaluation on three widely used KGC datasets has shown that PDKGC often outperforms the baselines including the state-of-the-art, and its components are all effective. Our codes and data are available at https://***/genggengcss/PDKGC. © 2023, CC BY.

关键词： Knowledge graph

来源：评论

学校读者我要写书评

暂无评论

AgInS_(2)/ZnS quantum dots for noninvasive cervical cancer screening with intracellular pH sensing using fluorescence lifetime imaging microscopy

引用

Nano Research 2022年第6期15卷 5193-5204页

作者： Wenhua Su Dan Yang Yulan Wang Yawei Kong Wanlu Zhang Jing Wang Yiyan Fei Ruiqian Guo Jiong Ma Lan Mi Department of Optical Science and Engineering Shanghai Engineering Research Center of Ultra-precision Optical ManufacturingKey Laboratory of Micro and Nano Photonic Structures(Ministry of Education)School of Information Science and TechnologyFudan UniversityShanghai 200433China Institute for Electric Light Sources School of Information Science and TechnologyFudan UniversityShanghai 200433China Department of Gynecology and Obstetrics The Central Hospital of WuhanTongji Medical CollegeHuazhong University of Science and TechnologyWuhan 430014China Institute of Photonic Chips University of Shanghai for Science and TechnologyShanghai 200093China Centre for Artificial-Intelligence NanophotonicsSchool of Optical-Electrical and Computer EngineeringUniversity of Shanghai for Science and TechnologyShanghai 200093China Institute of Biomedical Engineering and Technology Academy for Engineer and TechnologyFudan University220 Handan RoadShanghai 200433China Shanghai Engineering Research Center of Industrial Microorganisms the Multiscale Research Institute of Complex Systems(MRICS)School of Life SciencesFudan University220 Handan RoadShanghai 200433China

Intracellular pH plays a critical role in biological functions,and abnormal pH values are related to various ***,we report on an intracellular pH sensor AgInS_(2)(AIS)/ZnS quantum dots(QDs)that show long fluorescence lifetimes of hundreds of nanoseconds and low *** lifetime imaging microscopy(FLIM)combined with AIS/ZnS QDs is used for the imaging of live cells in different pH buffers and different cell *** FLIM images of AIS/ZnS QDs in live cells demonstrate different intracellular pH values in different regions,such as in lysosomes or *** method can also distinguish cancer cells from normal cells,and the fluorescence lifetime difference of the AIS/ZnS QDs between the two types of cells is 100±7 *** importantly,the exfoliated cervical cells from 20 patients are investigated using FLIM combined with AIS/ZnS *** lifetime difference value between the normal and cervical cancer(CC)groups is 115±9 ns,and the difference between the normal and the precancerous lesion group is 64±9 *** the first time,the noninvasive method has been used for cervical cancer screening,and it has shown great improvement in sensitivity compared with a clinical conventional cytology examination.

关键词： AIS/ZnS quantum dots fluorescence lifetime imaging microscopy intracellular pH sensing cervical cancer screening noninvasive

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：