检索结果-内蒙古大学图书馆

您好，读者！请登录

内蒙古大学图书馆

首页
概况
党建
资源
服务
科研支持
- 论文收录引用证明
- 科技查新
知识产权
档案馆
帮助

咨询与建议

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

您的常用邮箱：*

您的手机号码：*

问题描述：

当前已输入0个字，您还可以输入200个字

全部搜索
期刊论文
图书
学位论文
标准
纸本馆藏
外文资源发现
数据库导航
超星发现

高级检索

时间限定

出版年份：

文献类型

图书期刊文献学位论文多媒体

馆藏选择

电子馆藏纸本馆藏

核心期刊

全部期刊 SCI 收录期刊 SSCI 收录期刊 EI 收录期刊 CSCD 收录期刊 CSSCI 收录期刊

语言

中文英文

文献类型

期刊文献图书学位论文标准纸本馆藏

帮助

文字说明：

T=题名（书名、题名），A=作者（责任者），K=主题词，P=出版物名称，PU=出版社名称，O=机构（作者单位、学位授予单位、专利申请人），L=中图分类号，C=学科分类号，U=全部字段，Y=年（出版发行年、学位年度、标准发布年）

检索规则说明：

AND代表“并且”；OR代表“或者”；NOT代表“不包含”；(注意必须大写,运算符两边需空一格)

检索范例：

范例一：(K=图书馆学 OR K=情报学) AND A=范并思 AND Y=1982-2016
范例二：P=计算机应用与软件 AND (U=C++ OR U=Basic) NOT K=Visual AND Y=2011-2016

分类表

所选分类

>> <<

限定检索结果

文献类型

5,626 篇 会议
90 篇 期刊文献
10 册 图书

馆藏范围

5,726 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

2,768 篇 工学
- 2,326 篇 计算机科学与技术...
- 1,324 篇 软件工程
- 566 篇 信息与通信工程
- 466 篇 电气工程
- 200 篇 生物工程
- 176 篇 控制科学与工程
- 174 篇 生物医学工程（可授...
- 109 篇 机械工程
- 84 篇 交通运输工程
- 83 篇 化学工程与技术
- 81 篇 电子科学与技术（可...
- 79 篇 光学工程
- 70 篇 仪器科学与技术
- 65 篇 动力工程及工程热...
- 55 篇 安全科学与工程
- 54 篇 土木工程
- 52 篇 环境科学与工程（可...
899 篇 理学
- 478 篇 数学
- 235 篇 生物学
- 232 篇 物理学
- 191 篇 统计学（可授理学、...
- 119 篇 系统科学
- 67 篇 化学
589 篇 管理学
- 326 篇 图书情报与档案管...
- 307 篇 管理科学与工程(可...
- 164 篇 工商管理
290 篇 医学
- 244 篇 临床医学
- 144 篇 基础医学(可授医学...
- 80 篇 药学(可授医学、理...
76 篇 法学
- 71 篇 社会学
55 篇 经济学
45 篇 教育学
40 篇 农学
26 篇 文学
2 篇 军事学
1 篇 历史学
1 篇 艺术学

主题

1,599 篇 data models
534 篇 predictive model...
529 篇 training
498 篇 machine learning
461 篇 data mining
416 篇 big data
404 篇 computational mo...
343 篇 feature extracti...
333 篇 task analysis
326 篇 prediction algor...
267 篇 deep learning
255 篇 machine learning...
245 篇 classification a...
238 篇 analytical model...
191 篇 clustering algor...
190 篇 support vector m...
182 篇 neural networks
158 篇 natural language...
142 篇 training data
141 篇 mathematical mod...

机构

19 篇 sun yat sen univ...
19 篇 daffodil interna...
12 篇 univ chinese aca...
11 篇 tsinghua univers...
11 篇 university of ch...
11 篇 school of data a...
10 篇 carnegie mellon ...
9 篇 renmin univ chin...
9 篇 lviv polytechnic...
8 篇 shenzhen researc...
7 篇 shanghai jiao to...
7 篇 college of compu...
7 篇 university of el...
7 篇 school of comput...
7 篇 national univers...
7 篇 harbin institute...
7 篇 beijing key lab ...
7 篇 natl univ def te...
7 篇 renmin univ chin...
6 篇 university of sc...

作者

7 篇 li li
7 篇 wang wei
7 篇 xiao yanghua
6 篇 wen ji-rong
6 篇 cui bin
6 篇 zhao wayne xin
6 篇 ying liu
6 篇 syed akhter hoss...
5 篇 yang tong
5 篇 liu yang
5 篇 li zhang
5 篇 jia weijia
5 篇 chen liu
5 篇 yang yang
5 篇 xiao hongbo
5 篇 nguyen trong-the
5 篇 yu jie
5 篇 albert bifet
5 篇 wang bin
5 篇 carlos ordonez

语言

5,682 篇 英文
36 篇 其他
9 篇 中文
2 篇 俄文
1 篇 乌克兰文

检索条件"任意字段=2020 International Conference on Data Processing Algorithms and Models, ICDPAM 2020"

共 5726 条记录，以下是51-60 订阅

全选清除本页清除全部题录导出标记到"检索档案"

详细简洁

排序：

Towards a Standardized Real-Time data Repository based on Laboratory Test Results 14

Towards a Standardized Real-Time Data Repository based on La...

引用

14th international conference on Emerging Ubiquitous Systems and Pervasive Networks / 13th international conference on Current and Future Trends of Information and Communication Technologies in Healthcare, EUSPN/ICTH 2023

作者： Sousa, Regina Peixoto, Hugo Guimarães, Tiago Abelha, António Machado, José LASI/Algoritmi Research Centre University of Minho Guimarães Portugal

Healthcare facilities use huge quantities of real-time and analytical data to discover meaningful information from patient clinical lab results. Advanced analytics and machine learning algorithms help doctors identify and treat patients more accurately. Accurate models must be trained, tested, and validated with enough data. New real-time data allows healthcare practitioners to quickly and accurately analyse patient demands. Healthcare organizations can improve patient care and outcomes through knowledge discovery. The goal of this effort is to develop a real-time data repository based on patient clinical exams. This collection feeds real-time monitoring panels and machine or deep learning algorithms that forecast patient progression from clinical lab results. Integrate HL7 messages from diverse sources, preprocess them, and add them to an API-accessible data warehouse. In conclusion, the proposed method creates an international-standard data warehouse. This data warehouse can increase healthcare decision-making accuracy and efficacy when utilised with machine learning models, improving patient care and outcomes through more personalised treatment options. © 2024 The Authors. Published by Elsevier B.V.

关键词： data warehouses

来源：评论

学校读者我要写书评

暂无评论

Analysis of Bias in GPT Language models through Fine-tuning Containing Divergent data

Analysis of Bias in GPT Language Models through Fine-tuning ...

引用

international Joint conference on Neural Networks (IJCNN)

作者： Turi, Leandro Furlam Cavalini, Athus Comarela, Giovanni Oliveira-Santos, Thiago Badue, Claudine De Souza, Alberto F. Univ Fed Espirito Santo Dept Informat Vitoria ES Brazil Inst Fed Espirito Santo Alegre Nucleo Inform Vitoria ES Brazil

ISBN: (纸本)9798350359329;9798350359312

In this study, we examined the effects of integrating data that contains divergent information, especially concerning anti-vaccination narratives, into the training of a GPT-2 language model. The model was fine-tuned using content sourced from anti-vaccination groups and channels on Telegram, aiming to analyze its ability to generate coherent and rationalized texts in comparison to a model pre-trained on OpenAI's WebText dataset. The results demonstrate that fine-tuning a GPT-2 model with biased data leads the model to perpetuate these biases in its responses, albeit with a certain degree of rationalization. This finding underscores the importance of using high-quality and reliable data in training natural language processing models, highlighting the implications for information dissemination through these models. It also provides social scientists with a tool to explore and understand the complexities and challenges associated with public health misinformation via the use of language models, particularly in the context of vaccines.

关键词： GPT-2 Fine-tuning Telegram Anti-vaccination

来源：评论

学校读者我要写书评

暂无评论

Naturalistic Music Decoding from EEG data via Latent Diffusion models

Naturalistic Music Decoding from EEG Data via Latent Diffusi...

引用

2025 IEEE international conference on Acoustics, Speech, and Signal processing, ICASSP 2025

作者： Postolache, Emilian Polouliakh, Natalia Kitano, Hiroaki Connelly, Akima Rodolà, Emanuele Cosmo, Luca Akama, Taketo DAIS Ca' Foscari University of Venice Venice Italy Sony CSL Tokyo Japan Dept. of TSE Tokyo Institute of Technology Tokyo Japan Dept. of Computer Science Sapienza University of Rome Rome Italy

ISBN: (纸本)9798350368741

In this article, we explore the potential of using latent diffusion models, a family of powerful generative models, for the task of reconstructing naturalistic music from electroencephalogram (EEG) recordings. Unlike simpler music with limited timbres, such as MIDI-generated tunes or monophonic pieces, the focus here is on intricate music featuring a diverse array of instruments, voices, and effects, rich in harmonics and timbre. This study represents an initial foray into achieving general music reconstruction of high-quality using non-invasive EEG data, employing an end-to-end training approach directly on raw data without the need for manual pre-processing and channel selection. We train our models on the public NMED-T dataset and perform quantitative evaluation proposing neural embedding-based metrics. Our work contributes to the ongoing research in neural decoding and brain-computer interfaces, offering insights into the feasibility of using EEG data for complex auditory information reconstruction. © 2025 IEEE.

关键词： diffusion models electroencephalography Generative AI music generation

来源：评论

学校读者我要写书评

暂无评论

Mitigating Shortcut Learning via Smart data Augmentation based on Large Language Model 31

Mitigating Shortcut Learning via Smart Data Augmentation bas...

引用

31st international conference on Computational Linguistics, COLING 2025

作者： Sun, Xinyi Tan, Hongye Guo, Yaxin Qiang, Pengpeng Li, Ru Zhang, Hu School of Computer and Information Technology Shanxi University Taiyuan China Institute of Intelligent Information Processing Shanxi University Taiyuan China Key Laboratory of Computational Intelligence and Chinese Information Processing of Ministry of Education Shanxi University Taiyuan China

ISBN: (纸本)9798891761964

data-driven pre-trained language models typically perform shortcut learning wherein they rely on the spurious correlations between the data and the ground truth. This reliance can undermine the robustness and generalization of the model. To address this issue, data augmentation emerges as a promising solution. By integrating anti-shortcut data to the training set, the models' shortcut-induced biases can be mitigated. However, existing methods encounter three challenges: (1) Manual definition of shortcuts is tailored to particular datasets, restricting generalization. (2) The inherent confirmation bias during model training hampers the effectiveness of data augmentation. (3) Insufficient exploration of the relationship between the model performance and the augmented data quantity may result in excessive data consumption. To tackle these challenges, we propose a method of Smart data Augmentation based on Large Language models (SAug-LLM). It leverages the LLMs to autonomously identify shortcuts and generate their anti-shortcut counterparts. In addition, the dual validation is employed to mitigate the confirmation bias during the model retraining. Furthermore, the data augmentation process is optimized to effectively rectify model biases while minimizing data consumption. We validate the effectiveness and generalization of our method through extensive experiments across various natural language processing tasks, demonstrating an average performance improvement of 5.61%. © 2025 Association for Computational Linguistics.

关键词： data assimilation

来源：评论

学校读者我要写书评

暂无评论

A Privacy Protected Sleep Quality Prediction Approach Using Ultrawideband Ambient Sensor, Synthetic data, and Deep Learning 24

A Privacy Protected Sleep Quality Prediction Approach Using ...

引用

9th international conference on Machine Learning Technologies (ICMLT)

作者： Uddin, Md Zia SINTEF Digital Sustainable Commun Technol N-0373 Oslo Norway

ISBN: (纸本)9798400716379

Sleep quality assessment is crucial for maintaining overall wellbeing and health. This paper proposes a novel approach for modeling sleep quality based on ultrawideband sensor data and machine learning techniques. The methodology involves data collection using an ultrawideband sensor placed near the subject's bed to record respiration patterns throughout the night. Due to limited available data, synthetic data generation techniques were employed to augment the dataset. The synthesized data was then categorized into specific sleep quality categories (Bad, Okay, Good) using the K-Nearest Neighbors (K-NN) algorithm based on Euclidean distance. Following data preprocessing and categorization, bidirectional Long Short-Term Memory (LSTM) models were utilized to model the relationship between respiration patterns and sleep quality. LSTM models are well-suited for sequential data processing and have shown promising results in various time-series prediction tasks. Hence, the performance of the proposed approach was evaluated through experiments using augmented real and synthetic data, and the results demonstrated the effectiveness of the bidirectional LSTM models with reasonable accuracy. Thus, utilizing ultrawideband sensor-based respirations and synthetic data combined with machine learning techniques can contribute to objective sleep quality assessment.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Proceedings of the ACM SIGMOD international conference on Management of data

Proceedings of the ACM SIGMOD International Conference on Ma...

引用

2020 ACM SIGMOD international conference on Management of data, SIGMOD 2020

ISBN: (纸本)9781450367356

The proceedings contain 230 papers. The topics discussed include: recommending deployment strategies for collaborative tasks;human-in-the-loop outlier detection;Marviq: quality-aware geospatial visualization of range-selection queries using materialization;transactional causal consistency for serverless computing;cost models for big data query processing: learning, retrofitting, and our findings;lambada: interactive data analytics on cold data using serverless cloud infrastructure;starling: a scalable query engine on cloud functions;learning a partitioning advisor for cloud databases;sample debiasing in the themis open world database system;stochastic package queries in probabilistic databases;fast and reliable missing data contingency analysis with predicate-constraints;mining approximate acyclic schemes from relations;and an ontology-based conversation system for knowledge bases.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Sub-system Integration and Health Dashboard for Autonomous Mobile Robots 3rd

Sub-system Integration and Health Dashboard for Autonomous M...

引用

3rd international conference on Optimization, Learning algorithms and Applications (OL2A)

作者： Franca, Andre Loures, Eduardo Jorge, Luisa Mendes, Andre Inst Politecn Braganca IPB Braganca Portugal Univ Tecnol Fed Parana UTFPR Curitiba Parana Brazil

ISBN: (纸本)9783031530357;9783031530364

data visualization has become increasingly important to improve equipment monitoring, reduce operational costs and increase process efficiency with the ever-increasing amount of data being generated and collected in various fields. This paper proposes the development of a health monitoring system for an Autonomous Mobile Robot (AMR) that allows data acquisition and analysis for decision-making. The implementation of the proposed system showed favourable results in data acquisition, analysis, and visualization for decision-making. Through the use of a hybrid control architecture, the data acquisition and processing demonstrated efficiency without significant impact on battery consumption or resource usage of the AMR embedded microcomputer. The developed dashboard proved to be efficient in navigating and visualizing the data, providing important tools for the platform manager's decision-making. This work contributes to the health monitoring of devices based on Robot Operating System (ROS), which may be of interest to professionals and researchers in fields related to robotics and automation. Furthermore, the system presented will be open source, making it accessible and adaptable for use in different contexts and applications.

关键词： Human Machine Interface data visualization Autonomous Mobile Robot Robot Operating System Open Source Software

来源：评论

学校读者我要写书评

暂无评论

NavCim: Comprehensive Design Space Exploration for Analog Computing-in-Memory Architectures 24

NavCim: Comprehensive Design Space Exploration for Analog Co...

引用

international conference on Parallel Architectures and Compilation Techniques (PACT)

作者： Park, Juseong Kim, Boseok Sung, Hyojin Pohang Univ Sci & Technol Pohang South Korea Seoul Natl Univ Seoul South Korea

ISBN: (数字)9798400706318

ISBN: (纸本)9798400706318

Analog computing-in-memory (ACiM) technology has shown strong potential for neural network accelerators, addressing von-Neumann performance bottlenecks with in-memory data processing and computation. Understanding the ACiM design space, including its trade-offs and constraints, and systematically and effectively exploring it for optimal performance is essential to turn the promise into a viable product. Recent research demonstrated that multi-objective searches for ACiM architectures with heterogeneous tiles can simultaneously optimize power, performance, and area (PPA), outperforming existing tiled ACiM proposals. In this paper, we propose NavCim, a comprehensive ACiM design space exploration mechanism that advances the prior work in terms of search efficiency, search space coverage, and optimization metrics. NavCim introduces predictive modeling of ACiM hardware performance and uses the PPA prediction models instead of running simulators, significantly reducing search overheads. Faster searches enable NavCim to extend the architecture and model search spaces with an evolutionary search process to optimize architectures with more than two different tile sizes for multiple input models. With accuracy-aware searches, NavCim considers PPA and model accuracy together as optimization goals to achieve more balanced trade-offs. The experimental searches show that NavCim leverages predictive models to reduce search time by up to 7.3x without compromising the quality of search results. It also successfully identifies heterogeneous ACiM architectures that can efficiently execute multiple models on a single chip, improving accuracy by up to 19% over the prior work.

关键词： Accuracy Neural networks Predictive models Extraterrestrial measurements data processing Hardware Space exploration Parallel architectures Proposals Optimization

来源：评论

学校读者我要写书评

暂无评论

Method for sharing test data based on blackboard model

Method for sharing test data based on blackboard model

引用

2020 international conference on data processing algorithms and models, icdpam 2020

作者： Du, Zhanlong Li, Bo Yang, Qiushi Wang, Tianqi Jinzhou Test and Research Center Jinzhou Liaoning China

With the accelerated development of the equipment under test towards informatization and systemization, higher requirements are put forward for the construction of the test capacity of the equipment under test. It is a good way to maximize the value of test data as a core resource through building a test data distributing and sharing platform. A test data distributing and sharing method based on the blackboard model is proposed in this paper. Then a data sharing model is established including data management service center, data demanders, and operating mechanism to meet the needs of remote storage and global sharing of test data. © Published under licence by IOP Publishing Ltd.

关键词： Informatization

来源：评论

学校读者我要写书评

暂无评论

On the Use of VGs for Feature Selection in Supervised Machine Learning - A Use Case to Detect Distributed DoS Attacks 1

引用

3rd international conference on Optimization, Learning algorithms and Applications (OL2A)

作者： Lopes, Joao Partida, Alberto Pinto, Pedro Pinto, Antonio Inst Politecn Viana Do Castelo ADiT Lab Viana Do Castelo Portugal Rey Juan Carlos Univ Data Complex Networks & Cybersecur Sci Technol In Madrid Spain Univ Maia Maia Portugal Inst Politecn Porto ESTG CIICESI Felgueiras Portugal INESC TEC Porto Portugal

ISBN: (数字)9783031530258

ISBN: (纸本)9783031530241;9783031530258

Information systems depend on security mechanisms to detect and respond to cyber-attacks. One of the most frequent attacks is the Distributed Denial of Service (DDoS): it impairs the performance of systems and, in the worst case, leads to prolonged periods of downtime that prevent business processes from running normally. To detect this attack, several supervised Machine Learning (ML) algorithms have been developed and companies use them to protect their servers. A key stage in these algorithms is feature pre-processing, in which, input data features are assessed and selected to obtain the best results in the subsequent stages that are required to implement supervised ML algorithms. In this article, an innovative approach for feature selection is proposed: the use of Visibility Graphs (VGs) to select features for supervised machine learning algorithms used to detect distributed DoS attacks. The results show that VG can be quickly implemented and can compete with other methods to select ML features, as they require low computational resources and they offer satisfactory results, at least in our example based on the early detection of distributed DoS. The size of the processed data appears as the main implementation constraint for this novel feature selection method.

关键词： Artificial intelligence Machine Learning Supervised Learning Denial of Service attack Visibility Graph Cybersecurity

来源：评论

学校读者我要写书评

暂无评论

没有更多数据了...

全选清除本页清除全部题录导出标记到“检索档案”

共500页 << < 2 3 4 5 6 7 8 9 10 11 > >>

检索报告对象比较合并检索0

隐藏清空

合并搜索

回到顶部

执行限定条件

内容：

评分：

请选择保存的检索档案：

请选择收藏分类：

订阅名称：

通借通还

温馨提示：

图书名称：

借书校区：

取书校区：

手机号码：

邮箱地址：

一卡通帐号：

电话和邮箱必须正确填写，我们会与您联系确认。

联系人：

所在院系：

联系邮箱：

联系电话：

内蒙古自治区呼和浩特市赛罕区大学西街235号邮编: 010021

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：