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

7,928 篇 会议
5,360 篇 期刊文献
91 册 图书

馆藏范围

13,379 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

8,825 篇 工学
- 6,870 篇 计算机科学与技术...
- 5,648 篇 软件工程
- 1,805 篇 信息与通信工程
- 1,082 篇 控制科学与工程
- 926 篇 生物工程
- 698 篇 电气工程
- 628 篇 机械工程
- 552 篇 电子科学与技术（可...
- 512 篇 光学工程
- 499 篇 生物医学工程（可授...
- 344 篇 化学工程与技术
- 298 篇 仪器科学与技术
- 295 篇 安全科学与工程
- 280 篇 动力工程及工程热...
- 267 篇 网络空间安全
- 260 篇 交通运输工程
- 245 篇 建筑学
4,172 篇 理学
- 2,482 篇 数学
- 1,003 篇 生物学
- 826 篇 物理学
- 718 篇 统计学（可授理学、...
- 454 篇 系统科学
- 374 篇 化学
2,698 篇 管理学
- 1,647 篇 管理科学与工程(可...
- 1,178 篇 图书情报与档案管...
- 595 篇 工商管理
424 篇 医学
- 365 篇 临床医学
- 312 篇 基础医学(可授医学...
380 篇 法学
- 284 篇 社会学
221 篇 经济学
- 220 篇 应用经济学
181 篇 教育学
134 篇 农学
56 篇 文学
40 篇 艺术学
38 篇 军事学
3 篇 哲学
1 篇 历史学

主题

353 篇 computer science
321 篇 feature extracti...
318 篇 semantics
289 篇 computational mo...
279 篇 deep learning
218 篇 data mining
196 篇 optimization
184 篇 educational inst...
181 篇 software enginee...
178 篇 training
166 篇 machine learning
158 篇 predictive model...
156 篇 image segmentati...
151 篇 neural networks
135 篇 wireless sensor ...
135 篇 accuracy
132 篇 servers
129 篇 internet of thin...
128 篇 support vector m...
126 篇 convolution

机构

474 篇 school of comput...
373 篇 state key labora...
295 篇 school of softwa...
275 篇 school of softwa...
265 篇 school of softwa...
262 篇 department of co...
260 篇 school of inform...
218 篇 school of comput...
210 篇 college of compu...
176 篇 school of softwa...
161 篇 school of comput...
160 篇 college of compu...
139 篇 school of comput...
138 篇 school of comput...
127 篇 school of comput...
127 篇 school of comput...
123 篇 school of comput...
119 篇 school of softwa...
116 篇 school of comput...
101 篇 school of comput...

作者

50 篇 gao yang
43 篇 jin wang
41 篇 liu yang
41 篇 qi lianyong
38 篇 wang lei
38 篇 wang wei
34 篇 chen huajun
33 篇 qi liu
33 篇 zhang wen
33 篇 tao dacheng
31 篇 zhao jian
30 篇 li li
30 篇 liu qi
29 篇 junping du
28 篇 sun xingming
28 篇 shen furao
27 篇 xiang-yang li
27 篇 zhang zhao
27 篇 zhang qiang
26 篇 lei wang

语言

12,593 篇 英文
545 篇 其他
257 篇 中文
2 篇 日文
1 篇 斯洛文尼亚文

检索条件"机构=School of Computer Science and Software Technology"

共 13379 条记录，以下是331-340 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：

What Are the Trends in Eco-Design Research When We Talk about Digital technology? - A Five Year Analytical Dive into Research Data

What Are the Trends in Eco-Design Research When We Talk abou...

引用

2023 International Symposium on World Ecological Design, ISWED 2023

作者： Zhuang, Nan Ma, Yanni Zhai, Shuo Zhao, Xin Weng, Shitong Ma, Zhenyuan Shi, Shang Ying, Fangtian School of Software Technology Zhejiang University China College of Computer Science and Technology Zhejiang University China Polytechnic Institute Zhejiang University China

ISBN: (纸本)9781643685069

The convergence of digital technology with eco-design offers an integrative approach, merging environmental sustainability with technological innovation in design. In the realm of eco-design, there is a growing emphasis on the application of digital technology. However, the focal areas and trends of eco-design studies utilizing digital technology remain underexplored. This leads to a deficiency in our deep understanding and prediction of the evolution and transformation of this domain. To comprehend the progression in this domain, we curated and scrutinized a dataset of 1,359 papers related to digital technology and eco-design presented at the CHI conference over the past five years. Through keywords analysis from the past half-decade, we pinpointed prevailing research areas in eco-design utilizing digital technology, such as virtual reality, sustainability, health, and human-computer interaction. We also gathered essential information about the papers for descriptive statistical analysis, including the count, authors' nationalities and gender distribution, and the scale of the authorship teams. Coupled by the visual insights from keyword clouds, we discerned trends in eco-design research in the backdrop of digital technology. Our findings underscore that the eco-design domain, when integrated with digital technology, persistently captivates academic interest, with comparatively smaller teams often embarking on projects in this research sphere. Predominantly, researchers from the United States and male participants lead these endeavors. Moreover, there's an escalating emphasis on people-centered design, striving to engineer solutions that harmonize environmental interactions with health promotions. This study's outcomes furnish insights for a more profound exploration in the realm of digital technology and eco-design, offering recommendations to further propel sustainable progress and innovative design. © 2024 The Authors.

关键词： Ecodesign

来源：评论

学校读者我要写书评

暂无评论

Autonomous Aspect-Image Instruction A2II: Q-Former Guided Multimodal Sentiment Classification 30

Autonomous Aspect-Image Instruction A2II: Q-Former Guided Mu...

引用

Joint 30th International Conference on Computational Linguistics and 14th International Conference on Language Resources and Evaluation, LREC-COLING 2024

作者： Feng, Junjia Lin, Mingqian Shang, Lin Gao, Xiaoying State Key Laboratory for Novel Software Technology Nanjing University China Department of Computer Science and Technology Nanjing University China School of Engineering and Computer Science Victoria University of Wellington New Zealand

ISBN: (纸本)9782493814104

Multimodal aspect-oriented sentiment classification (MABSC) task has garnered significant attention, which aims to identify the sentiment polarities of aspects by combining both language and vision information. However, the limited multimodal data in this task has become a big gap for the vision-language multimodal fusion. While large-scale vision-language pretrained models have been adapted to multiple tasks, their use for MABSC task is still in a nascent stage. In this work, we present an attempt to use the instruction tuning paradigm to MABSC task and leverage the ability of large vision-language models to alleviate the limitation in the fusion of textual and image modalities. To tackle the problem of potential irrelevance between aspects and images, we propose a plug-and-play selector to autonomously choose the most appropriate instruction from the instruction pool, thereby reducing the impact of irrelevant image noise on the final sentiment classification results. We conduct extensive experiments in various scenarios and our model achieves state-of-the-art performance on benchmark datasets, as well as in few-shot settings. © 2024 ELRA Language Resource Association: CC BY-NC 4.0.

关键词： Sentiment analysis

来源：评论

学校读者我要写书评

暂无评论

IEARACDA: Predicting circRNA-disease associations based on information enhancement and arctangent rank approximation

IEARACDA: Predicting circRNA-disease associations based on i...

引用

2024 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2024

作者： Pang, Shanchen Song, Zheqi Liu, Tiyao Wu, Wenhao Zhang, Yuanyuan Wang, Shudong College of Computer Science and Technology Qingdao Institute of Software Qingdao China Qingdao University of Technology School of Information and Control Engineering Qingdao China

ISBN: (纸本)9798350386226

Circular RNAs (circRNAs) are non-coding RNA molecules that play a significant role in cell regulation and disease occurrence. In recent years, the use of computational methods to predict circRNAs associated with diseases has become a research focus. However, these methods are often constrained by the noise interference and an insufficient exploration of the underlying information in known associations. Therefore, this paper proposes an information enhancement and arctangent rank approximation based method to predict potential circRNA-disease associations (IEARACDA). Firstly, information enhancement methods are used to make circRNA and disease similarity information more complete and to reduce the sparsity of known association. Subsequently, the arctangent rank approximation method is employed to mitigate the potential bias issues that may arise from the nuclear norm, and optimization is carried out using the inexact augmented Lagrange multiplier (IALM) method. Finally, potential associations are predicted through heterogeneous graph inference method. The experimental results demonstrate that IEARACDA exhibits superior performance compared to existing methods. Furthermore, case studies for hepatocellular carcinoma and lung cancer provide additional confirmation of the accuracy and practical significance of the model predictions. © 2024 IEEE.

关键词： Lung cancer

来源：评论

学校读者我要写书评

暂无评论

SparseCoder: Identifier-Aware Sparse Transformer for File-Level Code Summarization 31

SparseCoder: Identifier-Aware Sparse Transformer for File-Le...

引用

31st IEEE International Conference on software Analysis, Evolution and Reengineering, SANER 2024

作者： Wang, Yanlin Huang, Yanxian Guo, Daya Zhang, Hongyu Zheng, Zibin School of Software Engineering Sun Yat-sen University China School of Computer Science and Technology Sun Yat-sen University China School of Big Data and Software Engineering Chongqing University China

ISBN: (纸本)9798350330663

Code summarization aims to generate natural language descriptions of source code, facilitating programmers to understand and maintain it rapidly. While previous code summarization efforts have predominantly focused on method-level, this paper studies file-level code summarization, which can assist programmers in understanding and maintaining large source code projects. Unlike method-level code summarization, file-level code summarization typically involves long source code within a single file, which makes it challenging for Transformer-based models to understand the code semantics for the maximum input length of these models is difficult to set to a large number that can handle long code input well, due to the quadratic scaling of computational complexity with the input sequence length. To address this challenge, we propose SparseCoder, an identifier-aware sparse transformer for effectively handling long code sequences. Specifically, the SparseCoder employs a sliding window mechanism for self-attention to model short-term dependencies and leverages the structure message of code to capture long-term dependencies among source code identifiers by introducing two types of sparse attention patterns named global and identifier attention. To evaluate the performance of SparseCoder, we construct a new dataset FILE-CS for file-level code summarization in Python. Experimental results show that our SparseCoder model achieves state-of-the-art performance compared with other pre-trained models, including full self-attention and sparse models. Additionally, our model has low memory overhead and achieves comparable performance with models using full self-attention mechanism. Furthermore, we verify the generality of SparseCoder on other code understanding tasks, i.e., code clone detection and code search, and results show that our model outperforms baseline models in both tasks, demonstrating that our model can generate better code representations for various downstream tasks. Our

关键词： Semantics

来源：评论

学校读者我要写书评

暂无评论

Chinese Speech Emotion Recognition Based on Pre-Trained Model 5

Chinese Speech Emotion Recognition Based on Pre-Trained Mode...

引用

5th International Conference on Big Data and Artificial Intelligence and software Engineering, ICBASE 2024

作者： Xu, Sukui Jiang, Nan Lian, Shun Pan, Jingmin Anhui Institute of Information Technology College of Computer and Software Engineering Wuhu China Fujian Polytechnic of Information Technology School of General Education Fuzhou China Anhui University School of Computer Science and Technology Hefei China

ISBN: (纸本)9798331506612

This paper proposes a method based on large-scale speech pre-trained models for the task of Chinese speech emotion recognition. Similar to the transfer learning approach in image classification task, speech pre-trained model is used as a fixed feature extractor to extract features from speech data, followed by a fully connected network for classification. Experimental results show that, on the seven-class speech emotion recognition task of the Chinese M3ED dataset, the proposed method achieves classification accuracies of 0.506 and 0.560 using base and large sized pre-trained models respectively, surpassing the baseline accuracy of 0.454 for the ECAPA-TDNN model. © 2024 IEEE.

关键词： Transfer learning

来源：评论

学校读者我要写书评

暂无评论

Time Series Data Cleaning under Expressive Constraints on Both Rows and Columns 40

Time Series Data Cleaning under Expressive Constraints on Bo...

引用

40th IEEE International Conference on Data Engineering, ICDE 2024

作者： Ding, Xiaoou Li, Genglong Wang, Hongzhi Wang, Chen Song, Yichen School of Computer Science and Technology Harbin Institute of Technology China Tsinghua University National Engineering Laboratory for Big Data Software EIRI China

ISBN: (纸本)9798350317152

Time series data generated by thousands of sensors are suffering data quality problems. Traditional constraint-based techniques have greatly contributed to data cleaning applications. However, cleaning methods that support expressive constraints on time series data remain insufficient. Given the notable characteristics of time series data, existing cleaning approaches are challenged to provide good repair solutions. To address the challenges, we propose a novel data cleaning method for time series which incorporates expressive constraints that support arithmetic operations between attributes and time context. In the violation detection phase, we introduce specialized violation degree quantification functions and design a violation cell discovery algorithm to identify errors hidden in time series data. In the data repairing phase, we formalize the cleaning task as a constrained optimization problem and develop a novel repair objective function that considers both modification costs and conformance degrees of constraints. We effectively reduce the repair search space through the evaluation of time-context constraints and propose a bidirectional repairing algorithm. We also provide theoretical analysis of the proposed repairing method. Experimental results on three real-world IoT datasets across five metrics demonstrate that our proposed method outperforms seven state-of-the-art cleaning techniques specialized for time series data. Specifically, we achieve a 60% improvement in repairing effectiveness and a 70% reduction in time costs with our designed cleaning strategy. © 2024 IEEE.

关键词： Time series

来源：评论

学校读者我要写书评

暂无评论

Empowering Cross-Device Data Security Verification for IoT Sensor Nodes 7

Empowering Cross-Device Data Security Verification for IoT S...

引用

7th International Conference on Machine Learning and Natural Language Processing, MLNLP 2024

作者： Shi, Xin He, Sheng Wang, Ting Zhang, Chong Wang, Yang Zhang, Xiao School of Computer Science and Software Engineering Southwest Petroleum University Chengdu China School of Computer Science Chengdu University of Information Technology Chengdu China School of Information Engineering Mianyang Teachers College Mianyang China

ISBN: (纸本)9798350354973

In the process of realizing the Internet of Everything through the Internet of Things (IoT), the massive deployment of sensor nodes poses significant security challenges. This paper introduces a novel approach to anomaly detection. The proposed method focuses on generating secure replicas of sensor data, which are compared with real-time data to identify anomalies. This process ensures robust detection across multiple devices and terminals, a key challenge in the realization of the Internet of Everything. The model combines Long Short-Term Memory (LSTM) networks and Variational Autoencoders (VAE), leveraging their strengths in capturing temporal dependencies and learning latent feature representations from sensor data. To enhance detection accuracy in complex environments, an adaptive threshold algorithm is employed, dynamically adjusting thresholds based on real-time data's statistical properties. A crossattention mechanism is also integrated, allowing the model to effectively capture spatio-temporal relationships between sensors. Additionally, we employed a weighted smoothing algorithm to reduce noise while preserving data integrity, ensuring accurate anomaly detection even in noisy environments. Finally, we evaluated our method using the real-world dataset of the Belgian railway bridge KW51. The results indicate that our system can generate sensor data replicas with 99.02% accuracy and detect abnormal data with 99.8% precision. Based on these findings, we believe that this novel approach can effectively perform anomaly detection and provide robust support for IoT security across multiple terminals and devices. © 2024 IEEE.

关键词： Sensor nodes

来源：评论

学校读者我要写书评

暂无评论

引用

25th International Conference on Web Information Systems Engineering, WISE 2024

作者： Tu, Longchuan Meng, Shunmei Liu, Xiao Liu, Guanfeng Beheshti, Amin Zhang, Xuyun School of Computer Science and Engineering Nanjing University of Science and Technology Nanjin China State Key Laboratory for Novel Software Technology Nanjing University Nanjin China School of Computing Macquarie University Sydney Australia

ISBN: (纸本)9789819605699

Recently, graph neural networks(GNNs) have played a key crucial in many recommendation situations. In particular, contrastive learning-based hypergraph neural networks (HGNNs) are gradually becoming a research focus for addressing issues of data sparsity and noise. Despite many studies proving their outstanding performance, there are still some shortcomings: i) Most contrastive learning-based HGNNs primarily rely on cross-view contrastive learning, while neglecting contrastive learning on the interaction graph. ii) Utilizing node embedding for hypergraph structure learning is susceptible to the influence of low-quality representations, thereby constraining the learning capability of HGNNs. To address these issues, we offer a Semantic Similarity-based Graph Contrastive Learning framework (SSGCL), which aims to jointly learn representations with rich semantic information through within-view and cross-view contrastive learning. Specifically, we first introduce consistency contrastive learning, which captures self-supervised signals through semantic similarity between nodes and their neighborhoods. It better captures the unique features of nodes through the connections between nodes and their neighborhoods. Then, we utilize interaction graph learning hypergraph structure, promoting it to extract potential node connections and thus improving its ability to describe homogeneous node relationships. Experimental evaluations on three actual datasets show that SSGCL performs much better than the current baseline models. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Contrastive Learning

来源：评论

学校读者我要写书评

暂无评论

SAT-GAV: A Electricity-Costs Aware Resources Placement Strategy for Data Centers 22

SAT-GAV: A Electricity-Costs Aware Resources Placement Strat...

引用

22nd IEEE International Symposium on Parallel and Distributed Processing with Applications, ISPA 2024

作者： Feng, Hao Xu, Xinren Chen, Lin Li, Jie Hainan University School of Computer Science and Technology Haikou570100 China South China Normal University School of Software Foshan528225 China

ISBN: (纸本)9798331509712

With the rise of cloud computing and artificial intelligence, the resource utilization rate of data centers is soaring, resulting in significant power consumption and electricity costs. Traditional inappropriate resource placement methods cannot match the local electricity pricing form well, leading to data centers consuming a large amount of energy and requiring large electricity bills. In this paper, firstly, this paper study a global electricity-cost-minimization model, which takes into account both IT and non-IT resource usage. Secondly, We introduce a two-step algorithm (SAT-GAV) to solve the NP-hard TVMP problem. The first step of SAT-GAV uses the simulated annealing algorithm to arrange task placements to reduce electricity costs. In the second step, we uses the greedy algorithm to place virtual machines by leveraging of minimizing data center electricity costs. We conduct extensive experiments to evaluate the effectiveness of SAT-GAV. And compare the performance of our SAT-GAV with other state-of-art algorithms. Experimental results indicate that, compared to other algorithms, our VMP strategy can reduce the electricity costs by 8.9% compared to the best-performing PDGA algorithm and by 33.34% compared to the earlier XINT-GA algorithm. © 2024 IEEE.

关键词： Simulated annealing

来源：评论

学校读者我要写书评

暂无评论

Research on operation optimization problem of energy storage station in microgrid based on improved particle swarm optimization 3

Research on operation optimization problem of energy storage...

引用

3rd International Conference on Signal Processing and Machine Learning, CONF-SPML 2023

作者： Fan, Yikun School of Computer and Software Nanjing University of Information Science and Technology Jiangsu Nanjing210032 China

In many microgrids with a lot of uncontrollable DGs, a well-planned operation of the energy storage station is an important guarantee for the stability and economy of the microgrid. To solve the operation optimization problem, the Chaos mechanism, differential evolution, and random inertia weight were introduced to propose the traditional PSO algorithm. A mathematical model for minimizing the running cost of Microgrid is established, and through MATLAB simulation, both algorithms are used to solve the same problem to observe the improvement of the algorithm. The experimental results show that the IPSO algorithm achieves performance improvement. © Published under licence by IOP Publishing Ltd.

关键词： Particle swarm optimization (PSO)

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 << < 30 31 32 33 34 35 36 37 38 39 > >>

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：