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

16,204 篇 会议
2,513 篇 期刊文献
147 册 图书

馆藏范围

18,864 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

11,292 篇 工学
- 7,620 篇 计算机科学与技术...
- 6,363 篇 软件工程
- 3,231 篇 信息与通信工程
- 1,888 篇 控制科学与工程
- 1,718 篇 电子科学与技术（可...
- 1,705 篇 电气工程
- 1,167 篇 生物工程
- 1,033 篇 生物医学工程（可授...
- 885 篇 光学工程
- 757 篇 机械工程
- 701 篇 动力工程及工程热...
- 691 篇 仪器科学与技术
- 575 篇 化学工程与技术
- 477 篇 安全科学与工程
- 421 篇 交通运输工程
- 377 篇 材料科学与工程（可...
5,819 篇 理学
- 3,033 篇 数学
- 1,787 篇 物理学
- 1,280 篇 生物学
- 995 篇 统计学（可授理学、...
- 669 篇 系统科学
- 579 篇 化学
2,756 篇 管理学
- 1,699 篇 管理科学与工程(可...
- 1,212 篇 图书情报与档案管...
- 891 篇 工商管理
870 篇 医学
- 764 篇 临床医学
- 712 篇 基础医学(可授医学...
- 451 篇 药学(可授医学、理...
- 367 篇 公共卫生与预防医...
501 篇 法学
- 399 篇 社会学
328 篇 经济学
239 篇 农学
208 篇 教育学
78 篇 文学
44 篇 军事学
15 篇 艺术学
1 篇 历史学

主题

558 篇 accuracy
410 篇 deep learning
401 篇 feature extracti...
393 篇 computational mo...
292 篇 support vector m...
285 篇 training
279 篇 real-time system...
262 篇 internet of thin...
227 篇 machine learning
220 篇 optimization
219 篇 predictive model...
197 篇 computer science
196 篇 computer archite...
181 篇 reliability
179 篇 convolutional ne...
177 篇 neural networks
176 篇 wireless communi...
170 篇 data mining
162 篇 routing
158 篇 throughput

机构

84 篇 institut univers...
82 篇 north-west unive...
82 篇 national centre ...
82 篇 tno technical sc...
79 篇 infn sezione di ...
79 篇 nikhef national ...
78 篇 university würzb...
78 篇 university of jo...
76 篇 infn sezione di ...
76 篇 université de st...
66 篇 università di ca...
65 篇 ncsr demokritos ...
64 篇 university moham...
54 篇 university moham...
53 篇 leiden universit...
51 篇 dept. of compute...
50 篇 school of automa...
43 篇 in2p3 lpc campus...
42 篇 infn lnf via enr...
41 篇 university of gr...

作者

85 篇 ferrara g.
85 篇 ardid m.
84 篇 calvo d.
84 篇 gal t.
84 篇 bozza c.
82 篇 kalekin o.
82 篇 díaz a.f.
82 篇 boumaaza j.
82 篇 coleiro a.
81 篇 chen a.
81 篇 gozzini s.r.
81 篇 dallier r.
78 篇 anguita m.
78 篇 enzenhöfer a.
76 篇 boettcher m.
75 篇 celli s.
73 篇 aly z.
72 篇 dornic d.
70 篇 huang f.
69 篇 carretero v.

语言

17,740 篇 英文
861 篇 其他
190 篇 中文
51 篇 日文
21 篇 朝鲜文
2 篇 斯洛文尼亚文
1 篇 阿拉伯文
1 篇 德文
1 篇 法文
1 篇 土耳其文

检索条件"机构=Dept. of Computer Engineering and Informatics and Computer Technology"

共 18864 条记录，以下是801-810 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：

Enhancing Hospital Mortality Prediction for Heart Failure Patients through Hyperparameter Optimization and Interpretability Analysis with LIME and SHAP 1

Enhancing Hospital Mortality Prediction for Heart Failure Pa...

引用

1st International Conference for Women in Computing, InCoWoCo 2024

作者： Meena, S. Murthy, Monisha Kodipalli, Ashwini Global Academy of Technology Dept. of Computer Science and Engineering Karnataka Bengaluru India Global Academy of Technology Dept. of Artificial Intelligence & Data Science Karnataka Bengaluru India

ISBN: (纸本)9798331518943

Heart failure is one of the primary causes for deaths caused in the hospital. Predicting mortality rate of such patients is extremely important for the efficient use of health care resources. This research aims to estimate the hospital mortality rate of Heart Failure(HF) patients using machine learning(ML). Using computational technique, the obtained model has given the most efficient accuracy. This paper uses the classification model to detect two outcomes (0 and 1, i.e., if the patient will survive or not). The classification models used for the hospital mortality prediction are, single classifiers such as Logistic regression, SVM, KNN, Decision tree (Ginni and Entropy);with Logistic regression obtaining highest accuracy of 88.9%, Bagging and boosting models such as Randomforest, Adaptive boosting, Gradient boosting, XG boosting, Categorical boosting;with CatBoost obtaining highest accuracy of 90.2%. To achieve the best accuracy, ensemble models were used out of which ensemble classifier ensemble gave 91.1% accuracy. To understand the features playing important role in decision making, explainable AI(XAI) is used. LIME and SHAP are considered. LIME generated local explanations, it explained the decision of a complex model for a specific instance or observation. In contrast, SHAP provided global explanations, it explained the overall behavior of the model across all instances. © 2024 IEEE.

关键词： Adaptive boosting

来源：评论

学校读者我要写书评

暂无评论

Timing Mechanism for a Low-Cost, Single Use, Nucleic Acid Amplification Diagnostic Test

Timing Mechanism for a Low-Cost, Single Use, Nucleic Acid Am...

引用

2024 IEEE MIT Undergraduate Research technology Conference, URTC 2024

作者： Gordon, Savannah Jaffe, Ellie Garcia, Sebastian Kim, Suhan Kang, Ziliang Hanumara, Nevan C. Traverso, Giovanni Massachusetts Institute of Technology Dept. of Mechanical Engineering CambridgeMA02139 United States Massachusetts Institute of Technology Dept. of Electrical Engineering & Computer Science CambridgeMA02139 United States

ISBN: (纸本)9798331531003

Nucleic Acid Amplification Tests (NAATs) are used to diagnose infectious diseases such as tuberculosis (TB), SARS-CoV-2, and Human Papillomavirus (HPV). Conventional testing requires a bench-top system that limits its accessibility to potential patients. A self-contained, low-cost, single use NAAT would increase worldwide access to critical diagnostics. In support of an ongoing NAAT diagnostic project, we prototyped a timing mechanism to control the critical heating step that effects amplification. Herein we present a design consisting of a micro controller, a dual-channel Mosfet, and LEDs to visualize the operation. We selected electrical components that were low cost and tested the design for accuracy under two conditions: 1) the elevated temperatures required for the NAAT process and 2) a fluctuating power source, as would result from batteries suitable for a disposable device. We prototyped iteratively, ultimately demonstrating a design by creating a flex PCB approximately 3 cm by 2 cm with a cost less than 1 USD at scale. With this work, we aim to help further the development of more distributed and accessible diagnostic tests. © 2024 IEEE.

关键词： Microfluidics

来源：评论

学校读者我要写书评

暂无评论

Evaluation of Multiple Apache Spark Applications using Kubernetes as a Cluster manager on Google Cloud 4

Evaluation of Multiple Apache Spark Applications using Kuber...

引用

4th International Conference on Evolutionary Computing and Mobile Sustainable Networks, ICECMSN 2024

作者： Jayanthi, M. Rao, K. Ram Mohan Sukanya, Vuppala Dept of Computer Science and Informatics Mahatma Gandhi University Nalgonda India Dept of Information Technology Vasavi College of Engineering Hyderabad India Dept of CSE Hyderabad India

Big data processing frameworks demands for scalable and efficient cluster management. Apache Spark has emerged as prominent big data processing framework providing high-speed data processing and analytics capabilities for multiple applications. This paper explores the integration of Kubernetes as a cluster manager for Apache Spark applications leveraging its containerization capabilities to improve resource utilization and simplify deployment. In this paper the challenges of deploying spark applications on traditional cluster managers and showcase the advantages of adopting Kubernetes are analysed. The experimental evaluation demonstrates the benefits of Kubernetes as a cluster manager for Apache Spark framework. To execute the multiple Apache Spark applications on Kubernetes a homogenous cluster on Google Cloud is created by History bucket and service account. Finally multiple applications are executed on Google Kubernetes Engine. Output can be shown as the number of executor pods created with the performance metrics can be viewed. In conclusion, this paper compares the performance metrics such as job execution time and resource utilization with the different cluster. © 2025 The Authors. Published by Elsevier B.V.

关键词： Information management

来源：评论

学校读者我要写书评

暂无评论

Detection of PCOS Leveraging Machine Learning and Interpretation Using Explainable AI 1

Detection of PCOS Leveraging Machine Learning and Interpreta...

引用

1st International Conference for Women in Computing, InCoWoCo 2024

作者： Madhavi, Bindu V. Firdouse, Asfiya Kodipalli, Ashwini Global Academy of Technology Dept. of Computer Science and Engineering Karnataka Bengaluru India Global Academy of Technology Dept. of Artificial Intelligence & Data Science Karnataka Bengaluru India

ISBN: (纸本)9798331518943

Polycystic Ovary Syndrome (PCOS) is a widespread endocrine disorder impacting women globally. This research aims to early predict and detect PCOS which is needed to reduce long-term complications. Since it is considered to be a hard-to-diagnose disorder, machine learning is utilized for this purpose. This study leveraged the power of computational algorithms trained on patient data for model prediction where Decision tree with criterion Gini index outperformed with 88.07% accuracy, 85.29% precision, 78.37% recall and 81.69% F1 Score. In addition to this, Bagging and boosting algorithms were used to monitor their performance metrics where Gradient Boost stood out with a remarkable accuracy of 91.74%, 91.00% precision, 97.00% recall and 94.00% F1 Score. By optimizing the chosen parameters through Hyperparameter tuning, a notable increase in the model's accuracy was observed. Besides, three ensemble models were proposed out of which the ensemble classifier ensemble model involving bagging, boosting and single classifiers brought a significant difference of 95.41% accuracy. Additionally, Explainable (XAI) methodologies like LIME (Local Interpretable Model-Agnostic Explanations) and SHAP (SHapley Additive exPlanations) were used for model interpretability. © 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

Empirical Evaluation of Machine Learning Techniques for Autism Spectrum Disorder 12

Empirical Evaluation of Machine Learning Techniques for Auti...

引用

12th International Electrical engineering Congress, iEECON 2024

作者： Sethi, Akshit Khan, Kainat Katarya, Rahul Yingthawornsuk, Thaweesak Delhi Technological University Dept. Of Computer Science & Engineering New Delhi India King Mongkut's University Of Technology Thonburi Dept. Of Media Technology Bangkok Thailand

ISBN: (纸本)9798350383591

Autism spectrum disorder (ASD) is a complicated neurological system disorder that has severe effects on a person's spoken communication, logical thinking, and person-to-person interaction. The early symptoms start looking visible at the age of two to four years and the main ground of these symptoms could be hereditary or ecological. Presently, the standardized approach for detecting ASDs is usually very time-consuming and the cost of medical care is extravagant. Therefore, early detection of ASD would be helpful. Machine Learning (ML) algorithms have the required potential to predict the chances of having autism or not, based on the type of dataset provided to it and the kind of algorithms that are effectively applied to it. The focus of this study is on screening data sets and the use of machine learning algorithms, including XGBoost (XGB) (Ensemble Technique), Random Forest Classifier (RFC), Support Vector Classifier (SVC), Logistic Regression (LR), and Artificial Neural Network (ANN). Our aim for this research was to develop a model that shortens the process of identification of ASDs at an early stage. The accuracy and precision scores of 92.2% and 0.88, respectively, indicate that our model has done well. Our research could be extended in developing a large-scale model that contains a large dataset having a variety of attributes and the integration of brain and facial MRI scans could be helpful in identifying ASD. © 2024 IEEE.

关键词： Diagnosis

来源：评论

学校读者我要写书评

暂无评论

Combining image and point cloud segmentation to improve heritage understanding 10

Combining image and point cloud segmentation to improve heri...

引用

10th International Workshop 3D-ARCH "3D Virtual Reconstruction and Visualization of Complex Architectures"

作者： Bassier, Maarten Mazzacca, Gabriele Battisti, Roberto Malek, Salim Remondino, Fabio Dept. of Civil Engineering Geomatics KU Leuven Faculty of Engineering Technology Ghent Belgium Trento Italy Dept. Mathematics Computer Science and Physics University of Udine Italy

Current 2D and 3D semantic segmentation frameworks are developed and trained on specific benchmark datasets, often rich of synthetic data, and when they are applied to complex and real-world heritage scenarios they offer much lower accuracy than expected. In this work, we present and demonstrate an early and late fusion of methods for semantic segmentation in cultural heritage applications. We rely on image datasets, point clouds and BIM models. The early fusion utilizes multi-view rendering to generate RGBD imagery of the scene. In contrast, the late fusion approach merges image-based segmentation with a Point Transformer applied to point clouds. Two scenarios are considered and inference results show that predictions are primarily influenced by whether the scene has a predominantly geometric or texture-based signature, underscoring the necessity of fusion methods. © 2024 International Society for Photogrammetry and Remote Sensing. All rights reserved.

关键词： Semantic Segmentation

来源：评论

学校读者我要写书评

暂无评论

Parallel Neural Computing for Scene Understanding from LiDAR Perception in Autonomous Racing 12

Parallel Neural Computing for Scene Understanding from LiDAR...

引用

12th International Conference on Intelligent Systems and Embedded Design, ISED 2024

作者： Sah, Suwesh Prasad Chinara, Suchismita National Institute of Technology Dept. Computer Science and Engineering Rourkela India

ISBN: (纸本)9798331522612

Autonomous driving in high-speed racing, as opposed to urban environments, presents significant challenges in scene understanding due to rapid changes in the track environment. Traditional sequential network approaches may struggle to meet the real-time knowledge and decision-making demands of an autonomous agent covering large displacements in a short time. This paper proposes a novel baseline architecture for developing sophisticated models capable of true hardware-enabled parallelism, achieving neural processing speeds that mirror the agent's high velocity. The proposed model (Parallel Perception Network (PPN)) consists of two independent neural networks, segmentation and reconstruction networks, running parallelly on separate accelerated hardware. The model takes raw 3D point cloud data from the LiDAR sensor as input and converts it into a 2D Bird's Eye View Map on both devices. Each network independently extracts its input features along space and time dimensions and produces outputs parallelly. The proposed method's model is trained on a system with two NVIDIA T4 GPUs, using a combination of loss functions, including edge preservation, and demonstrates a 2x speedup in model inference time compared to a sequential configuration. Implementation is available at: github/ParallelPerceptionNetwork. Learned parameters of the trained networks are provided at: huggingface/ParallelPercentionNetwork. © 2024 IEEE.

关键词： Accelerated Computing Autonomous Racing CNN computer Vision Deep Learning LiDAR Perception

来源：评论

学校读者我要写书评

暂无评论

Mathematical Morphology Adopted Automatic Detection of Ground Glass Opacities in Lung CT Images of COVID-19 Patients

Mathematical Morphology Adopted Automatic Detection of Groun...

引用

2023 International Conference on Intelligent Systems, Advanced Computing and Communication, ISACC 2023

作者： Chatterjee, Soma Chatterjee, Rohit Kamal Goswami, R.T. Techno International New Town Dept. of Computer Applications Kolkata India Birla Institute of Technology Dept. of Computer Science & Engineering Mesra Ranchi India Techno International New Town Dept. of Computer Science Kolkata India

ISBN: (纸本)9798350399387

The severity of the nCOVID infection relies on the presence of Ground Glass Opacities (GGO) present in the patient's chest CT scan images. Although, detecting and delineating the precise boundaries of GGO in the chest CT images is challenging. Here, we proposed a fast and novel technique to automatically segment the regions containing GGO in lung CT images using mathematical morphology. We have tested our algorithm on the chest CT images of 145 Covid-positive cases. This unique segmentation approach correctly segments the lung field from chest CT images and identifies GGO with average sensitivity, specificity, and accuracy of 96.89%, 95.23%, and 97.22%, respectively. We used expert radiologists' hand-curated segmentation of GGO as ground truth for quantificational performance analysis. Our research results indicate that this algorithm performs well found in the literature. © 2023 IEEE.

关键词： COVID-19

来源：评论

学校读者我要写书评

暂无评论

Enhancing Detection of Breast Cancer Through a Novel Framework: A Machine Learning Approach with Explainable AI Interpretation 1

Enhancing Detection of Breast Cancer Through a Novel Framewo...

引用

1st International Conference for Women in Computing, InCoWoCo 2024

作者： Vidyashree, R. Kodipalli, Ashwini Rao, Trupthi Global Academy of Technology Dept. of Computer Science & Engineering Karnataka Bengaluru India Global Academy of Technology Dept. of Artificial Intelligence & Data Science Karnataka Bangalore India

ISBN: (纸本)9798331518943

Breast cancer, the most prevalent cancer among women, significantly contributes to increased mortality rates and ranks as the second leading cause of cancer-related deaths in women. Early detection is crucial for effective treatment, yet traditional diagnostic approaches often involve multiple laboratory tests supervised by medical experts. To mitigate human error and expedite breast cancer detection, there is a pressing need for automated systems capable of accurate and timely diagnosis. This study aims to investigate the application of machine learning (ML) techniques in classifying breast cancer using features from digitized images of fine-needle aspiration (FNA) breast mass samples. Machine learning methods are instrumental in addressing this imperative. The study conducts a comparative analysis of various ML classification methods, including Logistic Regression, Support Vector Machine (SVM), K Nearest Neighbor (KNN), Decision Trees, Bagging-Boosting, and ensemble models, using a breast cancer dataset to establish a novel framework. The performance of each algorithm is assessed based on metrics such as accuracy, precision, recall, and F1 score. The findings underscore the effectiveness of ensemble classifier models, achieving a notable accuracy rate of 98.87%. Additionally, the integration of explainable Artificial Intelligence enhances the interpretability of the models by providing valuable insights into their decision-making processes. © 2024 IEEE.

关键词： Contrastive Learning

来源：评论

学校读者我要写书评

暂无评论

Symptoms-based Classification of Disease Using Various ML Algorithms and Interpretation using LIME and SHAP KERNELS 4

Symptoms-based Classification of Disease Using Various ML Al...

引用

4th IEEE Asian Conference on Innovation in technology, ASIANCON 2024

作者： Soujanya, K.J. Kodipalli, Ashwini Gosai, Sanjeev Sneha, B.J. Rao, Trupthi Global Academy of Technology Dept. of Artificial Intelligence & Data Science Karnataka Bangalore India Global Academy of Technology Dept. of Computer Science & Engineering Karnataka Bangalore India

ISBN: (纸本)9798350354218

Using a variety of machine learning techniques, this research study suggests a unique method for classifying diseases using symptom-based analysis. To improve model transparency and comprehension, the study makes use of the interpretability tools, SHAP kernels and LIME. The research attempts to close the gap between interpretability and prediction accuracy in medical diagnosis by combining two approaches. A thorough assessment of symptom-based categorization is ensured by the use of many machine learning methods. The application of LIME and SHAP kernels aids in the clarification of model predictions and provides information on the primary symptoms that impact illness categorization. This study advances the creation of accurate and comprehensible illness categorization models, promoting confidence in the use of machine learning methods in healthcare. © 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

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 << < 77 78 79 80 81 82 83 84 85 86 > >>

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：