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

95 篇 会议
56 篇 期刊文献

馆藏范围

151 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

95 篇 工学
- 66 篇 计算机科学与技术...
- 59 篇 软件工程
- 23 篇 生物医学工程（可授...
- 21 篇 控制科学与工程
- 20 篇 光学工程
- 19 篇 信息与通信工程
- 18 篇 生物工程
- 10 篇 电气工程
- 8 篇 电子科学与技术（可...
- 7 篇 化学工程与技术
- 6 篇 仪器科学与技术
- 5 篇 动力工程及工程热...
- 5 篇 建筑学
- 4 篇 机械工程
- 4 篇 土木工程
48 篇 理学
- 20 篇 生物学
- 19 篇 物理学
- 14 篇 数学
- 9 篇 化学
- 6 篇 统计学（可授理学、...
- 5 篇 地球物理学
- 4 篇 系统科学
17 篇 管理学
- 10 篇 管理科学与工程(可...
- 7 篇 工商管理
- 7 篇 图书情报与档案管...
15 篇 医学
- 14 篇 基础医学(可授医学...
- 14 篇 临床医学
- 10 篇 公共卫生与预防医...
- 7 篇 药学(可授医学、理...
7 篇 法学
- 5 篇 社会学
2 篇 经济学
2 篇 教育学

主题

9 篇 internet of thin...
6 篇 machine learning
6 篇 artificial intel...
5 篇 covid-19
5 篇 accuracy
4 篇 blockchain
3 篇 neural networks
3 篇 kalman filters
3 篇 predictive model...
3 篇 image reconstruc...
2 篇 neurons
2 篇 reinforcement le...
2 篇 dynamical system...
2 篇 deep learning
2 篇 smart city
2 篇 transformers
2 篇 planning
2 篇 education
2 篇 natural language...
2 篇 intelligent robo...

机构

12 篇 department of co...
11 篇 department of co...
11 篇 department of co...
10 篇 graphic era hill...
9 篇 waterloo univers...
8 篇 artificial intel...
8 篇 department of co...
8 篇 department of ch...
7 篇 ai and robotics ...
7 篇 waterloo univers...
7 篇 ai and robotics ...
7 篇 research center ...
6 篇 university of sc...
6 篇 ai and robotics ...
6 篇 artificial intel...
6 篇 ai and robotics ...
6 篇 university of ky...
6 篇 abes engineering...
5 篇 artificial intel...
5 篇 graphic era hill...

作者

41 篇 al-turjman fadi
29 篇 fadi al-turjman
26 篇 salama ramiz
22 篇 ramiz salama
17 篇 altrjman chadi
13 篇 satya prakash ya...
12 篇 yadav satya prak...
12 篇 chadi altrjman
8 篇 satvik vats
7 篇 vats satvik
6 篇 bakas spyridon
5 篇 kofler florian
5 篇 sinem al-turjman
5 篇 mubarak auwalu s...
4 篇 reinke annika
4 篇 glocker ben
4 篇 summers ronald m...
4 篇 reyes mauricio
4 篇 al-turjman sinem
4 篇 alturjman sinem

语言

141 篇 英文
10 篇 其他
1 篇 朝鲜文

检索条件"机构=Artificial Intelligence Engineering Department and AI and Robotics Institutes"

共 151 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：

PhysORD: A Neuro-Symbolic Approach for Physics-infused Motion Prediction in Off-road Driving

PhysORD: A Neuro-Symbolic Approach for Physics-infused Motio...

引用

IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)

作者： Zhipeng Zhao Bowen Li Yi Du Taimeng Fu Chen Wang Department of Computer Science and Engineering Spatial AI & Robotics (SAIR) Lab Institute for Artificial Intelligence and Data Science University at Buffalo Buffalo NY USA Robotics Institute Carnegie Mellon University Pittsburgh PA USA

ISBN: (数字)9798350377705

ISBN: (纸本)9798350377712

Motion prediction is critical for autonomous off-road driving, however, it presents significantly more challenges than on-road driving because of the complex interaction between the vehicle and the terrain. Traditional physics-based approaches encounter difficulties in accurately modeling dynamic systems and external disturbance. In contrast, data-driven neural networks require extensive datasets and struggle with explicitly capturing the fundamental physical laws, which can easily lead to poor generalization. By merging the advantages of both methods, neuro-symbolic approaches present a promising direction. These methods embed physical laws into neural models, potentially significantly improving generalization capabilities. However, no prior works were evaluated in real-world settings for off-road driving. To bridge this gap, we present PhysORD, a neural-symbolic approach integrating the conservation law, i.e., the Euler-Lagrange equation, into data-driven neural models for motion prediction in off-road driving. Our experiments showed that PhysORD can accurately predict vehicle motion and tolerate external disturbance by modeling uncertainties. It outperforms existing methods both in accuracy and efficiency and demonstrates data-efficient learning and generalization ability in long-term prediction.

关键词： Bridges Uncertainty Accuracy Neural networks Merging Predictive models Mathematical models Dynamical systems Intelligent robots

来源：评论

学校读者我要写书评

暂无评论

Internet of Things (IoT) and Machine Learning (ML) in Cyber-Security

Internet of Things (IoT) and Machine Learning (ML) in Cyber-...

引用

2022 International Conference on artificial intelligence of Things and Crowdsensing (aioTCs)

作者： Malik Abdelrahim Fadi Al-Turjman Artificial Intelligence Engineering Department Research Center for AI and IoT Near East University Nicosia North Cyprus Artificial Intelligence Engineering Department AI and Robotics Institute Near East University Mersin 10 Turkey

With the technological advancement, the world is going through, at such a high pace, new challenges arise that might require new approaches. ML is, without a doubt, on the lead of technology, as it is evolving with minimal human intervention. However, new models of ML are crucial to preventing hackers from manipulating data. It is true that with new models, new gates for attacks are opened, which is why ML security must follow the same pace in evolving. In this paper, a brief introduction to ML and ML security will be discussed to give an insight on the topic, before going through a more specific point; the challenges faced by ML security. By introducing these terms, the reader will come to grasp the importance of ML security, and the huge role it plays when it comes to protecting data against hackers. However, this by no means indicates that it is flawless; on the contrary, there are flaws in the methods used in our present day, which is another topic this paper will give an insight on. Our main focus in this paper will be supervised learning due to its application in security. Algorithms used in ML models is the main gate that hackers use to breach the system, for this precise reason, engineers and experts are challenged to come with new algorithms, as we will conclude this work.

关键词： Technological innovation Machine learning algorithms Computer hacking Supervised learning Machine learning Learning (artificial intelligence) Logic gates

来源：评论

学校读者我要写书评

暂无评论

A review of artificial intelligence of things

A review of artificial intelligence of things

引用

The International Conference on Forthcoming Networks and Sustainability (FoNeS 2022)

作者： A. Conteh F. Al-Turjman Artificial Intelligence Engineering Department Research Center for AI and IoT AI and Robotics Institute Near East University Mersin 10 Turkey

The Internet of Things (IoT) has introduced a current and up to date global powered with the aid of networking producing diverse heterogeneous records for a very long time in so many fields and applications. In removing entire facts from those records, advance artificial intelligence (ai) technology, particularly deep learning (DL), has shown a success in facilitating records analytics, destiny prediction, and choice making. The combination of ai and the IoT has appreciably promoted the fast improvement of artificial intelligence-of-Things (aioT) structures that examine and reply to outside stimuli extra intelligently without human intervention. However, it's far difficult or infeasible to method huge quantities of records in the cloud because of the unfavorable effect of records volume, velocity, and veracity and deadly transmission latency on communication infrastructures. This article conducts a survey of the internet of things and artificial intelligence orchestrated architecture for flexible artificial intelligence of things (aioT) systems. It begins by explaining fundamental concept of the internet of things and artificial intelligence with this it explains the overall artificial intelligence of things architecture show and example of aioT to illustrate how ai can be used in real world and summarize IoT and ai application.

关键词： artificial intelligence Internet of Things

来源：评论

学校读者我要写书评

暂无评论

Design and Implementation of a Conference Attendance Monitoring System Using Blockchain and ai Technologies 2

Design and Implementation of a Conference Attendance Monitor...

引用

2nd IEEE International Conference on artificial intelligence in Everything, aiE 2022

作者： Vubangsi, Mercel Al-Turjman, Fadi Ai and Robotics Institute Near East University Artificial Intelligence Engineering Dept. Mersin 10 Nicosia Turkey Htttc Bambili University of Bamenda Nwr Computational Materials Science Lab Department of Computer Science Cameroon University of Kyrenia Research Center for Ai and IoT Faculty of Engineering Mersin 10 Kyrenia Cyprus

ISBN: (数字)9781665474009

ISBN: (纸本)9781665474009

In this work, we design and implement a conference attendance monitoring system based on blockchain and artificial intelligence (ai) technologies. This system is built with *** for front-end and makes use of Google's real-time database for storage. The system is designed to auto-track the users device location and screen behavior during a time slot allocated to a conference or conference session for which the user has subscribed. ai powered analytics of the data using custom mathematical models and JavaScript Machine Learning Libraries permits decision making on the data, facilitating the task on the conference organizers with regards to rating attendee performances. © 2022 IEEE.

关键词： Smart contract

来源：评论

学校读者我要写书评

暂无评论

Applications of Transformer Attention Mechanisms in Information Security: Current Trends and Prospects 2

Applications of Transformer Attention Mechanisms in Informat...

引用

2nd IEEE International Conference on artificial intelligence of Things and Crowdsensing, aioTCs 2022

作者： Vubangsi, M. Abidemi, Sarumi Usman Akanni, Olukayode Mubarak, Auwalu Saleh Al-Turjman, Fadi Artificial Intelligence Engineering Dept. Ai and Robotics Institute Near East University Mersin 10 Nicosia Cyprus Research Center for Ai and IoT Faculty of Engineering University of Kyrenia Mersin 10 Kyrenia Cyprus Computational Materials Science Lab Department of Computer Science Htttc Bambili University of Bamenda NWR Cameroon

ISBN: (纸本)9798350334104

In this work, we present a comprehensive survey on applications of the most recent transformer architecture based on attention in information security. Our review reveals three primary areas of application: Intrusion detection, Anomaly Detection and Malware Detection. We have presented an overview of attention-based mechanisms and their application in each cybersecurity use case, and discussed open grounds for future trends in artificial intelligence enabled information security. © 2022 IEEE.

关键词： Anomaly detection

来源：评论

学校读者我要写书评

暂无评论

Network Parameter Control in Cellular Networks through Graph-Based Multi-Agent Constrained Reinforcement Learning

Network Parameter Control in Cellular Networks through Graph...

引用

IEEE International Conference on Automation Science and engineering (CASE)

作者： Albin Larsson Forsberg Alexandros Nikou Aneta Vulgarakis Feljan Jana Tumova Ericsson Research Research Area Artificial Intelligence (AI) Stockholm Sweden Department of Electrical Engineering and Computer Science Division of Robotics Perception and Learning KTH Stockholm Sweden

Cellular networks are growing in complexity at increasing speed and the geographical locations in which they are deployed in are getting denser. Traditional control methods fall short in providing a scalable and dynamic way of adapting the network to new conditions. Distributed multiagent reinforcement learning successfully addresses scalability problems seen in centralized approaches. The question of achieving learning with constraint satisfaction in distributed systems is still left unanswered in the state-of-the-art. In this work, we aim to perform distributed multi-agent constrained reinforcement learning in order to learn a policy online while satisfying imposed constraints. We use a coordination graph to model the interactions between agents and decompose the global value function. A conservative safety critic is trained in parallel to evaluate the safety of proposed actions. Our method allows for separate training of both the critic and the value network independently of each other, and hence offers flexibility in how and when to train the different models. The results are compared to a baseline using no safety critic. Simulations show that the agents succeed in learning a policy that can satisfy the constraints, while still maximizing the objective.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Research on artificial intelligence Ethical Risk of Threat intelligence Analysis and Electronic Forensics

Research on Artificial Intelligence Ethical Risk of Threat I...

引用

作者： Xu, Fajian Zheng, Xu Lin, Lizhi Chen, Shuzhen Altrjman, Chadi Department of Computer and Information Security Management Fujian Police College Fujian Fuzhou350007 China Fujian Ruiyan Judicial Expertise Institute Fujian Fuzhou350011 China School of Big Data Fuzhou University of International Studies and Trade Fujian Fuzhou350202 China Artificial Intelligence Engineering Department AI and Robotics Institute Near East University Mersin10 Turkey

The research on artificial intelligence ethics is partial to theory, and most of them have no specific practical foothold. We can analyze the ethical principles of artificial intelligence in intelligent policing according to the applications of electronic forensics and threat intelligence analysis. Taking text analysis, image forgery identification, and artificial intelligence research and judgment as examples, we can find and clarify the security ethical boundary of artificial intelligence application. It has great practical significance for social and public security. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Risk assessment

来源：评论

学校读者我要写书评

暂无评论

airShot: Efficient Few-Shot Detection for Autonomous Exploration

AirShot: Efficient Few-Shot Detection for Autonomous Explora...

引用

IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)

作者： Zihan Wang Bowen Li Chen Wang Sebastian Scherer Institute for Imaging Data and Communications School of Engineering The University of Edinburgh UK AirLab Robotics Institute Carnegie Mellon University Pittsburgh PA USA Department of Computer Science and Engineering Spatial AI & Robotics (SAIR) Lab Institute for Artificial Intelligence and Data Science University at Buffalo NY USA

ISBN: (数字)9798350377705

ISBN: (纸本)9798350377712

Few-shot object detection has drawn increasing attention in the field of robotic exploration, where robots are required to find unseen objects with a few online provided examples. Despite recent efforts have been made to yield online processing capabilities, slow inference speeds of low-powered robots fail to meet the demands of real-time detection-making them impractical for autonomous exploration. Existing methods still face performance and efficiency challenges, mainly due to unreliable features and exhaustive class loops. In this work, we propose a new paradigm airShot, and discover that, by fully exploiting the valuable correlation map, airShot can result in a more robust and faster few-shot object detection system, which is more applicable to robotics community. The core module Top Prediction Filter (TPF) can operate on multi-scale correlation maps in both the training and inference stages. During training, TPF supervises the generation of a more representative correlation map, while during inference, it reduces looping iterations by selecting top-ranked classes, thus cutting down on computational costs with better performance. Surprisingly, this dual functionality exhibits general effectiveness and efficiency on various off-the-shelf models. Exhaustive experiments on COCO2017, VOC2014, and SubT datasets demonstrate that TPF can significantly boost the efficacy and efficiency of most off-the-shelf models, achieving up to 36.4% precision improvements along with 56.3% faster inference speed. Code and Data are at: https://***/ImNotPrepared/airShot.

关键词： Training Correlation Codes Computational modeling Atmospheric modeling Object detection Real-time systems Computational efficiency Intelligent robots Faces

来源：评论

学校读者我要写书评

暂无评论

Machine Learning In Sustainable Development–An Overview

Machine Learning In Sustainable Development–An Overview

引用

Computational intelligence, Communication Technology and Networking (CICTN), International Conference on

作者： Ramiz Salama Fadi Al-Turjman Chadi Altrjman Richa Gupta Department of Computer Engineering AI and Robotics Institute Research Center for AI and IoT Near East University Nicosia Turkey Artificial Intelligence Engineering Dept. AI and Robotics Institute Near East University Turkey Faculty of Engineering University of Kyrenia Kyrenia Turkey Waterloo University Canada Department of Computer Science and Engineering Graphic Era Hill University Dehradun India

I have studied how artificial intelligence (ai) or machine learning (ML) is applied in a sustainable system called "Eugenie" for my work, project, and thesis. In this project, I get to discuss Eugenie’s role in ensuring the sustainability of large environmental business organizations. I also get to discuss how it aids operation managers in making predictions about when their machines will break down days, weeks, and months in advance, allowing them to schedule maintenance cycles more effectively. In other words, Eugenie provides plant operators with data so they can prioritize repairs. Eugenie executes this process by utilizing real-time data from numerous sensors attached to large machinery and equipment in the process industry, metals and mining, oil and gas, and smart cities industries. Two products make up this program; the first is named RAY-FINN and the second is called PAPILLON. Eugenie assists businesses in a variety of ways, including:•aids in the attainment of operational excellence by process organizations•Always raise overall profitability.•Contributes to a greener and safer future.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Mobile Application System for Online Surveys and Questionnaires

Mobile Application System for Online Surveys and Questionnai...

引用

Mechatronics, IoT and Industrial Informatics (ICMIII), International Conference on

作者： Ramiz Salama Fadi Al-Turjman Chadi Altrjman Department of Computer Engineering AI and Robotics Institute Research Center for AI and IoT Near East University Nicosia Mersin 10 Turkey Artificial Intelligence Engineering Dept AI and Robotics Institute Near East University Nicosia Mersin 10 Turkey Research Center for AI and IoT Faculty of Engineering University of Kyrenia Kyrenia Mersin 10 Turkey Waterloo University canada

The Covid-19 pandemic, which shook the entire world and altered the dynamics of humanity, resulted in drastic alterations in our life. With the pandemic, human history has understood that the digital world is more important than ever. Existing efforts to digitize pre-pandemic surveys have not entirely replaced face-to-face research. The fundamental issue with online survey platforms can be divided into two categories. It is mostly due to the fact that the particular question types used in practically all research cannot be customized and adjusted using a simple internet program, and certain limited alterations cannot be matched to the research patterns. Second, in addition to the inadequacies of these applications, the online services provided are mainly fee-based programs or applications. The application that is proposed to be established and developed in this context aims to overcome the bottleneck experienced by the end user and to supply the users with high-quality tools that they may use in the global world.

关键词：

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16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：