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

48 篇 会议
10 篇 期刊文献

馆藏范围

58 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

34 篇 工学
- 21 篇 计算机科学与技术...
- 20 篇 软件工程
- 8 篇 信息与通信工程
- 8 篇 控制科学与工程
- 7 篇 机械工程
- 7 篇 化学工程与技术
- 7 篇 生物医学工程（可授...
- 6 篇 光学工程
- 6 篇 电气工程
- 6 篇 生物工程
- 6 篇 安全科学与工程
- 4 篇 电子科学与技术（可...
- 3 篇 仪器科学与技术
- 3 篇 材料科学与工程（可...
- 3 篇 动力工程及工程热...
- 3 篇 石油与天然气工程
- 3 篇 交通运输工程
23 篇 理学
- 11 篇 数学
- 9 篇 物理学
- 6 篇 生物学
- 5 篇 化学
- 3 篇 统计学（可授理学、...
9 篇 管理学
- 5 篇 管理科学与工程(可...
- 4 篇 工商管理
- 4 篇 图书情报与档案管...
5 篇 医学
- 5 篇 临床医学
- 4 篇 基础医学(可授医学...
- 3 篇 公共卫生与预防医...
- 2 篇 药学(可授医学、理...
3 篇 经济学
- 3 篇 应用经济学
1 篇 法学
1 篇 教育学
1 篇 农学

主题

6 篇 accuracy
5 篇 testing
4 篇 support vector m...
4 篇 training
3 篇 convolutional ne...
2 篇 internet of thin...
2 篇 vehicle dynamics
2 篇 nearest neighbor...
2 篇 electric vehicle...
2 篇 stethoscope
2 篇 logistic regress...
2 篇 fast fourier tra...
2 篇 vibrations
2 篇 sliding mode con...
2 篇 yolo
2 篇 machine learning
2 篇 state of charge
2 篇 mel frequency ce...
1 篇 fuzzy logic
1 篇 microwave antenn...

机构

9 篇 automotive and r...
5 篇 automotive and r...
5 篇 computer enginee...
4 篇 computer enginee...
4 篇 binus aso school...
3 篇 bina nusantara u...
3 篇 automotive and r...
2 篇 product design p...
2 篇 bina nusantara u...
2 篇 automotive & rob...
2 篇 bina nusantara u...
2 篇 faculty of engin...
2 篇 computer enginee...
2 篇 binus aso school...
2 篇 binus aso school...
1 篇 university of mu...
1 篇 electrical engin...
1 篇 institute of rob...
1 篇 binus aso school...
1 篇 bina nusantara u...

作者

17 篇 astuti winda
15 篇 winda astuti
8 篇 muhammad nurul p...
7 篇 puji muhammad nu...
4 篇 oey endra
4 篇 mariana yosica
4 篇 solihin mahmud i...
3 篇 tan sofyan
3 篇 mahmud iwan soli...
3 篇 sofyan tan
3 篇 muhammad zacky a...
3 篇 sukra zener lie
3 篇 yosica mariana
3 篇 andriatin yuli a...
3 篇 liawatimena sury...
3 篇 asy'ari muhammad...
3 篇 zener sukra lie
3 篇 lie zener sukra
3 篇 suryadiputra lia...
2 篇 qadri munzir

语言

56 篇 英文
1 篇 其他

检索条件"机构=Automotive and Robotics Engineering Program"

共 58 条记录，以下是11-20 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：

Analysis of Knocking Potential Based on Vibration on a Gasoline Engine for Pertalite and Pertamax Turbo Using Signal Processing Methods 1

引用

International Conference on Innovative Technologies in Intelligent Systems and Industrial Applications, CITISIA 2022

作者： Qadri, Munzir Astuti, Winda Automotive and Robotics Program Computer Engineering Department BINUS ASO School of Engineering Bina Nusantara University Jakarta11480 Indonesia

ISBN: (数字)9783031290787

ISBN: (纸本)9783031290770

Knocking is one of the problems in internal combustion engines with many influencing factors, one of which is the use of fuel octane values that are not in accordance with the recommended use or engine specifications. Knocking can lead to poor performance of an engine and shorten its lifetime. To prevent this from happening, a study was conducted on how the octane rating can affect the knocking of an engine by comparing two types of fuel that have different octane rating levels. The most appropriate signal processing method was also determined to carry out this research. The engine speed was predetermined in each experiment. The achieved results prove that the engine has the potential of knocking to occur when using Pertalite-type fuel, caused by misfires. Signal processing is carried out using the Fast Fourier Transform (FFT) and Low Pass Filter (LPF) methods to obtain clear data. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023.

关键词： Gasoline

来源：评论

学校读者我要写书评

暂无评论

Automation Lamp Healing Application based on Face Expression Identification System using Convolution Neural Network (CNN)

Automation Lamp Healing Application based on Face Expression...

引用

2023 International Conference on Electrical engineering and Informatics, ICEEI 2023

作者： Saduki Simangunsong, Devin Onil Mahesh Puji, Muhammad Nurul Astuti, Winda Binus Aso School of Engineering Bina Nusantara University Automotive and Robotics Program Computer Engineering Department Jakarta11480 Indonesia

ISBN: (纸本)9798350381290

The disruption of routines, education, recreation, as well as concerns about family income and health, has left many young people feeling fearful, angry, and worried about their future. In this system, a smart system will be developed that can capture, process, and interpret facial expressions so that a person's emotions can be easily and accurately identified, which is one of the best solutions. The system will use artificial intelligence that has been trained beforehand using suitable datasets. In the processed of developing the system, Face image with the size of 48 x 48 x 1 became the input of the system, processes by Convolution layer using Relu activation function. The activation function used in the output layer is softmax because it is suitable for more than 2 classifications. by applying CNN based on Adam optimization which have result on 98.96% and 70%, for training and testing accuracy, respectively. Furthermore, the system accurately turn-on the healing lamp based on the emotion identified. © 2023 IEEE.

关键词： Face recognition

来源：评论

学校读者我要写书评

暂无评论

License plate recognition system based on principal component analysis and one-against-one multi-class support vector machine 3

License plate recognition system based on principal componen...

引用

3rd International Conference on Eco engineering Development, ICEED 2019

作者： Kosasih, Kevin Kristofer Astuti, Winda Oey, Endra Automotive and Robotics Program Computer Engineering Department BINUS ASO School of Engineering Bina Nusantara University Jakarta11480 Indonesia

The license plate number which identifies the original registered place of the vehicle, as well as the usage of each vehicle which belongs to a private entity, a government vehicle, and a commercial vehicle, is identified in this work. Vehicle plate detection by a camera that mounted on parking gate. Detection process starts with collecting data using the camera. This work consists two important parts, namely image processing and classification system, respectively. In the image processing, the plate image capture by the camera is extracted to the feature space which will use as the input to the classification system. The classification system is then will identify the extracted input to the plat recognition identification. The Fast Fourier Transform (FFT) and Support Vector Machine (SVM) are applied as feature extraction technique and classification methods, respectively. The results of the training and testing phase are 80% and 66%, respectively. © 2020 Published under licence by IOP Publishing Ltd.

关键词： Fast Fourier transforms

来源：评论

学校读者我要写书评

暂无评论

Traffic Signs Detection System Using YOLO (You Only Look Once) That Provides Notification 1

Traffic Signs Detection System Using YOLO (You Only Look Onc...

引用

1st International Conference on Smart Mechatronics, ICSMech 2024

作者： Setiawan, Yosua Puji, Muhammad Nurul Astuti, Winda Binus Aso School of Engineering Bina Nusantara University Automotive & Robotics Program Computer Engineering Department Jakarta11480 Indonesia

ISBN: (纸本)9798350368918

Road accidents have become a problem for many road users in many countries. It may affect human daily activity and tasks, potentially influencing productivity and safety. Therefore, reducing road accidents as swiftly and effectively as possible is critical. For this reason, a Traffic signs detection system has been developed in this work to improve road safety. The detection system can detect traffic signs on the road such as traffic lights, speed limits, and no U-turn signs, and then it will provide users with the corresponding text on an LCD and vibration feedback using a motor. Throughout this work, the You Only Look Once (YOLO) algorithm is proposed for detecting traffic signs on the road. Moreover, a camera is used to extract live videos which serve as an input for the Raspberry Pi 4 model B containing custom YOLOv5 and YOLOv8 models. The system then sends the output to an LCD, a vibration motor, and a radio frequency (RF) module as notifications for users. In the end, the performance of the proposed method has been collected and it is found to produce good accuracy within an inconsiderable amount of 1.677 images and 2.263 annotations. Therefore, the accuracy of 0.69 for YOLOv5 and 0.7 for YOLOv8 were obtained from the training and validation process. Furthermore, the system accurately detects the traffic signs on the road. © 2024 IEEE.

关键词： Traffic signs

来源：评论

学校读者我要写书评

暂无评论

Emotion Recognition Based on Voice Using Combination of Long Short Term Memory (LSTM) and Recurrent Neural Network (RNN) for Automation Music Healing Application 1

引用

International Conference on Innovative Technologies in Intelligent Systems and Industrial Applications, CITISIA 2022

作者： Trisyanto, Daryl Elangi Reynard, Michael Oey, Endra Astuti, Winda Automotive and Robotics Program Computer Engineering Department BINUS ASO School of Engineering Bina Nusantara University Jakarta11480 Indonesia

ISBN: (数字)9783031290787

ISBN: (纸本)9783031290770

Stress has become a problem for many people experience in the world. It can affect in decrease in activity and productivity in daily life. Therefore, it is important to reduce or even heal this stress. One way to do that is by listening to appropriate music. Emotion recognition based on voice intonation has been developed in this work. The system has the ability to recognize the emotion of the speaker then automatically play the appropriate music based on emotion of the speaker. In this work, the combination of Long Short Term Memory (LSTM) and Recurrent Neural Network (RNN) approach for identifying emotion based on voice intonation of the speaker is proposed. The Mel Frequency Cepstral Coefficient (MFCC) is adopted as a feature extraction of the voice, which will used as input to the combination of Long Short Term Memory (LSTM) and Recurrent Neural Network (RNN)-based identifier. The performance of the proposed technique has been investigated, especially for multiclass classification and it is found to produce good accuracy within short duration training time. The accuracy of 99.8% and 62.5%, for training and testing accuracy respectively. Furthermore, the system accurately plays the music based on the emotion identified. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023.

关键词： Long short-term memory

来源：评论

学校读者我要写书评

暂无评论

Computer Vision-Based Hydroponic Lettuce Contour and Area Recognition System

Computer Vision-Based Hydroponic Lettuce Contour and Area Re...

引用

2023 International Conference on Electrical engineering and Informatics, ICEEI 2023

作者： Pranowo, Samuel Raymond Sukra, Zener Lie Asy'ari, Muhammad Zacky Paryasto, Marisa Binus Aso School of Engineering Bina Nusantara University Automotive and Robotics Program Computer Engineering Department Jakarta Indonesia Telkom University Computer Engineering Program Electrical Engineering Department Bandung Indonesia

ISBN: (纸本)9798350381290

Agriculture is a vital industry for the people of Indonesia, but there are several obstacles, including limited space in urban areas and inefficient conventional sorting and harvesting methods. Using computer vision to choose hydroponic lettuce that is ready to be harvested and a robotic arm to bring the selected lettuce yields, the produced system aims to solve this problem. The system's computer vision algorithms include color space conversion, intensity transformation, and an algorithm for following borders. This project's research methodology combines a quantitative approach with an experimental approach, which consists of conducting several trials on the built system. Several trials demonstrated that the computer vision software was able to accomplish the specified objectives. The average success rate of the developed computer vision system is 93%, while the average success rate of the robot arm is 85%. © 2023 IEEE.

关键词： Lettuce

来源：评论

学校读者我要写书评

暂无评论

Development of Detection Lung Disease Stand Alone System Based on Convolutional Neural Network (CNN) 7

Development of Detection Lung Disease Stand Alone System Bas...

引用

7th International Conference of Computer and Informatics engineering, IC2IE 2024

作者： Liewarnata, Edgar Caesar Mariana, Yosica Tan, Sofyan Liawatimena, Suryadiputra Astuti, Winda Bina Nusantara University Binus Aso School of Engineering Automotive and Robotics Program Computer Engineering Department Jakarta11480 Indonesia Bina Nusantara University Binus Aso School of Engineering Product Design Program Industrial Engineering Department Jakarta11480 Indonesia Bina Nusantara University Binus Graduate Program - Master of Computer Science Automotive and Robotics Program Computer Engineering Department Binus Aso School of Engineering Computer Science Department Jakarta11480 Indonesia

ISBN: (纸本)9798331505530

Lung disease, especially Tuberculosis (TBC), placed the highest death rate in Indonesia. Tuberculosis (TB) in Indonesia is ranked second after India. Therefore, it is important to reduce or early detection of the lung disease, to prevent this disease and speed up handling. The system can recognize the disease lung identification, and the system applied as standalone system. In this work, the Convolutional Neural Network (CNN) approach for identifying diseases lung identification is proposed. The Mel Frequency Cepstral Coefficient (MFCC) applied to process the stethoscope sounds which will used as input to the CNN. The performance of the proposed system has been investigated and resulted. The accuracy of 99% and 98%, for training and testing accuracy respectively. Furthermore, the system accurately detects lung diseases identification. © 2024 IEEE.

关键词： Lung cancer

来源：评论

学校读者我要写书评

暂无评论

Intelligent Small Scale Autonomous Vehicle Development Based on Convolutional Neural Network (CNN) for Steering Angle Prediction 1

引用

International Conference on Innovative Technologies in Intelligent Systems and Industrial Applications, CITISIA 2022

作者： Asy’ari, Muhammad Zacky Phang, Maxson Suganda, Nicholas Mariana, Yosica Automotive and Robotics Program Computer Engineering Department BINUS ASO School of Engineering Bina Nusantara University Jakarta Indonesia Architecture Department Faculty of Engineering Binus University Jakarta Indonesia

ISBN: (数字)9783031290787

ISBN: (纸本)9783031290770

Human error is the most significant factor in traffic accidents. 61% of accidents in Indonesia are caused by driver negligence. Autonomous vehicles are unmanned vehicles that are believed to be able to reduce the number of accidents caused by human error. This study aims to create a prototype of a small-scale unmanned vehicle using computer vision that can move around the track. The prototype captures an image using a USB webcam and is processed by a Raspberry Pi 4 to predict the correct steering angle based on input from the camera. A convolutional neural network (CNN) algorithm is used to recognize the path. The material used to make the prototype is PLA (polylactic acid). The prototype steering system uses a servo motor, and the drive system uses a brushless DC motor controlled by the PCA9685 module. More than 1600 image data were used and taken based on a simplified track. The results of this study indicate that the prototype can move along the given track with a steering angle range of 20°–130° for right turns and 60°–170° for left turns. The throttle value capable of moving the prototype at a steady speed is 0.075. The Keras Tensorflow model, dataset, and autonomous car design can achieve the desired level of autonomy with an RMSE accuracy of 0.1145. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023.

关键词： Forecasting

来源：评论

学校读者我要写书评

暂无评论

Emotion Recognition based on Heart Rate Detection using Logistic Regression for Automation Food Healing Application 8

Emotion Recognition based on Heart Rate Detection using Logi...

引用

8th International Conference on Education and Technology, ICET 2022

作者： Antonio, Nicholas Jason Nobel, Yosse Ricardo Ho, Hwi-Chie Astuti, Winda Bina Nusantara University Binus Aso School of Engineering Automotive and Robotics Program Computer Engineering Department Jakarta Indonesia Bina Nusantara University Industrial Engineering Department Jakarta Indonesia

ISBN: (数字)9781665492140

ISBN: (纸本)9781665492140

Daily pressure activity especially in work place or any society condition may causing stress or pressure for the people deal with that condition. This stress may causing of decreasing of work performance and achievement in the daily activity. Furthermore in worse condition, people may went to psychiatrist consulting regarding the condition in order to heal the stress or pressure feeling. In this work, food recommendation healing in order to improve the mood based on mood recognition using heartbeat rate detection system is developed. Mood detection results will be used to recommend foods that can improve the mood. the mood detection system work based on automatic intelligent heartbeat rate identification. This system installed on an Android cellphone, so its make the system more flexible and portable. the system has also connected to the web, in order used by doctors to monitor the patient's condition if the patient is being monitoring due to health mental diseases treatment. This system has worked properly with mood detection based on heartbeat rate with 96% and 97%, training and testing accuracy, respectively. Furthermore, this system is connected to the website for monitoring purposes for the psychiatrist to monitor their patient intern of mood changing fluctuation © 2022 IEEE.

关键词： Data handling

来源：评论

学校读者我要写书评

暂无评论

Inpatient Monitoring System: Temperature, Oxygen Saturation, Blood Pressure, Heart Rate, and Infusion Automation Based on ESP 32, IoT, and Mobile Application 7

Inpatient Monitoring System: Temperature, Oxygen Saturation,...

引用

7th International Conference of Computer and Informatics engineering, IC2IE 2024

作者： Joseph, Irvanda Anthony, Patrick Astuti, Winda Lie, Zener Sukra Iwan Solihin, Mahmud Bina Nusantara University Binus Aso School of Engineering Automotive and Robotics Program Computer Engineering Department Jakarta11480 Indonesia Ucsi University Department of Mechanical and Mechatronics Engineering Kuala Lumpur Malaysia

ISBN: (纸本)9798331505530

The implementation of a patient monitoring system and infusion automation which aims to ensure regular and periodic monitoring of inpatient conditions are applied in this system. This embedded system is applied in hospitals and addresses the uneven distribution of healthcare workers in Indonesia, particularly in remote areas. Currently, manual checks by nurses can lead to errors and reduced patient comfort. The improvement supervision is developed in this work. The system monitored body temperature, oxygen saturation, blood pressure, heart rate, and automated infusions. All the embedded systems are connected to Internet of Things (IoT) and a real-time database accessible through an application and web. This system allows doctors and hospital authorities to make decisions based on patient condition history. The testing phase of the system shows four data acquisition devices (temperature, oxygen saturation, blood pressure, and heart rate), an ESP 32, and Firebase as a database, have ability to capture and send real-time data every five seconds and can be accessed by doctors, patients, and hospital authorities. © 2024 IEEE.

关键词： Remote patient monitoring

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6页 << < 1 2 3 4 5 6 > >>

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：