检索结果-内蒙古大学图书馆

Adaptive region reaching control of fully actuated ocean surface vessels

Journal of Control and Decision 2021年第3期8卷 251-259页

作者： X.M.Sun S.S.Ge Q.Xu Y.Zhou X.W.Zheng School of Engineering Science and Technology Shanghai Ocean UniversityShanghai 201306People’s Republic of China Robotics Institute and School of Computer Science and EngineeringUniversity of Electronic Science and Technology of ChinaChengduPeople’s Republic of China School of Electrical and Computer Engineering National University of SingaporeSingaporeSingapore School of Electronic and Information Engineering Beihang UniversityBeijingPeople’s Republic of China

In this paper,region reaching controller is designed for fully actuated ocean surface vessels to reach a desired target region instead of a *** are not the requirements for both the pre-specified trajectory outside the desired region and the desired pinpoint position inside the desired *** controller design is based on the potential energy function,backstepping recursive design methodology,and the Lyapnov stability analysis *** the target region is specified arbitrarily small,the target region reduces to a point,and hence the region reaching control can be a generalisation of the setpoint *** results are presented to illustrate the performance of the proposed controller.

关键词： Reaching control potential energy function adaptive control backstepping technique Lyapunov stability

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

Deep Learning and Improved Particle Swarm Optimization Based Multimodal Brain Tumor Classicatio

引用

computers, Materials & Continua 2021年第7期68卷 1099-1116页

作者： Ayesha Bin T.Tahir Muhamamd Attique Khan Majed Alhaisoni Junaid Ali Khan Yunyoung Nam Shui-Hua Wang Kashif Javed Department of Computer Science HITEC UniversityTaxila47040Pakistan College of Computer Science and Engineering University of Ha’ilHa’ilSaudi Arabia Department of Computer Science and Engineering Soonchunhyang UniversityAsanKorea School of Architecture Building and Civil Engineering Loughborough UniversityLoughboroughLE113TUUK Department of Robotics SMME NUSTIslamabadPakista

Background:A brain tumor reects abnormal cell ***:Surgery,radiation therapy,and chemotherapy are used to treat brain tumors,but these procedures are painful and *** resonance imaging(MRI)is a non-invasive modality for diagnosing tumors,but scans must be interpretated by an expert ***:We used deep learning and improved particle swarm optimization(IPSO)to automate brain tumor *** scan contrast is enhanced by ant colony optimization(ACO);the scans are then used to further train a pretrained deep learning model,via transfer learning(TL),and to extract features from two dense *** fused the features of both layers into a single,more informative *** IPSO algorithm selected the optimal features,which were classied using a support vector ***:We analyzed high-and low-grade glioma images from the BRATS 2018 dataset;the identication accuracies were 99.9%and 99.3%,***:The accuracy of our method is signicantly higher than existing techniques;thus,it will help radiologists to make diagnoses,by providing a“second opinion.”

关键词： Brain tumor contrast enhancement deep learning feature selection classication

来源：评论

学校读者我要写书评

暂无评论

3D Printed Biomimetic Composite for Treatment of Osteochondral Defects: A Preliminary Study in Porcine

SSRN

引用

SSRN 2025年

作者： Eckstein, Kevin N. Liu, Boyuan Schoonraad, Sarah A. Guastaldi, Fernando Pozzi Semeghini Uzcategui, Camila Muralidharan, Archish McLeod, Robert R. Randolph, Mark A. Bryant, Stephanie J. Ferguson, Viginia L. Paul M. Rady Department of Mechanical Engineering University of Colorado at Boulder BoulderCO80309 United States Materials Science and Engineering Program University of Colorado at Boulder BoulderCO80309 United States Division of Oral and Maxillofacial Surgery Department of Surgery Massachusetts General Hospital Harvard School of Dental Medicine Harvard Medical School BostonMA02114 United States Division of Plastic and Reconstructive Surgery Department of Surgery Massachusetts General Hospital Harvard Medical School BostonMA02114 United States Department of Electrical Computer and Energy Engineering University of Colorado at Boulder BoulderCO80309 United States Department of Chemical and Biological Engineering University of Colorado at Boulder BoulderCO80309 United States BioFrontiers Institute University of Colorado at Boulder BoulderCO80309 United States

Osteochondral defects in diarthrodial joints can occur as a result of trauma. When left untreated, the surrounding tissues experience abnormal mechanical loads that can cause further degeneration. Thus, treatment of osteochondral defects requires the ability to support physiological loads and prevent further degeneration of surrounding tissues. Additive manufacturing techniques, such as bio-ink printing, have been explored to structurally reinforce soft scaffolds;however, these methods struggle to accurately print complex designs with small feature sizes (e.g., on the order of ~100 micrometers). In this study, we present a composite osteochondral scaffold with regional stiffness gradients, optimized to mimic the mechanical properties of articular cartilage and limit high strains in the subchondral bone. This scaffold incorporates a load-bearing structure, with ≥ 180 μm diameter truss elements, that is 3D printed via projection micro-stereolithography with a biomimetic soft hydrogel. We hypothesized that incorporating a reinforcing structure with cartilage and bone regions possessing tissue-specific stiffnesses, compared to a soft gel alone, would reduce degradation of native cartilage tissue adjacent to osteochondral defects and promote multi-tissue integration in porcine knees after six weeks. Histological analysis and microcomputed tomography revealed site-specific changes in the surrounding tissue, notably in the adjacent cartilage. Mechanical evaluation of adjacent native tissue showed that scaffolds with the 3D printed composite structure resulted in 33% less surrounding cartilage degradation compared to gel-only treatments. Within the defect, the soft gel alone limited mineralization, while the composite supported mineralization but only in its stiffer region. These findings suggest that incorporating a 3D printed reinforcing osteochondral mimetic structure protects the adjacent cartilage, enhances tissue integration, and spatially supports mineralization. © 2

关键词： Bone

来源：评论

学校读者我要写书评

暂无评论

3D Printed 6-Axis Collaborative Arm Robot Using Force Limiting Feature for Service Robot 3

3D Printed 6-Axis Collaborative Arm Robot Using Force Limiti...

引用

3rd International Conference on Eco engineering Development, ICEED 2019

作者： Saerang, Raymond Wiliem, David Tinggogoy, Feraldy Carles, Deddi Dani, M. Suwandi, Agri Oey, Endra Tan, Sofyan Automotive and Robotics Engineering Program Computer Engineering Department BINUS ASO School of Engineering Bina Nusantara University Jakarta11480 Indonesia

Collaborative arm robot is a robot that can work alongside humans. By using force limiting (FL) feature, where the force of the arm robot is limited and controlled, the robot can sense collision and stop its movement when it occurs. The idea is to apply the mentioned concept for service purposes. In this research a 6-axis arm robot with collision detection is developed. The design of the arm robot adopted the design of Universal Robot's UR3 with each joint capable of 360° rotation. The design approach is chosen for its flexibility to work in tight space with a maximum reach of half meter, as it is intended to work closely with human. This initial version robot is not intended to carry heavy load or move at high precision. With a maximum load of one Kg, this arm robot targets numerous applications that help human to do complex repetitive tasks, extend the reach of human operators, and help humans on many daily chores that usually does not involve heavy loads. The whole frame, which also serve as the cover of the robot, was made by 3D printing with multiple materials that fit to the strength and temperature requirement at each part of the robot. In order to detect collision, the arm robot employed smart servos at each joint with the ability to detect overcurrent and overvoltage, which allow the implementation of force limiting (FL) feature that will stop the robot in case of collision. The resulting arm robot managed to lift1 kg load and able stop its movement in the event of collision. Future research to improve the movement precision of the arm robot by adaptive methods is promising. © 2020 Published under licence by IOP Publishing Ltd.

关键词： 3D printers

来源：评论

学校读者我要写书评

暂无评论

Design and Development of an Internet of Things (IoT)-Based Application and System to Detect Stunting in Infants and Toddlers 10

Design and Development of an Internet of Things (IoT)-Based ...

引用

10th International HCI and UX Conference in Indonesia, CHIuXiD 2024

作者： Tiffany, Theresa Jeremia, James Lie, Zener Sukra Bina Nusantara University Binus Aso School of Engineering Automotive and Robotics Engineering Program Computer Engineering Department Jakarta11480 Indonesia

ISBN: (纸本)9798350380439

Currently, the process of monitoring children's growth in Indonesia relies on manual methods for collecting anthropometric data. These methods pose a risk of data recording errors. Additionally, the ratio of healthcare workers to children in Indonesia is 1:90, a significant disparity that hinders efforts to reduce the prevalence of stunting in the country. To support the third Sustainable Development Goal (SDG), which emphasizes 'Good Health and Well-being,' it is crucial to address issues in the stunting management process, from data collection to monitoring. The design and development of this iOS-based mobile application aim to assist in monitoring child growth and provide guidance and steps for prevention and treatment. Besides application development, it also involves the design and development of an Internet of Things (IoT) system to aid in the collection of children's anthropometric data. The research methodology includes studying stunting cases in Indonesia, anthropometric data calculation methods, stunting prevention and management steps, application design and development, automatic anthropometric data collection, and online data storage and transmission using IoT technology. The developed application and system have been tested and successfully integrated. The IoT device has an accuracy rate of 99.83% for weight measurement calibration and 98.68% for height or length measurement calibration. From the testing results of the child condition calculation method in the application, an accuracy rate of 100% was achieved. © 2024 IEEE.

关键词： Anthropometry

来源：评论

学校读者我要写书评

暂无评论

Analyze and Predict Car Accidents Using Different Machine Learning Algorithms 8

Analyze and Predict Car Accidents Using Different Machine Le...

引用

8th International Conference on Information Management and Technology, ICIMTech 2023

作者： Harimanto, Farrell Putra Andrew, Chris William, Henry Asy'ari, Muhammad Zacky Artanto, Samuel Albert Puji, Muhammad Nurul Binus Aso School of Engineering Bina Nusantara University Automotive & Robotics Program Computer Engineering Department Jakarta11480 Indonesia

ISBN: (纸本)9798350326093

Traffic accidents can occur from various factors, ranging from the driver themselves to problems with the vehicle. Road and traffic accidents are the most significant factor of fatalities in the world. Most of the causes of accidents are the drivers themselves. Poor physical and mental conditions can significantly impact how to drive. The driving experience is also important;the longer the driver has been driving, the more professional he will be, and vice versa. Smart City solutions can predict the severity of accidents and give information to the authorities in order to reduce the number of fatalities. This paper investigates the factors that may lead to an accident on the road. By looking at data collected from traffic-related accidents and then visualizing it to make it easy to analyze;then, from this data, we will predict the causes of traffic accidents so they can be avoided. The best algorithm based on accuracy, MAE and RMSE is Random Forest Classifier with 0.8461, 0.1663 and 0.4376, respectively. © 2023 IEEE.

关键词： Machine learning

来源：评论

学校读者我要写书评

暂无评论

Corrigendum "SOH-KLSTM: A hybrid Kolmogorov-Arnold network and LSTM model for enhanced lithium-ion battery health monitoring" [journal of energy storage, volume 122 (2025), 116,541](S2352152X2501254X)(10.1016/***.2025.116541)

引用

Journal of Energy Storage 2025年 124卷

作者： Jarraya, Imen Ben Atitallah, Safa Alahmed, Fatimah Abdelkader, Mohamed Driss, Maha Abdelhadi, Fatma Koubaa, Anis Robotics and Internet of Things Laboratory College of Computer and Information Sciences Prince Sultan University Riyadh12435 Saudi Arabia RIADI Laboratory National School of Computer Science University of Manouba Manouba2010 Tunisia College of Electrical and Computer Engineering King Abdulaziz University Jeddah22254 Saudi Arabia

关键词：

来源：评论

学校读者我要写书评

暂无评论

Development of Fish Separator Conveyor based on Fish Identification System 3

Development of Fish Separator Conveyor based on Fish Identif...

引用

3rd International Conference on Eco engineering Development, ICEED 2019

作者： Dzulfiqar Agung, Muhammad Rangga Elian, Adrian Adhe Astuti, Winda Puji, Muhammad Nurul Automotive and Robotics Program Computer Engineering Department BINUS ASO School of Engineering Bina Nusantara University Jakarta11480 Indonesia

Indonesia as the largest archipelago and maritime country in the world has a very large marine resources. Fish is one of the marine wealthties (marine biota), which have large numbers in Indonesia. Fishermen is an important role in the process of fishing, however fish caught by fishermen are often mixed with other types of fish. Currently, the process of fist separation is done manually, which takes longer time and many error occur due to fatigue. In this work the conveyer separator based on the fish identification system is developed. The fish conveyer separator is designed and developed. The fish identification system is based on Fast Fourier Transform (FTT) technique and Artificial Neural Network (ANN). The system is working properly, since it resulting the training and testing accuracy of 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

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

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：

请选择收藏分类：

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

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：