检索结果-内蒙古大学图书馆

30th IEEE International Conference on Electronics, Electrical engineering and Computing, INTERCON 2023

作者： Romero, Fabiola Cieza Pajes Leon, Sebastian Wong, Lenis Universidad Peruana de Ciencias Aplicadas Information Systems Engineering Program Lima Peru

ISBN: (纸本)9798350315578

In the current digital era, efficiently accessing relevant information is crucial for various applications such as restaurant recommendation systems, website searches, book recommendations, among others. This study presents an approach for personalized recommendations in improving the customer service process in restaurants using OpenAI's Contextual Chatbot. The approach consists of six phases: (1) Data preprocessing, (2) Embedding and storage, (3) Scheduled updating, (4) Document retrieval, (5) Context adaptation and request creation, and (6) Response generation. OpenAI's text embeddings are used to convert application data into vectors and store them in a vector database. These vectors are used to retrieve similar records and generate contextualized responses using the GPT-3.5 model. The chatbot's performance is evaluated in terms of accuracy and user satisfaction. Two scenarios were used in the experimentation: (a) with the proposed solution and (b) without the solution. The results demonstrated an operational efficiency of 86.67% with the proposed solution and the versatility of the proposed methodology, showcasing its potential for application in a wide range of domains, including websites, books, PDFs, and other forms of documentation. © 2023 IEEE.

关键词： Embeddings

来源：评论

学校读者我要写书评

暂无评论

Design of an Infusion Capacity Monitoring System for Patients Based on the Internet of Things in Hospitals 9

Design of an Infusion Capacity Monitoring System for Patient...

引用

9th International Conference on Business and Industrial Research, ICBIR 2024

作者： Windyasari, Vina Septiana Murad, Silvia Ayunda Syam, Syahriani Mahardika, Maulia Budiman, Johan Rahmawati, Diah Islamic Syekh-Yusuf University Information Systems Study Program Tangerang Indonesia Binus University Binus Online Learning Information System Department Jakarta Indonesia Islamic Syekh-Yusuf University Informatics Engineering Study Program Tangerang Indonesia Islamic Syekh-Yusuf University Civil Engineering Study Program Tangerang Indonesia

ISBN: (纸本)9798350383010

The patient's infusion fluid will only be changed if the nurse changes it or based on information from the patient's family. The research method used in terms of fluid volume utilizes the function of the Arduino microcontroller as the brain, the load cell sensor as an infusion fluid weight detector connected to the IoT, fuzzy logic calculations on the infusion volume weight measuring device in line with real-time decision-making when reading gram weight changes with sensors, and the system development method using a prototype model. The test results of three infusion bottles containing mineral water with a liquid volume of 500 ml and a load cell sensor as an infusion weight detector can be accepted by the Arduino Wemos D1 as a load cell sensor processing component. The infusion liquid weight data is uploaded to the MySQL database, and a notification is sent and displayed on the smartphone when the infusion volume reaches 12% of its weight. The results of this study indicate that the design of tools connected to applications on smartphones can work well and facilitate the process of monitoring infusions for patients in real-time © 2024 IEEE.

关键词： Smartphones

来源：评论

学校读者我要写书评

暂无评论

Elderly Pedestrian-Crossing Strategy When Perceiving an Autonomous Vehicle in a Shared Space 4

Elderly Pedestrian-Crossing Strategy When Perceiving an Auto...

引用

4th IEEE International Conference on Human-Machine Systems, ICHMS 2024

作者： Dong, Yichen Andrijanto Yano, Hiroaki Itoh, Makoto University Of Tsukuba Degree Program Of Risk And Resilience Engineering Tsukuba Japan Institute Of Systems And Information Engineering University Of Tsukuba Tsukuba Japan University Of Tsukuba Institute Of Systems And Information Engineering Center For Artificial Intelligence Research Tsukuba Japan

ISBN: (纸本)9798350315790

This study clarified a pedestrian crossing strategy for elderly Japanese pedestrians when perceiving an autonomous vehicle in a shared space by eliminating road features. Crossing strategy is the basis of pedestrian crossing behavior, and this study distinguishes two types of crossing strategies: conservative and aggressive. We proposed a process for pedestrians who use a strategy to cross the road. Experimental data collected in a virtual reality facility were analyzed to investigate pedestrian-crossing strategies. The variables contributing to the pedestrian crossing behavior and crossing strategy selection were explored. The results indicated that the proposed crossing strategy predicted the observed behaviors of the participants. Pedestrian crossing behavior is influenced by gender, age, and vehicle speed. Higher vehicle speed and pedestrian age lead to pedestrians increasing their crossing time and selecting a conservative walking strategy. The study also showed that males selected an aggressive strategy more frequently than females and that males needed more time to cross the road than females. © 2024 IEEE.

关键词： Crosswalks

来源：评论

学校读者我要写书评

暂无评论

A Note on Even-Sized Spectral Clustering 13

A Note on Even-Sized Spectral Clustering

引用

Joint 13th International Conference on Soft Computing and Intelligent Systems and 25th International Symposium on Advanced Intelligent Systems, SCIS and ISIS 2024

作者： Miyakawa, Hiroki Endo, Yasunori Graduate School of Science and Technology Degree Programs in Systems and Information Engineering Master's Program in Risk and Resilience Engineering University of Tsukuba Ibaraki Tsukuba Japan Institute of Systems and Information Engineering University of Tsukuba Ibaraki Tsukuba Japan

ISBN: (纸本)9798350373332

Clustering is a typical unsupervised learning method for classifying unsupervised data. One of the clustering meth-ods, even-sized clustering based on optimization (ECBO), is a clustering algorithm that imposes a constraint to equalize the size of each cluster. ECBO has been suggested to be effective in delivery and other problems. However, it is limited to Euclidean space. On the other hand, spectral clustering with a wide range of applicability for partitioning graph data has been proposed. In this paper, we propose even-sized spectral clustering, which imposes a size-equal constraint on spectral clustering, and show that it is an extension of the graph partitioning problem. We also verify the validity of the results through numerical examples. © 2024 IEEE.

关键词： Unsupervised learning

来源：评论

学校读者我要写书评

暂无评论

Enabling Smart Home Energy Management through Gesture-Based Control and IoT Technology

Enabling Smart Home Energy Management through Gesture-Based ...

引用

2023 International Conference on Consumer Electronics - Taiwan, ICCE-Taiwan 2023

作者： Rambe, Khairul Hawani Ou, Chia-Ho International Master Program in Information Technology and Applications Sweden National Pingtung University Department of Computer Science and Information Engineering Taiwan

ISBN: (纸本)9798350324174

The Internet of Things (IoTs) have become ubiquitous in all aspects of public needs today. The application of IoT technology is crucial for promoting energy-saving behavior. This paper presents a control system used for smart home devices based on hand gesture control and Android applications. The hardware design uses the ESP32 microcontroller, which has an in-chip Wi-Fi module, making it very suitable for creating IoT application systems. The software was designed using the Arduino IDE, and the application display design was developed using Kodular Creator, which is used to control the lamps and switches. The experiment results show that the electrical equipment can be activated using the Android application with gesture sensors by waving down, up, left, and right. © 2023 IEEE.

关键词： Internet of things

来源：评论

学校读者我要写书评

暂无评论

Weed Detection Based on Fine-Tuned YOLOv5 16

Weed Detection Based on Fine-Tuned YOLOv5

引用

16th International Conference on information Technology and Electrical engineering, ICITEE 2024

作者： Agustian, Indra Wibirama, Sunu Ardiyanto, Igi Anggraini, Ika Novia Noviansyah, Pariyanto Universitas Gadjah Mada Department of Electrical and Information Engineering Yogyakarta Indonesia Universitas Bengkulu Study Program of Electrical Engineering Bengkulu Indonesia Universitas Gadjah Mada Department of Electrical and Information Engineering Yogyakarta55281 Indonesia Universitas Gadjah Mada Department of Electrical and Information Engineerig Yogyakarta Indonesia

ISBN: (纸本)9798350375817

Conventional weed control often ignores weed locations, potentially causing land damage. AI-based weed detection offers a modern solution. Unfortunately, little attention has been paid to how an augmentation technique improves performance of AI-based weed detection. To address this research gap, we proposed a weed detection model based on fine-tuned YOLOv5 to detect weeds in corn fields aged 1 to 3 weeks. YOLOv5 offers computational benefits, includes auto-augmentation capabilities, and presents a more organized visualization of the outcomes from the training data. The primary dataset used in this study comprised 3,437 images with a total of 18,267 annotated objects, including corn plants and weeds. We observed the effect of mosaic augmentation on the dataset images based on auto-augmentation in YOLOv5. We found that mosaic augmentation with a 0.75 probability outperformed 0.5 and 1.0. The best mAP performance was at the level @0.5 with score of 0.776 for all classes. Meanwhile, the mAP@0.5:0.95 was 0.573 for all classes, indicating that the model's performance requires further improvement. Our study is promising as a guidance for future development of AI-based weed detection. © 2024 IEEE.

关键词： weed deep learning Weed detection weed-yolo yolov5

来源：评论

学校读者我要写书评

暂无评论

Performance Evaluation of KNIME Low Code Platform in Deep Learning Study and Optimal Hyperparameter Tuning

Performance Evaluation of KNIME Low Code Platform in Deep Le...

引用

2024 IEEE Region 10 Conference, TENCON 2024

作者： Thongkhome, Pornpawee Yonezawa, Takuro Kawaguchi, Nobuo G30 International Program in Electrical Electronic and Information Engineering School of Engineering Nagoya University Aichi Japan Graduate School of Engineering Nagoya University Aichi Japan

ISBN: (纸本)9798350350821

A low-code platform is a software development environment that allows for the creation of applications through graphical user interfaces and configuration instead of traditional hand-coded computer programming. In this study, the application to classify a dataset of traffic sign images using the KNIME low-code deep learning development platform will be discussed to represents this software performance especial in term of model optimization processes. By creates the workflow to perform image preprocessing, create the CNN layer under KERAS sequential API and finding the best set of key hyperparameters among traditional KNIME build-in optimization algorithm including Brute force, Hill climbing, random search, Bayesian Optimization and black-box optimizer Optuna optimization algorithm under 3 types CNN architecture as simple CNN, Resnet-50 and VGG16 to classify traffic sign images. The result demonstrates that both grid search and random search optimization can be effective, while both Optuna and Bayesian optimization stands out as a powerful method due to its ability to efficiently explore the hyperparameter space and achieve superior results to meet 99% accuracy under simple CNN environment, but Optuna is significantly improve optimization times than Bayesian about 7 - 8 times. The KNIME low-code platform provides a user-friendly environment for developing and fine-tuning models to contribute the ongoing progress in machine learning and deep learning research development. © 2024 IEEE.

关键词： Graphical user interfaces

来源：评论

学校读者我要写书评

暂无评论

Trade Ease with Machine Learning and AWS

引用

IEEE Access 2023年 11卷 25893-25905页

作者： Teja, Kamurthi Ravi Liu, Chuan-Ming National Taipei University of Technology International Program of Electrical Engineering and Computer Science Taipei10608 Taiwan National Taipei University of Technology Department of Computer Science and Information Engineering Taipei10608 Taiwan

Global trading is undergoing significant changes, necessitating modifications to the trading strategies. This study presents a newly developed cloud-based trading strategy that uses Amazon Web Services (AWS), machine learning (ML), and data science to automate trading tasks. The study begins by creating a machine learning trading strategy using a customized deep neural network (DNN). The strategy was then tested using a trading station before deployment on a cloud machine. The execution of the strategy resulted in a total profit of 42.74526 USD, with a test accuracy score of 87.45% and a training accuracy score of 89.15% over 6047 epochs. The roadmap provides a step-by-step overview of the entire process from strategy development to execution. In addition, this study offers insights into related issues and solutions that can enhance the effectiveness of trading strategies. Overall, this study contributes significantly to the field of cloud-based trading strategies and opens avenues for future research. © 2013 IEEE.

关键词： Deep neural networks

来源：评论

学校读者我要写书评

暂无评论

Web-Based Incentive Calculations System at CV Karya Prima using Prototyping Method 7

Web-Based Incentive Calculations System at CV Karya Prima us...

引用

7th International Conference on New Media Studies, CONMEDIA 2023

作者： Cornelia, Monica Suryasari Universitas Multimedia Nusantara Information Systems Study Program Faculty of Engineering and Informatics Tangerang Indonesia

ISBN: (纸本)9798350307504

Consumption is an essential aspect of daily life, and fulfilling customer needs requires efficient distribution of goods. Therefore, distributors are needed and they frequently set targets for their employees to achieve, and motivation plays a significant role in employee performance. An organization that distributes goods called CV Karya Prima motivates its employees by offering incentives. However, manual incentive calculation sets out problems such as a lack of progress tracking, irregular payout dates, and probable inaccuracies. This study aims to develop a web-based incentive calculation system using the analytical hierarchy process method and a database for data retrieval. The system utilizes PHP, CodeIgniter, and MySQL and adopts the SDLC prototyping method. The developed system is focused on the sales division and variables like total sales, effective calls, calls, and outlets. The web-based system is capable of solving the issues using the features that were built based on user needs and have already been tested through user acceptance testing. © 2023 IEEE.

关键词： Websites

来源：评论

学校读者我要写书评

暂无评论

Unraveling Game Addiction Behavior Among Digital Native Students: Leveraging Machine Learning for Insights 13

Unraveling Game Addiction Behavior Among Digital Native Stud...

引用

13th IEEE International Conference on Communication, Networks and Satellite, COMNETSAT 2024

作者： Amriza, Rona Nisa Sofia Fadhilla, Cut Alna Telkom University Department of Information System Purwokerto Indonesia Universitas Samudra Informatics Study Program Faculty of Engineering Aceh Indonesia

ISBN: (纸本)9798350368086

The allure of gaming often leads to excessive engagement, which can result in addictive and problematic behaviors, negatively impacting academic performance and school achievements. While gaming becomes increasingly prevalent, concerns about game addiction have grown, particularly among students. The excessive and obsessive usage of video games that characterizes game addiction can have detrimental effects like academic deterioration, social isolation, and mental health problems. This study seeks to elucidate the complex patterns of game addiction among digital-native students by utilizing advanced machine learning techniques. We employed Random Forest, SVM, Decision Tree, and Naïve Bayes algorithms to classify game addiction data from students. To address the class imbalance, we applied Borderline-SMOTE. Our results demonstrate that decision tree and random forest outperformed other machine learning approaches, achieving an accuracy of 95% in classifying game addiction. These findings contribute to the expanding body of knowledge on game addiction. Furthermore, in order to provide real-time monitoring and intervention for students who are at risk of developing a game addiction, future research may investigate incorporating these findings into educational platforms or applications. © 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

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：