检索结果-内蒙古大学图书馆

2023 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2023

作者： Hung, Che-Lun Lin, Keng-Hung Lee, Yu-Kai Lin, ChunHsien Tsai, Yin-Te Institute of Biomedical Informatics National Yang Ming Chiao Tung University Taiwan Taichung Veterans General Hospital Department of Ophthalmology Taiwan Providence University Department of Computer Science and Information Engineering Taiwan Providence University Department of Computer Science and Communication Engineering Taiwan

ISBN: (纸本)9798350337488

Macular holes (MHs) can be either idiopathic or secondary to a result of concurrent or previous pathology such as ocular inflammation, trauma or surgery. Idiopathic macular holes may eventually impair the life quality and self-care capability of patients. In clinical, the optical coherence tomography (OCT) images of macular holes can be divided into 4 stages based upon the size of macular hole. The size of macular hole is inversely influencing surgical success rate and visual outcomes. Minimizing human judgment errors in the classification of MHs and enhancing the overall quality of classification are critical objectives. In this paper, we develop a deep learning algorithm to detect MHs on OCT images and also propose an automatic algorithm to measure the size of MH. The MH detection algorithm demonstrates exceptional accuracy, while the measurement algorithm offers superior efficiency when compared to the conventional caliper-based method utilized with spectral-domain OCT devices - a time-consuming procedure for ophthalmologists. These advancements promise to expedite the diagnostic process and facilitate to rapidly recognize the stage 2 MHs from stage 3 or 4 cases. © 2023 IEEE.

关键词： Deep Learning Macular Holes OCT images

来源：评论

学校读者我要写书评

暂无评论

Analysis of Gamification and Blockchain Integration in Intelligent Learning Systems 3

Analysis of Gamification and Blockchain Integration in Intel...

引用

3rd International Conference on Creative Communication and Innovative Technology, ICCIT 2024

作者： Padeli Lukita, Chandra Fahrurroji Purnama, Suryari Rizky, Agung Fazri, Muhammad Faizal University of Raharja Department of Computer Science Tangerang Indonesia University of Catur Insan Cendekia Department of Management Cirebon Indonesia University of Bina Bangsa Department of Informatics Engineering Serang Indonesia University of Esa Unggul Department of Management Jakarta Indonesia Pandawan Sejahtera Indonesia Department of Informatics Engineering Tangerang Indonesia Bosindo Department of Business Intelligence Tangerang Indonesia

ISBN: (纸本)9798350367492

Gamification, the implementation of game mechanics in non-game settings, is the primary approach driving current advancements in education. Educational gamification has arisen as a possible way to address the issues posed by traditional learning methods, which are generally seen as incompatible with contemporary human features and behavior. Concurrently, blockchain technology has emerged as a highly popular subject and has experienced significant growth in recent years. Blockchain, which has its origins in diverse global communities and companies, serves as an infrastructure technology that is gaining prominence in several industries, such as industry and education. An inherent benefit of blockchain technology is its capacity to function autonomously, eliminating the necessity for third-party involvement and ensuring a heightened level of security, transparency, and integrity. Regrettably, the current body of research on the integration of blockchain technology in the realm of educational gamification remains scarce. Hence, this article seeks to analyze and address the primary challenges associated with education by utilizing educational gamification facilitated by the blockchain system. A mixed-methods approach was employed, involving quantitative surveys and qualitative interviews with 500 participants and 20 key informants. Findings indicate enhanced user engagement and motivation, with increased satisfaction and active participation. The study provides a first gamification model using blockchain, serving as a foundation for future research and development in this field. © 2024 IEEE.

关键词： Decentralized finance

来源：评论

学校读者我要写书评

暂无评论

A Self-matching Training Method with Annotation Embedding Models for Ontology Subsumption Prediction

arXiv

引用

arXiv 2024年

作者： Shiraishi, Yukihiro Kaneiwa, Ken Department of Computer and Network Engineering Graduate School of Informatics and Engineering The University of Electro-Communications Tokyo Japan

Recently, ontology embeddings representing entities in a low-dimensional space have been proposed for ontology completion. However, the ontology embeddings for concept subsumption prediction do not address the difficulties of similar and isolated entities and fail to extract the global information of annotation axioms from an ontology. In this paper, we propose a self-matching training method for the two ontology embedding models: Inverted-index Matrix Embedding (InME) and Co-occurrence Matrix Embedding (CoME). The two embeddings capture the global and local information in annotation axioms by means of the occurring locations of each word in a set of axioms and the co-occurrences of words in each axiom. The self-matching training method increases the robustness of the concept subsumption prediction when predicted superclasses are similar to subclasses and are isolated to other entities in an ontology. Our evaluation experiments show that the self-matching training method with InME outperforms the existing ontology embeddings for the GO and FoodOn ontologies and that the method with the concatenation of CoME and OWL2Vec* outperforms them for the HeLiS ontology. Copyright © 2024, The Authors. All rights reserved.

关键词： Ontology

来源：评论

学校读者我要写书评

暂无评论

Non-Invasive Detection System for Blood Sugar, Cholesterol, Uric Acid, and Body Temperature Using MAX30105 and MLX90614 Sensors

Non-Invasive Detection System for Blood Sugar, Cholesterol, ...

引用

2022 International Conference on computer engineering, Network and Intelligent Multimedia, CENIM 2022

作者： Fauzi, Rahmat Noor Ristiani, Nadia Saida, Nur Darmawan, Helmy Yusuf Sanubari, Agung Oktivasari, Prihatin Wardhani, Rika Novita Riandini Politeknik Negeri Jakarta Departement of Electrical Engineering Depok Indonesia Politeknik Negeri Jakarta Departement of Informatics and Computer Engineering Depok Indonesia

ISBN: (纸本)9781665476508

Currently, blood sugar, cholesterol and uric acid checks are still carried out by invasive methods. This method requires taking blood from the body using a needle, for this shortcoming we made a Blood Sugar, Cholesterol, Uric Acid, and Body Temperature Monitoring Tool using MAX30105 and MLX90614 Sensors with Non-Invasive Methods using linear regression formulas, in the test, checking blood sugar levels gets an average value of checking accuracy of 86%, checking cholesterol by 92.5%, on uric acid by 86.7%, and for measuring body temperature getting an average checking accuracy of 98.7%. Based on the testing and analysis that has been done, this tool still needs to be developed with more data collection, so that the accuracy of checking is getting better. Based on the testing and analysis that has been done, this tool still needs to be developed by taking more data, so that the checking accuracy is getting better. © 2022 IEEE.

关键词： Cholesterol

来源：评论

学校读者我要写书评

暂无评论

A Non-Iterative LMI-Based Design of Static Output Feedback Control with L2 Gain Performance for Linear Systems 6

A Non-Iterative LMI-Based Design of Static Output Feedback C...

引用

6th International Conference on Electrical, Control and Instrumentation engineering, ICECIE 2024

作者： Oya, Hidetoshi Asada, Daiki Nagai, Shunya Nakano, Kazushi Tokyo City University Department of Computer Science Tokyo Japan Graduate School of Integrative Science and Engineering Tokyo City University Tokyo Japan Niihama College Department of Electronics and Control Engineering Ehime Japan Graduate School of Informatics and Engineering The University of Electro-Communications Tokyo Japan

ISBN: (纸本)9798350380040

In this paper, we present a new LMI-based non-iterative design strategy for static output feedback controllers with L2 Gain Performance for linear systems. In our approach, on the basis of the well-known necessary and sufficient condition for the existence of the static output feedback control for linear systems, the non-iterative LMI-based design procedure for the proposed static output feedback controller is derived. In this paper, we show the LMI-based non-iterative design procedure for static output feedback controllers with L2 Gain Performance and the effectiveness of the proposed static output feedback control is presented through a simple illustrative example. © 2024 IEEE.

关键词： Feedback control

来源：评论

学校读者我要写书评

暂无评论

Wireless Infrastructure uses DSSS (Direct Sequence Spread Spectrum) Mechanism for Smart Government Concept 5

Wireless Infrastructure uses DSSS (Direct Sequence Spread Sp...

引用

5th IEEE International Conference on computer and informatics engineering, IC2IE 2022

作者： Bagus, Muhammad Yusuf Arbi, Fachroni Elisa, Rizki Hermawan, Indra Bank Indonesia Jakarta Pusat Indonesia Politeknik Negeri Jakarta Departement of Informatics and Computer Engineering Depok Indonesia

ISBN: (数字)9781665453387

ISBN: (纸本)9781665453387

The concept of Smart Government must provide technology to be able to compete in providing fast and reliable services to the community, apart from the application technology side, it must be supported by sufficient network access. Smart governments also utilize data to improve their services for the well-being of the community through citizen engagement and policy codevelopment. To achieve it, the government must provide network access so that the community easy to access application services via the internet. This research focuses on managing wireless network access using DSSS (Direct Sequence Spread Spectrum) to avoid interference and overlap modulation. Frequency and channel management is useful so that the signal output obtained by the user runs well. Use the analytics tool to make sure result quality of signal that receive by user. Concept development in this research using NDLC (Network Development Life Cycle). With good network support, the community will get easy and fast service, using a mobile phone that is connected to a wireless network. This research also checks and measures the quality of wireless networks with the combined existing network. © 2022 IEEE.

关键词： Life cycle

来源：评论

学校读者我要写书评

暂无评论

Real-time Monitoring Using AWS Cloud Platform For Agriculture Soil 1

Real-time Monitoring Using AWS Cloud Platform For Agricultur...

引用

1st IEEE International Symposium on Consumer Technology, ISCT 2024

作者： Tirtakusuma, Danar Ikram Sukaridhoto, Sritrusta Nourma Budiarti, Rizqi Putri Mulyo, Dwi Alfarezi, Fitratama Aminputra, Bima Briliandhika Hakim, Oktafian Sultan Politeknik Elektronika Negeri Surabaya Dept. of Creative Multimedia Technology Indonesia Politeknik Elektronika Negeri Surabaya Dept. of Informatics and Computer Engineering Indonesia Universitas Nahdlatul Ulama Surabaya Indonesia

ISBN: (纸本)9798350365191

In the era of modern agriculture, real-time monitoring of soil conditions is crucial for increasing productivity and efficiency. This research proposes an agricultural soil monitoring system that utilizes the AWS Cloud platform to capture, analyze, and present real-time soil data. This system is designed to integrate various sensors that can measure humidity, pH, temperature and soil nutrients, all connected via the Internet of Things (IoT). The data collected by these sensors is sent to the AWS Cloud, where it is processed using cloud computing services such as AWS Lambda and Amazon EC2. The use of the AWS Cloud enables high scalability, reliability, and data security, and facilitates big data analysis using Amazon S3 and Amazon RDS. By using an intuitive dashboard, farmers can see soil analysis results in real-time and make informed decisions based on the data. Additionally, this system is equipped with machine learning algorithms that run on the AWS Cloud to predict soil needs and provide optimal fertilizer recommendations. This research shows how implementing AWS Cloud in agriculture can bring digital transformation to agriculture, enabling farmers to increase crop yields while reducing waste and operational costs. © 2024 IEEE.

关键词： Cloud platforms

来源：评论

学校读者我要写书评

暂无评论

Optimizing Power Allocation and Beamforming in mmWave-NOMA Downlink with Deep Reinforcement Learning

Optimizing Power Allocation and Beamforming in mmWave-NOMA D...

引用

Communications and Networking (MECOM), IEEE Middle East Conference on

作者： Abbas Akbarpour Kasgari Chrysostomos Chrysostomou Department of Electrical Engineering Computer Engineering and Informatics Frederick University and Frederick Research Center Nicosia Cyprus

ISBN: (数字)9798350376715

ISBN: (纸本)9798350376722

The high demand for data rates in the fifth generation (5G) and beyond of wireless communication can be met by the Non-Orthogonal Multiple Access (NOMA) approach in the millimeter-wave (mmWave) frequency band. Joint power allocation and beamforming for 5 G and beyond mmWave-NOMA systems are essential, which can be achieved through optimization approaches. To this end, we have employed a Deep Reinforcement Learning (DRL) approach for policy generation, leading to an optimized sum-rate for users. Unlike existing methods, our approach is not susceptible to channel impulse response (CIR) estimation errors. The actor-critic framework is utilized to measure the immediate reward and provide new actions to maximize the overall Q-value of the network. The immediate reward is defined based on the summation of the rates of two users, considering the minimum guaranteed rate for each user and the total consumed power as constraints. The simulation results demonstrate the superiority of the proposed approach compared to state-of-the-art counterparts, including Time-Division Multiple Access (TDMA) and NLOS-NOMA optimization strategies, in terms of sum-rate of users, while considering both perfect and imperfect channel state information (CSI) at the receiver. This work can also be beneficial for communications in vehicular networks, particularly in applications involving Collective Perception Messages (CPMs) dissemination for autonomous driving.

关键词： Wireless communication NOMA Time division multiple access Array signal processing 5G mobile communication Deep reinforcement learning Resource management Millimeter wave communication Channel impulse response Optimization

来源：评论

学校读者我要写书评

暂无评论

PREDICTING FROM A DIFFERENT PERSPECTIVE IN RE-RANKING MODEL FOR INDUCTIVE KNOWLEDGE GRAPH COMPLETION

arXiv

引用

arXiv 2024年

作者： Iwamoto, Yuki Kaneiwa, Ken Department of Computer Network Engineering Graduate School of Informatics and Engineering The University of Electro-Communications Tokyo Japan

Rule-induction models have demonstrated great power in the inductive setting of knowledge graph completion. In this setting, the models are tested on a knowledge graph entirely composed of unseen entities. These models learn relation patterns as rules by utilizing subgraphs. Providing the same inputs with different rules leads to differences in the model’s predictions. In this paper, we focus on the behavior of such models. We propose a re-ranking-based model called ReDistLP (Re-ranking with a Distinct Model for Link Prediction). This model enhances the effectiveness of re-ranking by leveraging the difference in the predictions between the initial retriever and the re-ranker. ReDistLP outperforms the state-of-the-art methods in 2 out of 3 benchmarks. Copyright © 2024, The Authors. All rights reserved.

关键词： Knowledge graph

来源：评论

学校读者我要写书评

暂无评论

Reassessing Glove Embeddings in Deep Learning: A Comparative Study with Classical ML Approaches 15

Reassessing Glove Embeddings in Deep Learning: A Comparative...

引用

15th International Conference on Emerging Ubiquitous Systems and Pervasive Networks / 14th International Conference on Current and Future Trends of Information and Communication Technologies in Healthcare, EUSPN/ICTH 2024

作者： Labd, Zakia Bahassine, Said Housni, Khalid Aadi, Fatima Zahrae Aithamou Laboratory of research in informatics LatRI Department of Computer Science Faculty of Sciences Ibn Tofail University Kenitra Morocco Laboratory of Artificial Intelligence and Complex Systems Engineering Department of Computer Science National Higher School of Arts and Crafts Hassan II University Casablanca Morocco

The importance of text classification algorithms has increased due to the growing availability of large-scale data. This has led to a greater demand for efficient classification techniques and encoding algorithms. Word embedding techniques, like Glove, have shown significant success in encoding semantic relationships between words. This research paper aims to reassess the effectiveness of Glove embeddings coupled with deep learning algorithms. The impact of Glove embedding on two widely used deep learning models: Recurrent Neural Networks (RNN) and Recurrent Convolutional Neural Networks (RCNN) is analyzed. The results highlight the impact of Glove embeddings on deep learning models, showcasing significant performance enhancements in some cases while having minimal effects in others. By examining the impact of Glove embeddings on traditional ML algorithms in a previous study, valuable context for understanding the performance differences between the two approaches is obtained. © 2024 The Authors. Published by Elsevier B.V.

关键词： Convolutional neural networks

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：