检索结果-内蒙古大学图书馆

2023 International Conference on informatics, Multimedia, Cyber and Information Systems, ICIMCIS 2023

作者： Dhuhita, Windha Mega Pradnya Farid, Muhammad Farhan Al Yaqin, Ainul Haryoko, Haryoko Huda, Arif Akbarul Universitas Amikom Yogyakarta Informatics Yogyakarta Indonesia Universitas Amikom Yogyakarta Informatics Engineering Yogyakarta Indonesia Universitas Amikom Yogyakarta Information Technology Yogyakarta Indonesia

ISBN: (纸本)9798350307306

Gold, a highly valued precious metal, has significant intrinsic value in contemporary society. Therefore, more and more people are embarking on precious metal investments known as gold. Individuals who wish to invest in gold should be vigilant in monitoring the fluctuations in this precious metal's buying and selling prices. Yahoo Finance is a leading online platform that can be used as a reliable reference for monitoring the fluctuations in gold's buying and selling prices. These factors mainly include changes in the closing price, opening price, highest value, and lowest value of *** observed phenomenon shows that gold prices exhibit high volatility, mainly due to frequent and repeated fluctuations. The LSTM (Long Short-Term Memory) technique, coupled with applying hyperparameter optimization through grid search, enables accurate gold price prediction using historical gold price data. This result is achieved after the grid search procedure, where the lowest error result is 0.00033, generated by the LSTM parameter unit of 200 with a dropout of 0.1. © 2023 IEEE.

关键词： Forecasting

来源：评论

学校读者我要写书评

暂无评论

Analysis of Distribution Transformers at Various Insulating Conditions by Frequency Method 8

Analysis of Distribution Transformers at Various Insulating ...

引用

8th International Symposium on Multidisciplinary Studies and Innovative Technologies, ISMSIT 2024

作者： Gutten, Miroslav Korenciak, Daniel Kanuch, Jan University of Zilina Faculty of Electrical Engineering and Information Technology Zilina Slovakia Technical University of Kosice Faculty of Electrical Engineering and Informatics Slovakia

ISBN: (纸本)9798350354423

The study examines the insulation properties of various power transformers using method of frequency dielectric spectroscopy (FDS). It compares different transformers at the same indoor temperature and analyzes how temperature affects insulation properties. Compared to other methods of diagnosing the insulation system of high-voltage equipment, method FDS allows for separate assessment of quality and specific conductivity in oil and moisture content in the transformer solid insulation. Using capacity measurements via method FDS to determine condition of insulation system has the advantage of being less temperature-dependent compared to the dissipation factor method. However, a drawback of the capacity method is that it is influenced by the insulation geometric arrangement, which varies based on the power transformer type and performance. Given this limitation, when comparing frequency-dependent capacities to assess insulation condition, it is advisable to compare machines of the same construction and power rating. © 2024 IEEE.

关键词： Distribution transformers

来源：评论

学校读者我要写书评

暂无评论

Acoustic Emission Analysis of Dry Distribution Transformers 8

Acoustic Emission Analysis of Dry Distribution Transformers

引用

8th International Symposium on Multidisciplinary Studies and Innovative Technologies, ISMSIT 2024

作者： Korenciak, Daniel Gutten, Miroslav Kanuch, Jan University of Zilina Faculty of Electrical Engineering and Information Technology Zilina Slovakia Technical University of Kosice Faculty of Electrical Engineering and Informatics Slovakia

ISBN: (纸本)9798350354423

This article primarily discusses the acoustic emission analysis method and its application in the contactless diagnostics of distribution transformers with resin dry insulation. Initially, the article outlines a measurement technique used to compare the acoustic emissions of two machines of the same type and power during their operation. A parabolic camera was employed to pinpoint the source of increased noise in the exposed transformer. This approach enables the analysis of the frequency spectrum, allowing for 3D observation of the transformer and identification of the highest noise levels and acoustic emissions. The latter part of the article details the methods for measuring and evaluating the instability and magnitude of acoustic emissions in dry transformers under laboratory conditions. The measurements were conducted using a noise measuring device equipped with a three-octave spectral filter, covering a frequency range of 100 to 10 000 Hz. © 2024 IEEE.

关键词： Distribution transformers

来源：评论

学校读者我要写书评

暂无评论

A STUDY ON THE FORMATION PROCESS OF PUBLIC HOUSING COMPLEXES WITH SELF-FUNDED EXTENSIONS AND RENOVATIONS IN OMUTA MUNICIPAL HOUSING

引用

AIJ Journal of technology and Design 2024年第75期30卷 927-932页

作者： Tetsuharu, Oki Yoshiki, Nishikawa Tetsu, Masaki Mizue, Hayashi Yohei, Sadohara Division of Architecture Faculty of Science and Technology Graduate School of Engineering Oita Univ Japan Social Informatics Laboratorie Nippon Telegraph and Telephone Corporation M. Media Design Japan Social Informatics Laboratories Nippon Telegraph and Telephone Corporation Japan National Institute of Technology Ariake College M. Human-Environment Japan National Institute of Technology Ariake College Dr. Human-Environment Japan

In order to obtain suggestions regarding planning methods that do not involve too much planning, this study investigated the actual conditions of public housing in Omuta City, where voluntary additions to public housing were actively conducted. The results showed that it is important to clearly indicate in advance which spaces are to be occupied, and to leave it to the ingenuity of the residents. © 2024 Architectural Institute of Japan. All rights reserved.

关键词： Extension and renovation Grounded housing complexes Municipal housing Public housing Spatial rearrangements

来源：评论

学校读者我要写书评

暂无评论

Web-Based Mental Health Predicting System Using K-Nearest Neighbors and XGBoost Algorithms 8th

Web-Based Mental Health Predicting System Using K-Nearest Ne...

引用

8th International Visual informatics Conference, IVIC 2023

作者： Zulkefli, Nurul Farhanaa Diah, Norizan Mat Ismail, Azlan Hanum, Haslizatul Fairuz Mohamed Ibrahim, Zaidah Arif, Yunifa Miftachul School of Computing Sciences College of Computing Informatics and Mathematics Universiti Teknologi MARA Shah Alam Malaysia Informatics Engineering Faculty of Science and Technology Universitas Islam Negeri Maulana Malik Ibrahim Malang Indonesia

ISBN: (纸本)9789819973385

Problems with mental health are common presently and have been a worry for a long time. Mental health problems, like anxiety, depression, and panic attacks, can be caused by numerous things. Therefore, recognising the start of mental disease is becoming increasingly crucial to maintaining a good life balance. This study uses machine learning to identify any possible mental health disorders in an individual to attain this goal. The investigation employed supervised machine learning to predict mental health status, namely K-Nearest Neighbors (KNN) and XGBoost, with performance evaluation criteria including accuracy, precision, recall, and F1 score. When these two algorithms were compared, it was discovered that XGBoost produced a more effective prediction model, which was then employed to develop a web-based mental health prediction system. The web-based method creates a questionnaire for mental health issues. Based on the user’s responses to the questions, the system will predict his or her mental health status as normal, depression, anxiety, stress, loneliness, or regularity. Every component of the system, including buttons and forms, has been successfully tested using functionality tests. Moreover, the system’s advantages, weaknesses, and future study directions are identified. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Nearest neighbor search

来源：评论

学校读者我要写书评

暂无评论

Enhancing Intent Detection Through ChatGPT-Driven Data Augmentation 5th

Enhancing Intent Detection Through ChatGPT-Driven Data Augme...

引用

5th Doctoral Symposium on Computational Intelligence, DoSCI 2024

作者： Tesfagergish, Senait Gebremichael Damasevicius, Robertas Kapociute-Dzikiene, Jurgita Department of Software Engineering Kaunas University of Technology Kaunas Lithuania Department of Applied Informatics Vytautas Magnus University Kaunas Lithuania

ISBN: (纸本)9789819771776

This study investigates the improvement of intent detection tasks, focusing on the Facebook Multilingual Task Oriented Dataset, which encompasses 12 classes, including specific intents like weather and alarms. To address the scarcity of datasets in the Amharic language for intent detection, we first translated the English dataset into Amharic using Google Translator. Additionally, we expanded the dataset to include Lithuanian, German, French, and Czech languages. Next, we balance the dataset through data augmentation using ChatGPT, particularly targeting the four least-covered classes by adding 50 sentences to each. For text vectorization, the language-agnostic BERT sentence embedding model was used for its multilingual capabilities and Amharic language support. The classification was based on Cosine similarity, incorporating a majority voting mechanism from the most similar training instances. We conducted multilingual experiments to evaluate the performance of intent detection across various languages, both before and after data augmentation. Our findings highlight the effectiveness of using ChatGPT for data augmentation in intent detection tasks across all investigated languages, particularly in enhancing underrepresented languages and specific intents. We achieved improvement in intent detection performance for minority classes. This shows the benefit of using ChatGPT with imbalanced datasets for multilingual tasks and applications. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Translation (languages)

来源：评论

学校读者我要写书评

暂无评论

Feature analysis and selection for BGP anomaly detection 28

Feature analysis and selection for BGP anomaly detection

引用

28th Conference on Innovation in Clouds, Internet and Networks, ICIN 2025

作者： Hakimi, Rifqy Reed, Martin J. School of Computer Science and Electronic Engineering University of Essex Colchester United Kingdom School of Electrical Engineering and Informatics Bandung Institute of Technology Bandung Indonesia

ISBN: (纸本)9798331542399

Automated incidence reporting requires accurate and timely anomaly detection. This paper considers this in the context of the Border Gateway Protocol (BGP). BGP is crucial for Internet routing but is vulnerable to attacks due to a lack of widespread authentication. While rare, BGP disruptions can be highly detrimental to Internet performance and security. Detecting BGP anomalies helps network operators protect their networks and improve Internet reliability. In this work, we investigate and develop anomaly detection for BGP using Machine-Learning. We extract relevant features of BGP control plane messages from RIPE RIS and RouteViews public datasets. After extracting features, we employ various feature selection algorithms to extract the most relevant features and explore balancing the datasets. Finally, we explore detection latency, an important operating parameter for automated anomaly detection. The results show that BGP anomalies can be detected in the order of seven minutes when using real attack data and that the observation point for the BGP data has a significant effect on anomaly detection. © 2025 IEEE.

关键词： Adversarial machine learning

来源：评论

学校读者我要写书评

暂无评论

Applying CNN to Classify Gender for Identity Verification System 9

Applying CNN to Classify Gender for Identity Verification Sy...

引用

9th International Conference on Wireless and Telematics, ICWT 2023

作者： Rashida, Amadea Gunardi, Christopher Ivan Hendrawan Mulyana, Eueung Hermawan, Wawan School of Electrical Engineering and Informatics Bandung Institute of Technology Telecommunication Engineering Bandung Indonesia School of Electrical Engineering and Informatics Bandung Institute of Technology Bandung Indonesia Data and Information Center National Research and Innovation Agency Bandung Indonesia

ISBN: (纸本)9798350305029

Computers have difficulty recognizing and distinguishing between faces, especially when it comes to gender and age. Gender is important for emotional recognition and security reasons and can help identify individuals who look alike. This research proposes a binary gender recognition system that consists of two stages: face detection and gender classification. The face detection component is compared to three models: Python face recognition library, SSD MobileNet, and EfficientNet. The gender classification component uses two models: custom CNN and VGG Face models. Based on this research, the final prototype is accessible via a web application and is capable of performing image-based face detection and processing each known face to determine its gender (male or female). The face identification model yields varying results, with the EfficientNet model outperforming the others after the model is deployed. The VGG Face model also performs well, with an average accuracy of 99% for faces taken under optimal settings (training and testing datasets) as well as for specific images collected outside of the dataset. However, for masked faces and captures at low brightness levels, it still results in less accurate detection and classification for several types of images. © 2023 IEEE.

关键词： Face recognition

来源：评论

学校读者我要写书评

暂无评论

Semantic Segmentation of Sentinel-2 Satellite Image for Rice Growth Phase Classification Using Deep Learning

Semantic Segmentation of Sentinel-2 Satellite Image for Rice...

引用

2024 IEEE International Conference on Imaging Systems and Techniques, IST 2024

作者： Mubarok, Moh. Jabir Yuniarno, Eko Mulyanto Sihombing, Yogie Oktavianus Purnomo, Mauridhi Hery Institut Teknologi Sepuluh Nopember Faculty of Intelligent Electrical and Informatics Technology Department of Electrical Engineering Surabaya60111 Indonesia

ISBN: (纸本)9798350378214

Sentinel-2 satellite image is one of the big data for remote sensing. This research explores the usage of U-Net model for segmentation of rice fields and CNN Model for classification of rice growth phase on SentineL-2 L2A satellite image. This study investigates the use of the U-net method for segmentation. Rice growth phases are classified using CNN model. The results show that CNN model can work better for various computer vision tasks, including preprocessing of existing satellite data for rice growth phases. For the suggested semantic segmentation model, the accuracy and IoU score values for the proposed semantic segmentation model were 0.99 and 0.66, respectively. Conversely, the suggested CNN classification model for rice growth phase, the accuracy was 0.86, while specificity was 0.97 and sensitivity was 0.85. The goal of this research is to establish the viability of such a system and to pave the way for future research including rice field extraction and rice growth phase classification using satellite imagery. The segmentation and classification model has shown excellent performance. However, the model still struggles to accurately identify the correct pixels belonging to a specific mask for segmentation or correctly recognize the right class for a specific group of area based on the spectral indices, as evidenced by a few samples in the results. © 2024 IEEE.

关键词： Semantic Segmentation

来源：评论

学校读者我要写书评

暂无评论

Concept and Pictogram-Based User-Interface Design of a Helper Tool for People with Aphasia

引用

Studies in Health technology and informatics 2023年 301卷 77-82页

作者： Mayer, Peter Werner, Katharina Al-Radhi, Mohammed Csapo, Tamas Gabor Czeba, Bálint Nemeth, Géza Rocha, Ana Patrícia Oliveira, Ilídio C. Silva, Samuel Szeker, Melinda Teixeira, António Panek, Paul Applied Assistive Technologies Group HCI Group TU Wien Vienna Austria Department of Telecommunications and Media Informatics Budapest University of Technology and Economics Budapest Hungary EvoAId Kft. Budapest Hungary Institute of Electronics and Informatics Engineering of Aveiro Department of Electronics Telecommunications and Informatics Intelligent Systems Associate Laboratory University of Aveiro Aveiro Portugal Aphasie Association Budapest Hungary

ISBN: (纸本)9781643683867

Background: Aphasia describes the lack of the already gained ability to use language in a common way. "Language" here covers all variations of forming or understanding messages. Objectives: The APH-Alarm project aims to develop a service concept that provides alternative communication options for people with Aphasia to trigger timely help when needed. It considers that a typical user may not be familiar with modern technologies and offers several simple and intuitive options. Methods: The approach is based on event detection of gestures (during daytime or in bed), movement pattern recognition in bed, and an easy-to-use pictogram-based smartphone app. Results: Agile evaluation of the smartphone app showed a promising outcome. Conclusion: The idea of a versatile and comprehensive solution for aphasic people to easily contact private or public helpers based on their actions or automatic detection is promising and will be further investigated in an upcoming field trial. © 2023 The authors, AIT Austrian Institute of technology and IOS Press.

关键词： Pattern 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：