检索结果-内蒙古大学图书馆

2nd IEEE International Conference on Trends in Quantum Computing and Emerging Business Technologies, TQCEBT 2024

作者： Sundaram, Aishwarya Subramaniam, Hema Ab Hamid, Siti Hafizah Nor, Azmawaty Mohamad Universiti Malaya Institute for Advanced Studies Kuala Lumpur Malaysia Universiti Malaya Faculty of Computer Science and Information Technology Department of Software Engineering Kuala Lumpur Malaysia Universiti Malaya Faculty of Education Department of Educational Psychology and Counselling Kuala Lumpur Malaysia

ISBN: (纸本)9798350384277

Social media is a crucial aspect of modern society, shaping global communication and information exchange. Social media slang encompasses informal language expressions, abbreviations, and unconventional words on these platforms, serving purposes such as concise communication and identity establishment. Data analytics from social media slang plays a vital role in providing real-time trends, enhancing sentiment analysis, and improving the accuracy of predictive models by capturing evolving linguistic trends. This study aims to address gaps in existing social media slang analytics by proposing a three-step process for extracting and validating domain-specific social media slang terms, specifically focusing on the domain of anxiety prediction in the context of mental health. The proposed approach involves the identification of relevant users, extraction of social media slang terms, and validation by subject matter experts. A pilot study is conducted in the domain of anxiety prediction, employing a self-prepared questionnaire and involving participants aged 13-14 from schools in Selangor, Malaysia. The pilot study identifies ten social media slang terms associated with anxiety, validated by subject matter experts who are licensed mental health practitioners. The slang terms exhibit varying prevalence levels among adolescents, with some terms absent from popular slang dictionaries like Urban Dictionary. The findings highlight the need for extracting slang terms from pertinent users and subject matter expert validation in incorporating social media slang into more appropriate predictive analytics. © 2024 IEEE.

关键词： Data Analytics

来源：评论

学校读者我要写书评

暂无评论

Development of Dementia Care Training System Using AR and Large Language Model

Development of Dementia Care Training System Using AR and La...

引用

IEEE International Conference on Systems, Man and Cybernetics

作者： Tomoya Miyawaki Yuuki Nishiura Ryouta Fukuda Kazuto Nakashima Ryo Kurazume Graduate School of Information Science and Electrical Engineering Kyushu University Japan Department of Electrical Engineering and Computer Science Faculty of Engineering Kyushu University Japan Faculty of Information Science and Electrical Engineering Kyushu University Japan

ISBN: (数字)9781665410205

ISBN: (纸本)9781665410212

We have developed HEARTS, a dementia care training system using augmented reality based on Humanitude. Humanitude is a multimodal comprehensive care technique for dementia, and has attracted attention as a method to reduce the burden on both caregivers and patients. However, the HEARTS developed so far could not evaluate “speaking” skills based on the content of conversations among “seeing,” “touching,” and “speaking,” all of which are fundamental skills in Humanitude. Therefore, we attempted a new quantitative evaluation of trainees' “speaking” skills by estimating the emotional value of conversational content using GPT-4 named HEARTS 5. A survey of caregivers was conducted using the developed system and was well received by the participants. We also developed a HEARTS 5 conversational version based on HEARTS 5, with the addition of GPT-4 conversation generation and Azure Text-to-Speech.

关键词： Heart Training Surveys Large language models Oral communication Text to speech Robots Cybernetics Augmented reality Dementia

来源：评论

学校读者我要写书评

暂无评论

Performing Aerobatic Maneuver with Imitation Learning 23rd

Performing Aerobatic Maneuver with Imitation Learning

引用

23rd International Conference on Computational science, ICCS 2023

作者： Freitas, Henrique Camacho, Rui Silva, Daniel Castro Department of Informatics Engineering Faculty of Engineering University of Porto Rua Dr. Roberto Frias s/n. Porto4200-465 Portugal LIAAD/INESC TEC - Artificial Intelligence and Decision Support Laboratory/Institute for Systems and Computer Engineering Technology and Science Porto Portugal LIACC - Artificial Intelligence and Computer Science Laboratory Porto Portugal

ISBN: (纸本)9783031359941

The work reported in this article addresses the challenge of building models for non-trivial aerobatic aircraft maneuvers in an automated fashion. It is built using a Behavioural Cloning approach where human pilots provide a set of example maneuvers used by a Machine Learning algorithm to induce a control model for each maneuver. The best examples for each maneuver were selected using a set of objective evaluation metrics. Using those example sets, robust models were induced that could replicate (and in some cases outperform) the human pilots that provided the examples (the clean-up effect). Complete complex maneuvers were performed using a meta-controller capable of sequencing the basic ones learned by imitation. This endeavor was rewarded by the results that show several Machine Learning models capable of performing highly complex aircraft maneuvers. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Cloning

来源：评论

学校读者我要写书评

暂无评论

Automating the Diagnosis of Cucumber Plant Diseases Using Machine Learning 25

Automating the Diagnosis of Cucumber Plant Diseases Using Ma...

引用

25th International Arab Conference on Information Technology, ACIT 2024

作者： Banimustafa, Ahmed Qattouz, Hazem Almatarneh, Sattam Mansour, Khalid Alazaidah, Raed Bulkrock, Olla Higher Colleges of Technology Computer Information Science Dept Abu Dhabi United Arab Emirates Princess Sumaya University for Technology Software Engineering Dept Amman Jordan Zarqa University Data Science & Artificial Intelligence Dept Zarqa Jordan University of Business and Technology College of Engineering Jeddah Saudi Arabia Arab-Open University Bahrain Faculty of Computer Studies Bahrain

ISBN: (纸本)9798331540012

Farmers all over the world struggle to fight plant diseases. However, the incorrect use of pesticides can waste time, effort, and money and can also be very harmful to the environment and human health. In this work, we present an empirical study that involves identifying two pathogens related to Cucumbers plant diseases: Powdery Mildew and Alternaria Cucumerina. The study aims to develop a computer-based solution based on deep learning and machine learning algorithms to detect these diseases. To achieve this, a dataset of hundreds of samples was collected from ordinary farms in Beqaa, an agricultural region 15 KM north of Amman, Jordan. Three machine learning models were created in this study using Support Vector Machines (SVM), Logistic Regression (LR), and Multi-layer perceptron algorithms. The constructed models were applied to the dataset after embedding the dataset images using the Convolutional Neural Networks (CNN) InceptionV3 pre-trained model. The model was tested and evaluated using cross-evaluation and F1-Score, CA, AUC, Precision, Recall, and Specificity, which all showed excellent results, particularly using the SVM algorithm. The constructed methods are intended to be deployed to farms in their field condition environments using a CCTV system that can capture images of plants during growth, which can help identify plant diseases at that right stage, which would save time, effort, and money and reduce the impact of wrong and overuse of pesticides on consumers and the environment. © 2024 IEEE.

关键词： Convolutional neural networks

来源：评论

学校读者我要写书评

暂无评论

Different Devices Behavior in Fingerprinting Indoor Positioning for Mobile Robot in Healthcare Industries 4

Different Devices Behavior in Fingerprinting Indoor Position...

引用

4th IEEE Global Conference on Life sciences and Technologies, LifeTech 2022

作者： Ahmad Sa'ahiry, Ahmad Hakimi Ismail, Abdul Halim Bin Kamaruddin, Latifah Munirah Toyoura, Masahiro Universiti Malaysia Perlis Faculty of Electrical Engineering Technology Perlis Malaysia University of Yamanashi Department of Computer Science and Engineering Yamanashi Japan

ISBN: (纸本)9781665419048

In the recent light of the 4th Industrial Revolution particularly in medical industries, the use of medical robot is an adaptable alternative to reduce the burden in medical services. A mobile robot is normally developed and embedded with numerous sensors especially for its indoor positioning system. This matter has hindered the use of such robots as it increases the development cost. One solution is to employ the readily available sensors such as Wi-Fi. Wi-Fi is widely deployed, and it does not have additional hardware to configure unlike Bluetooth. Despite the potential of Wi-Fi, some adjustment needs to be executed to provide a better accuracy. The Wi-Fi signal has their own disadvantage such as the multipath and shadowing effect making it stand-alone unreliable. Hence, the fingerprinting technique is proposed to solve this issue. The fingerprinting technique mainly used one device in collecting the fingerprinting database. Nonetheless, if the device is broken or new software needed to deploy, the device needs to be substituted. The contribution of this paper is to investigate the behavior of different devices in the fingerprinting method and evaluate the positioning result. © 2022 IEEE.

关键词： Mobile robots

来源：评论

学校读者我要写书评

暂无评论

Security Governance in IOT Environment: A State of Art 6

Security Governance in IOT Environment: A State of Art

引用

6th IEEE International Conference on Cloud Computing and Artificial Intelligence: Technologies and Applications, CloudTech 2023

作者： Mokhtari, Ilyass El Outmani, Ayyoub Jaara, El Miloud Mohammed First University Computer Science Research Laboratory Faculty of Sciences Oujda Morocco High Studies of Engineering School Ehei High Studies of Engineering School Ehei Research Center Oujda Morocco

ISBN: (纸本)9798350303063

With the increase in utilization of the internet of things (IOT) in information systems (IS), providing appropriate lever and type of governance in environment and security control in the same environment has become the new challenge limiting the adoption of this new paradigm. The aim of this paper is to compare the latest models of IOT's governance frameworks applicable for this type of environment such as: CobiT, ITIL and ISO 2700X. This paper aims at identifying the strengths and weaknesses of each model and proposing a list of evaluation criteria to be used while using IOT and to solve the problem of security by adopting a better governance. © 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

Waste-to-Energy: Reviewing Gasification of Municipal Solid Waste

Waste-to-Energy: Reviewing Gasification of Municipal Solid W...

引用

2023 International Conference on Power Energy, Environment and Intelligent Control, PEEIC 2023

作者： Aravindan, M.K. Kantak, Ganesh Kumar Wadhwa, Bhawna Faculty of Engineering and Technology Department of Mechanical Engineeing Bangalore India Vivekananda Global University Department of Mechanical Engineering Jaipur India Noida Institute of Engineering & Technology Department of Computer Science Uttar Pradesh Greater Noida India

ISBN: (纸本)9798350357769

In the context of growing population and industrialization, depleting fossil fuels and inadequate waste management provide major difficulties that call for the investigation of novel waste-to-energy sources. A viable approach involves converting municipal solid waste-which is expected to exceed 2.6 billion metric tons by 2030-into fuels generated from garbage. Gaseous fuels like hydrogen and syngas are produced via gasification, a chemical process that is triggered by heat. We examine practices in different countries, new developments in gasification technology, gasification modeling, or economic assessments as we dig into the fuel produced by refuse gasification in this study. According to the assessment, replacing coal with fuel produced from trash may reduce CO2 emissions by 40% and the quantity of municipal rubbish that is dumped in landfills by more than 50% in certain nations. Gasification of refuse-derived fuel is expected to provide energy at a cost of around 0.05 USD/kWh. In addition, co-gasification-which uses two feedstocks-shows to be more beneficial than traditional gasification, with less tar production and improved process efficiency. © 2023 IEEE.

关键词： Co-Gasification CO2 Emission and Industrial Ecosystem Gasification Hydrogen Municipal Solid Waste Refuse-Derived Fuel Waste-To-Energy

来源：评论

学校读者我要写书评

暂无评论

Keyphrase Extraction Using Pre-Trained Language Models BERT and Topic-Guided Graph Attention Networks

Keyphrase Extraction Using Pre-Trained Language Models BERT ...

引用

Data science and Its Applications (ICoDSA), International Conference on

作者： Novi Yusliani Siti Nurmaini Firdaus Firdaus Aini Nabilah Annisa Darmawahyuni Abdiansah Abdiansah Faculty Engineering Universitas Sriwijaya Palembang South Sumatera Informatic Engineering Faculty of Computer Science Universitas Sriwijaya Palembang South Sumatera Intelligent System Research Group Faculty of Computer Science Universitas Sriwijaya Palembang South Sumatera

ISBN: (数字)9798350365351

ISBN: (纸本)9798350365368

Keyphrase extraction aims to extract a set of keyphrases from the input document that highly summarizes the document. One of the issue in keyphrase extraction is how to extract representative keyphrases that is relevance and describe the information in the document. This study addresses pretrained language model (PLM) and topic-guided graph attention network (TgGAT) to extract a set of keyphrases from the input document. PLM can effectively capture knowledge from massive data and well perform on both language understanding and language generation tasks. BERT is one of PLM that designed to process bidirectionally, allowing BERT to understand word context based on the surrounding words. To enhance the keyphrase relevance, latent-dirichlet allocation used to learn the latent topic information and aiding the semantic understanding of the input document. For capturing semantic relationships between phrases in document based on their topics, this study used TgGAT. TgGAT models the anchoraware graph which organizes the initial anchor phrases. Experiment was conducted on a dataset containing 100 Indonesian accredited scientific article, Sinta 2 and Sinta 3, to evaluate the system“ $s$ performance. The experimental results show a precision value of 0.058, a recall value of 0.070, and an F1-score of 0.062 for the five generated keywords across the entire tested dataset. Further in-depth analyses shows that pattern of phrases used has the important role in determining the representative phrases in input document.

关键词： Semantics Bidirectional control Network architecture Data science Encoding Data models Data mining

来源：评论

学校读者我要写书评

暂无评论

Modeling of Gapless MOSA at Low Current Region Considering Harmonic Content of Operating Voltage

引用

Journal of The Institution of Engineers (India): Series B 2021年第3期102卷 521-530页

作者： Khodsuz, Masume Seyyedbarzegar, Seyyedmeysam Faculty of Electrical and Computer Engineering University of Science and Technology of Mazandaran BehsharMazandaran Iran Faculty of Electrical Engineering Shahrood University of Technology ShahroodSemnan Iran

A surge arrester is modeled as a simplified electrical circuit in power frequency applied voltage that consists of a capacitance branch in parallel with a nonlinear resistor. Under applied harmonic voltage, the obtained resistive current of the simplified model exhibits some deficiency, especially in its harmonic contents. This paper presents a harmonic model for metal-oxide surge arresters that can be utilized to simulate their performances under applied harmonic voltage. It has three parallel RC branches to simulate fundamental, third and fifth harmonics contents of total leakage current. Proposed and conventional models have been simulated under different applied harmonic voltages to show the capability of the proposed model. Also, real voltage and leakage current signals, which have been measured experimentally from a 20 kV metal-oxide surge arrester, have been compared with simulation results. Results show that the proposed model can simulate the performance of metal-oxide surge arresters more accurately than the conventional ones under applied harmonic voltages. © 2021, The Institution of Engineers (India).

关键词： Capacitance

来源：评论

学校读者我要写书评

暂无评论

Research on long and short-term social recommendation based on convolutional and gated recurrent units 29

Research on long and short-term social recommendation based ...

引用

29th IEEE International Conference on Parallel and Distributed Systems, ICPADS 2023

作者： Jia, Zihe Xue, Peng Dai, Zhiqiang Gao, Qian Zhang, Xiaomeng Key Laboratory of Computing Power Network and Information Security Ministry of Education Shandong Computer Science Center Jinan250014 China Shandong Engineering Research Center of Big Data Applied Technology Faculty of Computer Science and Technology Jinan250353 China Shandong Fundamental Research Center for Computer Science Shandong Provincial Key Laboratory of Computer Networks Jinan250014 China

ISBN: (纸本)9798350330717

The development of the Internet has made people more closely related and has put forward higher requirements for recommendation models. Most recommendation models are studied only for the long-term interests of users. In this paper, the interaction time between the user and the item is introduced as auxiliary information in the model construction. Interaction time is used to determine users' long-term preferences and short-term preferences. In this paper, temporal features are extracted by building a convolutional gated recurrent unit with attention neural network (CNN-GRU-Attention). Firstly, for the problem of accurate feature extraction, CNN are constructed to extract higher-level and more abstract features of themselves and transform high-dimensional data into low-dimensional data;secondly, for the problem of social temporality, GRU are used to not only extract temporal information, but also effectively reduce gradient dispersion, making model convergence and training easier;finally, Graph Attention networks are used to aggregate the social relationship information of users and items respectively, which constitute the final feature representation of users and items respectively. In particular, a modified cosine similarity is used to reduce the error caused by data insensitivity when constructing the social information of the item. In this study, simulation experiments are conducted on two publicly available datasets (Epinions and Ciao), and the experimental results show that the proposed recommended model performs better than other social recommendation models, improving the evaluation metrics of MAE and RMSE by 1.06%-1.33% and 1.19%-1.37%, respectively. The effectiveness of the model innovation is proved. © 2023 IEEE.

关键词： convolutional gated recurrent unit graph attention networks neighborhood recommendation systems social 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：