检索结果-内蒙古大学图书馆

8th International Conference on Medical and Health Informatics, ICMHI 2024

作者： Li, Ai-Hsien Adams Aruperes, Cristian Daniel Lai, Yen-Jun Chien, Ting-Ying Chiu, Yen-Ling Chan, Chien-Lung Division of Cardiology Far Eastern Memorial Hospital New Taipei TaiwanGraduate Program in Biomedical Informatics Yuan Ze University Taoyuan Taiwan Graduate Program in Biomedical Informatics Yuan Ze University Taoyuan Taiwan TaiwanDepartment of Computer Science and Engineering Yuan Ze University Taoyuan Taiwan TaiwanInnovation Center for Big Data and Digital Convergence Yuan Ze University Taoyuan Taiwan Department of Information Management Yuan Ze University Taoyuan Taiwan Graduate Institute of Medicine and Graduate Program in Biomedical Informatics Yuan Ze University Taoyuan Taiwan TaiwanGraduate Institute of Medicine Yuan Ze University Taoyuan Taiwan TaiwanDepartment of Medical Research Far Eastern Memorial Hospital New Taipei Taiwan Department of Radiology Far Eastern Memorial Hospital New Taipei Taiwan Department of Information Management Yuan Ze University Taoyuan Taiwan

ISBN: (纸本)9798400716874

In the realm of research, the global health challenge posed by lung cancer remains pronounced, contributing substantially to annual cancer-related fatalities. The critical imperative lies in the early identification of pulmonary nodules, frequently indicative of impending lung cancer, to enhance patient outcomes and diminish mortality rates. Computed Tomography (CT) imaging stands out as a pivotal diagnostic instrument for the timely detection of these nodules. The swift proliferation of medical imaging data has underscored the pressing necessity for precise and efficient methodologies dedicated to nodule segmentation and measurement. These approaches are crucial in assisting radiologists in their diagnostic and clinical decision-making endeavors. In this study, we introduced a thorough method for analyzing lung nodules, leveraging dataset from Far Eastern Memorial Hospital (FEMH) comprising original CT images and manually annotated ground truth masks obtained with the assistance of radiologists at FEMH. This dataset is utilized for the segmentation of nodules. We employed advanced deep learning models, specifically the U-Net architecture, identified as the optimal model through our training process. We made substantial progress in nodule segmentation, attaining an Intersection over Union (IoU) score of 0.824 and a Dice Coefficient of 0.903 for the FEMH dataset. Furthermore, our performance improved when utilizing the merged dataset comprising FEMH and Luna16, yielding an IoU score of 0.862 and a Dice Coefficient of 0.926. Luna16 has been extensively utilized in numerous studies related to nodule detection and segmentation. In the next phase of the study, the best-performing model from our segmentation phase was utilized to predict nodule masks on the merged dataset. Subsequently, we measured the size of each predicted nodule by comparing it with the size ground truth mask in millimeters. In detail, this study achieved the Pearson Correlation Coefficient (PCC) at 0.

关键词： Computerized tomography

来源：评论

学校读者我要写书评

暂无评论

An energy ratio approach to the analysis of forced oscillations in power grids

An energy ratio approach to the analysis of forced oscillati...

引用

Annual North-American Power Symposium

作者： Erlan R. M. Aguirre Arturo R. Messina Graduate Studies Program in Electrical Engineering Cinvestav IPN Guadalajara Mexico

ISBN: (纸本)9781665499224

In this paper, a new framework based on non-modal stability theory to study the forced system response to harmonic excitation. Using this approach, the amplification of forced oscillation can be studied as a function of system location and excitation frequency. As a by-product, the technique enables comparing the output and the input sizes and is not limited to modal frequencies. In addition, the forcing and response modes give the dominant behavior of the forced oscillations. Applications to a two-area, four-machine test system are used to assess the applicability of the proposed framework.

关键词： Shape Power system stability Power system harmonics Harmonic analysis Power grids Stability analysis Behavioral sciences

来源：评论

学校读者我要写书评

暂无评论

SynHING: Synthetic Heterogeneous Information Network Generation for Graph Learning and Explanation

arXiv

引用

arXiv 2024年

作者： Hong, Ming-Yi Huang, Yi-Hsiang Lin, Shao-En Teng, You-Chen Wang, Chih-Yu Lin, Che Graduate Program of Data Science National Taiwan University Academia Sinica Taiwan Graduate Institute of Communication Engineering National Taiwan University Taiwan Research Center for Information Technology Innovation Academia Sinica Taiwan

Graph Neural Networks (GNNs) excel in delineating graph structures in diverse domains, including community analysis and recommendation systems. As the interpretation of GNNs becomes increasingly important, the demand for robust baselines and expansive graph datasets is accentuated, particularly in the context of Heterogeneous Information Networks (HIN). Addressing this, we introduce SynHING, a novel framework for Synthetic Heterogeneous Information Network Generation aimed at enhancing graph learning and explanation. SynHING systematically identifies major motifs in a target HIN and employs a bottom-up generation process with intra-cluster and inter-cluster merge modules. This process, supplemented by post-pruning techniques, ensures the synthetic HIN closely mirrors the original graph’s structural and statistical properties. Crucially, SynHING provides ground-truth motifs for evaluating GNN explainer models, setting a new standard for explainable, synthetic HIN generation and contributing to the advancement of interpretable machine learning in complex networks. Copyright © 2024, The Authors. All rights reserved.

关键词： Graph neural networks

来源：评论

学校读者我要写书评

暂无评论

Adaptive Virtual Synchronous Machine Applied to Four-Leg Three-Phase VSC

Adaptive Virtual Synchronous Machine Applied to Four-Leg Thr...

引用

2021 IEEE Southern Power Electronics Conference, SPEC 2021

作者： Marin-Hurtado, A.J. Escobar-Mejia, A. Alzate-Gomez, A. Gil-Gonzalez, W. Universidad Tecnológica de Pereira Electrical Engineering Graduate and Undergraduate Program Pereira Colombia Institución Universitaria Pascual Bravo Electrical Engineering Program Medellín Colombia

ISBN: (纸本)9781665436236

Nowadays, the power distribution grid is dominated by single-phase loads that produce unbalance currents, which cause stability problems and large frequency deviations in power systems. The Virtual Synchronous Machine (VSM) method has been proposed for renewable energy sources to reproduce the static and dynamic properties of the traditional synchronous generator, injecting/absorbing active/reactive power to/from the grid. However, the implementation and design of a VSM are not straightforward tasks, especially in an unbalanced network. Because it is necessary to compute and adjust the required inertia and damping parameters during unbalanced currents. Therefore, this paper proposes an adaptive inertia control scheme for a Four-Leg Three-Phase Voltage Source Converter (4LVSC), using the VSM approach, to improve a four-wire power system stability and compensate unbalanced currents. The proposed adaptive inertia comprises a Proportional-Integral (PI), and a Linear Quadratic Regulator (LQR) controller, which uses an optimization problem to minimize the power change and frequency droop when unbalances are presented in a power system. Time-domain simulations have been carried out on a unbalance four-wire power system considering active power variations to evaluate both the power and frequency responses using both controllers. Results show that the LQR-VSM controller presents lower frequency oscillations when compared to the VSM with constant inertia approach. © 2021 IEEE.

关键词： Frequency response

来源：评论

学校读者我要写书评

暂无评论

A novel label-free electrochemical immunosensor for the detection of heat shock protein 70 of lung adenocarcinoma cell line following paclitaxel treatment using l-cysteine-functionalized Au@MnO2/MoO3 nanocomposites

引用

RSC Advances 2023年第43期13卷 29847-29861页

作者： Chen, Yi-An Shie, Ming-You Ho, Chia-Che Ye, Sheng-Wen Chen, I.-Wen Peter Shih, Yu-Yin Shen, Yu-Fang Chen, Yi-Wen x-Dimension Center for Medical Research and Translation China Medical University Hospital Taichung City404332 Taiwan The Master Program for Biomedical Engineering China Medical University Taichung City406040 Taiwan Department of Biomedical Engineering China Medical University Taichung City40447 Taiwan Department of Bioinformatics and Medical Engineering Asia University Taichung City41354 Taiwan Department of Chemistry National Cheng Kung University Tainan70101 Taiwan Graduate Institute of Biomedical Sciences China Medical University Taichung City40447 Taiwan

The future trend in achieving precision medicine involves the development of non-invasive cancer biomarker sensors that offer high accuracy, low cost, and time-saving benefits for risk clarification, early detection, disease detection, and therapeutic monitoring. A facile approach for the synthesis of MoO3 nanosheets was developed by thermally oxidizing MoS2 nanosheets in air followed by thermal annealing. Subsequently, Au@MnO2 nanocomposites were prepared using a combined hydrothermal process and in situ chemical synthesis. In this study, we present a novel immunosensor design strategy involving the immobilization of antiHSP70 antibodies on Au@MnO2/MoO3 nanocomposites modified on a screen-printed electrode (SPE) using EDC/NHS chemistry. This study establishes HSP70 as a potential biomarker for monitoring therapeutic response during anticancer therapy. Impedance measurements of HSP70 on the Au@MnO2/MoO3/SPE immunosensor using EIS showed an increase in impedance with an increase in HSP70 concentration. The electrochemical immunosensor demonstrated a good linear response in the range of 0.001 to 1000 ng mL−1 with a detection limit of 0.17 pg mL−1 under optimal conditions. Moreover, the immunosensor was effective in detecting HSP70 at low concentrations in a lung adenocarcinoma cell line following Paclitaxel treatment, indicating its potential for early detection of the HSP70 biomarker in organ-on-a-chip and clinical applications. © 2023 The Royal Society of Chemistry.

关键词： Nanosheets

来源：评论

学校读者我要写书评

暂无评论

Thermodynamic and Environmental Assessment of Low-GWP Alternative Refrigerants for Domestic Cooling

引用

Journal of The Institution of Engineers (India): Series C 2023年第2期104卷 377-383页

作者： Islam, Md. Amirul Rupam, Tahmid Hasan Hosan, Shahadat Saha, Bidyut Baran Institute for Materials Chemistry and Engineering Kyushu University Kasuga-Koen 6-1 Kasuga-Shi Fukuoka816-8580 Japan Department of Electrical and Electronics Engineering Bangabandhu Sheikh Mujibur Rahman Science and Technology University Gopalganj8100 Bangladesh Kyushu University 744 Motooka Nishi-Ku Fukuoka819-0395 Japan Kyushu University Program for Leading Graduate School Green Asia Education Center Kyushu University Fukuoka Japan Department of Mechanical Engineering Kyushu University 744 Motooka Nishi-Ku Fukuoka819-0395 Japan

Nearly two billion air-conditioning (AC) units are currently being used for space cooling worldwide. The majority of these ACs use R134a as the working fluid, a greenhouse gas (GHG) with a global warming potential (GWP) of 1300 kg-CO2-eq. According to the rules set by the world environment safety organizations, the GWP of domestic air-conditioning systems must not exceed 750 kg-CO2-eq. Hence, the R134a must be phased out by 2025, and an alternative refrigerant with similar thermodynamic properties yet low GWP is required. Therefore, the authors have investigated several potential binary/ternary refrigerant blends in this study. Among the studied refrigerants, R445A, R30A, and NPB2 (newly proposed blend: 8% R152a + 92% R1234yf) can reduce 90–99% global warming impact (more than 200 million tonnes of CO2 emission equivalent) caused by the domestic air-conditioning systems every year. © 2023, The Institution of Engineers (India).

关键词： Refrigerants

来源：评论

学校读者我要写书评

暂无评论

The Deep Learning Approach For American Sign Language Detection

The Deep Learning Approach For American Sign Language Detect...

引用

2022 IEEE Creative Communication and Innovative Technology, ICCIT 2022

作者： Pangestu, Gusti Heryadi, Yaya Lukas Suparta, Wayan Arifin, Yulyani Bina Nusantara University School of Computer Science Computer Science Department Binus Graduate Program Computer Science Computer Science Department Jakarta Indonesia Bina Nusantara University Binus Graduate Program Computer Science Computer Science Department Jakarta11480 Indonesia Faculty of Engineering Jakarta12930 Indonesia Institut Teknologi Nasional Yogyakarta Faculty of Industrial Technology Department of Electrical Engineering Yogyakarta55281 Indonesia

ISBN: (纸本)9781665468763

Sign language has importance rule to deal with communication process especially with impairments hearing people. Sign language detection also attract lot of researchers to join the challenge of research to detect and recognize the sign language in the field of Computer Science. Hence, there is still no any standard approach and method to recognize the meaning in every pose of sign language. This research proposed a mechanism to detect Alphabet American Sign Language by utilizing Convolutional Neural Network (CNN) process. The CNN approach was chosen based on the ability and capability to recognize image. In this research, MNIST dataset is used for traning and testing process. The proposed CNN architecture produced 97% of accuracy that outperform the previous research using the same dataset which made this architecture promising. © 2022 IEEE.

关键词： Convolutional neural networks

来源：评论

学校读者我要写书评

暂无评论

Decomposition and Reorganization of Phonetic Information for Speaker Embedding Learning

引用

IEEE/ACM Transactions on Audio Speech and Language Processing 2023年 31卷 1745-1757页

作者： Hong, Qian-Bei Wu, Chung-Hsien Wang, Hsin-Min National Cheng Kung University and Academia Sinica Graduate Program of Multimedia Systems and Intelligent Computing Tainan701 Taiwan Academia Sinica Taipei115 Taiwan National Cheng Kung University Department of Computer Science and Information Engineering Tainan701401 Taiwan Academia Sinica Institute of Information Science Taipei115 Taiwan

Speech content is closely related to the stability of speaker embeddings in speaker verification tasks. In this paper, we propose a novel architecture based on self-constraint learning (SCL) and reconstruction task (RT) to remove the influence of phonetic information on speaker embedding generation. First, SCL is used to reduce the divergence of frame-level features, which can avoid ambiguity between the resulting embeddings of the two utterances being compared. Second, RT is used to further remove phonetic information in frame-level layers, focusing on speaker-discriminative feature transformation. In our experiments, the speaker embedding models were trained on the VoxCeleb2 dataset and evaluated on the VoxCeleb1, Librispeech, SITW and VoxMovies datasets. Experimental results on VoxCeleb1 show that the proposed DROP-TDNN system reduced the EER by 7.5%, compared to the state-of-the-art ECAPA-TDNN system. Furthermore, the proposed DROP-TDNN system also outperformed the ECAPA-TDNN system in the experiments on SITW, Librispeech and VoxMovies under cross-dataset conditions. In the experiments on SITW, the proposed system reduced the EER by 3.4% compared to the ECAPA-TDNN system. In the experiments on Librispeech, the proposed system demonstrated the advantage of removing phonetic information under the clean speech condition, with a significant reduction of 25.5% in EER compared to the ECAPA-TDNN system. In the experiments on VoxMovies, the proposed system reduced the EER by up to 7.9% compared to the ECAPA-TDNN system under different pronunciation and background conditions. © 2014 IEEE.

关键词： Speech recognition

来源：评论

学校读者我要写书评

暂无评论

Analysis of the Brazilian Climate Data Influence on Soybean Pricing by Using Long Short-Term Memory Models

SSRN

引用

SSRN 2024年

作者： Oliva, Jefferson Tales Martelli, Otávio Pigozzo de Castro Barbosa, Marco Antônio Dal Molin, Viviane Casanova, Dalcimar Teixeira, Marcelo Graduate Program in Electrical and Computer Engineering Federal University of Technology-Paraná PR Pato Branco85503-390 Brazil Department of Academic Informatics Federal University of Technology-Paraná PR Pato Branco85503-390 Brazil Graduate Program in Production and Systems Engineering Federal University of Technology-Paraná PR Pato Branco85503-390 Brazil

This work uses machine learning to verify whether the Brazilian climate influences international soybean price prediction. For this, climatic data, dollar quotes, inflation, and annual soybean production were collected from different data sources. Then, the collected data were pre-processed and grouped by Brazilian state. Afterward, data from the five most productive Brazilian states are chosen, such as Mato Grosso (MT), Mato Grosso do Sul (MS), Goiás (GO), Paraná (PR), and Rio Grande do Sul (RS). Afterward, predictive models are built using the long short-term memory (LSTM) method, which is applied in each chosen state dataset considering two different settings: with and without climatic data. Thus, two models were built for each Brazilian state, totaling ten predictors. In the experimental evaluation, when trained with climatic data, the PR model achieved the lowest values of root mean squared error (RMSE) and mean absolute error (MAE). Regarding predictors trained without climate data, the RS and PR obtained the lowest values of RMSE and MAE, respectively. After conducting statistical hypothesis tests, no significant difference was found among models, stating, with 95% certainty, that, in this study, the Brazilian climatic data did not influence the model performance for predicting soybean prices. On the other hand, one of the main contributions of work is conducting an unprecedented study about soybean price prediction using Brazilian climatic data. © 2024, The Authors. All rights reserved.

关键词： Long short-term memory

来源：评论

学校读者我要写书评

暂无评论

Microencapsulation of bioactive compound extracts using maltodextrin and gum arabic by spray and freeze-drying techniques

引用

International Journal of Biological Macromolecules 2023年第Part4期253卷 126969页

作者： Laureanti, Emanuele Joana Gbur Paiva, Thainnane Silva de Matos Jorge, Luiz Mário Jorge, Regina Maria Matos Graduate Program in Chemical Engineering Department of Chemical Engineering Federal University of Paraná Coronel Francisco Heráclito dos Santos Avenue Curitiba81531-980 Brazil Graduate Program in Food Engineering Department of Chemical Engineering Federal University of Paraná Coronel Francisco Heráclito dos Santos Avenue Curitiba81531-980 Brazil Colombo Avenue 5790 CEP MaringáPR87020-900 Brazil

Microencapsulation techniques establish a protective barrier around a sensitive compound, reducing vulnerability to external influences and offering controlled release. This work evaluates microencapsulation of Brazilian seed known as pink pepper (Schinus terebinthifolius) extract incorporated with green propolis extract, (main propolis font from the South America native plant Baccharis dracunculifolia DC) to enhancement antioxidant activity through synergic interaction, comparing to the extracts individually. Four treatments were produced using maltodextrin and combined with gum arabic as encapsulating agent, employing two different microencapsulation technique applied (spray drying and freeze drying) to assess their impact on physicochemical properties. The incorporation of gum arabic into matrix yielded higher encapsulation efficiency values, exhibiting significant differences for both encapsulation techniques. Combining the two encapsulation agents afforded greater protection of the bioactive compounds, resulting in an increase of approximately 31 % in the inhibition of the DPPH● radical. In controlled release analysis, maltodextrin exhibits the best protective effect on total phenolic compounds during intestinal release, whereas combining maltodextrin and gum arabic enhanced protection during gastric phase. Microcapsules may contribute to the protection of important bioactive compound, possessing a wide range of applications such as flavors encapsulation in food industry, lipids, antioxidants and pharmaceutical industry for controlled drug release. © 2023 Elsevier B.V.

关键词： Microencapsulation

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：