检索结果-内蒙古大学图书馆

Bifunctional Supercapacitor and Photocatalytic Properties of Cuboid Ni-TMA MOF Synthesized Using a Facile Hydrothermal Approach

引用

Journal of Electronic Materials 2024年第1期53卷 16-29页

作者： Narwade, Vijaykiran N. Rahane, Ganesh K. Bogle, Kashinath A. Tsai, Meng-Lin Rondiya, Sachin R. Shirsat, Mahendra D. RUSA Centre for Advanced Sensor Technology Dr. Babasaheb Ambedkar Marathwada University Maharashtra Aurangabad431 004 India Department of Materials Engineering Indian Institute of Science Bangalore560 012 India School of Physical Sciences Swami Ramanand Teerth Marathwada University Maharashtra Nanded431 606 India Department of Materials Science and Engineering National Taiwan University of Science and Technology Taipei10607 Taiwan Department of Nuclear Physics and Biophysics Faculty of Mathematics Physics and Informatics Comenius University Bratislava842 48 Slovakia

Metal–organic frameworks (MOFs) with a substantial surface area and configurable porosity have gained the interest of researchers in energy storage devices and environmental management. Our investigation efficaciously employs a cuboid-shaped nickel and trimesic acid metal–organic framework (Ni-TMA MOF) as a bifunctional high-performance supercapacitor electrode as well as an efficient photocatalyst. The Ni-cuboid-like MOF's structure provides more electroactive sites along with a shorter pathway for electron transfer and electrolyte diffusion, resulting in a high specific capacitance of 236 F g−1 at 1 A g−1. The fabricated electrode exhibits particularly high capacitance retention, with over 98% retention even after 1000 cycles. The photocatalytic activity of the Ni-TMA MOF for the degradation of rhodamine 6G dye was investigated, which revealed that 90% of the dye was degraded in nearly 40 min, which follows the modified Freundlich process. The development of multifunctional materials to address emerging problems is of paramount importance, and this work ensures this possibility, with results showing improved energy storage and photocatalytic capability. Graphical Abstract: [Figure not available: see fulltext.] © 2023, The Minerals, Metals & Materials Society.

关键词： Supercapacitor

来源：评论

学校读者我要写书评

暂无评论

Lightning Statistics in Hungary between 2002 and 2022 37

Lightning Statistics in Hungary between 2002 and 2022

引用

37th International Conference on Lightning Protection, ICLP 2024

作者： Tóth, Zoltán Simon, Csilla Department of Electric Power Engineering Faculty of Electrical Engineering and Informatics Budapest University of Technology and Economics Budapest Hungary Institute of Digital Health Science Faculty of Public Services Semmelweis University Budapest Hungary Department of Meteorology Faculty of Science Eötvös Loránd University Budapest Hungary

ISBN: (纸本)9783800764174

Climate change is universally acknowledged as a global phenomenon with the potential to alter local climates significantly. However, contrary to the commonly perceived uniform warming and drying trend, local climates exhibit diverse changes. This article aims to explore the specific regional climatic shifts that have occurred in Hungary over the past 20 years. Utilising data from the Hungarian Meteorological Service, we employed both qualitative and quantitative methods to dissect the changes experienced across different Hungarian regions. Our findings reveal a complex tapestry of climatic alterations, with some areas undergoing transformations that defy the expectation of increased warmth and aridity. The study provides a detailed account of these regional changes, offering insights into the varied manifestations of climate change locally. Furthermore, it discusses the potential future scenarios for the climate of Hungary, laying a foundation for region-specific adaptation strategies. This article contributes to the broader understanding of how global climate dynamics can lead to a spectrum of local changes, some of which may be counterintuitive to prevailing climate change narratives. © 2024 IEEE, © VDE VERLAG GMBH ∙ Berlin ∙ Offenbach.

关键词： Miocene

来源：评论

学校读者我要写书评

暂无评论

Improving Recommendation Quality in Collaborative Filtering by Including Prediction Confidence Factors 20

Improving Recommendation Quality in Collaborative Filtering ...

引用

20th International Conference on Web Information Systems and Technologies, WEBIST 2024

作者： Sgardelis, Kiriakos Margaris, Dionisis Spiliotopoulos, Dimitris Vassilakis, Costas Ougiaroglou, Stefanos Department of Digital Systems University of the Peloponnese Sparta Greece Department of Management Science and Technology University of the Peloponnese Tripoli Greece Department of Informatics and Telecommunications University of the Peloponnese Tripoli Greece Department of Information and Electronic Engineering International Hellenic University Thessaloniki Greece

ISBN: (纸本)9789897587184

Collaborative filtering is a prevalent recommender system technique which generates rating predictions based on the rating values given by the users' near neighbours. Consequently, for each user, the items scoring the highest prediction values are recommended to them. Unfortunately, predictions inherently entail errors, which, in the case of recommender systems, manifest as unsuccessful recommendations. However, along with each rating prediction value, prediction confidence factors can be computed. As a result, items having low prediction confidence factor values, can be either declined for recommendation or have their recommendation priority demoted. In the former case, some users may receive fewer recommended items or even none, especially when using a sparse dataset. In this paper, we present an algorithm that determines the items to be recommended by considering both the rating prediction values and confidence factors of predictions, allowing for predictions with higher confidence factors to outrank predictions with higher value, but lower confidence. The presented algorithm achieves to enhance the recommendation quality, while at the same time retaining the number of recommendations for each user. Copyright © 2024 by SCITEPRESS.

关键词： Collaborative filtering

来源：评论

学校读者我要写书评

暂无评论

IoT Service Composition - An Estimation of Distribution Algorithm with Adaptive Bias

IoT Service Composition - An Estimation of Distribution Algo...

引用

2023 IEEE Congress on Evolutionary Computation, CEC 2023

作者： Sun, Fengyang Ma, Hui Chen, Gang Hartmann, Sven School of Engineering and Computer Science Victoria University of Wellington Wellington6012 New Zealand Clausthal University of Technology Department of Informatics Clausthal-Zellerfeld38678 Germany

ISBN: (纸本)9798350314588

Service composition in Internet of Things (SCIoT), as an emerging topic in service computing, aims to select optimal services to complete user requests according to various user requirements such as minimizing energy consumption and response time. To solve this NP-hard problem, numerous heuristic methods, e.g., local search and population-based algorithms, have been proposed, wherein Estimation of Distribution Algorithm (EDA) gains increasing attention because of its explicit global probabilistic nature. However, existing EDAs increase solution diversity by using fixed bias, yet interfere the stability of the learned distribution in the later stage of optimization. Therefore, this paper proposes an EDA with an adaptive bias strategy (EDA-AdaBias) to solve the service composition in IoT problem. The decreasing bias value is added onto the probability values for all choices of each solution variable over generations, which improves diversity of sampled solutions and avoids dramatic change of constructed distribution. Experiments indicate that EDA-AdaBias presents promising performance compared to other competitive methods on this problem. © 2023 IEEE.

关键词： Heuristic methods

来源：评论

学校读者我要写书评

暂无评论

Blockchain-Based Secure and Efficient Secret Image Sharing With Outsourcing Computation in Wireless Networks

引用

IEEE Transactions on Wireless Communications 2024年第1期23卷 423-435页

作者： Zhou, Zhili Wan, Yao Cui, Qi Yu, Keping Mumtaz, Shahid Yang, Ching-Nung Guizani, Mohsen Institute of Artificial Intelligence and Blockchain Guangzhou University Guangzhou510006 China Engineering Research Center of Digital Forensics Ministry of Education Nanjing University of Information Science and Technology Nanjing210044 China Graduate School of Science and Engineering Hosei University Tokyo184-8584 Japan RIKEN Center for Advanced Intelligence Project RIKEN Tokyo103-0027 Japan Department of Applied Informatics Silesian University of Technology Gliwice44-100 Poland Department of Engineering Nottingham Trent University NottinghamNG1 4FQ United Kingdom Department of Computer Science and Information Engineering National Dong Hwa University Hualien97401 Taiwan Abu Dhabi United Arab Emirates

Secret Image Sharing (SIS) is the technology that shares any given secret image by generating and distributing n shadow images in the way that any subset of k shadow images can restore the secret image. However, in the existing SIS schemes, the shadow images will be easily tampered and corrupted during the communication, which will pose serious security issues. Recently, blockchain has emerged as a promising paradigm in the field of data communication and information security. To securely communicate and effectively protect the secret image data in wireless networks, we propose a Blockchain-based Secure and Efficient Secret Image Sharing (BC-SESIS) scheme with outsourcing computation in wireless networks. In the proposed BC-SESIS scheme, the shadow images are encrypted and stored in the blockchain to prevent them from being tampered and corrupted. The identity authentication-enabled smart contract is deployed to achieve the (k,n) threshold for secret image restoring. Furthermore, to reduce the computational burden of smart contract and users, an efficient outsourcing computation method is designed to outsource the restoring task, which is securely implemented by agent miners in the encryption domain. Theoretical analysis and extensive experiments demonstrate that the BC-SESIS scheme can achieve desirable communication security and high computational efficiency in the wireless networks. © 2023 IEEE.

关键词： Smart contract

来源：评论

学校读者我要写书评

暂无评论

Ancient Character Recognition: A Novel Image Dataset of Shui Manuscript Characters and Classification Model

引用

Chinese Journal of Electronics 2023年第1期32卷 64-75页

作者： TANG Minli XIE Shaomin LIU Xiangrong Department of Computer Science and Technology School of Informatics Xiamen University School of Big Data Engineering KaiLi University Key Laboratory of Digital Protection and Intelligent Processing of Intangible Cultural Heritage of Fujian and Taiwan Ministry of Culture and Tourism Xiamen University

Shui manuscripts are part of the national intangible cultural heritage of China. Owing to the particularity of text reading, the level of informatization and intelligence in the protection of Shui manuscript culture is not adequate. To address this issue, this study created Shuishu＿C, the largest image dataset of Shui manuscript characters that has been reported. Furthermore, after extensive experimental validation, we proposed ShuiNet-A,a lightweight artificial neural network model based on the attention mechanism, which combines channel and spatial dimensions to extract key features and finally recognize Shui manuscript characters. The effectiveness and stability of ShuiNet-A were verified through multiple sets of experiments. Our results showed that, on the Shui manuscript dataset with 113 categories, the accuracy of ShuiN et-A was 99.8%, which is 1.5% higher than those of similar studies. The proposed model could contribute to the classification accuracy and protection of ancient Shui manuscript characters.

关键词： Training Speech recognition Artificial neural networks Feature extraction Stability analysis Character recognition Machine translation

来源：评论

学校读者我要写书评

暂无评论

Comparative Study of Machine Learning and Holt-Winters Exponential Smoothing Models for Prediction of CPI's Seasonal Data 2

Comparative Study of Machine Learning and Holt-Winters Expon...

引用

2nd International Conference on Software engineering and Information technology, ICoSEIT 2024

作者： Afrah, Ashri Shabrina Sari, Nur Fitriyah Ayu Tunjung Utama, Shoffin Nahwa Holle, Khadijah Fahmi Hayati Lestandy, Merinda Sintiya, Endah Septa Rizdania Universitas Islam Negeri Maulana Malik Ibrahim Malang Department of Informatics Engineering Malang Indonesia Universitas Muhammadiyah Malang Department of Electrical Engineering Malang Indonesia State Polytechnic of Malang Information Technology Department Malang Indonesia University of Pgri Wiranegara Computer Science Department Pasuruan Indonesia

ISBN: (纸本)9798350317503

Inflation is one of the factors influencing price stability. Inflation affects people's purchasing power and impacts their decisions as economic actors. Consumer Price Index (CPI) is one of the factors used by economists to measure the inflation or deflation in a country. This research focuses on comparing the prediction results of the CPI for the Education Goods and Services using the Holt's Winters Exponential Smoothing and Machine Learning Methods, namely Long Short-Term Memory (LSTM), Extreme Learning Machine (ELM), Ridge, and Least Absolute Shrinkage and Selection Operator (LASSO). The data used is univariate data on the CPI for the Education Goods and Services in Malang City in 1996-2013, which was obtained from the publication of the Statistics Indonesia (BPS), entitled 'Malang City in Figures' which was published in 1997-2014. The results of this research show that the Ridge Method produces the smallest Mean Absolute Percentage Error (MAPE) value compared to other Machine Learning Methods and the Multiplicative Holt-Winters Exponential Smoothing Method, with MAPE= 2.10723%%. Machine Learning models that have been simulated have very good accuracy values, with MAPE values © 2024 IEEE.

关键词： Forecasting

来源：评论

学校读者我要写书评

暂无评论

Bayesian estimation of trunk-leg coordination during walking using phase oscillator models

引用

Neuroscience Research 2025年 215卷 47-55页

作者： Furukawa, Haruma Arai, Takahiro Funato, Tetsuro Aoi, Shinya Aoyagi, Toshio Graduate School of Informatics Kyoto University Yoshida-Honmachi Kyoto Sakyo-ku 606-8501 Japan Japan Agency for Marine-Earth Science and Technology 3173-25 Showa-cho Kanazawa-ku Kanagawa Yokohama-shi 236-0001 Japan Department of Mechanical Engineering and Intelligent Systems Graduate School of Informatics and Engineering The University of Electro-Communications 1-5-1 Choufugaoka Tokyo Choufu 182-8585 Japan Department of Mechanical Science and Bioengineering Graduate School of Engineering Science The University of Osaka 1-3 Machikaneyama Osaka Toyonaka 560-8531 Japan

In human walking, the legs and other body parts coordinate to produce a rhythm with appropriate phase relationships. From the point of view for rehabilitating gait disorders, such as Parkinson Disorders, it is important to understand the control mechanism of the gait rhythm. A previous study showed that the antiphase relationship of the two legs during walking is not strictly controlled using the reduction of the motion of the legs during walking to coupled phase oscillators. However, the control mechanisms other than those of the legs remains unknown. In particular, the trunk moves in tandem with the legs and must play an important role in stabilizing walking because it is above the legs and accounts for more than half of the mass of the human body. This study aims to uncover the control mechanism of the leg-trunk coordination in the sagittal plane using the coupled phase oscillators model and Bayesian estimation. We demonstrate that the leg-trunk coordination is not strictly controlled, as well as the interleg coordination. © 2024 The Authors

关键词： Coupled phase oscillators Human walking Leg-trunk coordination Synchronization

来源：评论

学校读者我要写书评

暂无评论

Deciphering the Geometric Bonferroni Mean Operator in Pythagorean Neutrosophic Sets Framework

引用

Neutrosophic Sets and Systems 2025年 75卷 139-161页

作者： Kamari, Mohammad Shafiq Bin Mohammad Rodzi, Zahari Bin Md. Al-Obaidi, R.H. Al-Sharqi, Faisal Al-Quran, Ashraf Shlaka, Rawan A. College of Computing Informatics and Mathematics Studies MARA University of Technology Negeri Sembilan Branch Seremban Campus Negeri Sembilan Seremban70300 Malaysia Faculty of Science and Technology National University of Malaysia Selangor Bandar Baru Bangi43600 Malaysia Fuel and Energy Techniques Engineering Department College of Engineering and Technologies AI-mustaqbal University Babylon51001 Iraq Department of Mathematics Faculty of Education for Pure Sciences University of Anbar Anbar Ramadi Iraq Department of Basic Sciences Preparatory Year King Faisal University Al-Ahsa31982 Saudi Arabia College of Pharmacy National University of Science and Technology Dhi Qar Iraq

The Geometric Bonferroni Mean (GBM), is an extension of The Bonferroni mean (BM), that combines both BM and the geometric mean, allowing for the representation of correlations among the combined factors while acknowledging the inherent uncertainty within the decision-making process. Within the framework of Pythagorean neutrosophic set (PNS) that encompasses truth, indeterminacy, and falsity-membership degrees, each criterion can be integrated into a unified PNS value, portraying the overall evaluation of that criterion by employing the Geometric Bonferroni mean. This study aims to enhance decision-making in Pythagorean neutrosophic framework by introducing an aggregation operator to PNS using the Geometric Bonferroni Mean. Additionally, it proposes a normalized approach to resolve decision-making quandaries within the realm of PNS, striving for improved solutions. The novel Pythagorean Neutrosophic Normalized Weighted Geometric Bonferroni Mean (PNNWGBM) aggregating operator has been tested in a case of multi-criteria decision-making (MCDM) problem involving the selection of Halal products suppliers with several criteria. The result shows that this aggregating operator is offering dependable and pragmatic method for intricate decision-making challenges and able to effectively tackle uncertainty and ambiguity in MCDM problem. © 2025, University of New Mexico. All rights reserved.

关键词： Mathematical operators

来源：评论

学校读者我要写书评

暂无评论

Forecasting the Probability of Monthly Cloud Occurrence Over Eastern Java Using Deep Learning and Remote Sensing Data 9th

Forecasting the Probability of Monthly Cloud Occurrence Over...

引用

9th International Conference on Computer science and Computational Intelligence, ICCSCI 2024

作者： Hadiyanto, Ahmad Luthfi Wikantika, Ketut Prihatmanto, Ary Setijadi Trilaksono, Nurjanna Joko Candra, Danang Surya Research Center for Geoinformatics National Research and Innovation Agency Bogor Regency Indonesia Department of Geodesy and Geomatics Engineering Bandung Institute of Technology Bandung Indonesia School of Electrical Engineering and Informatics Bandung Institute of Technology Bandung Indonesia Atmospheric Science Research Group Bandung Institute of Technology Bandung Indonesia

Cloud forecast information is important in many applications like solar power planning, optical satellite acquisition, and weather study. The Numerical Weather Prediction (NWP) model is a powerful tool to predict future cloud occurrences. However, the model needs hardware resources with high performance and capacity to result in high spatial resolution. The complexity of the forecasting model can be reduced by using a data-driven method (machine learning or deep learning) instead of the NWP model. On the other hand, remote sensing data is a good source of data for making predictions over large areas. The current forecasting model, which utilizes remote sensing data and data-driven methods, results in very short-term forecasting because the model relies on cloud development. This research introduces the use of parameters from the ground surface and low atmosphere to create a longer-term forecasting model. The method combines statistical methods on temporal data and spatial interpolation to estimate the values of surface parameters under clouds. Moreover, data reconstruction is implemented in the basic Convolutional Neural Network (CNN) architecture. The model uses temporal data of aggregated-interpolated spectral values from Himawari-8 satellite data, which relate to the process of cloud formation. The model results in monthly forecasting, simulating cloud occurrence probability from February to July 2020 with a good accuracy of less than 10% Normalized RMSE (NRMSE). © 2024 The Authors.

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：