检索结果-内蒙古大学图书馆

Investigating the effect of different anisotropic surface roughening methods on ionic polymer metal composites behavior

引用

Journal of Computational and Applied Research in Mechanical engineering 2023年第1期13卷 113-121页

作者： Mosaddeghi, A. Soleimanimehr, H. Ziazi, A. Alinia Department of Mechanics Electrical Power and Computer Science and Research Branch Islamic Azad University Tehran Iran

As the smart materials, ionic polymer-metal composites (IPMCs), have a layered structure consisting of a polymeric membrane based on perfluorinated alkene, which is sandwiched between two noble metal-based electrodes, such as gold and platinum, and they can be bent significantly under applying a low-range of voltage. IPMCs are used in many applications, such as robotics, biomechanics, and medical purposes. In order to improve the performance of IPMC, in this article, three different anisotropic surface roughening methods with new and optimized fabrication instructions are used, and samples are compared. The experiments are applied to measure three main factors of IPMCs: displacement, blocking force, and lifetime. The results obtained from plasma samples show that the maximum displacement is 36.23 mm, the blocking force is 4.08 etching, 18 percent higher lifetime than micro sandblasting, and sandpaper under applying a voltage range between 1-7 V;as a result, the plasma etched IPMC sample has the most efficiency. © 2023 The author(s).

关键词： Precious metals

来源：评论

学校读者我要写书评

暂无评论

Data Driven Air Quality Analysis and Predictions: A Machine Learning Approach 2

Data Driven Air Quality Analysis and Predictions: A Machine ...

引用

2nd International Conference on Power, electrical, Electronics and Industrial Applications, PEEIACON 2024

作者： Ahad, Abdul Alam, Ajmain Mahtab North South University Department of Electrical and Computer Engineering Dhaka Bangladesh

ISBN: (纸本)9798331517984

Air is one of the natural elements of the world. Due to the growth of civilization and industries the air around us has become more polluted. So, predicting the air quality has become a necessary step. By predicting the air quality beforehand, we can take the necessary steps to make the place and the people aware. Machine learning algorithms can help to detect air quality using air pollutants elements. Many research has been done in this field so there are datasets that are available which we can use to predict the air quality. Accurate air quality forecasts can enable timely interventions and raise public awareness. In this study, we utilize machine learning algorithms to predict air quality based on air pollutant PM2.5 from 2016 to 2023. We employed five machine learning models: K-Nearest Neighbors (KNN) Classifier, Random Forest, Gaussian Naïve Bayes, Support Vector Machine (SVM), and Logistic Regression. Our findings indicate that KNN classifier performed the best among the models. This provides valuable insights into the effectiveness of different machine learning approaches for air quality prediction. © 2024 IEEE.

关键词： Random forests

来源：评论

学校读者我要写书评

暂无评论

An In-Depth Review of Machine Learning, Blockchain, and Deep Learning Models for Intelligent Security and Resilience Enhancement in Smart Cities

An In-Depth Review of Machine Learning, Blockchain, and Deep...

引用

2024 International Conference on Artificial Intelligence and Quantum Computation-Based Sensor Applications, ICAIQSA 2024

作者： Lanjewar, Umesh Khekare, Ganesh Wahi, Amitabh Bhagwant University Department of Computer Science & Engineering Ajmer India School of Computer Science & Engineering Vellore Institute of Technology Vellore India

ISBN: (纸本)9798331517953

A smart city is a fast-moving terrain that requires efficient and smart security mechanisms with resilience for solving the intricate challenges of modern urbanism. The current paper presents the critical review of machine learning, blockchain, and deep learning models in strengthening security and making the urban environment at smart cities more resilient. Not all the review articles heretofore successfully integrated these three pivotal domains, which lowered their practical applicability and insight depth. This paper reviews recent state-of-the-art models, including supervised and unsupervised machine learning algorithms, blockchain frameworks, and deep advanced learning architectures. The important machine learning models reviewed include Random Forest, Support Vector Machines, and K-means clustering. These were chosen for their already proved effectiveness in anomaly detection, predictive analytics, and classification tasks. On the other hand, blockchain models of Ethereum and Hyperledger Fabric would be evaluated for decentralized security features, immutability, and capability to improve data integrity and transparency. Deep learning models can handle large-scaled, unstructured data and extract complex patterns. Their integration, therefore, shows great promise in enhancing the security and resilience of smart cities. This paper contributes to a holistic, multidisciplinary viewpoint, filling literature gaps by providing a basic framework for further research and implementation of smart city initiatives. Such insights synthesized across these domains set a course for innovation in the formulation of solutions that fortify urban infrastructures against emerging threats and enhance overall urban resilience. (Abstract) © 2024 IEEE.

关键词： Adversarial machine learning

来源：评论

学校读者我要写书评

暂无评论

Daily Life Conversation in Bangla Sign Language Using Machine Learning Technique 6

Daily Life Conversation in Bangla Sign Language Using Machin...

引用

6th IEEE Eurasia Conference on Biomedical engineering, Healthcare and Sustainability, ECBIOS 2024

作者： Shakil, Mirza Md Amin, Al Anam, Tahmid Hussein, Molla Rashied Alam, Tahira Chowdhury, Jamim Hossain University of Asia Pacific Department of Computer Science and Engineering Dhaka Bangladesh University of Skill Enrichment & Technology Department of Computer Science and Engineering Narayanganj Bangladesh

ISBN: (纸本)9798350396133

Sign language is a way of communicating and interacting for access to information. Currently, deaf and mute people rely heavily on sign language to communicate. It enables the challenged person to interact with a hearing-enabled person to express themselves and participate in all facets of life. In these circumstances, research is needed in the area of sign language recognition as limited work has been conducted. Also, as it varies from region to region and in the context of BangIa sign language, related research is more mandated. The dataset in this study consisted of 9,000 video data. Alongside this, Artificial Neural Networks (ANN) and Long Short-Term Memory (LSTM) were used to establish a two-way communication system. LSTM is used for long-term dependencies and sequence predictions. To gather video data and extract characteristics from the video frames, MediaPipe and OpenCV were employed. Fine-tuning techniques, such as the number of hidden layers, the density of layers, the number of neurons within each layer, the learning rate, the optimizer, and other parameters were used to determine the optimal accuracy. The results showed that 96% of the categories were accurately represented by scikit-Iearn. This result offers a reference for employing deep learning structures for the detection of BangIa sign language and the development of dependable assistive technology tailored to the necessity of the hearing-impaired community. © 2024 IEEE.

关键词： Gesture recognition

来源：评论

学校读者我要写书评

暂无评论

Path Authentication for Multiple Switches within First Communication Packets 6

Path Authentication for Multiple Switches within First Commu...

引用

6th IEEE Novel Intelligent and Leading Emerging sciences Conference, NILES 2024

作者： Anna, Koziol Agata Shen, Shan-Hsiang Shen, Chung-An Huang, Chin-Ya National Taiwan University of Science and Technology Department of Computer Science and Information Engineering Taiwan National Taiwan University of Science and Technology Department of Electronic and Computer Engineering Taiwan

ISBN: (纸本)9798350378511

This paper introduces a new approach to switch authentication within a network environment, addressing the challenges associated with multiple switch configurations. The proposed continuous authentication process is seamlessly integrated into the TCP handshake, leveraging public-private key encryption and challenge-based authentication methodologies. This novel solution aims to improve performance of traditional one-to-one authentication methods, both in terms of efficiency and security. The research demonstrates the efficiency gains achieved by the proposed authentication process through a comparative analysis with one-to-one solution based on the same authentication mechanism. The results reveal a significant reduction in authentication time, thanks to link latency reduction. The incorporation of public-private key encryption enhances the security, ensuring protection against unauthorized access and switch spoofing attempts. © 2024 IEEE.

关键词： Authentication Protocol

来源：评论

学校读者我要写书评

暂无评论

On Improving Solar Forecasts with Enhanced IR Imaging and CNNs 26

On Improving Solar Forecasts with Enhanced IR Imaging and CN...

引用

26th Irish Machine Vision and Image Processing Conference, IMVIP 2024

作者： Nijhum, Ifran Rahman Hossain, Md Yearat Rakib, Md Mahbub Hasan Dev, Soumyabrata The ADAPT SFI Research Centre Ireland School of Computer Science University College Dublin Ireland Department of Electrical and Computer Engineering North South University Bangladesh

ISBN: (纸本)9781837242672

Renewable energy such as solar power has been widely adopted lately due to its sustainability and cost-effectiveness. However, due to the intermittent nature of photovoltaic systems, accurate solar forecasting is vital for efficient integration into the grid. In this paper, we propose a novel framework for effective solar irradiance estimation from infrared sky images. The proposed method utilizes contrast-limited adaptive Histogram Equalization (CLAHE) and OpenCV colormaps for pre-processing low-contrast and low-resolution infrared sky images. Additionally, it introduces an Inception module-based CNN-Regression model to get rich feature information and avoid feature loss. We perform a detailed comprehensive study to evaluate the effectiveness of the proposed method. While the baseline CNN regression model (without enhancement and Inception module) achieves an RMSE of 81.30 W/m2, employing the proposed technique reduces the loss to an impressive 47.85 W/m2. With a novel approach to address the existing issues of infrared sky images, the research advances the field of solar power estimation and forecasting for seamless integration into grids and residential settings. © This is an open access article published by the IET under the Creative Commons Attribution License (http://***/licenses/by/3.0/)

关键词： Solar irradiance

来源：评论

学校读者我要写书评

暂无评论

Uncertainty Assessment of Stochastic EM Problems via an Adaptive Anisotropic Polynomial-Chaos Technique

引用

Progress In Electromagnetics Research B 2022年 97卷 55-71页

作者： Salis, Christos I. Kantartzis, Nikolaos V. Zygiridis, Theodoros T. Department of Electrical and Computer Engineering University of Western Macedonia Kozani Greece Department of Electrical and Computer Engineering Aristotle Univ. of Thessaloniki Thessaloniki Greece

A novel polynomial-chaos (PC) technique is implemented based on anisotropic index sets. The proposed scheme takes advantage of the effect of each random variable on the output parameter of interest and adaptively constructs the PC expansion. Particularly, the algorithm starts by generating bases via low and high reliability heuristics and builds a PC representation, until an error criterion is satisfied or until the maximum desired polynomial order is reached. Our method is tested on a variety of uncertainty problems, where the statistical moments of the outputs of interest are estimated. Numerical results prove the efficiency of the proposed approach, since accurate outcomes are obtained in lower computational times than other techniques. © Progress In Electromagnetics Research B

关键词： Stochastic systems

来源：评论

学校读者我要写书评

暂无评论

An Explainable AI for Prostate Cancer Analysis 5th

An Explainable AI for Prostate Cancer Analysis

引用

5th Doctoral Symposium on Computational Intelligence, DoSCI 2024

作者： Kumar, M. Rakesh Athish, B.S. Devi, A. Chandini Kumar, P. Department of Computer Science and Engineering Rajalakshmi Engineering College TN Chennai India

ISBN: (纸本)9789819771776

Prostate cancer comes under SDG 3—Good Health and Well-Being is a global health concern affecting millions of men, demanding precise analysis for early detection and effective treatment. This project pioneers, innovative techniques for prostate cancer analysis, utilizing AI-driven segmentation and advanced analytical methods to address this pressing concern. Prostate cancer poses a significant worldwide health challenge, potentially metastasizing to neighboring organs and bones, leading to pain and fractures. The primary aim of this project is to enhance the precision and efficiency of prostate cancer analysis for early detection and timely intervention. Approximately one in eight men receive a prostate cancer diagnosis during their lifetime, with a higher prevalence among older individuals and non-Hispanic black men, particularly those aged 65 and older. Awareness levels vary, with 47.3% of survey respondents aware of the condition, primarily through media outlets (21.2%) and healthcare professionals (9%). This project addresses varying prostate cancer rates in distinct regions (peripheral zone: 70–80%, transitional zone: 10–20%, central zone: 5% or less). It employs AI-driven segmentation, image processing, and machine learning for accurate tumor detection, classification, and risk assessment. An innovative aspect is developing an explainable AI system for transparent and expert-empowered analysis. The project uses AI to diagnose prostate cancer accurately and early. It combines AI-driven segmentation, advanced analytical methodologies, refined algorithms, and a user-friendly interface. The aim is to enhance patient care through accurate and interpretable prostate cancer analyses in underserved areas. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Lung cancer

来源：评论

学校读者我要写书评

暂无评论

Generalization of Relay Node Deployment Problem for Wireless Sensor Network on jMetal 15th

Generalization of Relay Node Deployment Problem for Wirele...

引用

15th International Conference on Genetic and Evolutionary Computing, ICGEC 2023

作者： Kong, Lingping Gajdos, Petr Pan, Jeng-Shyang Snášel, Václav Faculty of Electrical Engineering and Computer Science VŠB-Technical University of Ostrava Ostrava Czech Republic College of Computer Science and Engineering Shandong University of Science and Technology Qingdao China

ISBN: (纸本)9789819700677

In Wireless Sensor Networks (WSNs), the relay nodes deployment problem is essential, as the relay nodes serve as cluster heads aggregating the data packages from sensors. Further, the relay nodes transmit collected packets to the Sink node (central processing point) via wired or wireless paths, thus forming a connected network. Various sensor networks tools, such as NetTopo, PiccSIM integrated with NS2, and Atarraya, improve the performance of simulation and protocols in WSNs. Those tools are not easy to start with for researchers whose research field is uncorrelated to the sensor network. Moreover, the studies based on heuristic algorithms on this problem focus more on a two-dimensional plane or an entire three-dimensional space with homogeneous nodes and omnidirectional sensors. Few pieces of research concentrate on relay nodes on three-dimensional terrain contour deployment, which simulates more natural circumstances to a real-life situation. Besides, due to the diverse optimization objectives, arrangement strategies, and sensor node requirements for distinct networks, conducting experiments to compare with existing deployed methods become more challenging. A generalization tool integrating the problem, network environment, and optimization objectives into a framework is essential, where a user can plug in blocks easily with framework interfaces, which makes the comparison more convenient. This design concentrates on users unfamiliar with network settings/models, such as NS2, adopting heuristic algorithms to solve WSN-related problems. In this study, we fill this gap by implementing a generalization framework based on the jMetal toolbox, which makes the WSN problem a benchmark, and benefits its solving by metaheuristic algorithms. © 2024, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Heuristic algorithms

来源：评论

学校读者我要写书评

暂无评论

EMPATH: MediaPipe-Aided Ensemble Learning with Attention-Based Transformers for Accurate Recognition of Bangla Word-Level Sign Language 27th

EMPATH: MediaPipe-Aided Ensemble Learning with Attention-Bas...

引用

27th International Conference on Pattern Recognition, ICPR 2024

作者： Hasan, Kazi Reyazul Adnan, Muhammad Abdullah Department of Computer Science and Engineering Bangladesh University of Engineering and Technology Dhaka Bangladesh

ISBN: (纸本)9783031783043

In this paper, we introduce EMPATH, an advanced computational framework developed to substantially enhance the recognition of Bangla Sign Language (BdSL). By integrating Ensemble Learning, MediaPipe Holistic for gesture tracking, and an Attention-based Transformer model, EMPATH addresses the challenges of sign language interpretation, setting new accuracy benchmarks and significantly surpassing previous records: achieving 79.81% on SignBD-Word-90 (previously best at 66.05%), 70.58% on SignBD-Word (previously best at 57%), and 99.25% on BdSL40 (previously best at 89%). A pioneering feature of EMPATH is its innovative interpolation model, built to overcome the limitations posed by missing Hand keypoints of MediaPipe. Validated in both EMPATH and a basic MLP framework, this model showcases remarkable versatility across architectures. EMPATH strategically selects its preprocessing and postprocessing techniques, optimizing each for maximum impact on accuracy and performance. Extensively trained across various word-level datasets beyond Bangla, including INCLUDE-50, INCLUDE, WLASL-100, and the Malaysian Sign Language Medical Dataset, EMPATH demonstrates its broad applicability and global potential. This diverse training scheme establishes superior accuracy benchmarks: achieving an impressive 100% on INCLUDE-50, 94.67% on INCLUDE, and 93.46% on the MSL Medical Dataset. Through EMPATH, we aspire to bridge communication barriers for the deaf and hard-of-hearing communities, showcasing the profound impact of integrating advanced technological solutions to tackle the complexities of sign language recognition. Source code is available at https://***/kreyazulh/EMPATH. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Benchmarking

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：