检索结果-内蒙古大学图书馆

Optimized Weighted Ensemble Using Dipper Throated Optimization Algorithm in Metamaterial Antenna

computers, Materials & Continua 2022年第12期73卷 5771-5788页

作者： Doaa Sami Khafaga El-Sayed M.El-kenawy Faten Khalid Karim Sameer Alshetewi Abdelhameed Ibrahim Abdelaziz AAbdelhamid Department of Computer Sciences College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Communications and Electronics Delta Higher Institute of Engineering and TechnologyMansoura35111Egypt Faculty of Artificial Intelligence Delta University for Science and TechnologyMansoura35712Egypt General Information Technology Department Ministry of DefenseThe Executive AffairsExcellence Services DirectorateRiyadh11564Saudi Arabia Computer Engineering and Control Systems Department Faculty of EngineeringMansoura UniversityMansoura35516Egypt Department of Computer Science Faculty of Computer and Information SciencesAin Shams UniversityCairo11566Egypt Department of Computer Science College of Computing and Information TechnologyShaqra University11961Saudi Arabia

Metamaterial Antennas are a type of antenna that uses metamaterial to enhance *** bandwidth restriction associated with small antennas can be solved using metamaterial *** learning is gaining popularity as a way to improve solutions in a range of *** learning approaches are currently a big part of current research,and they’re likely to be huge in the *** model utilized determines the accuracy of the prediction in large *** goal of this paper is to develop an optimized ensemble model for forecasting the metamaterial antenna’s bandwidth and *** basic models employed in the developed ensemble are Support Vector Regression(SVR),K-NearestRegression(KNR),Multi-Layer Perceptron(MLP),Decision Trees(DT),and Random Forest(RF).The percentages of contribution of these models in the ensemble model are weighted and optimized using the dipper throated optimization(DTO)*** choose the best features from the dataset,the binary(bDTO)algorithm is *** proposed ensemble model is compared to the base models and results are recorded and analyzed *** addition,two other ensembles are incorporated in the conducted experiments for *** ensembles are average ensemble and K-nearest neighbors(KNN)-based *** comparison is performed in terms of eleven evaluation *** evaluation results confirmed the superiority of the proposed model when compared with the basic models and the other ensemble models.

关键词： Metamaterial antenna dipper throated optimization feature selection parameters prediction

来源：评论

学校读者我要写书评

暂无评论

Time series numerical association rule mining variants in smart agriculture

引用

Journal of Ambient Intelligence and Humanized Computing 2023年第12期14卷 16853-16866页

作者： Fister, Iztok Fister, Dušan Fister, Iztok Podgorelec, Vili Salcedo-Sanz, Sancho Faculty of Electrical Engineering and Computer Science University of Maribor Koroška cesta 46 Maribor2000 Slovenia Department of Signal Processing and Communications Universidad de Alcalá Alcalá de Henares Madrid28805 Spain

Numerical association rule mining offers a very efficient way of mining association rules, where algorithms can operate directly with categorical and numerical attributes. These methods are suitable for mining different transaction databases, where data are entered sequentially. However, little attention has been paid to the time series numerical association rule mining, which offers a new technique for extracting association rules from time series data. This paper presents a new algorithmic method for time series numerical association rule mining and its application in smart agriculture. We offer a concept of a hardware environment for monitoring plant parameters and a novel data mining method with practical experiments. The practical experiments showed the method’s potential and opened the door for further extension. © 2023, The Author(s).

关键词： Internet of things

来源：评论

学校读者我要写书评

暂无评论

Online Simulator-Based Experimental Design for Cognitive Model Selection

引用

Computational Brain and Behavior 2023年第4期6卷 719-737页

作者： Aushev, Alexander Putkonen, Aini Clarté, Grégoire Chandramouli, Suyog Acerbi, Luigi Kaski, Samuel Howes, Andrew Department of Computer Science Aalto University Espoo 02150 Finland Department of Information and Communications Engineering Aalto University Espoo 02150 Finland Department of Computer Science University of Helsinki Helsinki 00560 Finland Department of Computer Science University of Manchester Manchester M13 9PR United Kingdom School of Computer Science University of Birmingham Birmingham B15 2TT United Kingdom

The problem of model selection with a limited number of experimental trials has received considerable attention in cognitive science, where the role of experiments is to discriminate between theories expressed as computational models. Research on this subject has mostly been restricted to optimal experiment design with analytically tractable models. However, cognitive models of increasing complexity with intractable likelihoods are becoming more commonplace. In this paper, we propose BOSMOS, an approach to experimental design that can select between computational models without tractable likelihoods. It does so in a data-efficient manner by sequentially and adaptively generating informative experiments. In contrast to previous approaches, we introduce a novel simulator-based utility objective for design selection and a new approximation of the model likelihood for model selection. In simulated experiments, we demonstrate that the proposed BOSMOS technique can accurately select models in up to two orders of magnitude less time than existing LFI alternatives for three cognitive science tasks: memory retention, sequential signal detection, and risky choice. © 2023, The Author(s).

关键词： Cognitive models Experimental design Likelihood-free inference Model selection

来源：评论

学校读者我要写书评

暂无评论

Socio-Transactional Impact of Recency, Frequency, and Monetary Features oN Customers’ Behaviour in Telecoms’ Churn Prediction

Iraqi Journal for Computer Science and Mathematics

引用

Iraqi Journal for computer Science and Mathematics 2022年第2期3卷 101-110页

作者： Ibitoye, Ayodeji O.J. Onime, Clement Zaki, Nashwan Dheyaa Onifade, Olufade F.W. Computer Science Programme Bowen University Iwo22021 Nigeria The Abdusalam ICTP Centre Trieste Italy University of information Technology and Communications College of Engineering Iraq Department of Computer Science University of Ibadan Ibadan20221 Nigeria

Due to the increasing competitiveness in telecom’s market, it has now become more necessary for operators to start building personal relationship with customers for targeted retention strategies. Achieving this goal requires the development of an effective churn prediction model that will solve the problem of churn misclassification, which is persistent in current churn prediction models. With several existing segment-oriented churn prediction models failing to harness the power of associative networking provided by telecoms users, churn prediction accuracy remains unguaranteed while targeted decision support is not enhanced. Here, the research introduced the Customer’s Influence Degree (I) to the existing Recency, Frequency, and Monetary (RFM) values as an additional predictive factor, towards determining the churn class of a customer. The essence is to utilise the socio-transactional affinities of customers’ direct dependent to targeted communication nodes through customers RFM analysis to determine the dominance of a customer in the community. The newly introduced predictive factor helped to minimise churn misclassification rate through appropriate reclassification of customers who were wrongly classified as churner or non-churner when using the existing RFM churn scores only. © 2022 Autoctonía. Revista de Ciencias Sociales e Historia. All rights reserved.

关键词： Forecasting

来源：评论

学校读者我要写书评

暂无评论

Automatic Identification of Ear Patterns Based on Convolutional Neural Network 7th

Automatic Identification of Ear Patterns Based on Convolutio...

引用

7th National Conference on New Trends in Information and communications Technology Applications, NTICT 2023

作者： Tuama, Saba A. Saud, Jamila H. Rashid, Omar Fitian Department of Engineering University of Information Technology and Communications Baghdad Iraq Department of Computer Science College of Science Al-Mustansiriyah University Baghdad Iraq Department of Geology College of Science University of Baghdad Baghdad Iraq

ISBN: (纸本)9783031628139

Biometrics represent the most practical method for swiftly and reliably verifying and identifying individuals based on their unique biological traits. This study addresses the increasing demand for dependable biometric identification systems by introducing an efficient approach to automatically recognize ear patterns using Convolutional Neural Networks (CNNs). Despite the widespread adoption of facial recognition technologies, the distinct features and consistency inherent in ear patterns provide a compelling alternative for biometric applications. Employing CNNs in our research automates the identification process, enhancing accuracy and adaptability across various ear shapes and orientations. The ear, being visible and easily captured in an image, possesses the unique characteristic that no two individuals share the same ear patterns. Consequently, our research proposes a system for individual identification based on ear traits, comprising three main stages: (1) pre-processing to extract the ear pattern (region of interest) from input images, (2) feature extraction, and (3) classification. Convolutional Neural Network (CNN) is employed for the feature extraction and classification tasks. The system remains invariant to scaling, brightness, and rotation. Experimental results demonstrate that the proposed system achieved an accuracy of 99.86% for all datasets. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.

关键词： Biometrics

来源：评论

学校读者我要写书评

暂无评论

Deep Radiomics: A Picture's Worth a Thousand Words - A Review 1

Deep Radiomics: A Picture's Worth a Thousand Words - A Revie...

引用

1st IEEE Karachi Section Humanitarian Technology Conference, Khi-HTC 2024

作者： Meraj, Syeda Shah, Asadullah Ismail, Ahsiah Sembokb, Tengku Mt Shadab, Syed Aftab, Syed Nageena, Syeda Khan, Nusratullah Nusratullah, Kajal Kulliyyah of Information and Communications Technology Department of Information Systems Selangor Malaysia Kulliyyah of Information and Communications Technology Department of Computer Science Selangor Malaysia Al Musanna College of Technology City Department of Information Technology Oman Higher Colleges of Technology Department of Aeronautical Engineering Technology Al-Ain United Arab Emirates Department of Health and Family Welfare Karnataka Koppal India Yanbu Industrial College Royal Commission Computer Science and Engineering Department Yanbu Saudi Arabia

ISBN: (纸本)9798350373042

In recent decades, the prevalence of diseases has witnessed a notable surge. The increasing health challenges have led to a greater use of advanced diagnostic machines for detecting and understanding these disease conditions. The diagnostic modalities, such as X-rays, CT scans, MRI scans, and nuclear medicine imaging, generate a wealth of interpretative data through medical images. Deep Radiomics aims to improve the efficiency and accuracy of image interpretation by automating the process of feature extraction, allowing for more comprehensive insights for advancing personalized medicine and improving outcomes in medical imaging. Enhance disease detection, diagnosis, and subsequent treatment strategies. © 2024 IEEE.

关键词： computer aided diagnosis

来源：评论

学校读者我要写书评

暂无评论

Low crosstalk and high extinction ratio all-optical 4 × 2 encoder based on metal–insulator–metal plasmonic waveguides

引用

Optical and Quantum Electronics 2025年第4期57卷 1-14页

作者： Qiaoling, Tang Afshari-Bavil, Mehdi Rezaei, Mir Hamid School of Physics and Electronic Information Engineering Neijiang Normal University Sichuan Province Neijiang641112 China Photonics Research Center Neijiang Normal University Sichuan Province Neijiang641112 China Department of Communications and Electronics School of Electrical and Computer Engineering Shiraz University Shiraz Iran

This paper presents an all-optical 4 × 2 encoder based on metal–insulator–metal (MIM) waveguides, designed for operation across a wide wavelength range of 1–2 μm. The MIM waveguides consist of SiO2 dielectric strips sandwiched between layers of silver metal. The encoder incorporates a straight waveguide to detect the state of the In0 input. Additionally, it includes one splitter and two combiners with outputs Out0 and Out1 for detecting the states of the In1, In2, and In3 inputs. A key innovation in this work is the distance created between the splitter and combiners, which allows for tuning and improving the encoder output characteristics. The proposed encoder was simulated using the finite-difference time-domain method. It demonstrates a minimum extinction ratio of 11.65 dB and a crosstalk level of − 15.65 dB at a wavelength of 1550 nm. The total footprint of the encoder is less than 8 μm2. Our research indicates that a 4 × 2 encoder utilizing MIM waveguides has not been previously reported. Given its straightforward fabrication process, high extinction ratio, and low crosstalk, the suggested encoder is a promising candidate for a wide range of plasmonic communication and signal-processing applications. © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2025.

关键词： Crosstalk

来源：评论

学校读者我要写书评

暂无评论

A Developer-Focused Genetic Algorithm for IoT Application Placement in the Computing Continuum

引用

IEEE Transactions on Services Computing 2025年第3期18卷 1185-1198页

作者： Herrera, Juan Luis Moya, Alejandro Berrocal, Javier Murillo, Juan Manuel Navarro, Elena University of Bologna Department of Computer Science Engineering Italy University of Castilla-La Mancha LoUISE Research Group Spain University of Extremadura Department of Computer Science and Communications Engineering Spain

The rise of the Internet of Things (IoT) paradigm has led to an interest in applying it not only in tasks for the general public but also to stringent domains such as healthcare. However, the developers of these next-generation IoT applications must consider additional non-functional requirements related to the criticality of the processes they automate, such as low response times or low deployment costs, as well as technical constraints, which include organizational, legal and policy-related constraints on where data can be processed or stored. While the Computing Continuum paradigm emerges as a valuable alternative for placing such applications, identifying the deployments that satisfy all these requirements becomes a tough challenge. The NP-hard nature of the problem makes it impractical to manually find such a deployment, and traditional approaches fail to consider the technical constraints. In this paper, we present the Genetic Algorithm for Application Placement (GAAP), an evolutionary computing-based meta-heuristic designed to help IoT application developers find deployments that satisfy their Quality of Service, business and technical constraints. Our evaluation of an Internet of Medical Things use case shows that GAAP supports larger scenarios than traditional approaches and gives IoT application developers more options while providing better scalability. © 2008-2012 IEEE.

关键词： Computing Continuum Deployment Genetic Algorithm Internet of Things Quality of Service Service Placement

来源：评论

学校读者我要写书评

暂无评论

Digital Twin Enabled Data-Driven Approach for Traffic Efficiency and Software-Defined Vehicular Network Optimization 100

Digital Twin Enabled Data-Driven Approach for Traffic Effici...

引用

100th IEEE Vehicular Technology Conference, VTC 2024-Fall

作者： Shahriar, Mohammad Sajid Subramaniam, Suresh Matsuura, Motoharu Hasegawa, Hiroshi Lin, Shih-Chun Department of Electrical and Computer Engineering NC United States George Washington University WA United States University of Electro-Communications Tokyo Japan Nagoya University Nagoya Japan

ISBN: (纸本)9798331517786

In the realms of the internet of vehicles (IoV) and intelligent transportation systems (ITS), software defined vehicular networks (SDVN) and edge computing (EC) have emerged as promising technologies for enhancing road traffic efficiency. However, the increasing number of connected autonomous vehicles (CAVs) and EC-based applications presents multi-domain challenges such as inefficient traffic flow due to poor CAV coordination and flow-table overflow in SDVN from increased connectivity and limited ternary content addressable memory (TCAM) capacity. To address these, we focus on a data-driven approach using virtualization technologies like digital twin (DT) to leverage real-time data and simulations. We introduce a DT design and propose two data-driven solutions: a centralized decision support framework to improve traffic efficiency by reducing waiting times at roundabouts and an approach to minimize flow-table overflow and flow re-installation by optimizing flow-entry lifespan in SDVN. Simulation results show the decision support framework reduces average waiting times by 22% compared to human-driven vehicles, even with a CAV penetration rate of 40%. Additionally, the proposed optimization of flow-table space usage demonstrates a 50% reduction in flow-table space requirements, even with 100% penetration of connected vehicles. © 2024 IEEE.

关键词： Ternary content adressable memory

来源：评论

学校读者我要写书评

暂无评论

A Robust Semantic Communication System for Image Transmission

A Robust Semantic Communication System for Image Transmissio...

引用

2024 IEEE Global communications Conference, GLOBECOM 2024

作者： Peng, Xiang Qin, Zhijin Tao, Xiaoming Lu, Jianhua Letaief, Khaled B. Tsinghua University Department of Electronic Engineering Beijing China Beijing China State Key Laboratory of Space Network and Communications Beijing China Hong Kong University of Science and Technology Department of Electronic and Computer Engineering Hong Kong

ISBN: (纸本)9798350351255

Semantic communications have gained significant attention as a promising approach to address the transmission bottleneck, especially with the continuous development of 6G techniques. Distinct from the well investigated physical channel impairments, this paper focuses on semantic impairments in images, particularly those arising from adversarial perturbations. Specifically, we propose a novel metric for quantifying the intensity of semantic impairment and develop a semantic impairment dataset. Furthermore, we introduce a deep learning enabled semantic communication system, termed as DeepSC-RI, to enhance the robustness of image transmission, which incorporates a multi-scale semantic extractor with a dual-branch architecture for extracting semantics with varying granularity, thereby improving the robustness of the system. The fine-grained branch incorporates a semantic importance evaluation module to identify and prioritize crucial semantics, while the coarse-grained branch adopts a hierarchical approach for capturing the robust semantics. These two streams of semantics are seamlessly integrated via an advanced cross-attention-based semantic fusion module. Experimental results demonstrate the superior performance of DeepSC-RI under various levels of semantic impairment intensity. © 2024 IEEE.

关键词： Image communication systems

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：