Internet Technology Letters最新文献_第5页

Optimization of Quantum Dilated Convolutional Neural Networks: Image Recognition With Quantum Computing 量子扩展卷积神经网络的优化：量子计算的图像识别

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Internet Technology Letters Pub Date : 2025-04-21 DOI: 10.1002/itl2.70027

Rahamat Basha, Pankaj Pathak, M. Sudha, K. V. Soumya, J. Arockia Venice

{"title":"Optimization of Quantum Dilated Convolutional Neural Networks: Image Recognition With Quantum Computing","authors":"Rahamat Basha, Pankaj Pathak, M. Sudha, K. V. Soumya, J. Arockia Venice","doi":"10.1002/itl2.70027","DOIUrl":"https://doi.org/10.1002/itl2.70027","url":null,"abstract":"<div>\u0000 \u0000 <p>As computer vision tasks increasingly rely on Convolutional Neural Networks (CNNs) with ever-expanding parameter counts, the need for computational resources for model training is growing unsustainable, surpassing traditional computing hardware's progress. To address this challenge, emerging paradigms such as quantum computing are gaining attention as prospective alternatives for the future. This manuscript proposes Quantum Dilated Convolutional Neural Networks Revolutionizing Image Recognition with Quantum Computing (QDCNN-IR-QC). The first step is to use the MNIST dataset for the input pictures. Subsequently, Improved Bilateral Texture Filtering (IBTF) is used to preprocess the input pictures. Subsequently, E-LBP is used to extract pertinent features from the preprocessed pictures. In most cases, E-LBP does not show that optimization methods for picture recognition have been adjusted. Therefore, in order to adjust the E-LBP weight parameter, this paper suggests an ISMO optimization approach. Lastly, a new quantum architecture for picture identification is developed using QDCNN. To implement the proposed approach, Python is used. This is where metrics like F-Measure, accuracy, sensitivity, specificity, and precision are assessed. When compared to current techniques such as QOCNN-IR-QC, ANN-IR-QC, and QKNN-IR-QC, the proposed approaches provide 5.27%, 7.21%, and 8.23% greater accuracy, respectively, in terms of efficiency.</p>\u0000 </div>","PeriodicalId":100725,"journal":{"name":"Internet Technology Letters","volume":"8 3","pages":""},"PeriodicalIF":0.9,"publicationDate":"2025-04-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143852699","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A Selective Data Sharing and Retrieval Scheme in Edge-Enabled IoV 基于边缘的车联网数据共享与检索方案

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Internet Technology Letters Pub Date : 2025-04-16 DOI: 10.1002/itl2.70028

Hongbo Qu, Yi Cao, Shuaipeng Li

{"title":"A Selective Data Sharing and Retrieval Scheme in Edge-Enabled IoV","authors":"Hongbo Qu, Yi Cao, Shuaipeng Li","doi":"10.1002/itl2.70028","DOIUrl":"https://doi.org/10.1002/itl2.70028","url":null,"abstract":"<div>\u0000 \u0000 <p>The swift advancement of the Internet of Vehicles (IoV) has generated a vast amount of valuable data, leading to an increasing demand for IoV data sharing. Given the substantial volume of data that often contains sensitive information about vehicle owners, storing such data in an encrypted format is common practice to ensure its confidentiality. However, this storage method presents a significant data-sharing challenge: retrieving encrypted data. In this paper, we address the issue of private data sharing and retrieval by proposing a selective data sharing and retrieval scheme for edge-enabled IoV. Our approach introduces a novel IoV architecture based on blockchain and edge computing, which delegates most computational tasks to edge nodes, thus conserving the computational resources of vehicles and users. Additionally, we design an attribute-based searchable encryption scheme that supports users in performing fine-grained data retrieval and outsourced data decryption. Our scheme accommodates a large attribute universe, offers a flexible access policy, and conserves computational resources during user decryption. Finally, an in-depth evaluation of the proposed scheme's performance is conducted, showcasing its feasibility and practicality through experimental results. The results confirm our scheme's effectiveness and reinforce its viability for real-world applications.</p>\u0000 </div>","PeriodicalId":100725,"journal":{"name":"Internet Technology Letters","volume":"8 3","pages":""},"PeriodicalIF":0.9,"publicationDate":"2025-04-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143840590","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Multi-Scale Context-Aware Sentiment Analysis for Language Teaching Applications in 6G Network 面向 6G 网络语言教学应用的多尺度情境感知情感分析

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Internet Technology Letters Pub Date : 2025-04-14 DOI: 10.1002/itl2.70018

Yunhe Zhu

{"title":"Multi-Scale Context-Aware Sentiment Analysis for Language Teaching Applications in 6G Network","authors":"Yunhe Zhu","doi":"10.1002/itl2.70018","DOIUrl":"https://doi.org/10.1002/itl2.70018","url":null,"abstract":"<div>\u0000 \u0000 <p>With the advent of 6G technology, which promises ultralow latency and unprecedented data transmission speeds, the potential for real-time sentiment analysis on a global scale becomes increasingly feasible, which has emerged as an indispensable tool for deciphering user opinions and emotions across a broad spectrum of domains, including language teaching. In response to these challenges, this work explores the theoretical framework and proposes practical implementations for context-aware and multi-scale sentiment analysis, which involve using advanced natural language processing techniques for teaching data preprocessing. Then, the recurrent neural networks (RNNs) are utilized for handling sequential dependencies in text, so as to further revolutionize sentiment analysis by enabling simultaneous consideration of entire contexts through self-attention mechanisms, making them highly effective for multi-scale and context-aware analysis. Our findings reveal significant improvements in the precision and recall rates of sentiment classification, underscoring the potential of multi-scale context-aware sentiment analysis to revolutionize how we understand and respond to human emotions across diverse sectors. By offering deeper insights into the sentiments expressed within textual data, this approach paves the way for more informed decision-making processes and tailored responses, ultimately contributing to enhanced user experiences and outcomes.</p>\u0000 </div>","PeriodicalId":100725,"journal":{"name":"Internet Technology Letters","volume":"8 3","pages":""},"PeriodicalIF":0.9,"publicationDate":"2025-04-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143831107","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Fog-Platform-Enabled Controlled Music Generation via Transformer Networks With Integrated Style Analysis 通过具有综合风格分析功能的变压器网络实现雾平台可控音乐生成

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Internet Technology Letters Pub Date : 2025-04-10 DOI: 10.1002/itl2.70025

Cui Cai

引用次数: 0

Multi-Sensor Fusion-Based Anomaly Traffic Monitoring and Optimization Method for Communication in 6G-Enabled Information Warehouse Systems 基于多传感器融合的6g信息仓库系统异常流量监控及通信优化方法

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Internet Technology Letters Pub Date : 2025-04-10 DOI: 10.1002/itl2.70020

Yongchuan Jin, Wenzhong Sun, Xiaofei Sun, Guanyu Wang

{"title":"Multi-Sensor Fusion-Based Anomaly Traffic Monitoring and Optimization Method for Communication in 6G-Enabled Information Warehouse Systems","authors":"Yongchuan Jin, Wenzhong Sun, Xiaofei Sun, Guanyu Wang","doi":"10.1002/itl2.70020","DOIUrl":"https://doi.org/10.1002/itl2.70020","url":null,"abstract":"<div>\u0000 \u0000 <p>In complex 6G-enabled industrial communication networks, the diversity of thresholds for anomaly traffic monitoring arises due to the extensive use of multiple sensors for external information collection. Current methods, which rely on single thresholds or anomaly traffic monitoring, suffer from low monitoring accuracy and poor timeliness. By leveraging the high speed and low latency of the 6G network, this paper introduces a multi-sensor information fusion technique to design an anomaly traffic monitoring method for industrial communication networks. First, the multi-sensor fusion technique is applied to improve the estimation accuracy of local filters by using predicted values of lost observations as compensation. The cross-covariance matrix between any two estimation errors is provided, and this filtering method is used to process communication network data. Then, based on the matrix model's plane and 2D coordinate attributes, traffic features are sorted according to certain rules. Since the feature experience library can identify abnormal traffic in communication networks, an anomaly traffic matching model is established by combining location features to monitor abnormal traffic in the network and determine its source. Finally, experimental results show that the new monitoring method has higher accuracy and ensures good timeliness, enabling rapid feedback on anomaly traffic monitoring.</p>\u0000 </div>","PeriodicalId":100725,"journal":{"name":"Internet Technology Letters","volume":"8 3","pages":""},"PeriodicalIF":0.9,"publicationDate":"2025-04-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143818734","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Optimized DDoS Detection in Software-Defined IIoT Using a Hybrid Deep Neural Network Model 基于混合深度神经网络模型的软件定义工业物联网优化DDoS检测

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Internet Technology Letters Pub Date : 2025-03-28 DOI: 10.1002/itl2.70012

Enlai Chen, Na Zhang, Xiaomei Tu, Xiaoan Bao

引用次数: 0

A Spatiotemporal Transformer Framework for Robust Threat Detection in 6G Networks 一种用于6G网络鲁棒威胁检测的时空转换框架

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Internet Technology Letters Pub Date : 2025-03-28 DOI: 10.1002/itl2.70017

Guihua Wu

引用次数: 0

Artificial Intelligence in 5G Systems: Management of Resources in High-Altitude Infrastructures 5G系统中的人工智能：高空基础设施资源管理

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Internet Technology Letters Pub Date : 2025-03-28 DOI: 10.1002/itl2.70015

Madhura K, Vikash Kumar Singh, Durga Sivashankar, Sourav Rampal, Swaroop Mohanty, Shubhi Goyal

{"title":"Artificial Intelligence in 5G Systems: Management of Resources in High-Altitude Infrastructures","authors":"Madhura K, Vikash Kumar Singh, Durga Sivashankar, Sourav Rampal, Swaroop Mohanty, Shubhi Goyal","doi":"10.1002/itl2.70015","DOIUrl":"https://doi.org/10.1002/itl2.70015","url":null,"abstract":"<div>\u0000 \u0000 <p>The emergence of the 5G generation has considerably advanced wireless communication systems, with higher data rates and increased connectivity. Massive Multiple Input Multiple Output (mMIMO) structures, utilizing numerous antennas, improve spectral efficiency. High-Altitude Platform Stations (HAPS) provide promising deployment structures for 5G networks. However, it faces challenges including useful resource allocation, interference mitigation, and dynamic beamforming adaptation. This study proposes an efficient method for optimizing communication systems through the use of HAPS through aggregate of game theory and dynamic optimization strategies. The model introduces a novel method known as Dynamic Levysalp Fusion Optimization (DLSFO), which integrates the Levy Flight Algorithm (LFA) and Improved Slap Swarm Optimization (ISSO) to enhance exploration and avoid local optima in mMIMO systems. The findings demonstrate the effectiveness of the proposed method with a system latency (SL), bit error rate (BER), and sum rate, showcasing its potential to increase overall system performance for multi-person, multi-beam conversation systems on HAPS.</p>\u0000 </div>","PeriodicalId":100725,"journal":{"name":"Internet Technology Letters","volume":"8 3","pages":""},"PeriodicalIF":0.9,"publicationDate":"2025-03-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143717276","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

MA2CL: Multi-Agent Actor-Critic Learning Scheme for Efficient Resource Management in 5G-Enabled NB-IoT Networks MA2CL：支持5g的NB-IoT网络中高效资源管理的多智能体actor - critical学习方案

IF 0.9

Internet Technology Letters Pub Date : 2025-03-20 DOI: 10.1002/itl2.70011

Sadhvi Parashar, Rajeev Arya

{"title":"MA2CL: Multi-Agent Actor-Critic Learning Scheme for Efficient Resource Management in 5G-Enabled NB-IoT Networks","authors":"Sadhvi Parashar, Rajeev Arya","doi":"10.1002/itl2.70011","DOIUrl":"https://doi.org/10.1002/itl2.70011","url":null,"abstract":"<div>\u0000 \u0000 <p>The allocation of spectrum resources for the future 5G-enabled Narrowband Internet of Things (NB-IoT) is one of the most critical issues that need to be resolved. Due to the massive amount of data that will be generated by the IoT, the need for efficient allocation of resources is also immense. This paper presents a novel interference model for managing the allocation of resources and avoiding overlapping interference in the 5G-enabled NB-IoT Networks. It adopts Reinforcement Learning (RL)-based algorithms to improve the network throughput and prevent overlapping interference. The proposed method utilizes a Multi-Agent Actor-Critic Learning (MA<sup>2</sup>CL) algorithm, which can improve the efficiency of the network. The simulation result illustrates the prominent enhancement in the throughput and spectral efficiency of the network. The performances of the proposed algorithm have been compared with benchmark schemes and achieved a 33.3% increase in network throughput and a 26.67% boost in spectral efficiency, respectively. The proposed work for efficient NB-IoT resource management may be suitable in industrial automation and intelligent transportation systems.</p>\u0000 </div>","PeriodicalId":100725,"journal":{"name":"Internet Technology Letters","volume":"8 3","pages":""},"PeriodicalIF":0.9,"publicationDate":"2025-03-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143688916","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Interior Planning and Design Analysis Considering the Improvement of PDR Positioning Technology 考虑PDR定位技术改进的室内规划设计分析

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Internet Technology Letters Pub Date : 2025-03-20 DOI: 10.1002/itl2.70014

Lili Wang

{"title":"Interior Planning and Design Analysis Considering the Improvement of PDR Positioning Technology","authors":"Lili Wang","doi":"10.1002/itl2.70014","DOIUrl":"https://doi.org/10.1002/itl2.70014","url":null,"abstract":"<div>\u0000 \u0000 <p>To solve the problem of insufficient indoor positioning accuracy, a motion recognition and positioning method based on improved gait detection is proposed. In this method, the data is collected by an acceleration sensor, and the plane step estimation and vertical distance estimation algorithms are used to identify and analyze the features of different motion states. A one-dimensional convolutional neural network is used to improve the accuracy of step size estimation in the process of going up and down stairs. Comparative experimental results show that the total positioning errors of Pedestrian Step Estimation and Vertical Estimation algorithms are 0.605 m and 0.367 m, respectively. The total errors of the traditional Route Planning Algorithm and the Non-dominated Sorting Genetic Algorithm-iii algorithm are 3.071 m and 2.316 m, respectively. The experimental results show that the 1D-CNN algorithm has obvious advantages in the case of non-synchronous length, and the positioning errors in the <i>X</i>, <i>Y</i>, and <i>Z</i> axes are 0.298 m, 0.187 m, and 0.103 m, respectively, indicating that the proposed method significantly improves the accuracy of position estimation in the indoor environment.</p>\u0000 </div>","PeriodicalId":100725,"journal":{"name":"Internet Technology Letters","volume":"8 3","pages":""},"PeriodicalIF":0.9,"publicationDate":"2025-03-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143688917","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0