检索结果-内蒙古大学图书馆

Attack-Aware Dynamic Upstream Bandwidth Assignment Scheme for Passive Optical Network

Journal of Optical communications 2023年第4期44卷 485-493页

作者： Butt, Rizwan Aslam Faheem, M. Ashraf, M. Waqar Khawaja, Attaullah Raza, Basit Electronic Engineering Department NED University of Engineering and Technology Karachi75220 Pakistan Department of Computer Engineering Abdullah Gul University Kayseri Turkey Electronic Engineering Department NED University of Engineering and Technology Sindh Karachi Pakistan COMSATS Institute of Information Technology Park Raod Islamabad Islamabad45550 Pakistan Department of Computer Engineering Bahauddin Zakariya University Multan Pakistan

Network security is an important component of today's networks to combat the security attacks. The passive optical network (PON) works at the medium access layer (MAC). A distributed denial of service (DDOS) attack may be launched from the network and transport layers of an Optical Network unit (ONU). Although there are various security techniques to mitigate its impact, however, these techniques cannot mitigate the impact on the MAC Layer of the PON and can cause an ONU to continuously drain too much bandwidth. This will result in reduced bandwidth availability to other ONUs and, thus, causing an increase in US delays and delay variance. In this work we argue that the impact of a DDOS attack can be mitigated by improving the Dynamic bandwidth assignment (DBA) scheme which is used in PON to manage the US bandwidth at the optical line terminal (OLT). The present DBA schemes do not have the capability to combat a security attack. Thus, this study, uses a machine learning approach to learn the ONU traffic demand patterns and presents a security aware DBA (SA-DBA) scheme that detects a rogue (attacker) ONU from its traffic demand pattern and limits its illegitimate bandwidth demand and only allows it the bandwidth assignment to it as per the agreed service level agreement (SLA). The simulation results show that the SA-DBA scheme results in up to 53%, 55% and 90% reduced US delays and up to 84%, 76% and 95% reduced US delay variance of T2, T3 and T4 traffic classes compared to existing insecure DBA schemes. © 2019 Walter de Gruyter GmbH, Berlin/Boston.

关键词： Passive optical networks

来源：评论

学校读者我要写书评

暂无评论

Generation of hyperentangled photon pairs based on lithium niobate waveguide

引用

Chinese Physics B 2023年第9期32卷 172-176页

作者：陈洋河姜震何广强 SJTU Pinghu Institute of Intelligent Optoelectronics Department of Electronic EngineeringShanghai Jiao Tong UniversityShanghai 200240China State Key Laboratory of Advanced Optical Communication Systems and Networks Department of Electronic EngineeringShanghai Jiao Tong UniversityShanghai 200240China

Generation of hyperentangled photon pairs is investigated based on the lithium niobate straight *** propose to use the nonlinear optical process of spontaneous parametric down-conversion(SPDC)and a well-designed lithium niobate waveguide structure to generate a hyperentangled(in the polarization dimension and the energy-time dimension)two-photon *** performing numerical simulations of the waveguide structure and calculating the possible polarization states,joint spectral amplitudes(JSA),and joint temporal amplitudes(JTA)of the generated photon pair,we show that the generated photon pair is indeed hyperentangled in both the polarization dimension and the energy-time dimension.

关键词： hyperentanglement nonlinear photonic crystal lithium niobate waveguide

来源：评论

学校读者我要写书评

暂无评论

Gene Array Based Cervical cancer categorization with Machine Learning Techniques

Gene Array Based Cervical cancer categorization with Machine...

引用

2024 International Conference on Integration of Emerging Technologies for the Digital World, ICIETDW 2024

作者： Nisha, K. Vijayalakshmi, A. Surya, N. Chennai Institute of Technology Department of Computer Science and Engineering Chennai India Chennai Institute of Technology Department of Electronics and Communication Engineering Chennai India

ISBN: (纸本)9798331541170

Cervical squamous cell carcinoma is anticipated to become the fourth most prevalent cancer globally and is expected to cause the death of one in three affected women. The World Health Organization (WHO) reports that 86% of all documented cases of cervical cancer occur in developing countries.. Gene expression profiling is still used extensively in the investigation of cervical cancer. Gene expression patterns have been investigated in biological networks, in particular a gene co-expression network, which emerges as an unconventional comprehensive method for microarray research. A component of the physiognomy in gene co-expression networks continues to be disproportionate even at the point in time when a particular biological issue has been ***, the Enhanced Bacterial colony Optimization Algorithm with Hilbert-Schmidt Independence Criterion (EBCO-HSIC) and the Support Vector Machine (SVM) method are bestowed in this investigation by selecting symbolic genes that encompass phases including normalisation, module detection, gene selection, and classification. The gene dataset is first percolated using the fuzzy C Means (FCM) approach, which is then used for both the purpose of normalisation and the removal of extraneous features. The EBO method is used in order to choose the suitable genes using the degree of accuracy in categorization as the fitness function. The approach that was devised focuses on gene importance as well as calibrating the dependence between differentially expressed genes (DEGs) in order to arbitrate a selection of the most informative genes by using an ultrafast beyond ascendable bat algorithm. In order to remedy this situation, HSIC, which is supported in part by EBO, is put into action. The SVM classifier is an effective tool for categorising high-dimensional data, such as that obtained from microarray gene expression. © 2024 IEEE.

关键词： Diseases

来源：评论

学校读者我要写书评

暂无评论

Deep Learning-Based Automated System for Multi-Classification of Plant Diseases in Real-Time Environments

Deep Learning-Based Automated System for Multi-Classificatio...

引用

2024 International Conference on communication, Computing and Internet of Things, IC3IoT 2024

作者： Aruna, K.B. Prema, S. Sureka, V. Sudha, L. Sasikala, V. S.A. Engineering College Computer Science And Engineering Department Chennai India Vel Tech Rangarajan Dr.Sagunthala R&d Institute Of Science And Technology Computer Science And Engineering Department Chennai India Sri Sairam Engineering College Department Of Electronic And Communication Engineering India

ISBN: (纸本)9798350352689

Agriculture provides food for the world's expanding population. Several developing nations are going through this period, and agriculture has been developed to fulfil the rising food demand. While agriculture seeks to feed the world's rapidly growing population, plant disease reduces the amount and quality of food, fiber, and biofuel crops. Although losses can be severe, they normally account for 42% of the yield of the six most important food crops. Managing illnesses costs farmers sometimes without enough professional assistance, which has unfavorable outcomes including pollution and subpar disease control. Deep learning algorithms are helping farmers all around the world identify and categories the illness. In order to identify disease in plant leaves, it employs techniques like Convolutional Neural Networks (CNN). This research discussed the preset and user specified models that were employed to identify diseases in plant leaves. We are transmitting the Driver circuit to power the pump motors to Arduino Uno using UART protocols. Determine the different soil types using an NPK sensor. At the end, we are using Arduino to control the motor model with a server motor. © 2024 IEEE.

关键词： Convolutional neural networks

来源：评论

学校读者我要写书评

暂无评论

Surface Functionalized Plasmonic Sensors for Uric Acid Detection With Gold-Graphene Stacked Nanocomposites

引用

Photonic Sensors 2025年第1期15卷 122-137页

作者： Olabisi Abdullahi ONIFADE Dinie Dayana MOHAMAD AZRI Muhammad Hafiz ABU BAKAR Mohammed Thamer ALRESHEEDI Eng Khoon NG Mohd Adzir MAHDI Ahmad Shukri MUHAMMAD NOOR Department of Computer and Communication Systems Engineering Faculty of EngineeringUniversiti Putra MalaysiaSerdang 43400Malaysia Wireless and Photonics Research Centre of Excellence Faculty of EngineeringUniversiti Putra MalaysiaSerdang43400Malaysia Department of Electrical Engineering College of EngineeringKing Saud UniversityRiyadh 11421Kingdom of SaudiArabia Department of Engineering University of CambridgeCambridge CB30FAThe United Kingdom Institute of Nanoscience and Nanotechnology(ION2) Universiti Putra MalaysiaSerdang 43400Malaysia

This study presented a surface-functionalized sensor probe using 3-aminopropyltriethoxysilane(APTES)self-assembled monolayers on a Kretschmann-configured plasmonic *** probe featured stacked nanocomposites of gold(via sputtering)and graphene quantum dots(GQD,via spin-coating)for highly sensitive and accurate uric acid(UA)detection within the physiological *** encompassed the field emission scanning electron microscopy for detailed imaging,energy-dispersive X-ray spectroscopy for elemental analysis,and Fourier transform infrared spectroscopy for molecular *** functionalization increased sensor sensitivity by 60.64%,achieving 0.0221°/(mg/dL)for the gold-GQD probe and 0.0355°/(mg/dL)for the gold-APTES-GQD probe,with linear correlation coefficients of 0.8249 and 0.8509,*** highest sensitivity was 0.0706°/(mg/dL),with a linear correlation coefficient of 0.993 and a low limit of detection of 0.2 mg/***,binding affinity increased dramatically,with the Langmuir constants of 14.29μM^(-1)for the gold-GQD probe and 0.0001μM^(-1)for the gold-APTES-GQD probe,representing a 142900-fold *** probe demonstrated notable reproducibility and repeatability with relative standard deviations of 0.166%and 0.013%,respectively,and exceptional temporal stability of 99.66%.These findings represented a transformative leap in plasmonic UA sensors,characterized by enhanced precision,reliability,sensitivity,and increased surface binding capacity,synergistically fostering unprecedented practicality.

关键词： Plasmon nanocomposite gold-graphene quantum dot uric acid,functionalize sensor

来源：评论

学校读者我要写书评

暂无评论

Metaheuristic Based Clustering with Deep Learning Model for Big Data Classification

引用

computer Systems Science & engineering 2023年第1期44卷 391-406页

作者： R.Krishnaswamy Kamalraj Subramaniam V.Nandini K.Vijayalakshmi Seifedine Kadry Yunyoung Nam Department of Electronics and Communication Engineering University College of Engineering AriyalurAriyalur621704India Department of Biomedical Engineering Faculty of EngineeringKarpagam Academy of Higher EducationCoimbatore641021India Department of Computer Science and Engineering Sona College of TechnologySalem636005India Department of Electronics and Communication Engineering Saveetha School of EngineeringSaveetha Institute of Medical and Technical SciencesChennai600077India Deparmtent of Applied Data Science Noroff University CollegeKristiansandNorway Department of Computer Science and Engineering Soonchunhyang UniversityAsanKorea

Recently,a massive quantity of data is being produced from a distinct number of sources and the size of the daily created on the Internet has crossed two *** the same time,clustering is one of the efficient techniques for mining big data to extract the useful and hidden patterns that exist in ***-based clustering techniques have gained significant attention owing to the fact that it helps to effectively recognize complex patterns in spatial *** data clustering is a trivial process owing to the increasing quantity of data which can be solved by the use of Map Reduce *** this motivation,this paper presents an efficient Map Reduce based hybrid density based clustering and classification algorithm for big data analytics(MR-HDBCC).The proposed MR-HDBCC technique is executed on Map Reduce tool for handling the big *** addition,the MR-HDBCC technique involves three distinct processes namely pre-processing,clustering,and *** proposed model utilizes the Density-Based Spatial Clustering of Applications with Noise(DBSCAN)techni-que which is capable of detecting random shapes and diverse clusters with noisy *** improving the performance of the DBSCAN technique,a hybrid model using cockroach swarm optimization(CSO)algorithm is developed for the exploration of the search space and determine the optimal parameters for density based ***,bidirectional gated recurrent neural network(BGRNN)is employed for the classification of big *** experimental validation of the proposed MR-HDBCC technique takes place using the benchmark dataset and the simulation outcomes demonstrate the promising performance of the proposed model interms of different measures.

关键词： Big data data classification clustering mapreduce dbscan algorithm

来源：评论

学校读者我要写书评

暂无评论

Adaptive Interference Detection and Removal in SAR Images Based on the Order-2 Tracy-Widom Distribution 2

Adaptive Interference Detection and Removal in SAR Images Ba...

引用

2nd IEEE International Conference on Signal, Information and Data Processing, ICSIDP 2024

作者： Yang, Huizhang Chen, Chengzhi Xi, Feng Lang, Ping Yin, Junjun Yang, Jian Nanjing University of Science and Technology Department of Electronic Engineering Nanjing China Tsinghua University Department of Electronic Engineering Beijing China University of Science and Technology Beijing School of Computer and Communication Engineering Beijing China

ISBN: (纸本)9798331515669

This paper proposes a novel eigenvalue-based detector for adaptive detection of radio interference in synthetic aperture radar (SAR) images. The proposed method leverages the increased eigenvalues caused by interference in single-look-complex SAR image blocks, where the interference is expected to have a small set of eigenvalues, particularly with a dominating one. Specifically, the method segments the image into multiple blocks, computes the eigenvalues of each block's covariance matrix, and compares the largest eigenvalue with a threshold to determine the presence of interference under the criteria of constant false alarm rate. The threshold is determined by the order-2 Tracy-Widom distribution of the largest eigenvalue for each image block under the assumption of image homogeneity. The proposed detector is integrated with our previously proposed block subspace filter for adaptive interference detection and removal. Experimental results on Sentinel-1 double-polarization and Gaofen-3 HV-polarization images demonstrate the effectiveness of the proposed method on adaptive detection and suppression of interference artefacts in SAR images. © 2024 IEEE.

关键词： Eigenvalues and eigenfunctions

来源：评论

学校读者我要写书评

暂无评论

Synergistic applications of nanostructured boron nitride in photocatalysis and targeted drug delivery

引用

Nanotechnology for Environmental engineering 2024年第2期9卷 179-188页

作者： Mali, Priyadarshani Shivakumar Jagtap, Bhagyashree Krishnarao Gowda V, Dankan Ashreetha, B. Vasanthakumar, G.U. kaur, Mandeep Hariram, Venkatesan Department of Electronics and Telecommunications Engineering Bharati Vidyapeeth’s college of Engineering Kolhapur Maharashtra416013 India Department of Electronics and Computer Engineering Sharad Institute of Technology college of Engineering Yadrav Maharashtra Ichalkaranji Kolhapur416115 India Department of Electronics and Communication Engineering BMS Institute of Technology and Management Bangalore Karnataka560064 India Department of Electronics and Communication Engineering School of Engineering Mohan Babu University Andhra Pradesh Tirupati India Department of Computer Science and Engineering Nitte Meenakshi Institute of Technology Yelahanka Bengaluru560064 India Department of Electronics and Communication Engineering Punjabi University Punjab Patiala147002 India Department of Practice of Medicine Vinayaka Mission’s Homoeopathic Medical College and Hospital A Constituent College of Vinayaka Mission’s Research Foundation Deemed to be University Tamilnadu Salem636 308 India

This study explores the applications of nanostructured boron nitride (BN) in photocatalysis and targeted drug delivery, highlighting its notable thermal conductivity, chemical stability, and wide bandgap. Through the synthesis and detailed characterization of BN nanoparticles, employing Scanning Electron Microscopy (SEM) and Transmission Electron Microscopy (TEM), the material’s efficacy in light-induced chemical reactions and potential as a nanocarrier for drug delivery systems are investigated. Photocatalytic experiments reveal an enhanced ability of BN to absorb light and facilitate charge separation, suggesting a promising approach for environmental detoxification and sustainable energy generation. In parallel, investigations into BN’s drug loading capacity, release kinetics, and targeting efficiency, particularly in the context of cancer therapy, are conducted. Findings indicate that BN nanoparticles significantly enhance photocatalytic performance and offer a safe, effective platform for controlled drug release. This research underscores the dual utility of BN in addressing critical challenges in environmental engineering and medical treatment, pointing towards novel interdisciplinary applications of this versatile nanomaterial. © The Author(s), under exclusive licence to Springer Nature Switzerland AG 2024.

关键词： Photocatalysis

来源：评论

学校读者我要写书评

暂无评论

A Hierarchical Aggregation Network with Edge Guidance for Sturdy Medical Image Segmentation 2

A Hierarchical Aggregation Network with Edge Guidance for St...

引用

2nd International Conference on Advances in Computation, communication and Information Technology, ICAICCIT 2024

作者： Rasheedha, A. Reethika, A. Rajeshwari, R. Remya, R. Kumar, M. Suresh Saranya, M.D. Department of Biomedical Engineering Sri Ramakrishna Engineering College Coimbatore India Department of Electronics and Communication Engineering Sri Ramakrishna Engineering College Coimbatore India Department of Computer Science and Engineering CMR Institute of Technology Bengaluru India Department of Electronics and Communication Engineering Vel Tech Rangarajan Dr Sagunthala R&D Institute of Science and Technology Chennai India Department of Computer Science and Engineering Sri Ranganathar Institute of Engineering and Technology Coimbatore India Department of Electronics and Communication Engineering KPR Institute of Engineering and Technology Coimbatore India

ISBN: (纸本)9798331541217

Convolutional neural networks (CNNs) are essential for medical picture segmentation in clinical analysis and illness detection. On the other hand, noise levels and intraclass variability are considerable in medical photos, but interclass differences are negligible. It is difficult to extract strong contextual information and combine discriminative characteristics for fine-grained segmentation. Current techniques are unable to produce precise mask edges, resulting in fuzzy borders and decreased segmentation precision. In this research, a new A Hierarchical Aggregation Network with Edge Guidance that maintains precise spatial features and gathers rich contextual information is presented. The Efficient Fusion Attention Module is used by the proposed model to highlight important spatial and channel information, the Adaptive Hierarchical Feature Aggregation Module to maximize feature fusion, and the Inter-layer Edge-aware Module to improve edge prediction accuracy. Experimentally and qualitatively, the proposed method will perform better than six other cutting-edge segmentation techniques. © 2024 IEEE.

关键词： Convolutional neural networks

来源：评论

学校读者我要写书评

暂无评论

An Intelligent Agent Based Optimal Scheduling & Congestion Free Routing Scheme to Enhance QoS of NFV Enabled Heterogeneous Wireless Sensor Network Framework 15

An Intelligent Agent Based Optimal Scheduling & Congestion F...

引用

15th International Conference on Computing communication and Networking Technologies, ICCCNT 2024

作者： Prathap, C. Sivaranjani, S. Sathya, M. Prabhakaran Rajalakshmi, J. Kavin Kumar, K. Gokulchandrasekaran NadarSaraswathi College of Engineering and Technology Department of Computer Science and Engineering Theni India SethuInstituteofTechnology Department of Computer Science and Engineering Virudhnagar India Nadar Saraswathi College of Engineering and Technology Department of Information Technology Theni India Nandha Engineering College Department of Electronics and Communication Engineering Erode India Sethu Institute of Technology Department of Electronics and Communication Engineering Virudhunagar India Kongu Engineering College Perundurai Department of Electronics and Communication Engineering Erode638060 India Karpagam Institute of Technology Department of Electronics and Communication Engineering Coimbatore India

ISBN: (纸本)9798350370249

In wireless sensor network (WSN), congestion is regarded as an unavoidable issue as of today's scenario at which the data traffic is increased to their aggregated channel capacity. This results in the consequence of buffer overflowing which leads to packets drop thereby reducing packet delivery ratio and degrades network throughput. Also, routing is the most favored approaches for the minimization of nodes energy consumption and the enhancement of Heterogeneous WSNs throughput. Since, the problem of routing has been proved to be an NP-hard, it has been realized that optimization-based technique offers better performance. For solving these issues, this paper proposes a congestion free optimal routing scheme based on Genetic algorithm-based distance aware-Low Energy Adaptive Clustering Hierarchy (GADA-LEACH) protocol to predict intelligent agent path. The major intention of this work is to enhance the efficiency of energy and QoS (throughput and delay) in edge-cloud based IoT environment of data transmission. Initially, the system model is initialized and the graph construction is made for the process of clustering using Spectral graph theory (SGT) at which the cluster head (CH) selection is made. Then, the scheduling process is carried by means of Packet weighted based ensemble optimization scheduling (PW-EOS) scheme. The NFV enabled optimal edge node is selected using Reconfigured Cuckoo Search optimizer (RCSO) after which the intelligent agent moving path in the Heterogeneous Network (HetNet) are predicted by GADA-LEACH technique. From this, an effective routing path is determined among CH and an optimized Edge node. Eventually, the performance assessment is carried in terms of throughput, energy consumption, survival rate, PDR, End-to-End delay and the outcomes conquered are compared with existing methods to attest the proficiency of proposed scheme. © 2024 IEEE.

关键词： Sensor nodes

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：