International Journal of Advanced Network, Monitoring and Controls最新文献_第2页

Deep Learning Based Melanoma Diagnosis Identification 基于深度学习的黑色素瘤诊断识别

International Journal of Advanced Network, Monitoring and Controls Pub Date : 2023-06-01 DOI: 10.2478/ijanmc-2023-0053

Gaole Duan, Changyuan Wang

{"title":"Deep Learning Based Melanoma Diagnosis Identification","authors":"Gaole Duan, Changyuan Wang","doi":"10.2478/ijanmc-2023-0053","DOIUrl":"https://doi.org/10.2478/ijanmc-2023-0053","url":null,"abstract":"Abstract Malignant melanoma is considered to be one of the deadliest types of skin cancer, and it is responsible for the death of a large number of people worldwide. However, distinguishing whether melanoma is benign or malignant has been a challenging task. Many Computer Aided Diagnosis and Detection Systems have been developed in the past for this task. This paper presents a deep learning framework based approach for melanoma diagnosis and recognition. In the proposed method, the original skin mirror image is first preprocessed and then passed to the VGG16 convolutional neural network for tumor property classification. VGG16 uses smaller convolutional kernels instead of a larger convolutional kernel to achieve a reduction in network parameters and thus improve network performance. The system is trained using segmented RGB images generated from ground truth images of the ISIC2016 dataset, and finally a softmax classifier is used for pixel-level classification of melanoma lesions. In this study, a new method to become a lesion classifier was designed to classify melanoma lesion regions into benign and malignant tumors based on the results of pixel-level classification, and experiments were conducted on two well-established public test datasets, ISIC2016 and ISIC2017, with a final accuracy of 96.1%. The results indicate that convolutional neural networks are suitable for melanoma diagnosis identification. This study is of great relevance for advanced cancer caused by malignant melanoma.","PeriodicalId":193299,"journal":{"name":"International Journal of Advanced Network, Monitoring and Controls","volume":"44 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124965119","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

Simulation of Comfort Algorithm for Automatic Driving of Urban Rail Train 城市轨道车辆自动驾驶舒适性算法仿真

International Journal of Advanced Network, Monitoring and Controls Pub Date : 2023-06-01 DOI: 10.2478/ijanmc-2023-0058

K. Li, Zhongsheng Wang

{"title":"Simulation of Comfort Algorithm for Automatic Driving of Urban Rail Train","authors":"K. Li, Zhongsheng Wang","doi":"10.2478/ijanmc-2023-0058","DOIUrl":"https://doi.org/10.2478/ijanmc-2023-0058","url":null,"abstract":"Abstract The automation and intelligence of transportation vehicles is the focus and hotspot of the future research and development of the entire transportation industry, which can effectively improve a series of social problems such as traffic accidents, exhaust pollution, and traffic jams caused by the current increase in the number of transportation vehicles. With the rapid development of rail transit in our country, more and more people choose urban rail transit for travel, which is greatly convenient for travel. The comfort of Automatic Train Operation (ATO) system is an inevitable consideration when people choose it. Aiming at the comfort of ATO system, this paper designs a train operation target curve that can meet the comfort index of train. At the same time, two simulation models are established by using the SIMULINK module of MATLAB software to compare the experiments. One model is the train simulation model based on PID control, and the other model is the train simulation model based on fuzzy PID. The final simulation results show that fuzzy PID control has stronger superiority in train comfort in the process of train motion simulation, and the traditional PID control is not as good as fuzzy PID control in train comfort.","PeriodicalId":193299,"journal":{"name":"International Journal of Advanced Network, Monitoring and Controls","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130577316","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

Exploring the Potential of A-ResNet in Person-Independent Face Recognition and Classification 探索A-ResNet在独立于人的人脸识别和分类中的潜力

International Journal of Advanced Network, Monitoring and Controls Pub Date : 2023-06-01 DOI: 10.2478/ijanmc-2023-0052

A. Obaid, Aws Saad Shawkat, Nazar Salih Abdulhussein

{"title":"Exploring the Potential of A-ResNet in Person-Independent Face Recognition and Classification","authors":"A. Obaid, Aws Saad Shawkat, Nazar Salih Abdulhussein","doi":"10.2478/ijanmc-2023-0052","DOIUrl":"https://doi.org/10.2478/ijanmc-2023-0052","url":null,"abstract":"Abstract This study offers a novel face recognition and classification method based on classifiers that use statistical local features. The use of ResNet has generated growing interest in a variety of areas of image processing and computer vision in recent years and demonstrated its usefulness in several applications, especially for facial image analysis, which includes tasks as varied as face detection, face recognition, facial expression analysis, demographic classification, etc. This paper is divided into two steps i.e. face recognition and classification. The first step in face recognition is automatic data cleansing which is done with the help of Multi-Task Cascaded Convolutional Neural Networks (MTCNNs) and face.evoLVe, followed by parameter changes in MTCNN to prevent dirty data. The authors next trained two models: Inception-ResNetV1, which had pre-trained weights, and Altered-ResNet (A-ResNet), which used Conv2d layers in ResNet for feature extraction and pooling and softmax layers for classifications. The authors use the best optimizer after comparing a number of them during the training phase, along with various combinations of batch and epoch. A-ResNet, the top model overall, detects 86/104 Labelled Faces in the Wild (LFW) dataset images in 0.50 seconds. The proposed approach was evaluated and received an accuracy of 91.7%. Along with this, the system achieved a training accuracy of 98.53% and a testing accuracy of 99.15% for masked face recognition. The proposed method exhibits competitive outcomes when measured against other cutting-edge algorithms and models. Finally, when it comes to why the suggested model is superior to ResNet, it may be because the A-ResNet is simpler thus it can perform at its best with little data, whereas deeper networks require higher data size.","PeriodicalId":193299,"journal":{"name":"International Journal of Advanced Network, Monitoring and Controls","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115887631","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

Research on Joint Modeling of Intent Detection and Slot Filling 意图检测与缝隙填充联合建模研究

International Journal of Advanced Network, Monitoring and Controls Pub Date : 2023-06-01 DOI: 10.2478/ijanmc-2023-0059

Dan Yang, Chaoyang Geng, Yi Li

引用次数: 0

Performance of Automatic Frequency Planning and Optimization Algorithm for Cellular Networks 蜂窝网络频率自动规划与优化算法的性能研究

International Journal of Advanced Network, Monitoring and Controls Pub Date : 2023-06-01 DOI: 10.2478/ijanmc-2023-0056

M. Abdulhamid, Kisenya Sayianka

{"title":"Performance of Automatic Frequency Planning and Optimization Algorithm for Cellular Networks","authors":"M. Abdulhamid, Kisenya Sayianka","doi":"10.2478/ijanmc-2023-0056","DOIUrl":"https://doi.org/10.2478/ijanmc-2023-0056","url":null,"abstract":"Abstract Frequency planning is one of the most expensive aspects of deploying a cellular network. If a set of base stations can be deployed with minimal service and planning, the cost of both deploying and maintaining the network will decrease. To ensure that the scarce frequency is utilized to its maximum, planning and optimization are done. This is also carried out to ensure that there is high efficiency in cellular radio systems and little or minimum interference due to co-channeling. This paper focuses on coming up with an automatic way of planning and optimizing the frequency in the cellular network. The approach replaces the inefficient, inaccurate and tedious manual approach. The automatic approach simplifies work for the radio frequency(RF) engineers and also reduces the cost of operation. The automatic approach ensures that the cellular network is extensively deployed in a way that criteria of maximum quality, quantity and good coverage are met. The paper focuses on coming up with an automatic planning and optimization algorithm that minimizes the intra-system interference levels to reasonable ranges within the key performance indicators (KPIs) defined for any acceptable cellular network.","PeriodicalId":193299,"journal":{"name":"International Journal of Advanced Network, Monitoring and Controls","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134613734","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

Improved Double Regression Nonlinear Image Super Resolution Model 改进的双回归非线性图像超分辨率模型

International Journal of Advanced Network, Monitoring and Controls Pub Date : 2023-06-01 DOI: 10.2478/ijanmc-2023-0055

Jieyi Lv, Zhongsheng Wang

引用次数: 0

IP Addresses through 2022: This article is reproduced from “The ISP Column-A monthly column on things Internet” of Geoff Huston's Blog IP地址到2022年:本文摘自杰夫·休斯顿博客的“ISP专栏-物联网每月专栏”

International Journal of Advanced Network, Monitoring and Controls Pub Date : 2023-06-01 DOI: 10.2478/ijanmc-2023-0054

G. Huston

引用次数: 0

Research on Intelligentization of Cloud Computing Programs Based on Self-awareness 基于自我意识的云计算程序智能化研究

International Journal of Advanced Network, Monitoring and Controls Pub Date : 2023-06-01 DOI: 10.2478/ijanmc-2023-0060

Han-Bin Liu, Wuqi Gao, Junmin Luo

{"title":"Research on Intelligentization of Cloud Computing Programs Based on Self-awareness","authors":"Han-Bin Liu, Wuqi Gao, Junmin Luo","doi":"10.2478/ijanmc-2023-0060","DOIUrl":"https://doi.org/10.2478/ijanmc-2023-0060","url":null,"abstract":"Abstract Through the research of MapReduce programming framework of cloud computing, the current MapReduce program only solves specific problems, and there is no design experience or design feature summary of MapReduce program, let alone formal description and experience inheritance and application of knowledge base. In order to solve the problem of intelligent cloud computing program, a general MapReduce program generation method is designed. This paper proposes the architecture of intelligent cloud computing by studying AORBCO model and combining cloud computing technology. According to the behavior control mechanism in AORBCO model, a program generation method of MapReduce in intelligent cloud computing is proposed. This method will extract entity information in input data set and entity information in knowledge base in intelligent cloud computing for similarity calculation, and extract the entity in the top order as key key-value pair information in intelligent cloud computing judgment data set. The data processing types are divided, and then aligned with each specific MapReduce capability, and the MapReduce program generation experiment is verified in the AORBCO model development platform. The experiment shows that the complexity of big data MapReduce program code is simplified, and the generated code execution efficiency is good.","PeriodicalId":193299,"journal":{"name":"International Journal of Advanced Network, Monitoring and Controls","volume":"124 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134126984","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

Research on Blockchain Anonymous Communication Based on Key Derivation 基于密钥派生的区块链匿名通信研究

International Journal of Advanced Network, Monitoring and Controls Pub Date : 2023-06-01 DOI: 10.2478/ijanmc-2023-0051

Yanxun Chen, Pingping Liu

{"title":"Research on Blockchain Anonymous Communication Based on Key Derivation","authors":"Yanxun Chen, Pingping Liu","doi":"10.2478/ijanmc-2023-0051","DOIUrl":"https://doi.org/10.2478/ijanmc-2023-0051","url":null,"abstract":"Abstract With the continuous development of the Internet and communication technologies, network communication provides convenience but also brings security problems such as exposure of users' personal privacy information and theft, private tampering, and forgery of false information. Modern cryptography technology is an important safeguard against message eavesdropping and tampering, while the rapidly developing anonymous communication technology in this century makes it difficult for attackers to infer user's personal information and communication relationships. In response to the potential threats of traditional centralized systems such as central nodes being vulnerable to attacks and data storage being tampered with, this paper proposes a blockchain anonymous communication algorithm KDAC based on key derivation, which takes advantage of the decentralization, data immutability, consensus mechanism and anonymity of blockchain and combines the ECC cryptographic derivation algorithm and anonymous communication technology to realize the key-at-a-time, one-address-at-a-time The key derivation scheme ensures the message integrity and tamper-evident while effectively hiding the identity information of both communication parties. In addition, this paper also optimizes the blockchain anonymous communication system with key derivation. Users only need the initial key of blockchain nodes to join the network for communication, and the information transmission is difficult to trace based on the blockchain network, which can effectively guarantee communication security and anonymity. The experimental results show that the efficiency of the derived key algorithm is roughly in the same order of magnitude as that of the 256-bit AES symmetric encryption algorithm, which can play a better role in practical applications. On the other hand, the derived key generated based on the algorithm has complete randomness in association verification, and it is impossible to reverse the initial parameters, which can well guarantee the anonymity of user identity.","PeriodicalId":193299,"journal":{"name":"International Journal of Advanced Network, Monitoring and Controls","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122078589","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

Optimization and Improvement of BP Decoding Algorithm for Polar Codes Based on Deep Learning 基于深度学习的BP极码译码算法优化与改进

International Journal of Advanced Network, Monitoring and Controls Pub Date : 2023-06-01 DOI: 10.2478/ijanmc-2023-0057

Li Ge, Guiping Li

引用次数: 0