The Internet of Things(IoT)has orchestrated various domains in numerous applications,contributing significantly to the growth of the smart world,even in regions with low literacy rates,boosting socio-economic *** stud...
详细信息
The Internet of Things(IoT)has orchestrated various domains in numerous applications,contributing significantly to the growth of the smart world,even in regions with low literacy rates,boosting socio-economic *** study provides valuable insights into optimizing wireless communication,paving the way for a more connected and productive future in the mining *** IoT revolution is advancing across industries,but harsh geometric environments,including open-pit mines,pose unique challenges for reliable *** advent of IoT in the mining industry has significantly improved communication for critical operations through the use of Radio Frequency(RF)protocols such as Bluetooth,Wi-Fi,GSM/GPRS,Narrow Band(NB)-IoT,SigFox,ZigBee,and Long Range Wireless Area Network(LoRaWAN).This study addresses the optimization of network implementations by comparing two leading free-spreading IoT-based RF protocols such as ZigBee and *** field tests are conducted in various opencast mines to investigate coverage potential and signal *** is tested in the Tadicherla open-cast coal mine in ***,LoRaWAN field tests are conducted at one of the associated cement companies(ACC)in the limestone mine in Bargarh,India,covering both Indoor-toOutdoor(I2O)and Outdoor-to-Outdoor(O2O)environments.A robust framework of path-loss models,referred to as Free space,Egli,Okumura-Hata,Cost231-Hata and Ericsson models,combined with key performance metrics,is employed to evaluate the patterns of signal *** field testing and careful data analysis revealed that the Egli model is the most consistent path-loss model for the ZigBee protocol in an I2O environment,with a coefficient of determination(R^(2))of 0.907,balanced error metrics such as Normalized Root Mean Square Error(NRMSE)of 0.030,Mean Square Error(MSE)of 4.950,Mean Absolute Percentage Error(MAPE)of 0.249 and Scatter Index(SI)of *** the O2O scenario,the Ericsson model
With the rapid development of information technologies,industrial Internet has become more open,and security issues have become more *** endogenous security mechanism can achieve the autonomous immune mechanism withou...
详细信息
With the rapid development of information technologies,industrial Internet has become more open,and security issues have become more *** endogenous security mechanism can achieve the autonomous immune mechanism without prior ***,endogenous security lacks a scientific and formal definition in industrial ***,firstly we give a formal definition of endogenous security in industrial Internet and propose a new industrial Internet endogenous security architecture with cost ***,the endogenous security innovation mechanism is clearly ***,an improved clone selection algorithm based on federated learning is ***,we analyze the threat model of the industrial Internet identity authentication scenario,and propose cross-domain authentication mechanism based on endogenous key and zero-knowledge *** conduct identity authentication experiments based on two types of blockchains and compare their experimental *** on the experimental analysis,Ethereum alliance blockchain can be used to provide the identity resolution services on the industrial *** of Things Application(IOTA)public blockchain can be used for data aggregation analysis of Internet of Things(IoT)edge ***,we propose three core challenges and solutions of endogenous security in industrial Internet and give future development directions.
Multi-label classification is a challenging problem that has attracted significant attention from researchers, particularly in the domain of image and text attribute annotation. However, multi-label datasets are prone...
详细信息
Multi-label classification is a challenging problem that has attracted significant attention from researchers, particularly in the domain of image and text attribute annotation. However, multi-label datasets are prone to serious intra-class and inter-class imbalance problems, which can significantly degrade the classification performance. To address the above issues, we propose the multi-label weighted broad learning system(MLW-BLS) from the perspective of label imbalance weighting and label correlation mining. Further, we propose the multi-label adaptive weighted broad learning system(MLAW-BLS) to adaptively adjust the specific weights and values of labels of MLW-BLS and construct an efficient imbalanced classifier set. Extensive experiments are conducted on various datasets to evaluate the effectiveness of the proposed model, and the results demonstrate its superiority over other advanced approaches.
Although lots of research has been done in recognizing facial expressions,there is still a need to increase the accuracy of facial expression recognition,particularly under uncontrolled *** use of Local Directional Pa...
详细信息
Although lots of research has been done in recognizing facial expressions,there is still a need to increase the accuracy of facial expression recognition,particularly under uncontrolled *** use of Local Directional Patterns(LDP),which has good characteristics for emotion detection has yielded encouraging *** innova-tive end-to-end learnable High Response-based Local Directional Pattern(HR-LDP)network for facial emotion recognition is implemented by employing fixed convolutional filters in the proposed *** combining learnable convolutional layers with fixed-parameter HR-LDP layers made up of eight Kirsch filters and derivable simulated gate functions,this network considerably minimizes the number of network *** cost of the parameters in our fully linked layers is up to 64 times lesser than those in currently used deep learning-based detection *** seven well-known databases,including JAFFE,CK+,MMI,SFEW,OULU-CASIA and MUG,the recognition rates for seven-class facial expression recognition are 99.36%,99.2%,97.8%,60.4%,91.1%and 90.1%,*** results demonstrate the advantage of the proposed work over cutting-edge techniques.
Dynamic graph fraud detection aims to distinguish fraudulent entities that deviate significantly from most benign entities within an ever-changing graph ***,when dealing with different financial fraud scenarios,existi...
详细信息
Dynamic graph fraud detection aims to distinguish fraudulent entities that deviate significantly from most benign entities within an ever-changing graph ***,when dealing with different financial fraud scenarios,existing methods face challenges,resulting in difficulty in effectively ensuring financial *** fraud scenarios,transaction data are generated in real time,in which a strong temporal relationship between multiple fraudulent transactions is *** dynamic graph models struggle to effectively balance the temporal features of nodes and spatial structural features,failing to handle different types of nodes in the graph *** this study,to extract the temporal and structural information,we proposed a dynamic heterogeneous transaction graph embedding(DyHDGE)network based on a dynamic heterogeneous transaction graph,considering both temporal and structural information while incorporating heterogeneous *** separately extract temporal relationships between transactions and spatial structural relationships between nodes,we used a heterogeneous temporal graph representation learning module and a temporal graph structure information extraction ***,we designed two loss functions to optimize node feature *** experiments demonstrated that the proposed DyHDGE significantly outperformed previous state-of-the-art methods on two simulated datasets of financial fraud *** capability contributes to enhancing security in financial consumption scenarios.
Social media is nowadays a vital platform where people can share their feelings about any incident, product, or any issue. Twitter is one of those platforms which are very popular. If we must make use of this to extra...
详细信息
Cervical cancer is one of the most fatal and prevalent illnesses affecting women globally. Early detection of cervical cancer is crucial for effective treatment. Pap smear tests are commonly used, but population-based...
详细信息
Nowadays, the proliferation of open Internet of Things (IoT) devices has made IoT systems increasingly vulnerable to cyber attacks. It is of great practical significance to solve the security issues of IoT systems. Dr...
详细信息
Accurate prediction of above ground biomass (AGB) is critical for monitoring forest health and carbon cycling. It is crucial for understanding and managing forest ecosystems. In this paper, we propose an enhanced fram...
详细信息
Automated detection of plant diseases is crucial as it simplifies the task of monitoring large farms and identifies diseases at their early stages to mitigate further plant degradation. Besides the decline in plant he...
详细信息
暂无评论