Time variant coverage, called sweep coverage in wireless sensor networks has got attention from various re-searchers in recent time. In this problem, a set of mobile sensors are collectively monitoring certain area of...
详细信息
Data-enabled Predictive Control (DeePC) allows controlling dynamic systems soley based on its input/output data. This approach is based on behavioral theory, which guarantees precise prediction of the output for given...
详细信息
With the rise of the Internet of Vehicles(IoV)and the number of connected vehicles increasing on the roads,Cooperative Intelligent Transportation Systems(C-ITSs)have become an important area of *** the number of Vehic...
详细信息
With the rise of the Internet of Vehicles(IoV)and the number of connected vehicles increasing on the roads,Cooperative Intelligent Transportation Systems(C-ITSs)have become an important area of *** the number of Vehicle to Vehicle(V2V)and Vehicle to Interface(V2I)communication links increases,the amount of data received and processed in the network also *** addition,networking interfaces need to be made more secure for which existing cryptography-based security schemes may not be ***,there is a need to augment them with intelligent network intrusion detection *** machine learning-based intrusion detection and anomaly detection techniques for vehicular networks have been proposed in recent ***,given the expected large network size,there is a necessity for extensive data processing for use in such anomaly detection *** learning solutions are lucrative options as they remove the necessity for feature ***,with the amount of vehicular network traffic increasing at an unprecedented rate in the C-ITS scenario,the need for deep learning-based techniques is all the more *** work presents three deep learning-based misbehavior classification schemes for intrusion detection in IoV networks using Long Short Term Memory(LSTM)and Convolutional Neural Networks(CNNs).The proposed Deep Learning Classification Engines(DCLE)comprise of single or multi-step classification done by deep learning models that are deployed on the vehicular edge *** data received by the Road Side Units(RSUs)is pre-processed and forwarded to the edge server for classifications following the three classification schemes proposed in this *** proposed classifiers identify 18 different vehicular behavior types,the F1-scores ranging from 95.58%to 96.75%,much higher than the existing *** running the classifiers on testbeds emulating edge servers,the prediction performance and prediction time comparison of
Due to the enormous usage of the internet for transmission of data over a network,security and authenticity become major *** challenges encountered in biometric system are the misuse of enrolled biometric templates st...
详细信息
Due to the enormous usage of the internet for transmission of data over a network,security and authenticity become major *** challenges encountered in biometric system are the misuse of enrolled biometric templates stored in database *** describe these issues various algorithms are implemented to deliver better protection to biometric traits such as physical(Face,fingerprint,Ear etc.)and behavioural(Gesture,Voice,tying etc.)by means of matching and verification *** this work,biometric security system with fuzzy extractor and convolutional neural networks using face attribute is proposed which provides different choices for supporting cryptographic processes to the confidential *** proposed system not only offers security but also enhances the system execution by discrepancy conservation of binary *** Face Attribute Convolutional Neural Network(FACNN)is used to generate binary codes from nodal points which act as a key to encrypt and decrypt the entire data for further *** Artificial Intelligence(AI)into the proposed system,automatically upgrades and replaces the previously stored biometric template after certain time period to reduce the risk of ageing difference while *** codes generated from face templates are used not only for cryptographic approach is also used for biometric process of enrolment and *** main face data sets are taken into the evaluation to attain system performance by improving the efficiency of matching performance to verify *** system enhances the system performance by 8%matching and verification and minimizes the False Acceptance Rate(FAR),False Rejection Rate(FRR)and Equal Error Rate(EER)by 6 times and increases the data privacy through the biometric cryptosystem by 98.2%while compared to other work.
In this work, a prototype system has been designed with a 0.18-μm CMOS technology to capture perspiration rate in daily life. To calculate an amount of perspiration, a temperature sensor is necessary concurrently wit...
详细信息
The significant impact of stress on health necessitates accurate assessment methods,where traditional questionnaires lack reliability and *** advancements like wearables with electrocardiogram(ECG)and galvanic skin re...
详细信息
The significant impact of stress on health necessitates accurate assessment methods,where traditional questionnaires lack reliability and *** advancements like wearables with electrocardiogram(ECG)and galvanic skin response(GSR)sensors face accuracy and artifact *** biosensors detecting cortisol,a critical stress hormone,present a promising ***,existing cortisol assays,requiring saliva,urine,or blood,are complex,expensive,and unsuitable for continuous *** study introduces a passive,molecularly imprinted polymer-radio-frequency(MIP-RF)wearable sensing system for real-time,non-invasive sweat cortisol *** system is wireless,flexible,battery-free,reusable,environmentally stable,and designed for long-term monitoring,using an inductance-capacitance *** transducer translates cortisol concentrations into resonant frequency shifts with high sensitivity(~160 kHz/(log(μM)))across a physiological range of 0.025–1μ*** with near-field communication(NFC)for wireless and battery-free operation,and threedimensional(3D)-printed microfluidic channel for in-situ sweat collection,it enables daily activity cortisol level *** of cortisol circadian rhythm through morning and evening measurements demonstrates its effectiveness in tracking and monitoring sweat cortisol levels.A 28-day stability test and the use of cost-effective 3D nanomaterials printing enhance its economic viability and *** innovation paves the way for a new era in realistic,on-demand health monitoring outside the laboratory,leveraging wearable technology for molecular stress biomarker detection.
Pareto set learning (PSL) is an emerging approach for acquiring the complete Pareto set of a multi-objective optimization problem. Existing methods primarily rely on the mapping of preference vectors in the objective ...
详细信息
In this article, an event-based neuroadaptive robust tracking controller for a perturbed and networked differential drive mobile robot (DMR) is designed with concurrent learning. A radial basis function neural network...
详细信息
This paper proposes three types of neural network-based attack detectors for Internet of Vehicles (IoV) networks. The proposed attack detectors consist of Long Short-Term Memory (LSTM) layers. The fault detector is im...
详细信息
Application of very large-scale integration circuit partitioning techniques toward those of power electronic systems reduces interconnect parasitics while improving overall power density. To that end, an EDA tool is c...
详细信息
暂无评论