Sensor-based human activity recognition (S-HAR) is a famous study focusing on detecting human physiological actions by interpreting various sensors, especially one-dimensional time series information. Typically, S-HAR...
Sensor-based human activity recognition (S-HAR) is a famous study focusing on detecting human physiological actions by interpreting various sensors, especially one-dimensional time series information. Typically, S-HAR machine learning methods were developed using handcrafted characteristics. Unfortunately, this is a complicated process that involves feature engineering and a high level of domain knowledge. Due to the development of deep neural networks, classification techniques could efficiently handle relevant characteristics from raw sensor data, resulting in enhanced classification outcomes. In this study, we describe a unique method for S-HAR based on ensemble deep learning with sensor nodes connected to the waist, chest, leg, and arm. Implementing and training three deep learning networks is performed using a publically available dataset, including wearable sensors from eight human actions. The findings demonstrate that the proposed Ens-ResNeXt model provides the maximum accuracy and F1-score, which is superior to existing techniques.
A botnet refers to a group of machines. These machines are controlled distantly by a specific attacker. It represents a threat facing the web and data security. Fast-flux service network (FFSN) has been engaged by bot...
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Room acoustic simulations can be performed by means of numerical methods, which typically solve the wave equation in an enclosure through discretization techniques. These methods provide high-fidelity solvers that inc...
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An invariant can be described as an essential relationship between program *** invariants are very useful in software checking and *** tools that are used to detect invariants are invariant *** are two types of invari...
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An invariant can be described as an essential relationship between program *** invariants are very useful in software checking and *** tools that are used to detect invariants are invariant *** are two types of invariant detectors:dynamic invariant detectors and static invariant *** software is an available computer program that implements a special case of a dynamic invariant detection *** proposes a dynamic invariant detection algorithm based on several runs of the tested program;then,it gathers the values of its variables,and finally,it detects relationships between the variables based on a simple statistical *** method has some *** of its biggest drawbacks is its overwhelming time *** is observed that the runtime for the Daikon invariant detection tool is dependent on the ordering of traces in the trace file.A mechanism is proposed in order to reduce differences in adjacent trace *** is done by applying some special techniques of mutation/crossover in genetic algorithm(GA).An experiment is run to assess the benefits of this *** findings reveal that the runtime of the proposed dynamic invariant detection algorithm is superior to the main approach with respect to these improvements.
Communication is crucial in multi-agent reinforcement learning when agents are not able to observe the full state of the environment. The most common approach to allow learned communication between agents is the use o...
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Data Assimilation (DA) is a Bayesian inference that combines the state of a dynamical system with real data collected by instruments at a given time. The goal of DA is to improve the accuracy of the dynamic system mak...
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We report the properties of molecular beam epitaxy deposited AlBN thin films on a recently developed epitaxial nitride metal electrode Nb2N. While a control AlN thin film exhibits standard capacitive behavior, distinc...
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A solution of linear systems of equations Ax=b and Ax=0 is a vital part of many computational packages. This paper presents a novel formulation based on the projective extension of the Euclidean space using the outer ...
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In this work, we investigate the security performance of an underlay cognitive radio network (CRN) with ambient backscatter communication (AmBC), where a backscattering device (BD) shares the spectrum and the receiver...
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ISBN:
(数字)9798331517786
ISBN:
(纸本)9798331517793
In this work, we investigate the security performance of an underlay cognitive radio network (CRN) with ambient backscatter communication (AmBC), where a backscattering device (BD) shares the spectrum and the receivers with the secondary user. Different from the related work, we consider a secondary user transmitter (ST) with multiple antenna in an AmBC-CRN with multiple receivers and multiple passive eavesdroppers. The ST performs joint antenna-user selection to enhance its security performance and overcome the performance degradation caused by BD interference. Considering the Nakagami-m fading model, closed-form expressions are derived for the secrecy outage probability for both the ST and the BD transmissions. Monte Carlo simulations are performed to validate the derived closed-form expressions. Numerical results show that employing joint antenna-user selection enhances the ST security performance by exploiting antenna and user diversity.
We consider the development of unbiased estimators, to approximate the stationary distribution of Mckean-Vlasov stochastic differential equations (MVSDEs). These are an important class of processes, which frequently a...
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