Falls are a serious problem in the hospital setting and home environments. However, this problem does not only affect the elderly, but also people who have had surgery, have disabling problems, have associated diagnos...
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This paper presents the design of a dual-polarized frequency-modulated continuous wave (FMCW) radar system with a coupler-integrated lens antenna for automotive synthetic aperture radar (SAR) applications. High-resolu...
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The Gastric Sleeve procedure is crucial for combating obesity, promoting weight loss, and improving metabolic health. Despite its effectiveness, the manual selection and placement of staples can lead to complications ...
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Identifying cyberattacks that attempt to compromise digital systems is a critical function of intrusion detection systems(IDS).Data labeling difficulties,incorrect conclusions,and vulnerability to malicious data injec...
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Identifying cyberattacks that attempt to compromise digital systems is a critical function of intrusion detection systems(IDS).Data labeling difficulties,incorrect conclusions,and vulnerability to malicious data injections are only a few drawbacks of using machine learning algorithms for *** overcome these obstacles,researchers have created several network IDS models,such as the Hidden Naive Bayes Multiclass Classifier and supervised/unsupervised machine learning *** study provides an updated learning strategy for artificial neural network(ANN)to address data categorization problems caused by unbalanced *** to traditional approaches,the augmented ANN’s 92%accuracy is a significant improvement owing to the network’s increased resilience to disturbances and computational complexity,brought about by the addition of a random weight and standard *** the ever-evolving nature of cybersecurity threats,this study introduces a revolutionary intrusion detection method.
This paper reports on ongoing and innovative research in the area of eXplainable Artificial Intelligence (XAI). A classical XAI task is considered as finding an explanation of the model generated via Machine Learning ...
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Skin cancer is the most prevalent cancer globally,primarily due to extensive exposure to Ultraviolet(UV)*** identification of skin cancer enhances the likelihood of effective treatment,as delays may lead to severe tum...
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Skin cancer is the most prevalent cancer globally,primarily due to extensive exposure to Ultraviolet(UV)*** identification of skin cancer enhances the likelihood of effective treatment,as delays may lead to severe tumor *** study proposes a novel hybrid deep learning strategy to address the complex issue of skin cancer diagnosis,with an architecture that integrates a Vision Transformer,a bespoke convolutional neural network(CNN),and an Xception *** were evaluated using two benchmark datasets,HAM10000 and Skin Cancer *** the HAM10000,the model achieves a precision of 95.46%,an accuracy of 96.74%,a recall of 96.27%,specificity of 96.00%and an F1-Score of 95.86%.It obtains an accuracy of 93.19%,a precision of 93.25%,a recall of 92.80%,a specificity of 92.89%and an F1-Score of 93.19%on the Skin Cancer ISIC *** findings demonstrate that the model that was proposed is robust and trustworthy when it comes to the classification of skin *** addition,the utilization of Explainable AI techniques,such as Grad-CAM visualizations,assists in highlighting the most significant lesion areas that have an impact on the decisions that are made by the model.
Resource allocation remains a challenging issue in communication networks,and its complexity is continuously increasing with the densification of the *** the evolution of new wireless technologies such as Fifth Genera...
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Resource allocation remains a challenging issue in communication networks,and its complexity is continuously increasing with the densification of the *** the evolution of new wireless technologies such as Fifth Generation(5G)and Sixth Generation(6G)mobile networks,the service level requirements have become stricter and more heterogeneous depending on the use *** this paper,we review a large body of literature on various resource allocation schemes that are used in particular in mobile wireless communication networks and compare the proposed schemes in terms of performance indicators as well as techniques *** review shows that among the strategies proposed in the literature,there is a wide variety of optimization targets and combinations thereof,focusing mainly on performance indicators such as energy efficiency,spectral efficiency,and network *** addition,in this paper,selected algorithms for resource allocation are numerically analyzed through simulations to compare and highlight the importance of how the resource algorithms are implemented to achieve efficient usage of the available *** performance of selected algorithms is evaluated in a multi-cell heterogeneous network and compared to proportional fair and eICIC,a widely-used combination of resource allocation and interferencemitigation techniques used by communication *** results show that one approach may performbetter when looking at the individual average user data rate but worse when looking at the overall spectral or energy efficiency,depending on the category of *** results,therefore,confirm that theremay not be a single algorithmthat visibly outperforms other candidates in terms of all performance ***,their efficiency is always a consequence of a strategic choice of goals,and the targeted parameters are optimized at a ***,the development and implementation of resource allocation algorithms must follow concrete usage scenarios and ne
The proposed system will introduce an IoT-based smart energy monitoring solution to enhance real-time tracking and management of electrical parameters, using the ESP32 Wi-Fi module as the core processing unit. The sys...
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An intelligent reflecting surface(IRS),or its various equivalents such as an reconfigurable intelligent surface(RIS), is an emerging technology to control radio signal propagation in wireless systems. An IRS is a digi...
An intelligent reflecting surface(IRS),or its various equivalents such as an reconfigurable intelligent surface(RIS), is an emerging technology to control radio signal propagation in wireless systems. An IRS is a digitally controlled metasurface consisting of a large number of passive reflecting elements, which are connected to a smart controller to enable dynamic adjustments of the amplitude and/or phase of the incident signal on each element independently [1].
The global automotive industry is in the phase where Internal Combustion vehicles are in decline and witnessing a shift towards sustainable development. The major parameter of a successful EV is an efficient battery p...
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