Herein, we present a novel transparent antenna with ultra-wideband (UWB) performance along with polarization diversity through 4 ports allowing MIMO operation. The antenna design can be of a great interest for a vehic...
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DC-DC power converters have become an integral part in various commercial and industrial applications with an ever-increasing need for efficient power management. Modern electronic systems often demand several differe...
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In this study, the performance and emissions of Al2O3 alkaline cottonseed biodiesel-powered compression ignition engines were predicted. An experiment was conducted using different biodiesel blends made from cottonsee...
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This article proposes a new topology of a three-phase high-frequency transformer (HFT) isolated bipolar ac-ac converter. It has a simple circuit topology consisting of nine active switches, three HFTs with primary and...
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Despite its long history,the anomalous Hall continues to attract attention due to its complex origins,its connection to topology,and its use as a probe of magnetic *** this work we investigate the anomalous Hall effec...
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Despite its long history,the anomalous Hall continues to attract attention due to its complex origins,its connection to topology,and its use as a probe of magnetic *** this work we investigate the anomalous Hall effect in 2871 ferromagnetic materials using an automatic high-throughput calculation *** analyze general properties of the effect,such as its reliance on spin-orbit coupling strength and *** materials with the largest anomalous Hall effect,we find that symmetry-protected band degeneracies in the non-relativistic electronic structure,such as mirror symmetry-protected nodal lines,are typically responsible for the large ***,we examine the dependence of the anomalous Hall effect on magnetization direction and demonstrate deviations from the commonly assumed expression j^(AHE)~M×E.
This article presents an innovative approach that leverages interpretable machine learning models and cloud computing to accelerate the detection of septic shock by analyzing electronic health *** traditional methods,...
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This article presents an innovative approach that leverages interpretable machine learning models and cloud computing to accelerate the detection of septic shock by analyzing electronic health *** traditional methods,which often lack transparency in decision-making,our approach focuses on early detection,offering a proactive strategy to mitigate the risks of *** integrating advanced machine learning algorithms with interpretability techniques,our method not only provides accurate predictions but also offers clear insights into the factors influencing the model’s ***,we introduce a preference-based matching algorithm to evaluate disease severity,enabling timely interventions guided by the analysis *** innovative integration significantly enhances the effectiveness of our *** leverage a clinical health dataset comprising 1,552,210 Electronic Health Records(EHR)to train our interpretable machine learning models within a cloud computing *** techniques like feature importance analysis and model-agnostic interpretability tools,we aim to clarify the crucial indicators contributing to septic shock *** transparency not only assists healthcare professionals in comprehending the model’s predictions but also facilitates the integration of our system into existing clinical *** validate the effectiveness of our interpretable models using the same dataset,achieving an impressive accuracy rate exceeding 98%through the application of oversampling *** findings of this study hold significant implications for the advancement of more effective and transparent diagnostic tools in the critical domain of sepsis management.
Blockchain technology is critical in cyber *** most recent cryptographic strategies may be hacked as efforts are made to build massive elec-tronic *** of the ethical and legal implications of a patient’s medical data...
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Blockchain technology is critical in cyber *** most recent cryptographic strategies may be hacked as efforts are made to build massive elec-tronic *** of the ethical and legal implications of a patient’s medical data,cyber security is a critical and challenging problem in *** image secrecy is highly vulnerable to various types of *** a result,designing a cyber security model for healthcare applications necessitates extra caution in terms of data *** resolve this issue,this paper proposes a Lionized Golden Eagle based Homomorphic Elapid Security(LGE-HES)algorithm for the cybersecurity of blockchain in healthcare *** blockchain algorithm preserves the security of the medical image by performing hash *** execution of this research is carried out by MATLAB *** suggested fra-mework was tested utilizing Computed Tumor(CT)pictures and MRI image data-sets,and the simulation results revealed the proposed model’s profound *** the simulation,94.9%of malicious communications were recognized and identified effectively,according to the total outcomes *** suggested model’s performance is also compared to that of standard approaches in terms of Root Mean Square Error(RMSE),Peak Signal to Noise Ratio(PSNR),Mean Square Error(MSE),time complexity,and other factors.
Islanding is a significant difficulty that arises from the high integration of distributed generation sources. Islanding could potentially damage the clients and their equipment. According to the IEEE 1547 DG intercon...
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This research work introduces a new system that utilizes Generative Pretrained Transformer (GPT) Large Language Models (LLMs) to enable language-based control for Unmanned Aerial Vehicles (UAVs). The system enables no...
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