This research article presents a modified isolated SEPIC converter suitable for high-power applications. It uses a transformer instead of coupled inductor for isolation between the input power source and the output lo...
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Spiking neural network offers the most bio-realistic approach to mimic the parallelism and compactness of the human brain. A spiking neuron is the central component of an SNN which generates information-encoded spikes...
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IEC 61499 is an emerging standard for distributed automation which requires well-defined design practises to improve development efficiency. In this paper, we extend the one-line engineering design pattern and provide...
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Variational Bayesian learning (VBL)-based sparse channel state information (CSI) estimation is conceived for multiple input multiple output (MIMO) orthogonal time frequency space (OTFS) and for orthogonal time sequenc...
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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,...
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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.
Solar energy is one of the most abundant sources of renewable energy in Indonesia. Solar energy is now typically harnessed using solar panels, but the low efficiency of photovoltaic cells requires the development of o...
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Cybersecurity-related solutions have become familiar since it ensures security and privacy against cyberattacks in this digital *** Uniform Resource Locators(URLs)can be embedded in email or Twitter and used to lure v...
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Cybersecurity-related solutions have become familiar since it ensures security and privacy against cyberattacks in this digital *** Uniform Resource Locators(URLs)can be embedded in email or Twitter and used to lure vulnerable internet users to implement malicious data in their *** may result in compromised security of the systems,scams,and other such *** attacks hijack huge quantities of the available data,incurring heavy financial *** the same time,Machine Learning(ML)and Deep Learning(DL)models paved the way for designing models that can detect malicious URLs accurately and classify *** this motivation,the current article develops an Artificial Fish Swarm Algorithm(AFSA)with Deep Learning Enabled Malicious URL Detection and Classification(AFSADL-MURLC)*** presented AFSADL-MURLC model intends to differentiate the malicious URLs from genuine *** attain this,AFSADL-MURLC model initially carries out data preprocessing and makes use of glove-based word embedding *** addition,the created vector model is then passed onto Gated Recurrent Unit(GRU)classification to recognize the malicious ***,AFSA is applied to the proposed model to enhance the efficiency of GRU *** proposed AFSADL-MURLC technique was experimentally validated using benchmark dataset sourced from Kaggle *** simulation results confirmed the supremacy of the proposed AFSADL-MURLC model over recent approaches under distinct measures.
Farmer uses traditional crop insurance to protect their farms against crop loss and natural risks. However, farmers are concerned about crop insurance claims due to delays in processing claims that cost significantly....
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This paper considers the problem of inaccurate measurement-to-track association (M2TA) and poor tracking caused by camera motion changes in drone-captured video. The camera often changes its feld of view to track targ...
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Polymorphic viruses pose a significant challenge to traditional malware detection methods due to their ability to modify their code structure with each infection, effectively evading signature-based detection. This pa...
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