This paper introduces Deep Convolutional Generative Adversarial Networks (DCGAN) as a potential solution for wireless systems aiming to enhance the Block Error Rate (BLER). The DCGAN under consideration consists of a ...
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Developing manufacturing methods for flexible electronics will enable and improve the large-scale production of flexible, spatially efficient, and lightweight devices. Laser sintering is a promising postprocessing met...
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Although conventional control systems are simple and widely used, they may not be effective for complex and uncertain systems. This study proposes a Hermite broad-learning recurrent neural network (HBRNN) with a wide ...
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Purpose: Potassium imbalance, often symptomless but potentially fatal, is prevalent in patients with kidney or heart conditions. Traditional laboratory tests for potassium measurement are costly and require skilled te...
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作者：
Shim, HyungboASRI
Electrical and Computer Engineering Department Seoul National University Korea Republic of
A swarm of individuals often exhibits behaviors that are not possible for each individual. This phenomenon is called emergence, and this paper mathematically demonstrates that new dynamics can arise in swarm behavior ...
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The variability of the output power of distributed renewable energy sources(DRESs)that originate from the fastchanging climatic conditions can negatively affect the grid ***,grid operators have incorporated ramp-rate ...
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The variability of the output power of distributed renewable energy sources(DRESs)that originate from the fastchanging climatic conditions can negatively affect the grid ***,grid operators have incorporated ramp-rate limitations(RRLs)for the injected DRES power in the grid *** the DRES penetration levels increase,the mitigation of high-power ramps is no longer considered as a system support function but rather an ancillary service(AS).Energy storage systems(ESSs)coordinated by RR control algorithms are often applied to mitigate these power ***,no unified definition of active power ramps,which is essential to treat the RRL as AS,currently *** paper assesses the various definitions for ramp-rate RR and proposes RRL method control for a central battery ESS(BESS)in distribution systems(DSs).The ultimate objective is to restrain high-power ramps at the distribution transformer level so that RRL can be traded as AS to the upstream transmission system(TS).The proposed control is based on the direct control of theΔP/Δt,which means that the control parameters are directly correlated with the RR requirements included in the grid *** addition,a novel method for restoring the state of charge(So C)within a specific range following a high ramp-up/down event is ***,a parametric method for estimating the sizing of central BESSs(BESS sizing for short)is *** BESS sizing is determined by considering the RR requirements,the DRES units,and the load mix of the examined *** BESS sizing is directly related to the constant RR achieved using the proposed ***,the proposed methodologies are validated through simulations in MATLAB/Simulink and laboratory tests in a commercially available BESS.
Roads are an important part of transporting goods and products from one place to another. In developing countries, the main challenge is to maintain road conditions regularly. Roads can deteriorate from time to time. ...
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Since gastric cancer is growing fast, accurate and prompt diagnosis is essential, utilizing computer-aided diagnosis (CAD) systems is an efficient way to achieve this goal. Using methods related to computer vision ena...
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Since gastric cancer is growing fast, accurate and prompt diagnosis is essential, utilizing computer-aided diagnosis (CAD) systems is an efficient way to achieve this goal. Using methods related to computer vision enables more accurate predictions and faster diagnosis, leading to timely treatment. CAD systems can categorize photos effectively using deep learning techniques based on image analysis and classification. Accurate and timely classification of histopathology images is critical for enabling immediate treatment strategies, but remains challenging. We propose a hybrid deep learning and gradient-boosting approach that achieves high accuracy in classifying gastric histopathology images. This approach examines two classifiers for six networks known as pre-trained models to extract features. Extracted features will be fed to the classifiers separately. The inputs are gastric histopathological images. The GasHisSDB dataset provides these inputs containing histopathology gastric images in three 80px, 120px, and 160px cropping sizes. According to these achievements and experiments, we proposed the final method, which combines the EfficientNetV2B0 model to extract features from the images and then classify them using the CatBoost classifier. The results based on the accuracy score are 89.7%, 93.1%, and 93.9% in 80px, 120px, and 160px cropping sizes, respectively. Additional metrics including precision, recall, and F1-scores were above 0.9, demonstrating strong performance across various evaluation criteria. In another way, to approve and see the model efficiency, the GradCAM algorithm was implemented. Visualization via Grad-CAM illustrated discriminative regions identified by the model, confirming focused learning on histologically relevant features. The consistent accuracy and reliable detections across diverse evaluation metrics substantiate the robustness of the proposed deep learning and gradient-boosting approach for gastric cancer screening from histopathology
This work proposes a distributed estimation and control approach in which a team of aerial agents equipped with radio jamming devices collaborate in order to intercept and concurrently track-and-jam a malicious target...
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