Traditionally, pneumonia detection relies on experts to analyze chest X-ray images, which is time-consuming for the healthcare system. Using AI technology to analyze the images beforehand enhances efficiency because i...
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Artificial intelligence (AI) in healthcare, especially in medical imaging, faces challenges due to data scarcity and privacy concerns. Addressing these, we introduce Med-DDPM, a diffusion model designed for 3D semanti...
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Object detection is a significant method in computer vision, mainly for detecting objects belonging to different classes in an image. Its applications are widely spread to video surveillance, human tracking, autonomou...
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Automatic detection of pathology in images can help in reducing the workload of pathologists and speed up the diagnosis. Advancements in medical imaging technologies have enabled high-quality visualization of tissue s...
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The integration of edge computing is critical to the development of Beyond 5G (B5G) and 6G networks, as the volume of data and processing demands continue to rise. Using the radio access network (RAN), mobile edge com...
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In the contemporary era,the global expansion of electrical grids is propelled by various renewable energy sources(RESs).Efficient integration of stochastic RESs and optimal power flow(OPF)management are critical for n...
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In the contemporary era,the global expansion of electrical grids is propelled by various renewable energy sources(RESs).Efficient integration of stochastic RESs and optimal power flow(OPF)management are critical for network *** study introduces an innovative solution,the Gaussian Bare-Bones Levy Cheetah Optimizer(GBBLCO),addressing OPF challenges in power generation systems with stochastic *** primary objective is to minimize the total operating costs of RESs,considering four functions:overall operating costs,voltage deviation management,emissions reduction,voltage stability index(VSI)and power loss ***,a carbon tax is included in the objective function to reduce carbon *** scrutiny,using modified IEEE 30-bus and IEEE 118-bus systems,validates GBBLCO’s superior performance in achieving optimal *** results demonstrate GBBLCO’s efficacy in six optimization scenarios:total cost with valve point effects,total cost with emission and carbon tax,total cost with prohibited operating zones,active power loss optimization,voltage deviation optimization and enhancing voltage stability index(VSI).GBBLCO outperforms conventional techniques in each scenario,showcasing rapid convergence and superior solution ***,GBBLCO navigates complexities introduced by valve point effects,adapts to environmental constraints,optimizes costs while considering prohibited operating zones,minimizes active power losses,and optimizes voltage deviation by enhancing the voltage stability index(VSI)*** research significantly contributes to advancing OPF,emphasizing GBBLCO’s improved global search capabilities and ability to address challenges related to local *** emerges as a versatile and robust optimization tool for diverse challenges in power systems,offering a promising solution for the evolving needs of renewable energy-integrated power grids.
Maritime transportation,a cornerstone of global trade,faces increasing safety challenges due to growing sea traffic *** study proposes a novel approach to vessel trajectory prediction utilizing Automatic Identificatio...
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Maritime transportation,a cornerstone of global trade,faces increasing safety challenges due to growing sea traffic *** study proposes a novel approach to vessel trajectory prediction utilizing Automatic Identification System(AIS)data and advanced deep learning models,including Long Short-Term Memory(LSTM),Gated Recurrent Unit(GRU),Bidirectional LSTM(DBLSTM),Simple Recurrent Neural Network(SimpleRNN),and Kalman *** research implemented rigorous AIS data preprocessing,encompassing record deduplication,noise elimination,stationary simplification,and removal of insignificant *** were trained using key navigational parameters:latitude,longitude,speed,and *** aware processing through trajectory segmentation and topological data analysis(TDA)was employed to capture dynamic *** using a three-month AIS dataset demonstrated significant improvements in prediction *** GRU model exhibited superior performance,achieving training losses of 0.0020(Mean Squared Error,MSE)and 0.0334(Mean Absolute Error,MAE),with validation losses of 0.0708(MSE)and 0.1720(MAE).The LSTM model showed comparable efficacy,with training losses of 0.0011(MSE)and 0.0258(MAE),and validation losses of 0.2290(MSE)and 0.2652(MAE).Both models demonstrated reductions in training and validation losses,measured by MAE,MSE,Average Displacement Error(ADE),and Final Displacement Error(FDE).This research underscores the potential of advanced deep learning models in enhancing maritime safety through more accurate trajectory predictions,contributing significantly to the development of robust,intelligent navigation systems for the maritime industry.
Radio-Frequency IDentification(RFID)technology is an essential enabler of a multitude of intelligent *** robust authentication of RFID system components is critical in providing trustworthy data delivery from/to *** t...
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Radio-Frequency IDentification(RFID)technology is an essential enabler of a multitude of intelligent *** robust authentication of RFID system components is critical in providing trustworthy data delivery from/to *** this paper,we propose an authentication protocol based on monitoring the transmissions between readers and tags in the *** proposed authentication scheme is based on injecting decoys within the exchanged communications(between RFID readers and tags)and is used in the authentication ***,the proposed authentication scheme is mathematically modeled and validated using extensive *** simulations results show that the proposed scheme provides a 100%confidence level in the authentication of tags and detection of compromised readers.
In cryptography,oblivious transfer(OT)is an important multiparty cryptographic primitive and protocol,that is suitable for many upperlayer applications,such as secure computation,remote coin-flipping,electrical contra...
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In cryptography,oblivious transfer(OT)is an important multiparty cryptographic primitive and protocol,that is suitable for many upperlayer applications,such as secure computation,remote coin-flipping,electrical contract signing and exchanging secrets ***,some nogo theorems have been established,indicating that one-out-of-two quantum oblivious transfer(QOT)protocols with unconditional security are ***,some one-out-of-two QOT protocols using the concept of Crepeau’s reduction have been demonstrated not to conform to Lo’s no-go theorem,but these protocols require more quantum resources to generate classical keys using all-or-nothing QOT to construct one-out-of-two *** paper proposes a novel and efficient one-out-of-two QOT which uses quantum resources directly instead of wasting unnecessary resources to generate classical *** proposed protocol is not covered by Lo’s no-go theorem,and it is able to check the sender’s loyalty and avoid the attack from the ***,the entangled state of the proposed protocol is reusable,so it can provide more services for the participants when *** with otherQOT protocols,the proposed protocol is more secure,efficient,and flexible,which not only can prevent external and internal attacks,but also reduce the required resources and resource distribution time.
This document discusses various techniques that are crucial for 5G mobile communication. These techniques include high-frequency transmission, direct communication, device-to-device (D2D) communication and massive mul...
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