The uncertainty issue in real-work optimization affects the level of optimization significantly. Because most future uncertainties cannot be foreseen in advance, the optimization must take the uncertainties as a risk ...
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Accurate recognition of food items along with quality assessment is of paramount importance in the agricultural industry. Such automated systems can speed up the wheel of the food processing sector and save tons of ma...
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We use electro-optically modulated ring cavities, integrated on thin-film lithium niobate, to model frequency dimension tight-binding lattices with versatile connectivity. Inter-mode coupling range, strength, and hopp...
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Vehicular Adhoc Networks (VANETs) provide communication among vehicles to build smart cities using Intelligent Transportation System (ITS). In this paper, we proposed Delay Tolerant and Multipath Reliability (DTMR) in...
Vehicular Adhoc Networks (VANETs) provide communication among vehicles to build smart cities using Intelligent Transportation System (ITS). In this paper, we proposed Delay Tolerant and Multipath Reliability (DTMR) in VANETs. The simulation of the DTMR method is performed using OMNet++ network simulator with Simulation of Urban Mobility (SUMO). The parameters which are considered for the performance analysis are end-to-end delay, data failure rate, data success rate and throughput. The results show that the DTMR method produces 85ms lower end-to-end delay, 13% lower data failure rate, 93 % higher data success rate and 614 Kbps higher throughput. The proposed DTMR method has better overall performance than the ISFF and VDPR methods.
Cloud-aided mobile edge networks (CAMENs) allow edge servers (ESs) to purchase resources from remote cloud servers (CSs), while overcoming resource shortage when handling computation-intensive tasks of mobile users (M...
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This study proposes an anti-slip control system for electric trains based on the fuzzy logic theory, which prevents the wheels from slipping during the acceleration and simultaneously tracks the desired speed profile....
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Microsatellite instability (MSI) is a pivotal genetic marker influencing the efficacy of immunotherapy in colorectal cancer. Traditional MSI examination often requires additional genetic or immunohistochemical tests, ...
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ISBN:
(数字)9798331518622
ISBN:
(纸本)9798331518639
Microsatellite instability (MSI) is a pivotal genetic marker influencing the efficacy of immunotherapy in colorectal cancer. Traditional MSI examination often requires additional genetic or immunohistochemical tests, whereas histology images, widely available in colorectal cancer diagnosis, offer a valuable alternative for MSI prediction. Although Transformer-based models have demonstrated promising outcomes in predicting MSI from histology images, they are hampered by traditional local attention mechanisms that struggle to capture long-range interdependencies and establish a comprehensive global receptive field. In this study, we introduce DiNAT-MSI, a novel framework for histology-based MSI prediction that incorporates the Dilated Neighborhood Attention Transformer (DiNAT). This model enhances global context recognition and substantially expands receptive fields, all without additional computational burden. Our results demonstrate that DiNAT-MSI achieves a superior patientwise AUROC compared to ResNet18 and Swin Transformer, along with commendable explainability. Our work not only illustrates a more accessible diagnostic tool for leveraging histological data but also underscores the potential of Transformerbased models with sophisticated attention designs in advancing precision medicine for colorectal cancer patients.
Future wireless systems are envisioned to utilize the large spectra available at THz bands for wireless communications. Extremely massive multiple-input multiple-output (MIMO) antennas can be costly and power ineffici...
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Aiming to support a cross-sector and cross-border eGovernance paradigm for sharing common public services, this paper introduces an AI-enhanced solution that enables beneficiaries to participate in a decentralized net...
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The impact of Artificial Intelligence (AI) on health care has been dramatic;however, there is a considerable degree of skepticism among clinicians about the real-world applicability of advanced predictive models;for t...
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