An efficient top-k ranking method for service selection based on ε-ADMOPSO algorithm

Yu, Wei; Li, Shijun; Tang, Xiaoyue; Wang, Kai

doi:10.1007/s00521-018-3640-9

Cited by 10 publications

(4 citation statements)

References 38 publications

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“…Some authors use first-order Gaussian filters in various directions to detect the lungs' boundary contours and then use LoG operators of different scales for boundary tracking to find the contours of the lungs. Methods based on specific theories introduce various mathematical theories 4 into image segmentation, such as segmentation methods based on fuzzy theory, segmentation methods based on mathematical morphology, and segmentation methods based on deformation models. 5 This article uses an individual transformation to enhance the CT image's details and uses a parallel U-Net network to improve the image segmentation effect.…”

Section: Methodsmentioning

confidence: 99%

Analysis of the Clinical Characteristics of Tuberculosis Patients based on Multi-Constrained Computed Tomography (CT) Image Segmentation Algorithm

Zhu

Zhang²

2021

Pak J Med Sci

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Objective: We used U-shaped convolutional neural network (U_Net) multi-constraint image segmentation method to compare the diagnosis and imaging characteristics of tuberculosis and tuberculosis with lung cancer patients with Computed Tomography (CT). Methods: We selected 160 patients with tuberculosis from the severity scoring (SVR) task is provided by Image CLEF Tuberculosis 2019. According to the type of diagnosed disease, they were divided into tuberculosis combined with lung cancer group and others group, all patients were given chest CT scan, and the clinical manifestations, CT characteristics, and initial suspected diagnosis and missed diagnosis of different tumor diameters were observed and compared between the two groups. Results: There were more patients with hemoptysis and hoarseness in pulmonary tuberculosis combined with lung cancer group than in the pulmonary others group (P<0.05), and the other symptoms were not significantly different (P>0.05). Tuberculosis combined with lung cancer group had fewer signs of calcification, streak shadow, speckle shadow, and cavitation than others group; however, tuberculosis combined with lung cancer group had more patients with mass shadow, lobular sign, spines sign, burr sign and vacuole sign than others group. Conclusion: The symptoms of hemoptysis and hoarseness in pulmonary tuberculosis patients need to consider whether the disease has progressed and the possibility of lung cancer lesions. CT imaging of pulmonary tuberculosis patients with lung cancer usually shows mass shadows, lobular signs, spines signs, burr signs, and vacuoles signs. It can be used as the basis for its diagnosis. Simultaneously, the U-Net-based segmentation method can effectively segment the lung parenchymal region, and the algorithm is better than traditional algorithms. doi: https://doi.org/10.12669/pjms.37.6-WIT.4795 How to cite this:Zhu F, Zhang B. Analysis of the Clinical Characteristics of Tuberculosis Patients based on Multi-Constrained Computed Tomography (CT) Image Segmentation Algorithm. Pak J Med Sci. 2021;37(6):1705-1709. doi: https://doi.org/10.12669/pjms.37.6-WIT.4795 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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Section: Methodsmentioning

confidence: 99%

Analysis of the Clinical Characteristics of Tuberculosis Patients based on Multi-Constrained Computed Tomography (CT) Image Segmentation Algorithm

Zhu

Zhang²

2021

Pak J Med Sci

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“…Similar works are from [123, 124]. Yu et al [125] transformed the top‐k ranking task into a multi‐objective programming problem when user preferences are considered along with user queries. Then an improved discrete PSO is proposed to make the aggregate rankings satisfy user queries and user preferences both.…”

Section: Nature‐inspired Computing (Nic) Approaches For Web Service Cmentioning

confidence: 99%

Advances on QoS‐aware web service selection and composition with nature‐inspired computing

Zhao

Zuo

2019

CAAI Transactions on Intelligence Technology

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“…The application range of the optimization results has significant limitations. It is difficult to apply to the actual control [1]. Real-time optimization is only optimized for the energy flow control of the vehicle's instantaneous operating conditions and is not subject to the overall restriction of the specific operating cycle.…”

Section: Introductionmentioning

confidence: 99%

Evaluation of vehicle engine thermal energy system detection effect based on target detection algorithm

et al. 2021

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The paper takes the front-mounted parallel structure of the transmission as an example and uses the target detection algorithm to introduce a real-time equivalent energy consumption control strategy for the vehicle engine thermal energy system. Based on studying the relationship between fuel thermal energy and electrical energy consumed when the vehicle is driving in a cycle, we elaborated on the strategy?s critical issue, namely, the equivalent method of the electrical energy of the battery pack and the fuel thermal energy consumption of the engine. Finally, the thesis carries out a simulation test on this strategy based on the vehicle simulation model and compares it with other control strategies.

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An efficient top-k ranking method for service selection based on ε-ADMOPSO algorithm

Cited by 10 publications

References 38 publications

Analysis of the Clinical Characteristics of Tuberculosis Patients based on Multi-Constrained Computed Tomography (CT) Image Segmentation Algorithm

Analysis of the Clinical Characteristics of Tuberculosis Patients based on Multi-Constrained Computed Tomography (CT) Image Segmentation Algorithm

Advances on QoS‐aware web service selection and composition with nature‐inspired computing

Evaluation of vehicle engine thermal energy system detection effect based on target detection algorithm

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