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An Enhanced Lung Cancer Detection Approach Using Dual-Model Deep Learning Technique

Computer Modeling in Engineering & Sciences 2025年第1期142卷 835-867页

作者： Sumaia Mohamed Elhassan Saad Mohamed Darwish Saleh Mesbah Elkaffas Department of Information Technology Institute of Graduate Studies and ResearchAlexandria UniversityAlexandria21526Egypt College of Computing and Information Technology Arab Academy for ScienceTechnology and Maritime TransportAlexandriaP.O.Box 1029Egypt

Lung cancer continues to be a leading cause of cancer-related deaths worldwide,emphasizing the critical need for improved diagnostic *** detection of lung tumors significantly increases the chances of successful treatment and ***,current diagnostic methods often fail to detect tumors at an early stage or to accurately pinpoint their location within the lung ***-model deep learning technologies for lung cancer detection,while beneficial,cannot capture the full range of features present in medical imaging data,leading to incomplete or inaccurate ***,it may not be robust enough to handle the wide variability in medical images due to different imaging conditions,patient anatomy,and tumor *** overcome these disadvantages,dual-model or multi-model approaches can be *** research focuses on enhancing the detection of lung cancer by utilizing a combination of two learning models:a Convolutional Neural Network(CNN)for categorization and the You Only Look Once(YOLOv8)architecture for real-time identification and pinpointing of *** automatically learn to extract hierarchical features from raw image data,capturing patterns such as edges,textures,and complex structures that are crucial for identifying lung ***8 incorporates multiscale feature extraction,enabling the detection of tumors of varying sizes and scales within a single *** is particularly beneficial for identifying small or irregularly shaped tumors that may be challenging to ***,through the utilization of cutting-edge data augmentation methods,such as Deep Convolutional Generative Adversarial Networks(DCGAN),the suggested approach can handle the issue of limited data and boost the models’ability to learn from diverse and comprehensive *** combined method not only improved accuracy and localization but also ensured efficient real-time processing,which is crucial for practical clinical applicati

关键词： Lung cancer detection dual-model deep learning technique data augmentation CNN YOLOv8

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Monogenic gene therapy for glaucoma and optic nerve injury

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Neural Regeneration research 2025年第3期20卷 815-816页

作者： Chikako Harada Xiaoli Guo Takayuki Harada Visual research Project Tokyo Metropolitan Institute of Medical ScienceTokyoJapan

The prevalence of glaucoma, the second leading cause of global blindness, is increasing due to aging populations. In glaucoma, degeneration of the optic nerve and retinal ganglion cells(RGCs) causes visual field defec... 详细信息

关键词： visual glaucoma degeneration

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Asking one mechanism in glial cells during neuroinflammation

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Neural Regeneration research 2025年第4期20卷 1077-1078页

作者： Xiaoli Guo Chikako Harada Takayuki Harada Visual research Project Tokyo Metropolitan Institute of Medical ScienceTokyoJapan

Multiple sclerosis(MS),which is characterized by inflammatory demyelination in the central nervous system(CNS),is the most common neurological disease in the young adult *** autoimmune encephalomyelitis(EAE),an animal model of MS,is often used in preclinical *** data indicate that in addition to immune cells such as T cells and dendritic cells,CNS resident microglia and astrocytes play important roles in demyelinating neuroinflammation(Healy et al.,2022).In particular,microglia are key immune-competent cells that can respond to environmental *** depletion of transforming growth factor-β-activated kinase 1,a mitogen-associated protein kinase kinase kinase,in microglia is reported to reduce CNS inflammation and diminish axonal and myelin damage *** suggests that elucidating the mechanisms of microglia-specific responses during pathologies may help in the development of treatments that reduce EAE/MS disease severity(Goldmann et al.,2013).

关键词： inflammation clinical

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Glia-to-neuron reprogramming to the rescue?

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Neural Regeneration research 2025年第5期20卷 1395-1396页

作者： Jack W.Hickmott Cindi M.Morshead Department of Surgery University of TorontoTorontoONCanada Donnelly Centre for Cellular and Biomolecular research TorontoONCanada institute of Biomedical Engineering University of TorontoTorontoONCanada The KITE research institute Toronto Rehabilitation InstituteUniversity Health NetworkTorontoONCanada

Over the last two decades,the dogma that cell fate is immutable has been increasingly challenged,with important implications for regenerative *** brea kth rough discovery that induced pluripotent stem cells could be generated from adult mouse fibroblasts is powerful proof that cell fate can be *** exciting extension of the discovery of cell fate impermanence is the direct cellular reprogram ming hypothesis-that terminally differentiated cells can be reprogrammed into other adult cell fates without first passing through a stem cell state.

关键词： programming passing proof

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Dispersed Computing Resource Discovery Model and Algorithm for Polymorphic Migration Network Architecture

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Chinese Journal of Electronics 2023年第4期32卷 821-839页

作者： ZHOU Chengcheng ZHANG Lukai ZENG Guangping LIN Fuhong School of Computer and Communication Engineering University of Science and Technology Beijing transport planning and research institute Ministry of Transport

Dynamic resource discovery in a network of dispersed computing resources is an open problem. The establishment and maintenance of resource pool information are critical, which involves both the polymorphic migration of the network and the time and energy costs resulting from node selection and frequent interactions of information between nodes. The resource discovery problem for dispersed computing can be considered a dynamic multi-level decision problem. A bi-level programming model of dispersed computing resource discovery is developed, which is driven by time cost, energy consumption and accuracy of information acquisition. The upper-level model is to design a reasonable network structure of resource discovery, and the lower-level model is to explore an effective discovery mode. Complex network topology features are used for the first time to analyze the polymorphic migration characteristics of resource discovery networks. We propose an integrated calibration method for energy consumption parameters based on two discovery modes(i.e., agent mode and self-directed mode). A symmetric trust region based heuristic algorithm is proposed for solving the system model. The numerical simulation is performed in a dispersed computing network with multiple modes and topological states, which proves the feasibility of the model and the effectiveness of the algorithm.

关键词： Energy consumption Costs Computational modeling Heuristic algorithms Complex networks Programming Numerical simulation

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A Study on Kinematics Characteristics of Freak Wave

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China Ocean Engineering 2013年第3期27卷 391-402页

作者：崔成张宁川左书华房卓 State Key Laboratory of Coastal and Offshore Engineering Dalian University of Technology Tianjin research institute for Water transport Engineering M.O.T. transport planning and research institute M.O.T.

Based on the 3rd-order Stokes wave theory, the speed of freak waves is formulated in terms of the period and the wave height. Finite modified wave steepness gives rise to a significant enhancement of the nonlinear contributions to the freak wave speed in comparison with the 3rd-order Stokes wave theory. For a fix modified wave steepness, the estimated amplification of the nonlinear contributions due to the deviation from the 3rd-order Stokes wave theory is 0.22-0.99. In addition, the velocity and acceleration fields are also documented in detail. In the present simulation, the horizontal velocities are smaller than the wave speed, and the freak wave exhibits a maximal horizontal velocity up to 37% of the wave speed and a maximal vertical acceleration up to about 20% of the gravitational acceleration.

关键词： freak wave speed velocity acceleration

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A Combination Prediction Model for Short Term Travel Demand of Urban Taxi

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Computers, Materials & Continua 2024年第6期79卷 3877-3896页

作者： Mingyuan Li Yuanli Gu Qingqiao Geng Hongru Yu School of Traffic and transportation Beijing Jiaotong UniversityBeijing100044China transport planning and research institute Ministry of TransportBeijing100028China

This study proposes a prediction model considering external weather and holiday factors to address the issue of accurately predicting urban taxi travel demand caused by complex data and numerous influencing *** model integrates the Complete Ensemble Empirical Mode Decomposition with Adaptive Noise(CEEMDAN)and Convolutional Long Short Term Memory Neural Network(ConvLSTM)to predict short-term taxi travel *** CEEMDAN decomposition method effectively decomposes time series data into a set of modal components,capturing sequence characteristics at different time scales and *** on the sample entropy value of components,secondary processing of more complex sequence components after decomposition is employed to reduce the cumulative prediction error of component sequences and improve prediction *** this basis,considering the correlation between the spatiotemporal trends of short-term taxi traffic,a ConvLSTM neural network model with Long Short Term Memory(LSTM)time series processing ability and Convolutional Neural Networks(CNN)spatial feature processing ability is constructed to predict the travel demand for urban *** combined prediction model is tested on a taxi travel demand dataset in a certain area of *** results show that the CEEMDAN-ConvLSTM prediction model outperforms the LSTM,Autoregressive Integrated Moving Average model(ARIMA),CNN,and ConvLSTM benchmark models in terms of Symmetric Mean Absolute Percentage Error(SMAPE),Root Mean Square Error(RMSE),Mean Absolute Error(MAE),and R2 ***,the SMAPE metric exhibits a remarkable decline of 21.03%with the utilization of our proposed *** results confirm that our study provides a highly accurate and valid model for taxi travel demand forecasting.

关键词： Urban transport taxi travel demand prediction CEEMDAN-ConvLSTM modal components

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Policy Iteration for Optimal Control of Discrete-Time Time-Varying Nonlinear Systems

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IEEE/CAA Journal of Automatica Sinica 2023年第3期10卷 781-791页

作者： Guangyu Zhu Xiaolu Li Ranran Sun Yiyuan Yang Peng Zhang Beijing research Center of Urban Traffic Information Sensing and Service Technologies Key Laboratory of transport Industry of Big Data Application Technologies for Comprehensive transport Beijing Jiaotong UniversityBeijing 100044China transport planning and research institute Ministry of TransportChinaBeijing 100028China

Aimed at infinite horizon optimal control problems of discrete time-varying nonlinear systems,in this paper,a new iterative adaptive dynamic programming algorithm,which is the discrete-time time-varying policy iteration(DTTV)algorithm,is *** iterative control law is designed to update the iterative value function which approximates the index function of optimal *** admissibility of the iterative control law is *** results show that the iterative value function is non-increasingly convergent to the Bellman-equation optimal *** implement the algorithm,neural networks are employed and a new implementation structure is established,which avoids solving the generalized Bellman equation in each ***,the optimal control laws for torsional pendulum and inverted pendulum systems are obtained by using the DTTV policy iteration algorithm,where the mass and pendulum bar length are permitted to be time-varying *** effectiveness of the developed method is illustrated by numerical results and comparisons.

关键词： Adaptive critic designs adaptive dynamic programming approximate dynamic programming optimal control policy iteration time-varying

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Road traffic congestion measurement considering impacts on travelers

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Journal of Modern transportation 2013年第1期21卷 28-39页

作者： Liang Ye Ying Hui Dongyuan Yang transport planning and research institute Ministry of Transport of China School of transportation Engineering Tongji University

The article intends to find a method to quantify traffic congestion＇s impacts on travelers to help transportation planners and policy decision makers well understand congestion situations. Three new congestion indicators, including transportation environment satisfaction （TES）, travel time satisfaction （TTS）, and traffic congestion frequency and feeling （TCFF）, are defined to estimate urban traffic congestion based on travelers＇ feelings. Data of travelers＇ attitude about congestion and trip information were collected from a survey in Shanghai, China. Based on the survey data, we estimated the value of the three indi- cators. Then, the principal components analysis was used to derive a small number of linear combinations of a set of variables to estimate the whole congestion status. A linear regression model was used to find out the significant variables which impact respondents＇ feelings. Two ordered logit models were used to select significant variables of TES and TTS. Attitudinal factor variables were also used in these models. The results show that attitudinal factor variables and cluster category variables are as important as sociodemographic variables in the models. Using the three congestion indicators, the government can collect travelers＇ feeling about traffic congestion and estimate the transportation policy that might be applied to cope with traffic congestion.

关键词： Traffic congestion indicator Attitudinalfactor variable Linear regression model - Ordered logitmodel

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Effect of organic materials on the chemical properties of saline soil in the Yellow River Delta of China

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Frontiers of Earth Science 2015年第2期9卷 259-267页

作者： Yan YU Jie LIU Chunmeng LIU Shuang ZONG Zhaohua LU School of Chemical and Environmental Engineering China University of Mining and Technology (Beijing) Beijing 100083 China transport planning and research institute Ministry of Transport Beijing 100028 China

A 180-day incubation experiment was con- ducted to investigate the effect of different organic materials on the chemical properties of coastal soil with high salinity and relatively low pH. Four organic materials （three kinds of plant residues： straw, composted straw, and fresh reed; and one kind of poultry manure： chicken manure） were applied at a ratio of 15 g·kg^-1 to samples of costal saline soil from the Yellow River Delta of China. The results showed that the soil pH and exchangeable sodium percentage （ESP） decreased, whereas soil cation exchangeable capacity （CEC） and macronutrient concen- trations increased, regardless of the type of organic material used. All treatments showed a remarkable increase in soil soluble organic carbon （SOC） during the 180-day incubation. The peak values of SOC in descend- ing order were chicken manure, reed, composted straw, straw, and control soil. At the end of incubation, the highest level of SOC occurred in the straw-amended soil, followed by composted straw, reed, and chicken manure- amended soils. Soil respiration rate and available nitrogen were significantly influenced by the type of material used. Although reed-amended soil had a relatively high SOC and respiration rate, the ESP was reduced the least. Consider- ing the possible risk of heavy metals caused by chicken manure, it is proposed that straw and composted straw are the more efficient materials to use for reclaiming costal saline soil and improving the availability of macronu- trients.

关键词： organic material soil organic carbon salt-affected soil ESP respiration rate

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