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Endoscopy-assisted lightweight diagnosis system based on transformers for colon polyp detection

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Optoelectronics Letters 2025年第1期21卷 57-64页

作者： FAN Weiming YU Jiahui JU Zhaojie School of Automation and Electrical Engineering Shenyang Ligong University department of Biomedical Engineering Zhejiang University School of Computing University of Portsmouth

The integration of endoscopy has significantly propelled the diagnosis and treatment of gastrointestinal diseases, with colonoscopy establishing itself as the primary method for early diagnosis and preventive care in colorectal cancer(CRC). Although deep learning holds promise in mitigating missed polyp rates, modern endoscopy examinations pose additional challenges, such as image blurring and atomizing. This study explores lightweight yet powerful attention mechanisms, introducing the spatial-channel transformer(SCT), an innovative approach that leverages spatial channel relationships for attention weight calculation. The method utilizes rotation operations for inter-dimensional dependencies, followed by residual transformation, encoding inter-channel and spatial information with minimal computational overhead. Extensive experiments on the CVC-Clinic DB polyp detection dataset, addressing endoscopy pitfalls, underscore the superiority of our SCT over other state-of-the-art methods. The proposed model maintains high performance, even in challenging scenarios.

关键词： Endoscopy

Collective Resources as a Precursor for Educating Children Toward a Sustainable Global World

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ECNU Review of Education 2019年第4期2卷 396-420页

作者： Jonna Larsson Ingrid Pramling Samuelsson department of Education Communication and LearningUniversity of GothenburgS-40530 GothenburgSweden University of Gothenburg

Purpose:Preserving and caring for nature in a sustainable way has long been part of Swedish preschool ***,recently has it been explicitly referenced in the Swedish preschool curriculum with the goal of incorporating sustainability holistically and coherently in all areas of children’s daily preschool experiences through play,care,and *** has revealed a potential roadblock to achieving this goal;the difficulty connecting the three inextricably linked dimensions of sustainability:ecological,social-cultural,and *** purpose is to generate knowledge about preschool teachers’professional understanding of education for sustainable development(ESD)in early childhood education(ECE)by implementing and enhancing the operationalization of such work in four Swedish ***/Approach/Methods:The design of the study rests on the involvement of teachers in work where they created sustainability activities supported by the Environmental Rating Scale for Sustainable Development in Early Childhood(ERS-SDEC).The data consist of teachers’narratives and interviews,and a qualitative content analysis is used from which a number of themes ***:The initial interviews foregrounded three themes:the value of collective resources,the wonders of nature,and a global *** the end of the project,the teachers’expressions of their practice revealed three qualitatively transformed themes:broadened awareness of sustainability,ecology embracing culture,and expanded perspectives,as factors of ***/Value:Teachers did increase their awareness of working with children and expressed a strength in using each other as collective *** that,their professional understandings of ESD in preschool developed.

关键词： Collective resources preschool education professional understanding sustainability

Relationship between Science Teaching Practices and Students’Achievement in Singapore,Chinese Taipei,and the US:An Analysis Using TIMSS 2011 Data

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Frontiers of Education in China 2014年第4期9卷 519-551页

作者： Su GAO department of Teaching&learning University of NevadaLas VegasNV 89154-3005USA

The assumption that inquiry-based instruction is more effective in influencing student science achievement than traditional didactic teaching has been the driving force of science education reform in recent decades and in many ***,the empirical relationship between these two kinds of science teaching and student science performance is not soundly established,which is worth a careful *** through the theoretical perspectives of inquiry-based instruction and culturally relevant pedagogy,using a two-level hierarchical linear modeling(HLM)approach and simultaneous multiple regression,this study examines the above relationship using the Trends in International Mathematics and Science Study(TIMSS)20118th grade dataset from Singapore,Chinese Taipei,and the *** study found that for the low-performing students,none of the inquiry-based teaching practice items measured had a significant relationship with the science achievements at any performance levels of students in any country/region except for the case of two inquiry-based teaching practice items that were positively related to Chinese Taipei students’*** didactic teaching practice items were associated with the Singapore students’science achievement,three of these practice items were found negatively related to Chinese Taipei students’science achievement,and one traditional didactic teaching practice was negatively related to the science achievement of ***,for medium-and high-performing students,none of these inquiry-based or traditional didactic science-teaching practices were found to be positive predictors of science performance in all three countries/***,in the case of Chinese Taipei,one didactic teaching practice item was negatively related with the medium level performing students’achievement and two didactic teaching practices were found to hinder high-performing students’science achievements.

关键词： inquiry-based teaching practice didactic teaching practice science achievement international comparison

Stability Prediction in Smart Grid Using PSO Optimized XGBoost Algorithm with Dynamic Inertia Weight Updation

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Computer Modeling in Engineering & Sciences 2025年第1期142卷 909-931页

作者： Adel Binbusayyis Mohemmed Sha department of Software Engineering College of Computer Engineering and Sciences in Al-Kharj Prince Sattam Bin Abdulaziz UniversityAl-Kharj11942Saudi Arabia

Prediction of stability in SG(Smart Grid)is essential in maintaining consistency and reliability of power supply in grid *** the fluctuations in power generation and consumption patterns of smart cities assists in effectively managing continuous power supply in the *** also possesses a better impact on averting overloading and permitting effective energy *** though many traditional techniques have predicted the consumption rate for preserving stability,enhancement is required in prediction measures with minimized *** overcome the complications in existing studies,this paper intends to predict stability from the smart grid stability prediction dataset using machine learning *** accomplish this,pre-processing is performed initially to handle missing values since it develops biased models when missing values are mishandled and performs feature scaling to normalize independent data ***,the pre-processed data are taken for training and *** that,the regression process is performed using Modified PSO(Particle Swarm Optimization)optimized XGBoost Technique with dynamic inertia weight update,which analyses variables like gamma(G),reaction time(tau1–tau4),and power balance(p1–p4)for providing effective future stability in *** PSO attains optimal solution by adjusting position through dynamic inertial weights,it is integrated with XGBoost due to its scalability and faster computational speed *** hyperparameters of XGBoost are fine-tuned in the training process for achieving promising outcomes on *** results are measured through evaluation metrics such as MSE(Mean Square Error)of 0.011312781,MAE(Mean Absolute Error)of 0.008596322,and RMSE(Root Mean Square Error)of 0.010636156 and MAPE(Mean Absolute Percentage Error)value of 0.0052 which determine the efficacy of the system.

关键词： Smart Grid machine learning particle swarm optimization XGBoost dynamic inertia weight update

Explainable Artificial Intelligence Solution for Online Retail

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Computers, Materials & Continua 2022年第6期71卷 4425-4442页

作者： Kumail Javaid Ayesha Siddiqa Syed Abbas Zilqurnain Naqvi Allah Ditta Muhammad Ahsan M.A.Khan Tariq Mahmood Muhammad Adnan Khan department of Computer Science University of South AsiaLahore54000Pakistan department of Mechatronics and Control Engineering University of Engineering and TechnologyLahore54000Pakistan department of Information Sciences Division of Science and TechnologyUniversity of EducationLahore54000Pakistan Riphah School of Computing and Innovation Faculty of ComputingRiphah International UniversityLahore CampusLahore54000Pakistan Division of Science and Technology University of EducationLahore54000Pakistan Pattern Recognition and machine learning Lab Department of SoftwareGachon UniversitySeongnam13557Korea

Artificial intelligence(AI)and machine learning(ML)help in making predictions and businesses to make key decisions that are beneficial for *** the case of the online shopping business,it’s very important to find trends in the data and get knowledge of features that helps drive the success of the *** this research,a dataset of 12,330 records of customers has been analyzedwho visited an online shoppingwebsite over a period of one *** main objective of this research is to find features that are relevant in terms of correctly predicting the purchasing decisions made by visiting customers and build ML models which could make correct predictions on unseen data in the *** permutation feature importance approach has been used to get the importance of features according to the output variable(Revenue).Five ML models i.e.,decision tree(DT),random forest(RF),extra tree(ET)classifier,Neural networks(NN),and Logistic regression(LR)have been used to make predictions on the unseen data in the *** performance of each model has been discussed in detail using performance measurement techniques such as accuracy score,precision,recall,F1 score,and ROC-AUC *** model is the bestmodel among all five chosen based on accuracy score of 90%and F1 score of 79%followed by extra tree ***,our study indicates that RF model can be used by online retailing businesses for predicting consumer buying *** research also reveals the importance of page value as a key feature for capturing online purchasing *** may give a clue to future businesses who can focus on this specific feature and can find key factors behind page value success which in turn will help the online shopping business.

关键词： Explainable artificial intelligence online retail neural network random forest regression

Rice Leaves Disease Diagnose Empowered with Transfer learning

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Computer Systems Science & Engineering 2022年第9期42卷 1001-1014页

作者： Nouh Sabri Elmitwally Maria Tariq Muhammad Adnan Khan Munir Ahmad Sagheer Abbas Fahad Mazaed Alotaibi College of Computer and Information Sciences Jouf UniversitySakaka72341Saudi Arabia department of Computer Science Faculty of Computers and Artificial IntelligenceCairo University12613Egypt School of Computer Science National College of Business Administration and EconomicsLahore54000Pakistan department of Computer Science Lahore Garrison UniversityLahore54000Pakistan Pattern Recognition and machine learning Lab Department of SoftwareGachon UniversitySeongnam13557Korea department of Information System Faculty of Computing and Information TechnologyKing Abdulaziz UniversityJeddah21589Saudi Arabia

In the agricultural industry,rice infections have resulted in significant productivity and economic *** infections must be recognized early on to regulate and mitigate the effects of the *** diagnosis of disease severity effects or incidence can preserve production from quantitative and qualitative losses,reduce pesticide use,and boost ta country’s *** the health of a rice plant through its leaves is usually done as a manual ocular *** this manuscript,three rice plant diseases:Bacterial leaf blight,Brown spot,and Leaf smut,were identified using the Alexnet *** research shows that any reduction in rice plants will have a significant beneficial impact on alleviating global food hunger by increasing supply,lowering prices,and reducing production's environmental impact that affects the economy of any *** would be able to get more exact and faster results with this technology,allowing them to administer the most acceptable treatment *** Using Alex Net,the proposed approach achieved a 99.0%accuracy rate for diagnosing rice leaves disease.

关键词： Rice bacterial leaf blight brown spot leaf smut machine learning alexnet

Targeting TrkB–PSD-95 coupling to mitigate neurological disorders

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Neural Regeneration Research 2025年第3期20卷 715-724页

作者： Xin Yang Yu-Wen Alvin Huang John Marshall department of Molecular Biology Cell Biology and BiochemistryBrown UniversityProvidenceRIUSA department of Neurology Warren Alpert Medical School of Brown UniversityProvidenceRIUSA Center for Translational Neuroscience Robert J.and Nancy D.Carney Institute for Brain Science and Brown Institute for Translational ScienceBrown UniversityProvidenceRIUSA

Tropomyosin receptor kinase B(TrkB)signaling plays a pivotal role in dendritic growth and dendritic spine formation to promote learning and *** activity-dependent release of brain-derived neurotrophic factor at synapses binds to pre-or postsynaptic TrkB resulting in the strengthening of synapses,reflected by long-term ***,the association of postsynaptic density protein-95 with TrkB enhances phospholipase Cγ-Ca^(2+)/calmodulin-dependent protein kinaseⅡand phosphatidylinositol 3-kinase-mechanistic target of rapamycin signaling required for long-term *** this review,we discuss TrkB-postsynaptic density protein-95 coupling as a promising strategy to magnify brain-derived neurotrophic factor signaling towards the development of novel therapeutics for specific neurological disorders.A reduction of TrkB signaling has been observed in neurodegenerative disorders,such as Alzheimer's disease and Huntington's disease,and enhancement of postsynaptic density protein-95 association with TrkB signaling could mitigate the observed deficiency of neuronal connectivity in schizophrenia and *** with brain-derived neurotrophic factor is problematic,due to poor pharmacokinetics,low brain penetration,and side effects resulting from activation of the p75 neurotrophin receptor or the truncated TrkB.T1 *** TrkB agonists and antibodies that activate TrkB are being intensively investigated,they cannot distinguish the multiple human TrkB splicing isoforms or cell type-specific *** TrkB–postsynaptic density protein-95 coupling provides an alternative approach to specifically boost TrkB signaling at localized synaptic sites versus global stimulation that risks many adverse side effects.

关键词： Angelman syndrome autism brain-derived neurotrophic factor depression neurodegenerative disorder neurodevelopmental disorder postsynaptic density protein-95 synaptic plasticity TrkB

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A NONLOCAL KRONECKER-BASIS-REPRESENTATION METHOD FOR LOW-DOSE CT SINOGRAM RECOVERY

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Journal of Computational Mathematics 2024年第4期42卷 1080-1108页

作者： Jian Lu Huaxuan Hu Yuru Zou Zhaosong Lu Xiaoxia Liu Keke Zu Lin Li Shenzhen Key Laboratory of Advanced machine learning and Applications College of Mathematics and StatisticsShenzhen UniversityShenzhen 518060China National Center for Applied Mathematics Shenzhen(NCAMS) Shenzhen 518055China department of Industrial and Systems Engineering University of Minnesota Twin CitiesMinneapolisMN55455USA department of Applied Mathematics The Hong Kong Polytechnic UniversityHong Kong SARChina School of Electronic Engineering Xidian UniversityXi'an 710071China

Low-dose computed tomography(LDCT)contains the mixed noise of Poisson and Gaus-sian,which makes the image reconstruction a challenging *** order to describe the statistical characteristics of the mixed noise,we adopt the sinogram preprocessing as a stan-dard maximum a posteriori(MAP).Based on the fact that the sinogram of LDCT has non-local self-similarity property,it exhibits low-rank *** conventional way of solving the low-rank problem is implemented in matrix forms,and ignores the correlations among similar patch *** avoid this issue,we make use of a nonlocal Kronecker-Basis-Representation(KBR)method to depict the low-rank problem.A new denoising model,which consists of the sinogram preprocessing for data fidelity and the nonlocal KBR term,is developed in this *** proposed denoising model can better illustrate the generative mechanism of the mixed noise and the prior knowledge of the ***-merical results show that the proposed denoising model outperforms the state-of-the-art algorithms in terms of peak-signal-to-noise ratio(PSNR),feature similarity(FSIM),and normalized mean square error(NMSE).

关键词： Low-dose computed tomography Kronecker-basis-representation Low-rank imation.Noise-generating-mechanism

Personalized course generation and evolution based on genetic algorithms

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Journal of Zhejiang University-Science C(Computers and Electronics) 2012年第12期13卷 909-917页

作者： Xiao-hong TAN Rui-min SHEN Yan WANG department of Computer Science and Engineering Shanghai Jiao Tong University Shanghai 200030 China E-learning Lab Shanghai Jiao Tong University Shanghai 200030 China

Online learners are individuals,and their learning abilities,knowledge,and learning performance differ substantially and are ever *** individual characteristics pose considerable challenges to online learning *** this paper,we propose an online course generation and evolution approach based on genetic algorithms to provide personalized *** courses generated consider not only the difficulty level of a concept and the time spent by an individual learner on the concept,but also the changing learning performance of the individual learner during the learning *** present a layered topological sort algorithm,which converges towards an optimal solution while considering multiple *** general approach makes use of the stochastic convergence of genetic *** results show that the proposed algorithm is superior to the free browsing learning mode typically enabled by online learning environments because of the precise selection of learning content relevant to the individual learner,which results in good learning performance.

关键词： Genetic algorithm Course generation Course evolution Personalized learning Domain ontology

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