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Privacy-preserving explainable AI: a survey

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Science China(Information Sciences) 2025年第1期68卷 23-56页

作者： Thanh Tam nguyen Thanh Trung HUYNH Zhao REN Thanh Toan nguyen Phi Le nguyen Hongzhi YIN Quoc Viet Hung nguyen School of Information and Communication Technology Griffith University School of Computer and Communication Sciences Ecole Polytechnique Federale de Lausanne Faculty of Mathematics and Computer Science University of Bremen Faculty of Information Technology HUTECH University Department of Computer Science Hanoi University of Science and Technology School of Electrical Engineering and Computer Science The University of Queensland

As the adoption of explainable AI(XAI) continues to expand, the urgency to address its privacy implications intensifies. Despite a growing corpus of research in AI privacy and explainability, there is little attention on privacy-preserving model explanations. This article presents the first thorough survey about privacy attacks on model explanations and their countermeasures. Our contribution to this field comprises a thorough analysis of research papers with a connected taxonomy that facilitates the categorization of privacy attacks and countermeasures based on the targeted explanations. This work also includes an initial investigation into the causes of privacy leaks. Finally, we discuss unresolved issues and prospective research directions uncovered in our analysis. This survey aims to be a valuable resource for the research community and offers clear insights for those new to this domain. To support ongoing research, we have established an online resource repository, which will be continuously updated with new and relevant findings.

关键词： privacy-preserving explainable AI privacy attacks privacy defences PrivEx PPXAI

Prediction of Shear Bond Strength of Asphalt Concrete Pavement Using Machine Learning Models and Grid Search Optimization Technique

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Computer Modeling in Engineering & Sciences 2025年第1期142卷 691-712页

作者： Quynh-Anh Thi Bui Dam Duc nguyen Hiep van Le Indra Prakash Binh Thai Pham Civil Engineering Department University of Transport Technology54 Trieu KhucThanh XuanHanoi100000Vietnam DDG(R)Geological Survey of India Gandhinagar382010India

Determination of Shear Bond strength(SBS)at interlayer of double-layer asphalt concrete is crucial in flexible pavement *** study used three Machine Learning(ML)models,including K-Nearest Neighbors(KNN),Extra Trees(ET),and Light Gradient Boosting Machine(LGBM),to predict SBS based on easily determinable input ***,the Grid Search technique was employed for hyper-parameter tuning of the ML models,and cross-validation and learning curve analysis were used for training the *** models were built on a database of 240 experimental results and three input variables:temperature,normal pressure,and tack coat *** validation was performed using three statistical criteria:the coefficient of determination(R2),the Root Mean Square Error(RMSE),and the mean absolute error(MAE).Additionally,SHAP analysis was also used to validate the importance of the input variables in the prediction of the *** show that these models accurately predict SBS,with LGBM providing outstanding ***(Shapley Additive explanation)analysis for LGBM indicates that temperature is the most influential factor on ***,the proposed ML models can quickly and accurately predict SBS between two layers of asphalt concrete,serving practical applications in flexible pavement structure design.

关键词： Shear bond asphalt pavement grid search optimization machine learning

Landslide Susceptibility Mapping Using RBFN-Based Ensemble Machine Learning Models

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Computer Modeling in Engineering & Sciences 2025年第1期142卷 467-500页

作者： Landslide Susceptibility Mapping Using RBFN-Based Ensemble Machine Learning Models Duc-Dam nguyen nguyen Viet Tiep Quynh-Anh Thi Bui Hiep van Le Indra Prakash Romulus Costache Manish Pandey Binh Thai Pham Faculty of Civil Engineering University of Transport TechnologyThanh XuanHa Noi100000Vietnam Faculty of Hydraulic Engineering Hanoi University of Civil EngineeringHa Noi100000Vietnam DDG(R)Geological Survey of India Gandhinagar382010India Research Institute of the University of Bucharest Bucharest050663Romania National Institute of Hydrology and Water Management Bucharest013686Romania Department of Civil Engineering Transilvania University of BrasovBrasov500152Romania Danube Delta National Institute for Research and Development Tulcea820112Romania Marwadi University Research Center(MURC) Marwadi UniversityRajkotGujaratBharat360003India Department of Civil Engineering Faculty of Engineering&TechnologyMarwadi UniversityRajkotGujaratBharat360003India

This study was aimed to prepare landslide susceptibility maps for the Pithoragarh district in Uttarakhand,India,using advanced ensemble models that combined Radial Basis Function Networks(RBFN)with three ensemble learning techniques:DAGGING(DG),MULTIBOOST(MB),and ADABOOST(AB).This combination resulted in three distinct ensemble models:DG-RBFN,MB-RBFN,and ***,a traditional weighted method,Information Value(IV),and a benchmark machine learning(ML)model,Multilayer Perceptron Neural Network(MLP),were employed for comparison and *** models were developed using ten landslide conditioning factors,which included slope,aspect,elevation,curvature,land cover,geomorphology,overburden depth,lithology,distance to rivers and distance to *** factors were instrumental in predicting the output variable,which was the probability of landslide *** analysis of the models’performance indicated that the DG-RBFN model,with an Area Under ROC Curve(AUC)of 0.931,outperformed the other *** AB-RBFN model achieved an AUC of 0.929,the MB-RBFN model had an AUC of 0.913,and the MLP model recorded an AUC of *** results suggest that the advanced ensemble ML model DG-RBFN was more accurate than traditional statistical model,single MLP model,and other ensemble models in preparing trustworthy landslide susceptibility maps,thereby enhancing land use planning and decision-making.

关键词： Landslide susceptibility map spatial analysis ensemble modelling information values(IV)

Cellular models of stress resistance may pave ways to fight neurodegenerative diseases

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Neural Regeneration Research 2025年第9期20卷 2579-2580页

作者： Thu nguyen Minh Pham Christian Behl Institute of Pathobiochemistry University Medical Center of the Johannes Gutenberg UniversityMainzGermany

Alzheimer's disease(AD),the most common form of neurodegeneration,is characterized by selective neuronal vulnerability and brain regionselective neuron *** entorhinal cortex and hippoc,ampal CA1 projection neurons are at greater risk in AD whereas other regions display resistance to ***,the cerebellum,a phylogenetically very old region,is affected only very late in the disease progression.

关键词： cortex resistance Alzheimer

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Dynamic Modeling and Experiment of a Fish Robot with a Flexible Tail Fin

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Journal of Bionic Engineering 2013年第1期10卷 39-45页

作者： Phi Luan nguyen van Phu do Byung Ryong Lee ~ Intelligent Control and Mechatronics Lab School of Mechanical Engineering University of Ulsan Daehak-ro 93 Nam-gu Ulsan 680-749 South Korea School of Mechanical Engineering University of Ulsan Daehak-ro 93 Nam-gu Ulsan 680-749 South Korea

This paper presents the dynamic modeling of a flexible tail for a robotic fish. For this purpose firstly, the flexible tail was simplified as a slewing beam actuated by a driving moment. The governing equation of the flexible tail was derived by using the Euler-Bernoulli theory. In this equation, the resistive forces were estimated as a term analogous to viscous damping. Then, the modal analysis method was applied in order to derive an analytical solution of the governing equation, by which the relationship between the driving moment and the lateral movement of the flexible tail was described. Finally, simulations and experiments were carried out and the results were compared to verify the accuracy of the dynamic model. It was proved that the dynamic model of a fish robot with a flexible tail fin well explains the real behavior of robotic fish in underwater environment.

关键词： robotic fish flexible tail dynamic modeling lateral movement

Dynamic Modeling of a Non-Uniform Flexible Tail for a Robotic Fish

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Journal of Bionic Engineering 2013年第2期10卷 201-209页

作者： Phi Luan nguyen van Phu do Byung Ryong Lee Intelligent Control and Mechatronics Lab School of Mechanical Engineering University of Ulsan Ulsan 680-749 Korea School of Mechanical Engineering University of Ulsan Ulsan 680-749 Korea

In this paper, a non-uniform flexible tail of a fish robot was presented and the dynamic model was developed. In this model, the non-uniform flexible tail was modeled by a rotary slender beam. The hydrodynamics forces, including the reactive force and resistive force, were analyzed in order to derive the governing equation. This equation is a fourth-order in space and second-order in time Partial Differential Equation （PDE） of the lateral movement function. The coefficients of this PDE were not constants because of the non-uniform beams, so they were approximated by exponential functions in order to obtain an analytical solution. This solution describes the lateral movement of the flexible tail as a function of material, geometrical and actuator properties. Experiments were then carried out and compared to simulations. It was proved that the proposed model is suitable for predicting the real behavior of fish robots.

关键词： fish robot flexible tail dynamic modeling kinematic lateral movement

Blockchain for Education:Verification and Management of Lifelong Learning Data

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Computer Systems Science & Engineering 2022年第11期43卷 591-604页

作者： Ba-Lam do van-Thanh nguyen Hoang-Nam Dinh Thanh-Chung Dao BinhMinh nguyen School of Information and Communication Technology Hanoi University of Science and TechnologyHanoiVietnam

In recent years,blockchain technology has been applied in the educational domain because of its salient advantages,i.e.,transparency,decentralization,and *** systems typically use public blockchain networks such as Ethereum and Bitcoin to store learning ***,the cost of writing data on these networks is significant,making educational institutions limit data sent to the target network,typically containing only hash codes of the issued *** this paper,we present a system based on a private blockchain network for lifelong learning data authentication and management named B4E(Blockchain For Education).B4E stores not only certificates but also learners’training data such as transcripts and educational programs in order to create a complete record of the lifelong education of each user and verify certificates that they have *** a result,B4E can address two types of fake certificates,i.e.,certificates printed by unlawful organizations and certificates issued by educational institutions for learners who have not met the training *** addition,B4E is designed to allow all participants to easily deploy software packages to manage,share,and check stored information without depending on a single point of *** such,the system enhances the transparency and reliability of the stored *** experiments show that B4E meets expectations for deployment in reality.

关键词： Training data certificate verification and management private blockchain

Antidiabetic and antioxidant activities of red seaweed Laurencia dendroidea

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Asian Pacific Journal of Tropical Biomedicine 2019年第12期9卷 501-509页

作者： The Han nguyen Thi Huyen nguyen van Minh nguyen Thi Lan Phuong nguyen Thi van Anh Tran Anh Duy do Sang Moo Kim Faculty of Food Technology Nha Trang University02 Nguyen Dinh Chieu StreetNha Trang CityKhanh HoaVietnam Quality Control Department Institute of Vaccines and Medical BiologicalsNha Trang CityKhanh HoaVietnam Faculty of Pharmacy University of Medicine and Pharmacy of Ho Chi Minh City41 Dinh Tien Hoang StreetHo Chi Minh CityVietnam Research Department of Marine Conservation Research Institute for Marine Fisheries224 Le Lai StreetHai Phong CityVietnam Department of Marine Food Science and Technology Gangneung-Wonju National University7 Jukheon-gilGangneung 25457Republic of Korea

Objective:To investigate antidiabetic and antioxidant activities of the extract and fractions from Vietnamese red seaweed Laurencia ***:The seaweed Laurencia dendroidea was extracted by using microwave-assisted extraction method in 80%*** seaweed extract was then fractionated using different solvents(n-hexane,chloroform,ethyl acetate,butanol and water).These obtained fractions were evaluated forα-glucosidase inhibitory and antioxidant *** activities were tested using DPPH,nitric oxide radical scavenging and metal chelating *** enzyme inhibition mode was determined using Lineweaver-Burk *** acidic and thermal stabilities,the ethyl acetate fraction was treated at pH 2.0 and 100℃,*** residual inhibitory activity of the fraction was calculated based on the initial inhibitory *** in vivo antidiabetic activity,mice were divided into four groups,including normal control,diabetic control,diabetic mice treated with ethyl acetate fraction and diabetic mice treated with *** glucose level of treated mice during acute and prolonged treatments was *** evaluate the toxicity of the ethyl acetate fraction,the body weight changes and activities of liver function enzymes(aspartate transaminase,alanine transaminase and gammaglutamyl transferase)were carried ***:The extract of Laurencia dendroidea showed strongα-glucosidase inhibitory and DPPH radical scavenging *** concentrations affected bothα-glucosidase inhibitory and antioxidant activities.A 80%aqueous methanol was the suitable solvent for extraction of enzyme inhibitors and *** solvent fractions,ethyl acetate fraction had the highest inhibitory activities againstα-glucosidase with a mixed type of inhibition and the strongest antioxidant activities,and was stable under acidic and thermal *** ethyl acetate fraction treated diabetic mice significantly reduced blood glucose level compare

关键词： α-Glucosidase inhibitor Antidiabetic Antioxidant Red seaweeds Vietnam

One-step hydrothermal synthesis of Sn-doped α-Fe_(2)O_(3) nanoparticles for enhanced photocatalytic degradation of Congo red

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Journal of Semiconductors 2022年第12期43卷 22-31页

作者： van Nang Lam Thi Bich Vu Quang Dat do Thi Thanh Xuan Le Tien Dai nguyen T-Thanh-Bao nguyen Hoang Tung do Thi Tu Oanh nguyen Department of Natural Sciences Hoa Lu UniversityNinh NhatNinh Binh CityViet Nam Institute of Theoretical and Applied Research Duy Tan UniversityHanoi 100000Viet Nam Faculty of Natural Sciences Duy Tan UniversityDa Nang 550000Vietnam Institute of Physics Vietnam Academy of Science and Technology10 Dao TanBa DinhHanoiVietnam Institute of Materials Science Vietnam Academy of Science and Technology18 Hoang Quoc VietCaugiayHanoiVietnam

We report on the synthesis of Sn-doped hematite nanoparticles(Sn-α-Fe_(2)O_(3) NPs)by the hydrothermal *** prepared Sn-α-Fe_(2)O_(3) NPs had a highly pure and well crystalline rhombohedral phase with an average particle size of 41.4 *** optical properties of as-synthesizedα-Fe_(2)O_(3) NPs show a higher bandgap energy(2.40-2.57 eV)than that of pure bulkα-Fe_(2)O_(3)(2.1 eV).By doping Sn intoα-Fe_(2)O_(3) NPs,the Sn-doped hematite was observed a redshift toward a long wavelength with in-creasing Sn concentration from 0%to 4.0%.The photocatalytic activity of Sn-dopedα-Fe_(2)O_(3) NPs was evaluated by Congo red(CR)dye *** degradation efficiency of CR dye using Sn-α-Fe_(2)O_(3) NPs catalyst is higher than that of pureα-Fe_(2)O_(3) *** highest degradation efficiency of CR dye was 97.8%using 2.5%Sn-dopedα-Fe_(2)O_(3) NPs catalyst under visible-light *** results suggest that the synthesized Sn-dopedα-Fe_(2)O_(3) nanoparticles might be a suitable approach to develop a photocatalytic degradation of toxic inorganic dye in wastewater.

关键词： α-Fe_(2)O_(3)nanoparticles Sn Congo red photocatalytic properties photodegradation

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