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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

越南海岸九龙盆地和南昆山盆地现今的应力和孔隙压力场

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海洋地质 2009年第3期25卷 8-18页

作者： nguyen thi thanh binh Tomochika Tokunaga Hoang Phuoc Son Mai Van binh 冯常茂（译）不详广州市1180信箱广州海洋地质调查局矿产所 510760

某一地区的应力，或该地区现今的应力场，对斜井或水平井的最佳定位，以及认识油藏特征都是非常重要的。同时地层应力也有助于我们更好地认识地球动力学过程及其对盆地演化的影响。本文在勘探和开发井的基础上，利用很多第一手分析资料... 详细信息

某一地区的应力，或该地区现今的应力场，对斜井或水平井的最佳定位，以及认识油藏特征都是非常重要的。同时地层应力也有助于我们更好地认识地球动力学过程及其对盆地演化的影响。本文在勘探和开发井的基础上，利用很多第一手分析资料对越南海岸九龙盆地和南昆山盆地沉积层的地层应力、孔隙压力等进行了分析。九龙盆地最大水平应力在北部及中央高部位主要呈NNW—SSE及N—S向；南昆山盆地最大水平应力在北部主要呈NE—SW向，而在盆地中部呈N—S向。垂向应力在3500m深处的应力梯度值约为22．2MPa／km，正常压力地层中最小水平应力值约为垂向应力值的61％。孔隙压力变化对水平应力大小的影响，可用因流体生产而引起的枯竭层中的孔隙压力及裂缝测试数据来评价，研究中得到的平均孔隙压力-应力耦合率（△Sh/△Pp）值为0．66。南昆山盆地的最小水平应力值接近于超压区的垂向应力值，这一结果表明地层具有均质性或深部超压地层中可能呈走滑断层的应力状态。

关键词：地层应力孔隙压力最小水平应力

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)

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中越边境地区越南市场及其贸易活动初探

南宁职业技术学院学报 2020年第5期25卷 14-21页

作者：高鲜菊阮氏青平谢氏心广西民族大学东盟学院广西南宁530007 越南社会科学翰林院民族学研究院越南河内100803

在越南与中国的边境地区,集市不仅是货物交换和商品交易的场所,而且是两国边境族群社会文化交流的场所。自越南20世纪80年代革新开放以及90年代中越关系正常化以来,中越边境沿线市场体系得以恢复和发展,为满足该地区及周边地区民族的商... 详细信息

在越南与中国的边境地区,集市不仅是货物交换和商品交易的场所,而且是两国边境族群社会文化交流的场所。自越南20世纪80年代革新开放以及90年代中越关系正常化以来,中越边境沿线市场体系得以恢复和发展,为满足该地区及周边地区民族的商品交易需求,促进文化交流,维系和拓宽两国边境族群之间的血缘关系和友谊关系等方面作出了贡献。近年来,中越边境市场逐渐形成自己的特征,其买卖人员关系及其社会网络受市场结构等影响,具有人口、商品流动的能动性。

关键词：市场贸易活动商品货币中越边境地区

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Carboxymethyl starch cross-linked by electron beam radiation in presence of acrylic acid sensitizer

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Nuclear Science and Techniques 2013年第B12期24卷 19-22页

作者： Doan binh nguyen thanh Duoc Pham thi Thu Hong R & D Center for Radiation Technology Vietnam Atomic Energy Institute 202A St. 11 Linh Xuan Ward Thu Duc District Ho Chi Minh City Vietnam

Carboxymethyl starch (CMS) can be cross-linked by electron beam radiation to form a biocompatible and environment-friendly hydrogel at a high absorbed dose and a condensed CMS concentration. Acrylic acid (AAc) can be used as a sensitizer in order to reduce the absorbed doses to an acceptable certain level. At an absorbed dose of 3-4 kGy, the gel content of crosslinked CMS can be obtained about 50% with 5% (w/w) AAc concentration used. The compressive strength of CMS samples increased with increasing their cross-linked densities due to raising absorbed doses. The swelling ratio of cross-linked CMS was also attainable at a maximum of 50 times in the distilled water. The enzymatic degradation of cross-linked CMS was carried out in acetate buffer pH 4.6 with 0.1% α-amylase enzymatic solution incubated at 40°C for 6 h. The crosslinked CMS samples were degraded slower than uncrosslinked CMS ones. The results indicated that the highly cross-linked CMS was almost fully degradable when the enzymatic hydrolysis was performed during 6 h. The FT IR spectra of cross-linked CMS in the presence of AAc were examined to observe the carboxyl group of AAc in the structure of cross-linked CMS. The hydrophilic of cross-linked CMS surface was determined by a contact-angle analysis. © 2013, Science Press. All rights reserved.

关键词：交联密度羧甲基淀粉电子束辐射丙烯酸敏化剂 FT-IR光谱吸收剂量 CMS

Multilevel Threshold Based Image Denoising in Curvelet Domain

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Journal of Computer Science & Technology 2010年第3期25卷 632-640页

作者： nguyen thanh binh Ashish Khare Department of Electronics and Communication University of Allahabad

In this paper, we propose a multilevel thresholding technique for noise removal in curvelet transform domain which uses cycle-spinning. Most of uncorrelated noise gets removed by thresholding curvelet coefficients at lowest level, while correlated noise gets removed by only a fraction at lower levels, so we used multilevel thresholding on curvelet coefficients. The threshold in the proposed method depends on the variance of curvelet coefficients, the mean and the median of absolute curvelet coefficients at a particular level which makes it adaptive in nature. Results obtained for 2-D images demonstrate an improved performance over other recent related methods available in literature.

关键词： curvelet transform denoising multilevel thresholding cycle-spinning

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A comparative analysis of weight-based machine learning methods for landslide susceptibility mapping in Ha Giang area

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Big Earth Data 2023年第4期7卷 1005-1034页

作者： thanh Trinh binh thanh Luu Trang Ha thi Le Duong Huy nguyen Trong Van Tran thi Hai Van nguyen Khanh Quoc nguyen Lien thi nguyen Faculty of Computer Science Phenikaa UniversityYen NghiaHa DongHanoi 12116Vietnam Phenikaa Research and Technology Institute(PRATI) A&A Green Phoenix Group JSCNo.167 Hoang NganTrung HoaCau GiayHanoi 11313Vietnam Northwestern Geological Division General Department of Geology and Minerals of VietnamHanoiVietnam Youth union office Thuyloi University175 Tay SonDong DaHanoiVietnam Center of Remote Sensing and Geohazards Vietnam Institute of Geosciences and Mineral ResourcesHanoiVietnam

Landslide susceptibility maps (LSMs) are very crucial for planningpolicies in hazardous areas. However, the accuracy and reliability ofLSMs depend on available data and the selection of suitable *** study is conducted to produce LSMs by combinations of machinelearning methods and weighting techniques for Ha Giang province,Vietnam, where has limited data. In study area, we gather 11 landslideconditioning factors and establish a landslide inventory *** the weights of classes (or factors) is very important toprepare data for machine learning methods to generate LSMs. Wefrst use frequency ratio (FR) and analytic hierarchy process (AHP)techniques to generate the weights. Then, random forest (RF), supportvector machine (SVM), logistic regression (LR), and AHP methods arecombined with FR and AHP weights to yield accurate and reliableLSMs. Finally, the performance of these methods is evaluated by fivestatistical metrics, ROC and R-index. The empirical results have shownthat RF is the best method in terms of R-index and the five metrics, *** rate (0.9661), FP rate (0.0), ACC (0.9835), MAE (0.0046), and RMSE(0.0350) for this study area. this study opens the perspective of weightbasedmachine learning methods for landslide susceptibility mapping.

关键词： Landslide logistic regression random forest SvM Vietnam

Electrochemical Immunosensor for Detection of Atrazine Based on Polyaniline/Graphene

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Journal of Materials Science & Technology 2016年第6期32卷 539-544页

作者： nguyen Van Chu nguyen Hai binh Cao thi thanh nguyen Van Tu nguyen Le Huy nguyen Tuan Dzung Phan Ngoc Minh Vu thi Thu Tran Dai Lam Institute of Materials Science Vietnam Academy of Science and Technology18 Hoang Quoc VietCau Giay.HanoiViet Nam School of Chemical Engineering.Hanoi University of Science and Technology 1 Dai Co VietHanoiViet Ham Institute for Tropical Technology.Vietnam Academy of Science and Technology 18 Hoang Quoc VietHanoiViet Nam Center for High Technology Development Vietnam Academy of Science and Technology18 Hoang Quoc VietHanoiViet Nam University of Science and Technology of Hanoi.18 Hoang Quoc Viet HanoiViet Ham Graduate University of Science and Technology.Vietnam Academy of Science and Technology 18 Hoang Quoc Viet.HanoiViet Nam

In this study, a novel layer-by-layer polyaniline/graphene （PANi/Gr） structure for electrochemical detec- tion of atrazine was developed. Gr film was synthesized by thermal chemical vapor deposition （CVD） method and transferred onto the PANi-predeposited microelectrode. The properties of PANi/Gr film were thoroughly investigated by high-resolution transmission electron microscopy and Raman techniques. The most attractive feature of this system is a suitable microenvironment, which could provide an amplifi- cation of the conductive signal, thus may contribute to enhancing electron transfer and subsequently improve the sensitivity in electrochemical measurements. With low detection limit （- 43 × 10 -12 g/L）, ac-ceptable stability and good reproducibility, the proposed electrochemical immunosensor could be advantageously extended for multiplexed detection of other agents of environmental pollution.

关键词： Electrochemical immunosensor Polyaniline Graphene Atrazine

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