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Adaptive data fusion framework for modeling of non-uniform aerodynamic data

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Chinese Journal of Aeronautics 2023年第7期36卷 316-336页

作者： Vinh PHAM Maxim TYAN Tuan anh nguyen Chi-Ho LEE L.V.Thang nguyen Jae-Woo LEE Department of Aerospace Information Engineering Konkuk UniversitySeoul 05029Republic of Korea Konkuk Aerospace Design-Airworthiness Institute Konkuk UniversitySeoul 05029Republic of Korea

Multi-fidelity Data Fusion(MDF)frameworks have emerged as a prominent approach to producing economical but accurate surrogate models for aerodynamic data modeling by integrating data with different fidelity ***,most existing MDF frameworks assume a uniform data structure between sampling data sources;thus,producing an accurate solution at the required level,for cases of non-uniform data structures is *** address this challenge,an Adaptive Multi-fidelity Data Fusion(AMDF)framework is proposed to produce a composite surrogate model which can efficiently model multi-fidelity data featuring non-uniform ***,the design space of the input data with non-uniform data structures is decomposed into subdomains containing simplified ***,different MDF frameworks and a rule-based selection process are adopted to construct multiple local models for the subdomain *** the other hand,the Enhanced Local Fidelity Modeling(ELFM)method is proposed to combine the generated local models into a unique and continuous global ***,the resulting model inherits the features of local models and approximates a complete database for the whole design *** validation of the proposed framework is performed to demonstrate its approximation capabilities in(A)four multi-dimensional analytical problems and(B)a practical engineering case study of constructing an F16C fighter aircraft’s aerodynamic *** comparisons of the generated models using the proposed AMDF framework and conventional MDF approaches using a single global modeling algorithm are performed to reveal the adaptability of the proposed approach for fusing multi-fidelity data featuring non-uniform ***,the results indicated that the proposed framework outperforms the state-of-the-art MDF approach in the cases of non-uniform data.

关键词： Aerodynamic modeling Data fusion Diverse data structure Multi-fidelity data Multi-fidelity surrogate modeling

A New Inertial Self-adaptive Gradient Algorithm for the Split Feasibility Problem and an Application to the Sparse Recovery Problem

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Acta Mathematica Sinica,English Series 2023年第12期39卷 2489-2506页

作者： nguyen The VINH Pham Thi HOAI Le anh DUNG Yeol Je CHO Department of Mathematical Analysis University of Transport and Communications3 Cau Giay StreetHanoiVietnam Department of Applied Mathematics School of Applied Mathematics and InformaticsHano University of Science and Technology1 Dai Co Viet RoadHanoiVietnam Department of Mathematics and Informatics Hanoi University of Education136 Xuan ThuyCau GiayHanoiVietnam Department of Mathematics Education Gyeongsang National UniversityJinju52828Republicof Korea

In this paper,by combining the inertial technique and the gradient descent method with Polyak's stepsizes,we propose a novel inertial self-adaptive gradient algorithm to solve the split feasi-bility problem in Hilbert spaces and prove some strong and weak convergence theorems of our method under standard *** examine the performance of our method on the sparse recovery prob-lem beside an example in an infinite dimensional Hilbert space with synthetic data and give some numerical results to show the potential applicability of the proposed method and comparisons with related methods emphasize it further.

关键词： Split feasibility problem CQ algorithm Hilbert space sparse recovery problem

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

Assessment of different machine learning techniques in predicting the compressive strength of self-compacting concrete

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Frontiers of Structural and Civil Engineering 2022年第7期16卷 928-945页

作者： Van Quan TRAN Hai-Van Thi MAI Thuy-anh nguyen Hai-Bang LY Faculty of Civil Engineering University of Transport TechnologyHanoi 100000Vietnam

The compressive strength of self-compacting concrete(SCC)needs to be determined during the construction design *** paper shows that the compressive strength of SCC(CS of SCC)can be successfully predicted from mix design and curing age by a machine learning(ML)technique named the Extreme Gradient Boosting(XGB)algorithm,including non-hybrid and hybrid *** ML techniques,such as Linear regression(LR),K-Nearest Neighbors(KNN),Support Vector Machine(SVM),Decision Trees(DTR),Random Forest(RF),Gradient Boosting(GB),and Artificial Neural Network using two training algorithms LBFGS and SGD(denoted as ANN_LBFGS and ANN_SGD),are also compared with the XGB ***,the hybrid models of eight ML techniques and Particle Swarm Optimization(PSO)are constructed to highlight the reliability and accuracy of SCC compressive strength prediction by the XGB_PSO hybrid *** highest number of SCC samples available in the literature is collected for building the ML *** with previously published works’performance,the proposed XGB method,both hybrid and non-hybrid models,is the most reliable and robust of the examined techniques,and is more accurate than existing ML methods(R2=0.9644,RMSE=4.7801,and MAE=3.4832).Therefore,the XGB model can be used as a practical tool for engineers in predicting the CS of SCC.

关键词： compressive strength self-compacting concrete machine learning techniques particle swarm optimization extreme gradient boosting

An Ontology-Based Question Answering System for University Admissions Advising

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Intelligent Automation & Soft Computing 2023年第4期36卷 601-616页

作者： Thi Thanh Sang nguyen Dang Huu Trong Ho Ngoc Tram anh nguyen School of Computer Science and Engineering International UniversityVNU-HCMCVietnam National UniversityHo Chi Minh CityVietnam

Question-Answer systems are now very popular and crucial to support human in automatically responding frequent questions in manyﬁ***,these systems depend on learning methods and training ***,it is necessary to prepare such a good dataset,but it is not an easy *** ontol-ogy-based domain knowledge base is able to help to reason semantic information and make effective answers given user *** study proposes a novel chatbot model involving ontology to generate efﬁcient responses automatically.A case study of admissions advising at the International University–VNU HCMC is taken into account in the proposed chatbot.A domain ontology is designed and built based on the domain knowledge of university admissions using Protégé.The Web user interface of the proposed chatbot system is developed as a prototype using *** includes a search engine reasoning the ontology and generat-ing answers to users’*** experiments are carried out to test how the system reacts to different ***ﬁrst experiment examines questions made from some templates,and the second one examines normal questions taken from frequent *** results have shown that the ontology-based chatbot can release meaningful and long *** results are analysed to prove the proposed chatbot is usable and promising.

关键词： Ontology chatbots answer-question systems domain knowledge base admissions advising

Fuzzy Unknown Input Observer for Estimating Sensor and Actuator Cyber‑Attacks in Intelligent Connected Vehicles

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Automotive Innovation 2023年第2期6卷 164-175页

作者： Juntao Pan anh‑Tu nguyen Sujun Wang Huifan Deng Hui Zhang School of Electrical and Information Engineering North Minzu UniversityYinchuan 750021China UniversitéPolytechnique Hauts-de-France CNRSUMR 8201–LAMIH59313 ValenciennesFrance INSA Hauts-de-France 59313 ValenciennesFrance Department of Vehicle Engineering Nanjing University of Aeronautics and AstronauticsNanjing 210016China School of Transportation Science and Engineering Beihang UniversityBeijing 100191China

The detection and mitigation of cyber-attacks in connected vehicle systems(CVSs)are critical for ensuring the security of intelligent connected *** paper presents a solution to estimate sensor and actuator cyber-attacks in CVSs.A novel method is proposed that utilizes an augmented system representation technique and a nonlinear unknown input observer(UIO)to achieve asymptotic estimation of both CVS dynamics and *** nonlinear CVS dynamics is represented in a Takagi–Sugeno(TS)fuzzy form with nonlinear consequents,which allows for the effective use of the differential mean value theorem to handle unmeasured premise ***,via Lyapunov stability theory sufficient conditions are proposed,expressed in terms of linear matrix inequalities,to design TS fuzzy *** test scenarios are performed with high-fidelity Simulink-CarSim co-simulations to show the effectiveness of the proposed cyber-attack estimation method.

关键词： Connected vehicle systems Cyber-attacks Unknown input observers Vehicle dynamics estimation Takagi-Sugeno fuzzy models

Emotion Recognition with Capsule Neural Network

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Computer Systems Science & Engineering 2022年第6期41卷 1083-1098页

作者： Loan Trinh Van Quang H.nguyen Thuy dao Thi Le School of Information and Communication Technology Hanoi University of Science and TechnologyHanoi10000Vietnam Faculty of Information Technology University of Transport and CommunicationsHanoi10000Vietnam

For human-machine communication to be as effective as human-tohuman communication, research on speech emotion recognition is *** the models and the classifiers used to recognize emotions, neural networks appear to be promising due to the network’s ability to learn and the diversity in configuration. Following the convolutional neural network, a capsuleneural network (CapsNet) with inputs and outputs that are not scalar quantitiesbut vectors allows the network to determine the part-whole relationships thatare specific 6 for an object. This paper performs speech emotion recognition basedon CapsNet. The corpora for speech emotion recognition have been augmented byadding white noise and changing voices. The feature parameters of the recognition system input are mel spectrum images along with the characteristics of thesound source, vocal tract and prosody. For the German emotional corpus EMODB, the average accuracy score for 4 emotions, neutral, boredom, anger and happiness, is 99.69%. For Vietnamese emotional corpus BKEmo, this score is94.23% for 4 emotions, neutral, sadness, anger and happiness. The accuracy scoreis highest when combining all the above feature parameters, and this scoreincreases significantly when combining mel spectrum images with the featuresdirectly related to the fundamental frequency.

关键词： Emotion recognition CapsNet data augmentation mel spectrum image fundamental frequency

Twin reversed arterial perfusion sequence-a rare and dangerous complication form of monochorionic twins:A case report

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World Journal of Clinical Cases 2022年第28期10卷 10214-10219页

作者： nguyen Duy anh nguyen-Thi Thu Ha nguyen-Thi Sim nguyen Khac Toan Phan-Thi Huyen Thuong nguyen Minh Duc Fetal Medicine Center Hanoi Obstetrics and Gynecology HospitalHanoi 100000Vietnam Department of Assisted Reproduction Hanoi Obstetrics and Gynecology HospitalHanoi 100000Vietnam Department of Obstetrics and Gynecology Hanoi University of Medicine and PharmacyHanoi 100000Vietnam Department of Radiology Pham Ngoc Thach University of MedicineHo Chi Minh City 700000Vietnam

BACKGROUND Twin reversed arterial perfusion(TRAP) sequence is an extremely rare congenital anomaly in monochorionic(MC) *** condition is characterized by a malformed fetus(acardiac twin) without cardiac activities being perfused by a structurally normal one(pump twin) via an artery-to-artery anastomosis in a reverse *** SUMMARY We described the first case of TRAP to receive laser surgery in *** 26-wk pregnancy was originally misdiagnosed in another hospital as MC twins with single intrauterine fetal *** admission to our center,the diagnosis was amended to a 26-wk TRAP sequence stage *** acardiac twin was 7.5 cm at the longest length,the ratio of the weight of the acardiac twin to the weight of the pump twin was more than 90%,the pump twin showed fetal distress with absent diastolic flow in umbilical artery of pump twin,and the peak systolic velocity in the middle cerebral artery = 1.6 Mo *** performed emergency laser photocoagulation of the acardiac twin’s umbilical *** surgery,we successfully maintained the pregnancy for 8 wk and ended it electively by cesarean section at 34 wk of gestation due to rupture of *** TRAP should be appropriately diagnosed and treated early to avoid complications of the pump *** laser photocoagulation is a new and effective treatment for this condition.

关键词： Twin reversed arterial perfusion Acardiac twin Pump twin Laser Case report

A Sensor Network Coverage Planning Based on Adjusted Single Candidate Optimizer

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Intelligent Automation & Soft Computing 2023年第9期37卷 3213-3234页

作者： Trong-The nguyen Thi-Kien dao Trinh-Dong nguyen Fujian Provincial Key Laboratory of Big Data Mining and Applications Fujian University of TechnologyFuzhou350118China University of Information Technology Ho Chi Minh CityVietnam Vietnam National University Ho Chi Minh City700000Vietnam

Wireless sensor networks(WSNs)are widely used for various practical applications due to their simplicity and *** quality of service in WSNs is greatly influenced by the coverage,which directly affects the monitoring capacity of the target ***,low WSN coverage and uneven distribution of nodes in random deployments pose significant *** study proposes an optimal node planning strategy for net-work coverage based on an adjusted single candidate optimizer(ASCO)to address these *** single candidate optimizer(SCO)is a metaheuristic algorithm with stable implementation ***,it has limitations in avoiding local optimum traps in complex node coverage optimization *** ASCO overcomes these limitations by incorporating reverse learning and multi-direction strategies,resulting in updated *** performance of the ASCO algorithm is compared with other algorithms in the literature for optimal WSN node *** results demonstrate that the ASCO algorithm offers efficient performance,rapid convergence,and expanded coverage ***,the ASCO achieves an archival coverage rate of 88%,while other approaches achieve coverage rates below or equal to 85%under the same conditions.

关键词： Wireless sensor network coverage and connection adapted single candidate optimizer objective function optimization