检索结果-南通市图书馆

An Enhanced Ensemble-Based Long Short-Term Memory Approach for Traffic Volume Prediction

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Computers, Materials & Continua 2024年第3期78卷 3585-3602页

作者： duy quang Tran Huy Q.Tran Minh Van Nguyen Faculty of Civil Engineering Nha Trang UniversityNha Trang650000Vietnam Robotics and Mechatronics Research Group Faculty of Engineering and TechnologyNguyen Tat Thanh UniversityHo Chi Minh City700000Vietnam Department of Civil Engineering Ho Chi Minh City University of Technology and EducationHo Chi Minh City700000Vietnam

With the advancement of artificial intelligence,traffic forecasting is gaining more and more interest in optimizing route planning and enhancing service *** volume is an influential parameter for planning and operating traffic *** study proposed an improved ensemble-based deep learning method to solve traffic volume prediction problems.A set of optimal hyperparameters is also applied for the suggested approach to improve the performance of the learning *** fusion of these methodologies aims to harness ensemble empirical mode decomposition’s capacity to discern complex traffic patterns and long short-term memory’s proficiency in learning temporal ***,a dataset for automatic vehicle identification is obtained and utilized in the preprocessing stage of the ensemble empirical mode decomposition *** second aspect involves predicting traffic volume using the long short-term memory ***,the study employs a trial-and-error approach to select a set of optimal hyperparameters,including the lookback window,the number of neurons in the hidden layers,and the gradient descent ***,the fusion of the obtained results leads to a final traffic volume *** experimental results show that the proposed method outperforms other benchmarks regarding various evaluation measures,including mean absolute error,root mean squared error,mean absolute percentage error,and *** achieved R-squared value reaches an impressive 98%,while the other evaluation indices surpass the *** findings highlight the accuracy of traffic pattern ***,this offers promising prospects for enhancing transportation management systems and urban infrastructure planning.

关键词： Ensemble empirical mode decomposition traffic volume prediction long short-term memory optimal hyperparameters deep learning

Machine learning based models for predicting compressive strength of geopolymer concrete

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Frontiers of Structural and Civil Engineering 2024年第7期18卷 1028-1049页

作者： quang-Huy LE duy-Hung NGUYEN Thanh SANG-TO Samir KHATIR Hoang LE-MINH Amir H.GANDOMI Thanh CUONG-LE Center for Engineering Application and Technology Solutions Ho Chi Minh City Open UniversityHo Chi Minh 700000Vietnam Institute of Civil Engineering Ho Chi Minh City University of TransportHo Chi Minh 700000Vietnam Faculty of Engineering&Information Technology University of Technology SydneyUltimoNSW 2007Australia

Recently,great attention has been paid to geopolymer concrete due to its advantageous mechanical and environmentally friendly *** effort has been made in experimental studies to advance the understanding of geopolymer concrete,in which compressive strength is one of the most important *** facilitate engineering work on the material,an efficient predicting model is *** this study,three machine learning(ML)-based models,namely deep neural network(DNN),K-nearest neighbors(KNN),and support vector machines(SVM),are developed for forecasting the compressive strength of the geopolymer concrete.A total of 375 experimental samples are collected from the literature to build a database for the development of the predicting models.A careful procedure for data preprocessing is implemented,by which outliers are examined and removed from the database and input variables are standardized before feeding to the fitting *** standard K-fold cross-validation approach is applied for evaluating the performance of the models so that overfitting status is well managed,thus the generalizability of the models is *** effectiveness of the models is assessed via statistical metrics including root mean squared error(RMSE),mean absolute error(MAE),correlation coefficient(R),and the recently proposed performance index(PI).The basic mean square error(MSE)is used as the loss function to be minimized during the model fitting *** three ML-based models are successfully developed for estimating the compressive strength,for which good correlations between the predicted and the true values are obtained for DNN,KNN,and *** numerical results suggest that the DNN model generally outperforms the other two models.

关键词： geopolymer concrete compressive strength prediction machine-learning based model deep neural network K-nearest neighbor support vector machines

Recent advances and innovations in the design and fabrication of wearable flexible biosensors and human health monitoring systems based on conjugated polymers

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Bio-Design and Manufacturing 2024年第4期7卷 476-516页

作者： Vinh Van Tran Viet-Duc phung Daeho Lee Department of Mechanical Engineering Gachon UniversitySeongnam 13120Republic of Korea Institute of Fundamental and Applied Sciences Duy Tan UniversityHo Chi Minh City 700000Vietnam Faculty of Environmental and Chemical Engineering Duy Tan UniversityDa Nang 550000Vietnam

Wearable biosensors have received great interest as patient-friendly diagnostic technologies because of their high flexibility and *** growing research and utilization of novel materials in designing wearable biosensors have accelerated the development of point-of-care sensing platforms and implantable biomedical devices in human health *** numerous potential materials,conjugated polymers(CPs)are emerging as ideal choices for constructing high-performance wearable biosensors because of their outstanding conductive and mechanical ***,CPs have been extensively incorporated into various wearable biosensors to monitor a range of target ***,fabricating highly reliable CP-based wearable biosensors for practical applications remains a significant challenge,necessitating novel developmental strategies for enhancing the viability of such ***,this review aims to provide consolidated scientific evidence by summarizing and evaluating recent studies focused on designing and fabricating CP-based wearable biosensors,thereby facilitating future *** the superior properties and benefits of CPs,this review aims to clarify their potential applicability within this ***,the fundamentals and main components of CP-based wearable biosensors and their sensing mechanisms are discussed in *** recent advancements in CP nanostructures and hybridizations for improved sensing performance,along with recent innovations in next-generation wearable biosensors are *** wearable biosensors have been—and will continue to be—an ideal platform for developing effective and user-friendly diagnostic technologies for human health monitoring.

关键词： Conjugated polymers Wearable biosensors E-skin electronics Implantable biosensors Conductive polymer hydrogels

Photocatalytic degradation of antibiotic sulfamethizole by visible light activated perovskite LaZnO_(3)

维普期刊数据库

同方期刊数据库评论

在线全文

学校读者我要写书评

暂无评论

Journal of Environmental Sciences 2024年第10期144卷 212-224页

作者： Bui The Huy XCuong Nguyen Vu Khac Hoang Bui Nguyen Ngoc Tri Iqra Rabani Nhu Hoa Thi Tran quang Viet Ly Hai Bang Truong Major of Biomedical Engineering Division of Smart HealthcareCollege of Information Technology and ConvergencePukyong National UniversityBusan 48513Korea Center for Advanced Chemistry Institute of Research and DevelopmentDuy Tan UniversityDa Nang 550000Viet Nam Faculty of Environmental and Chemical Engineering Duy Tan UniversityDa Nang 550000Viet Nam Department of Environment and Energy Sejong UniversitySeoul 05006Korea Lab of Computational Chemistry and Modelling Department of ChemistryFaculty of Natural SciencesQuy Nhon UniversityQuy NhonViet Nam Department of Nanotechnology and Advanced Materials Engineering Sejong UniversitySeoul 05006Korea Faculty of Materials Science and Technology University of ScienceHo Chi Minh City 700000Viet Nam Vietnam National University Ho Chi Minh City 700000Viet Nam Department of Environmental Engineering Seoul National University of Science and TechnologySeoul 01811Korea Optical Materials Research Group Science and Technology Advanced InstituteVan Lang UniversityHo Chi Minh CityViet Nam Faculty of Applied Technology School of TechnologyVan Lang UniversityHo Chi Minh CityViet Nam

In thiswork,the perovskite LaZnO_(3) was synthesized via sol-gel method and applied for photocatalytic treatment of sulfamethizole(SMZ)antibiotics under visible light *** was almost completely degraded(99.2%±0.3%)within 4 hr by photocatalyst LaZnO3 at the optimal dosage of 1.1 g/L,with amineralization proportion of 58.7%±0.4%.The efficient performance of LaZnO_(3) can be attributed to itswide-range light absorption and the appropriate energy band edge levels,which facilitate the formation of active agents such as·O_(2)^(−),h^(+),and·*** integration of RP-HPLC/Q-TOF-MS and DFT-based computational techniques revealed three degradation pathways of SMZ,which were initiated by the deamination reaction at the aniline ring,the breakdown of the sulfonamidemoieties,and a process known as Smile-type rearrangement and SO2 *** toxicity of SMZ and the intermediateswere analyzed by quantitative structure activity relationship(QSAR),indicating the effectiveness of LaZnO_(3)-based photocatalysis in preventing secondary pollution of the intermediates to the ecosystem during the degradation *** visible-light-activated photocatalyst LaZnO_(3) exhibited efficient performance in the occurrence of inorganic anions and maintained high durability across multiple recycling tests,making it a promising candidate for practical antibiotic treatment.

关键词： Perovskite Antibiotics Photocatalysis Density functional theory Toxicity

Transparent, stretchable, and rapid-response humidity sensor for body-attachable wearable electronics

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Nano Research 2017年第6期10卷 2021-2033页

作者： Tran quang Trung Le Thai duy Subramanian Ramasundaram Nae-Eung Lee School of Advanced Materials Science & Engineering Sungkyunkwan University (SKKU) Suwon Kyunggi-do 16419 Republic of Korea Center for Water Resource Cycle Research Korea Institute of Science and Technology Hwarang-ro 14 gil Seongbuk-gu Seoul 02793 Republic of Korea SKKU Advanced Institute of Nanotechnology (SAINT) SKKU Suwon Kyunggi-do 16419 Republic of Korea Samsung Advanced Institute for Health Sciences & Technology (SAIHST) SKKU Suwon Kyunggi-do 16419 Republic of Korea

Stretchable and conformal humidity sensors that can be attached to the human body for continuously monitoring the humidity of the environment around the human body or the moisture level of the human skin can play an important role in electronic skin and personal healthcare applications. However, most stretchable humidity sensors are based on the geometric engineering of non-stretchable components and only a few detailed studies are available on stretchable humidity sensors under applied mechanical deformations. In this paper, we propose a transparent, stretchable humidity sensor with a simple fabrication process, having intrinsically stretchable components that provide high stretchability, sensitivity, and stability along with fast response and relaxation time. Composed of reduced graphene oxide-polyurethane composites and an elastomeric conductive electrode, this device exhibits impressive response and relaxation time as fast as 3.5 and 7 s, respectively. The responsivity and the response and relaxation time of the device in the presence of humidity remain almost unchanged under stretching up to a strain of 60% and after 10,000 stretching cycles at a 40% strain. Further, these stretchable humidity sensors can be easily and conformally attached to a finger for monitoring the humidity levels of the environment around the human body, wet objects, or human skin.

关键词： transparent stretchablehumidity sensor reduced graphene oxide wearable electronics body-attachable intrinsically stretchable components

Integrating Machine Learning and Evidential Reasoning for User Profiling and Recommendation

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Journal of Systems Science and Systems Engineering 2023年第4期32卷 393-412页

作者： Toan Nguyen Mau quang-Hung Le Duc-Vinh Vo duy Doan Van-Nam Huynh University of Information Technology Ho Chi Minh CityVietnam Vietnam National University Ho Chi Minh CityVietnam Department of Information Technology Quy Nhon UniversityQuy NhonVietnam Ho Chi Minh City University of Banking Ho Chi Minh CityVietnam School of Knowledge Science Japan Advanced Institute of Science and TechnologyIshikawaJapan

User profiles representing users’preferences and interests play an important role in many applications of personalized *** the rapid growth of social platforms,there is a critical need for efficient solutions to learn user profiles from the information they shared on social platforms so as to improve the quality of recommendation *** problem of user profile learning is significantly challenging due to difficulty in handling data from multiple sources,in different formats and often associated with *** this paper,we introduce an integrated approach that combines advanced Machine Learning techniques with evidential reasoning based on Dempster-Shafer theory of evidence for user profiling and *** developed methods for user profile learning and multi-criteria collaborative filtering are demonstrated with experimental results and analysis that show the effectiveness and practicality of the integrated approach.A proposal for extending multi-criteria recommendation systems by incorporating user profiles learned from different sources of data into the recommendation process so as to provide better recommendation capabilities is also highlighted.

关键词： Machine learning Dempster-Shafer theory of evidence user profiles personalized recommendation preferences

Enabling intelligence in fog computing to achieve energy and latency reduction

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Digital Communications and Networks 2019年第1期5卷 3-9页

作者： quang duy La Mao V. Ngo Thinh quang Dinh Tony Q.S. Quek Hyundong Shin Singapore University of Technology and Design (SUTD) Singapore Institute for Infocomm Research (I^2R) Singapore Kyung Hee University South Korea Institute for Infocomm Research (I^2R) A^*STAR Singapore Singapore University of Technology and Design Singapore 487372 Department of Electronics Engineering Kyung Hee University Yongin-si Gyeonggi-do 17104 Korea

Fog computing is an emerging architecture intended for alleviating the network burdens at the cloud and the core network by moving resource-intensive functionalities such as computation, communication, storage, and analytics closer to the End Users (EUs). In order to address the issues of energy efficiency and latency requirements for the time-critical Internet-of-Things (IoT) applications, fog computing systems could apply intelligence features in their operations to take advantage of the readily available data and computing resources. In this paper, we propose an approach that involves device-driven and human-driven intelligence as key enablers to reduce energy consumption and latency in fog computing via two case studies. The first one makes use of the machine learning to detect user behaviors and perform adaptive low-latency Medium Access Control (MAC)-layer scheduling among sensor devices. In the second case study on task offloading, we design an algorithm for an intelligent EU device to select its offloading decision in the presence of multiple fog nodes nearby, at the same time, minimize its own energy and latency objectives. Our results show a huge but untapped potential of intelligence in tackling the challenges of fog computing。

关键词： Fog computing Edge computing Machine learning MAC scheduling Computational offloading Energy efficiency

Target tracking method of Siamese networks based on the broad learning system

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

CAAI Transactions on Intelligence Technology 2023年第3期8卷 1043-1057页

作者： Dan Zhang C.L.Philip Chen Tieshan Li Yi Zuo Nguyen quang duy Navigation College Dalian Maritime UniversityDalianChina Innovation and Entrepreneurship Education College Dalian Minzu UniversityDalianChina Computer Science and Engineering College South China University of TechnologyGuangzhouChina Department of Computer and Information Science Faculty of Science and TechnologyUniversity of MacaoMacaoChina School of Automation Engineering University of Electronic Science and Technology of ChinaChengduChina Faculty of Navigation Vietnam Maritime UniversityHaiphongVietnam

Target tracking has a wide range of applications in intelligent transportation,real‐time monitoring,human‐computer interaction and other ***,in the tracking process,the target is prone to deformation,occlusion,loss,scale variation,background clutter,illumination variation,etc.,which bring great challenges to realize accurate and real‐time *** based on Siamese networks promotes the application of deep learning in the field of target tracking,ensuring both accuracy and real‐time ***,due to its offline training,it is difficult to deal with the fast motion,serious occlusion,loss and deformation of the target during ***,it is very helpful to improve the performance of the Siamese networks by learning new features of the target quickly and updating the target position in time *** broad learning system(BLS)has a simple network structure,high learning efficiency,and strong feature learning *** at the problems of Siamese networks and the characteristics of BLS,a target tracking method based on BLS is *** method combines offline training with fast online learning of new features,which not only adopts the powerful feature representation ability of deep learning,but also skillfully uses the BLS for re‐learning and re‐*** broad re‐learning information is used for re‐detection when the target tracking appears serious occlusion and so on,so as to change the selection of the Siamese networks search area,solve the problem that the search range cannot meet the fast motion of the target,and improve the *** results show that the proposed method achieves good results on three challenging datasets and improves the performance of the basic algorithm in difficult scenarios.

关键词： broad learning system siamese network target tracking

EARLY NEOLITHIC SKULLS IN QUYNH VAN NGHE AN NORTH VIETNAM

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

古脊椎动物学报(中英文） 1966年第1期 49-57页

作者： NGUYEN duy NGUYEN quang QUYEN Section of Anthropology Institute of Archaeology Vietnam Section of Anatomy Faculty of Medicine Vietnam

In the beginning of 1964,our archaeologists excavated the old cemetery in Quynh van,and found 30 graves,in which 2 calva were rather well *** calva “Q.V.M.15”was exhumed with a mandible,2 very simple ceramics and 3 flakes,in the *** calva “Q.V.M.17”was exhumed in the grave *** to the Vietnamese Institute of Archaeology it is an ancient cemetery ina kjokkenmoding,in Quynh Van,Ngh

关键词： very than EARLY NEOLITHIC SKULLS IN QUYNH VAN NGHE AN NORTH VIETNAM