检索结果-南通市图书馆

A Deep Trash Classification Model on Raspberry Pi 4

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Intelligent Automation & Soft Computing 2023年第2期35卷 2479-2491页

作者： Thien Khai Tran Kha Tu Huynh Dac-Nhuong Le Muhammad Arif hoa minh Dinh ho chi minh city university of foreign languages and information technology Ho Chi Minh City700000Vietnam International university Ho Chi Minh CityVietnam-Vietnam National UniversityHo Chi Minh City70000Vietnam Faculty of information technology Haiphong UniversityHaiphong180000Vietnam Department of Computer Science and information technology University of LahoreLahorePakistan

Environmental pollution has had substantial impacts on human life,and trash is one of the main sources of such pollution in most countries.Trash classi-ﬁcation from a collection of trash images can limit the overloading of garbage dis-posal systems and efﬁciently promote recycling activities;thus,development of such a classiﬁcation system is topical and urgent.This paper proposed an effective trash classiﬁcation system that relies on a classiﬁcation module embedded in a hard-ware setup to classify trash in real time.An image dataset isﬁrst augmented to enhance the images before classifying them as either inorganic or organic trash.The deep learning–based ResNet-50 model,an improved version of the ResNet model,is used to classify trash from the dataset of trash images.The experimental results,which are tested both on the dataset and in real time,show that ResNet-50 had an average accuracy of 96%,higher than that of related models.Moreover,integrating the classiﬁcation module into a Raspberry Pi computer,which con-trolled the trash bin slide so that garbage fell into the appropriate bin for inorganic or organic waste,created a complete trash classiﬁcation system.This proves the efﬁciency and high applicability of the proposed system.

关键词： Trash classiﬁcation ResNet raspberry pi internet of things(IoT) deep learning

Dynamic Data Optimization in IoT-Assisted Sensor Networks on Cloud Platform

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 2022年第7期72卷 1357-1372页

作者： Nguyen A.Tuan D.Akila Souvik Pal Bikramjit Sarkar Thien Khai Tran G.Mothilal Nehru Dac-Nhuong Le Faculty of information technology Ho Chi Minh City University of Foreign Languages-Information TechnologyHo Chi Minh City70000Vietnam Department of information technology Vels Institute of ScienceTechnology&Advanced StudiesChennai600117India Department of Computer Science and Engineering Sister Nivedita UniversityKolkata700156India Department of Computer Science and Engineering JIS College of EngineeringNadia741235India Institute of Research and Development Duy Tan UniversityDanang550000Vietnam School of Computer Science Duy Tan UniversityDanang550000Vietnam

This article presents a new scheme for dynamic data optimization in IoT(Internet of Things)-assisted sensor networks.The various components of IoT assisted cloud platform are discussed.In addition,a new architecture for IoT assisted sensor networks is presented.Further,a model for data optimization in IoT assisted sensor networks is proposed.A novel Membership inducing Dynamic Data Optimization Membership inducing Dynamic Data Optimization(MIDDO)algorithm for IoT assisted sensor network is proposed in this research.The proposed algorithm considers every node data and utilized membership function for the optimized data allocation.The proposed framework is compared with two stage optimization,dynamic stochastic optimization and sparsity inducing optimization and evaluated in terms of reliability ratio,coverage ratio and sensing error.Data optimization was performed based on the availability of cloud resource,sensor energy,data flow volume and the centroid of each state.It was inferred that the proposed MIDDO algorithm achieves an average performance ratio of 76.55%,reliability ratio of 94.74%,coverage ratio of 85.75%and sensing error of 0.154.

关键词： Data optimization IoT sensor network reliability membership sensor energy

Fuzzy-Based Sentiment Analysis System for Analyzing Student Feedback and Satisfaction

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 2020年第2期62卷 631-655页

作者： Yun Wang Fazli Subhan Shahaboddin Shamshirband Muhammad Zubair Asghar Ikram UllahAmmara Habib School of Public Administration Zhengzhou UniversityZhengzhouChina National university of Modern languages IslamabadPakistan Department for Management of Science and technology Development Ton Duc Thang UniversityHo Chi Minh CityVietnam Faculty of information technology Ton Duc Thang UniversityHo Chi Minh CityViet Nam Institute of Computing and information technology Gomal UniversityD.I.Khan(KP)Pakistan

The feedback collection and analysis has remained an important subject matter for long.The traditional techniques for student feedback analysis are based on questionnaire-based data collection and analysis.however,the student expresses their feedback opinions on online social media sites,which need to be analyzed.This study aims at the development of fuzzy-based sentiment analysis system for analyzing student feedback and satisfaction by assigning proper sentiment score to opinion words and polarity shifters present in the input reviews.Our technique computes the sentiment score of student feedback reviews and then applies a fuzzy-logic module to analyze and quantify student’s satisfaction at the fine-grained level.The experimental results reveal that the proposed work has outperformed the baseline studies as well as state-of-the-art machine learning classifiers.

关键词： Student feedback analysis sentiments opinion words polarity shifters lexicon-based

Three-Dimensional Isogeometric Analysis of Flexoelectricity with MATLAB Implementation

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 2020年第11期65卷 1157-1179页

作者： Hamid Ghasemi Harold S.Park Xiaoying Zhuang Timon Rabczuk Department of Mechanical Engineering Arak University of TechnologyArak38181-41167Iran Department of Mechanical Engineering Boston UniversityBostonMA 02215USA Division of Computational Mechanics Ton Duc Thang UniversityHo Chi Minh CityVietnam Faculty of Civil Engineering Ton Duc Thang UniversityHo Chi Minh CityVietnam Department of Computer Engineering College of Computer and Information SciencesKing Saud UniversityRiyadhSaudi Arabia Institute of Structural Mechanics Bauhaus-Universität WeimarWeimarD-99423Germany

Flexoelectricity is a general electromechanical phenomenon where the electric polarization exhibits a linear dependency to the gradient of mechanical strain and vice versa.The truncated pyramid compression test is among the most common setups to estimate the flexoelectric effect.We present a three-dimensional isogeometric formulation of flexoelectricity with its MATLAB implementation for a truncated pyramid setup.Besides educational purposes,this paper presents a precise computational model to illustrate how the localization of strain gradients around pyramidal boundary shapes contributes in generation of electrical energy.The MATLAB code is supposed to help learners in the Isogeometric Analysis and Finite Elements Methods community to learn how to solve a fully coupled problem,which requires higher order approximations,numerically.The complete MATLAB code which is available as source code distributed under a BSD-style license,is provided in the part of Supplementary Materials of the paper.

关键词： Flexoelectricity Isogeometric Analysis(IGA) MATLAB B-spline elements finite elements coupled electromechanical problem