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Effi-CNN: real-time vision-based system for interpretation of sign language using CNN and transfer learning

Multimedia Tools and Applications 2025年第6期84卷 3137-3159页

作者： Pranav Katarya, Rahul Big Data Analytics and Web Intelligence Laboratory Computer Science & Engineering Department Delhi Technological University New Delhi India

The deaf and mute population has difficulty conveying their thoughts and ideas to others. Sign language is their most expressive mode of communication, but the general public is callow of sign language;therefore, the mute and deaf have difficulty communicating with others. A system that can correctly translate sign language motions to speech and vice versa in real time is required to overcome this communication barrier. Effi-CNN, a vision-based Sign Language Recognition (SLR) system employing transfer learning with EfficientNetB2, is proposed in this paper. We have also developed a system covering sign gestures to text in real time. Our approach was evaluated on eight publicly available datasets, including the Massey University gesture dataset, the ArSL2018 dataset, the MNIST-ASL dataset, and others. When comparing our results to state-of-the-art algorithms, the experimental findings showed that our proposed work is more successful than existing models. Our proposed model delivered an accuracy of 99.90 on MNIST dataset. The results show that our Effi-CNN surpasses most currently existing solutions and can categorize many gestures with a low error rate. © The Author(s), under exclusive licence to Springer science+Business Media, LLC, part of Springer Nature 2025.

关键词： Convolutional neural networks

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A generalized integrated framework for urban public transport operations evaluation based on interval neutrosophic TODIM and EDAS technique

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Soft Computing 2024年第17-18期28卷 10331-10344页

作者： Cai, Yunpeng Department of Data Science and Big Data Technology Shenyang Normal University Liaoning Shenyang110034 China

With the acceleration of urbanization construction, the contradiction between supply and demand of urban public transportation resources is becoming increasingly prominent, resulting in increasingly serious problems such as traffic congestion and environmental pollution, which has a great impact on the sustainable development of cities. The experience of mature markets both domestically and internationally indicates that priority must be given to the development of public transportation networks with rail transit as the backbone. Due to the fact that the operation of the rail transit system should not only focus on market benefits but also meet social benefits as much as possible, evaluating efficiency has become a prerequisite for managing rail transit and an important topic in the performance evaluation of urban public transportation. The urban public transport operations evaluation is a multiple-attribute group decision-making (MAGDM). Then, the TODIM and EDAS method has been constructed to deal with MAGDM issues. The interval neutrosophic sets (INSs) are constructed as an effective tool for representing uncertain information during the urban public transport operations evaluation. In this manuscript, the interval neutrosophic number TODIM-EDAS (INN-TODIM-EDAS) method is constructed to solve the MAGDM under INSs. Finally, a numerical example study for urban public transport operations evaluation is constructed to validate the INN-TODIM-EDAS method. The main research contribution of this paper is constructed: (1) the INN-TODIM-EDAS method is put up for MAGDM with INSs;(2) the INN-TODIM-EDAS method is put up for urban public transport operations evaluation and were compared with existing methods;(3) Through the detailed comparison, it is evident that INN-TODIM-EDAS method for urban public transport operations evaluation proposed in this paper are effective. © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2024.

关键词： Traffic congestion

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T³Planner: Multi-Phase Planning Across Structure-Constrained Optical, IP, and Routing Topologies

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IEEE Journal on Selected Areas in Communications 2025年第5期43卷 1823-1839页

作者： Hao, Yijun Yang, Shusen Li, Fang Zhang, Yifan Zhao, Cong Ren, Xuebin Zhao, Peng Xu, Chenren Wang, Shibo Xi’an Jiaotong University National Engineering Laboratory for Big Data Analytics Xi’an710049 China Xi’an Jiaotong University National Engineering Laboratory for Big Data Analytics Ministry of Education Key Laboratory for Intelligent Networks and Network Security Xi’an710049 China Peking University School of Computer Science Beijing100871 China The Chinese University of Hong Kong Department of Computer Science and Engineering Hong Kong National Engineering Laboratory for Big Data Analytics Xi'an Jiaotong University Xi'an710049 China

Network topology planning is an essential multi-phase process to build and jointly optimize the multi-layer network topologies in wide-area networks (WANs). Most existing practices target single-phase/layer planning, and are incapable of satisfying all rigorous topological structure constraints (e.g., dual-homing rings) defined by network standards and operators, especially in large-scale networks. These significantly limit their usability and performance in production networks. We consider a general topology planning problem with typical structure constraints over three essential phases (greenfield, reconfiguration, and site expansion) and topological layers (optical, IP, and routing topologies). We present, T3Planner, a novel practical solver to this problem in production. Specifically, we develop a structure-driven encoder based on graph neural network (GNN) for concise structure encoding, and design a new learning framework with optical-centric layer compression/reconstruction and rule-aided reinforcement learning (RL) for fast convergence and high performance. Extensive experiments on nine real topologies demonstrate that T3Planner scales to large optical networks with hundreds of sites, saves 46.6% cost, and supports 3.12x more demand when compared to related existing approaches. © 1983-2012 IEEE.

关键词： Network topology

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Computing Persistent Homology by Spanning Trees and Critical Simplices

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Research 2024年第2期2023卷 519-527页

作者： Dinghua Shi Zhifeng Chen Chuang Ma Guanrong Chen Department of Mathematics Cllege of ScienceShanghai UniversityShanghaiChina School of Big Data Fuzhou University of International Studies and TradeFuzhouChina Department of Data Science and Big Data Technology School of InternetAnhui UniversityHefeiChina Department of Electrical Engineering City University of Hong KongHong KongChina

Topological data analysis can extract effective information from higher-dimensional *** mathematical basis is persistent *** persistent homology can calculate topological features at different spatiotemporal scales of the dataset,that is,establishing the integrated taxonomic relation among points,lines,and ***,the simplicial network composed of all-order simplices in a simplicial complex is *** the sequence of nested simplicial subnetworks can be regarded as a discrete Morse function from the simplicial network to real values,a method based on the concept of critical simplices can be developed by searching all-order spanning *** this new method,not only the Morse function values with the theoretical minimum number of critical simplices can be obtained,but also the Betti numbers and composition of all-order cavities in the simplicial network can be calculated ***,this method is used to analyze some examples and compared with other methods,showing its effectiveness and feasibility.

关键词： Morse establishing topological

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Abaca Fiber as a Potential Reinforcer for Acoustic Absorption Material at Middle-High Frequencies

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Journal of Renewable Materials 2024年第5期12卷 909-921页

作者： Susilo Indrawati Lila Yuwana Suyatno Mochamad Zainuri Darminto Department of Physics Faculty of Science and Data AnalyticsInstitut Teknologi Sepuluh NopemberSurabaya60111Indonesia

Recently,abacaﬁbers have become the focus of specialized research due to their intriguing characteristics,with their outstanding mechanical properties being a particularly *** the conducted study,the abacaﬁbers underwent a preliminary treatment process involving an alkaline solution,which was composed of 0.5%sodium hydroxide(NaOH)and 50%acetic acid(CH3COOH).This process entailed immersing eachﬁber in the solution for a period of one *** treatment led to a 52.36%reduction in lignin content compared to the levels before treatment,resulting in a dramatic decrease in the full width at half maximum(FWHM)in the XRD spectra from 1.13 to *** change indicates that theﬁbers became more crystalline following the *** abacaﬁbers were also characterized using BET(Brunauer Emmett Teller)measurements,which revealed that the aver-age pore length ranged from 33–49 nm and the surface area was between 13–28 m^(2)·g^(-1).The morphology of the abacaﬁber after alkali an hydrolisis treatment(AFAH)appeared rougher and more *** measurements revealed a signiﬁcant rise in the storage modulus of the singleﬁber post-treatment,with dependencies on both frequency and *** exhibited an optimal absorption coefﬁcient ofα=0.9 for frequencies above 2500 *** combined effect of alkalization and hydrolyzation treatments,while resulting in an enhancement in the mechanical properties of theﬁbers,also reduced high-intensity noise produced by sources such as machin-ery,aircraft takeoffs and landings,etc.,across a broader working frequency range.

关键词： Abacaﬁber alkalization mechanical property acoustic characteristics middle frequency

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Adsorption of Malachite Green Using Activated Carbon from Mangosteen Peel: Optimization Using Box-Behnken Design

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Journal of Renewable Materials 2024年第5期12卷 981-992页

作者： Nabila Eka Yuningsih Latifa Ariani Suprapto Suprapto Ita Ulfin Harmami Harmami Hendro Juwono Yatim Lailun Ni’mah Department of Chemistry Faculty of Science and Data AnalyticsInstitute Technology of Sepuluh NopemberSurabaya60111Indonesia

In this research,activated carbon from mangosteen peel has been synthesized using sulfuric acid as an *** adsorption performance of the activated carbon was optimized using malachite green dye as ***-chite green dye waste is a toxic and non-biodegradable material that damages the *** of adsorption processes was carried out using Response Surface Methodology(RSM)with a Box-Behnken Design(BBD).The synthesized activated carbon was characterized using FTIR and SEM *** FTIR spectra conﬁrmed the presence of a sulfonate group(-SO_(3)H)in the activated carbon,indicating that the activation pro-cess using sulfuric acid was *** characterization shows that activated carbon has porous *** was carried out for three adsorption parameters,namely contact time(20,60,and 120 min),adsor-bent mass(0.005,0.025,and 0.05 g),and initial concentration of malachite green solution(5,50,and 100 mg·L^(-1)).The concentration of the malachite green solution was determined using a UV-Vis spectrophotometer at the max-imum wavelength of malachite green,618 *** optimum of malachite green adsorption using mangosteen peel activated carbon was obtained at a contact time of 80 min,an adsorbent mass of 0.032 g,and malachite green initial concentration of 25 mg·L^(-1),with a maximum removal percentage and maximum adsorption capacity of 93.66%and 19.345 mg·g^(-1),respectively.

关键词： Response surface methodology dyes activated carbon experimental design

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Human mobility and the infectious disease transmission:a systematic review

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地球空间信息科学学报（英文版） 2024年第6期27卷中插6,1824-1851页

作者： M.Naser Lessani Zhenlong Li Fengrui Jing Shan Qiao Jiajia Zhang Bankole Olatosi Xiaoming Li Geoinformation and Big Data Research Lab Department of GeographyUniversity of South CarolinaColumbiaSCUSA Big Data Health Science Center University of South CarolinaColumbiaSCUSA Big Data Health Science Center University of South CarolinaColumbiaSCUSA Department of Health Promotion Educationand BehaviorUniversity of South CarolinaColumbiaSCUSA Big Data Health Science Center University of South CarolinaColumbiaSCUSA Department of Epidemiology and Biostatistics Arnold School of Public HealthUniversity of South CarolinaColumbiaSCUSA Big Data Health Science Center University of South CarolinaColumbiaSCUSA Department of Health Services Policy and Management Arnold School of Public HealthUniversity of South CarolinaColumbiaSCUSA

Recent decades have witnessed several infectious disease outbreaks,including the coronavirus disease(COVID-19)pandemic,which had catastrophic impacts on societies around the *** the same time,the twenty-first century has experienced an unprecedented era of techno-logical development and demographic changes:exploding population growth,increased air-line flights,and increased rural-to-urban migration,with an estimated 281 million international migrants worldwide in 2020,despite COVID-19 movement *** this review,we synthesized 195 research articles that examined the association between human movement and infectious disease outbreaks to understand the extent to which human mobility has increased the risk of infectious disease *** article covers eight infectious diseases,ranging from respiratory illnesses to sexually transmitted and vector-borne *** review revealed a strong association between human mobility and infectious disease spread,particularly strong for respiratory illnesses like COVID-19 and *** significant research into the relationship between infectious diseases and human mobility,four knowl-edge gaps were identified based on reviewed literature in this study:1)although some studies have used big data in investigating infectious diseases,the efforts are limited(with the exception of COVID-19 disease),2)while some research has explored the use of multiple data sources,there has been limited focus on fully integrating these data into comprehensive analyses,3)limited research on the global impact of mobility on the spread of infectious disease with most studies focusing on local or regional outbreaks,and 4)lack of standardiza-tion in the methodology for measuring the impacts of human mobility on infectious disease *** tackling the recognized knowledge gaps and adopting holistic,interdisciplinary methods,forthcoming research has the potential to substantially enhance our comprehension of the intricate inter

关键词： Human mobility geography infectious diseases sexually transmitted diseases systematic review

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The Adsorption of Pb(II)Using Silica Gel Synthesized from Chemical Bottle Waste:Optimization Using Box-Behnken Design

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Journal of Renewable Materials 2023年第6期11卷 2913-2924页

作者： Yatim Lailun Ni’mah Nabila Eka Yuningsih Suprapto Suprapto Department of Chemistry Faculty of Science and Data AnalyticsInstitut Teknologi Sepuluh NopemberSurabayaIndonesia

The adsorption of Pb(II)on silica gel synthesized from chemical glass bottle waste has been *** effect of independent variables(adsorbent dose,initial concentration of Pb(II),contact time,and pH)on the Pb(II)removal from water was evaluated and optimized using the Response Surface Methodology(RSM).Under optimized conditions(adsorbent dose:20 mg;contact time:30 min;initial Pb(II)concentration:120 mg.L^(−1);and pH:8),the removal of Pb(II)was 99.77%.The adsorption equilibrium data obtained from the batch experiment were investigated using different isotherm *** Langmuir isotherm model fits the experimental *** shows that the surface of the silica gel synthesized from chemical bottles waste was covered by a Pb(II)*** analysis showed that the synthesized silica gel had a SiO_(2) content of 75.63%.Amorphous silica was observed from XRD ***-EDX characterization showed that Pb was adsorbed on the silica gel *** analysis showed that silica gel has irregular particles with a surface area of 297.08 m2.g^(−1) with a pore radius of 15.74 nm calculated from BET analysis.

关键词： Chemical bottle waste silica gel adsorption box-behnken design response surface methodology

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On the Convergence of Prey Predator Algorithm

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International Journal of Applied and Computational Mathematics 2024年第2期10卷 1-23页

作者： Tilahun, Surafel Luleseged Department of Mathematics HPC and Big Data Analytics Center of Excellence Addis Ababa Science and Technology University Addis Ababa 16417 Ethiopia

Unlike their success in solving complex and difficult problems, there is a lack of proper mathematical analysis and discussion of metaheuristic algorithms. Even though some researches are done on these aspects, the gap is still wide and different researchers outlined that more needs to be done to understand and analyse the search behaviour mathematically in order to move towards explainable AI. Convergence analysis is one of the issues researchers are trying to address. In this paper, a discussion on the convergence of prey predator algorithm will be presented. It is a swarm based algorithm which shows promising results. Furthermore, some initial researches show that it is a generalized algorithm where some well known algorithms fall as its special case. Hence, its analysis can be customized and used for other algorithms as well. Based on mathematical arguments, this paper discusses the convergence analysis of the algorithm to a near optimal solution with appropriate implementation, i.e. appropriate parameter setting. Prey predator algorithm is shown to be an ϵ-convergent algorithm that means there is a non infinity iteration number to get at least epsilon less quality from an optimal solution. © The Author(s), under exclusive licence to Springer Nature India Private Limited 2024.

关键词： Convergence Metaheuristic Prey predator algorithm Swarm intelligence

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Intrusion Detection and Prevention System AI Based Features with Random Forest

Intrusion Detection and Prevention System AI Based Features ...

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2024 IEEE Ural-Siberian Conference on Biomedical Engineering, Radioelectronics and Information Technology, USBEREIT 2024

作者： Al-Doori, Mohammed B. Komotskiy, Evgeny I. Ural Federal University Department Of Big Data Analytics And Methods Of Videoanalysis Ekaterinburg Russia

ISBN: (纸本)9798350362893

The research addresses sophisticated methods for Intrusion Detection Systems (IDS) and Intrusion Prevention Systems (IPS), leveraging AI-based feature optimization and diverse machine learning strategies to bolster network intrusion detection and prevention. The study primarily utilizes the NSLKDD dataset, an enhanced version of the KDD Cup 1999 dataset, chosen for its realistic portrayal of various attack types and for addressing the shortcomings of the original dataset. The methodology includes AI-based feature optimization using Particle Swarm Optimization and Genetic Algorithm, focusing on maximizing information gain and entropy. This is integrated with the use of Random Forest (RF) to reduce class overlapping, further enhanced by boosting techniques. Grey Wolves Optimization (GWO) is combined with Random Forest. This innovative approach, supplemented by grey wolf hunting strategies, is employed for classification tasks on the NSL-KDD dataset. The performance metrics for each intrusion class are meticulously evaluated, revealing that the GWO-RF combination achieves an accuracy of 0.94, precision of 0.95, recall of 0.93, and an F1 score of 0.94. © 2024 IEEE.

关键词： Anomaly detection

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