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Traffic engineering and Quality of Service in Hybrid Software Defined Networks

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China Communications 2024年第2期21卷 96-121页

作者： Samiullah Mehraban Rajesh Kumar Yadav IOT Lab Department of Computer Science&EngineeringDelhi Technological UniversityDelhi 110042India

For Future networks, many research projects have proposed different architectures around the globe;Software Defined Network(SDN) architectures, through separating Data and Control Layers, offer a crucial structure for it. With a worldwide view and centralized Control, the SDN network provides flexible and reliable network management that improves network throughput and increases link utilization. In addition, it supports an innovative flow scheduling system to help advance Traffic engineering(TE). For Medium and large-scale networks migrating directly from a legacy network to an SDN Network seems more complicated & even impossible, as there are High potential challenges, including technical, financial, security, shortage of standards, and quality of service degradation challenges. These challenges cause the birth and pave the ground for Hybrid SDN networks, where SDN devices coexist with traditional network devices. This study explores a Hybrid SDN network’s Traffic engineering and Quality of Services Issues. Quality of service is described by network characteristics such as latency, jitter, loss, bandwidth,and network link utilization, using industry standards and mechanisms in a Hybrid SDN Network. We have organized the related studies in a way that the Quality of Service may gain the most benefit from the concept of Hybrid SDN networks using different algorithms and mechanisms: Deep Reinforcement Learning(DRL), Heuristic algorithm, K path partition algorithm, Genetic algorithm, SOTE algorithm, ROAR method, and Routing Optimization with different optimization mechanisms that help to ensure high-quality performance in a Hybrid SDN Network.

关键词： DRL hSDN QoE QoS SDN TE

Atomically Adjustable Rhodium Catalyst Synthesis with Outstanding Mass Activity via Surface-Li mi ted Cation Exchange

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Energy & Environmental Materials 2024年第2期7卷 83-92页

作者： Hak Hyeon Lee Dong Su Kim Swagotom Sarker Ji Hoon Choi Ho Seong Lee Hyung Koun Cho department of Advanced Materials science&engineering Sungkyunkwan University2066Seobu-roJangan-guSuwon-siGyeonggi-doSeoul 16419Korea department of Advanced Materials science&engineering Kyungpook National University80Daehak-roBuk-guDaegu 41566Korea

Rh has been widely studied as a catalyst for the promising hydrazine oxidation reaction that can replace oxygen evolution reactions for boosting hydrogen production from hydrazine-containing *** Rh being expensive,only a few studies have examined its electrocatalytic mass ***,surface-limited cation exchange and electrochemical activation processes are designed to remarkably enhance the mass activity of *** atoms were readily replaced at the Ni sites on the surface of NiOOH electrodes by cation exchange,and the resulting RhOOH compounds were activated by the electrochemical reduction *** cation exchange-derived Rh catalysts exhibited particle sizes not exceeding 2 nm without agglomeration,indicating a decrease in the number of inactive inner Rh ***,an improved mass activity of 30 A mg_(Rh)^(-1)was achieved at 0.4 V versus reversible hydrogen ***,the two-electrode system employing the same CE-derived Rh electrodes achieved overall hydrazine splitting over 36 h at a stable low *** proposed surface-limited CE process is an effective method for reducing inactive atoms of expensive noble metal catalysts.

关键词： cation exchange synthesis electrochemical metallization hydrazine oxidation reaction mass activity rhodium catalyst

Surface-modified Ag@Ru-P25 for photocatalytic CO_(2) conversion with high selectivity over CH_(4) formation at the solid–gas interface

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Carbon Energy 2024年第1期6卷 182-196页

作者： Chaitanya B.Hiragond Sohag Biswas Niket SPowar Junho Lee Eunhee Gong Hwapyong Kim Hong Soo Kim Jin-Woo Jung Chang-Hee Cho Bryan M.Wong Su-Il In department of Energy science&engineering Daegu Gyeongbuk Institute of Science and Technology(DGIST)DaeguRepublic of Korea department of Chemical&Environmental engineering Materials Science&Engineering ProgramDepartment of ChemistryDepartment of Physics&AstronomyUniversity of California-RiversideRiversideCaliforniaUSA department of Physics and Chemistry Daegu Gyeongbuk Institute of Science and Technology(DGIST)DaeguRepublic of Korea Nicescience Corporation DaeguRepublic of Korea

Systematic optimization of the photocatalyst and investigation of the role of each component is important to maximizing catalytic activity and comprehending the photocatalytic conversion of CO_(2) reduction to solar fuels.A surface-modified Ag@Ru-P25 photocatalyst with H_(2)O_(2) treatment was designed in this study to convert CO_(2) and H_(2)O vapor into highly selective *** doping followed by Ag nanoparticles(NPs)cocatalyst deposition on P25(TiO_(2))enhances visible light absorption and charge separation,whereas H_(2)O_(2) treatment modifies the surface of the photocatalyst with hydroxyl(–OH)groups and promotes CO_(2) ***-resonance transmission electron microscopy,X-ray photoelectron spectroscopy,X-ray absorption near-edge structure,and extended X-ray absorption fine structure techniques were used to analyze the surface and chemical composition of the photocatalyst,while thermogravimetric analysis,CO_(2) adsorption isotherm,and temperature programmed desorption study were performed to examine the significance of H_(2)O_(2) treatment in increasing CO_(2) reduction *** optimized Ag1.0@Ru1.0-P25 photocatalyst performed excellent CO_(2) reduction activity into CO,CH4,and C2H6 with a~95%selectivity of CH4,where the activity was~135 times higher than that of pristine TiO_(2)(P25).For the first time,this work explored the effect of H_(2)O_(2) treatment on the photocatalyst that dramatically increases CO_(2) reduction activity.

关键词： gas-phase CO_(2) reduction H_(2)O_(2) treatment plasmonic nanoparticles solar fuel photocatalyst surface modification

Japanese Sign Language Recognition by Combining Joint Skeleton-Based Handcrafted and Pixel-Based Deep Learning Features with Machine Learning Classification

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Computer Modeling in engineering & sciences 2024年第6期139卷 2605-2625页

作者： Jungpil Shin Md.Al Mehedi Hasan Abu Saleh Musa Miah Kota Suzuki Koki Hirooka School of Computer science and engineering The University of AizuAizuwakamatsu965-8580Japan department of Computer science&engineering Rajshahi University of Engineering&TechnologyRajshahi6204Bangladesh

Sign language recognition is vital for enhancing communication accessibility among the Deaf and hard-of-hearing *** Japan,approximately 360,000 individualswith hearing and speech disabilities rely on Japanese Sign Language(JSL)for ***,existing JSL recognition systems have faced significant performance limitations due to inherent *** response to these challenges,we present a novel JSL recognition system that employs a strategic fusion approach,combining joint skeleton-based handcrafted features and pixel-based deep learning *** system incorporates two distinct streams:the first stream extracts crucial handcrafted features,emphasizing the capture of hand and body movements within JSL ***,a deep learning-based transfer learning stream captures hierarchical representations of JSL gestures in the second ***,we concatenated the critical information of the first stream and the hierarchy of the second stream features to produce the multiple levels of the fusion features,aiming to create a comprehensive representation of the JSL *** reducing the dimensionality of the feature,a feature selection approach and a kernel-based support vector machine(SVM)were used for the *** assess the effectiveness of our approach,we conducted extensive experiments on our Lab JSL dataset and a publicly available Arabic sign language(ArSL)*** results unequivocally demonstrate that our fusion approach significantly enhances JSL recognition accuracy and robustness compared to individual feature sets or traditional recognition methods.

关键词： Japanese Sign Language(JSL) hand gesture recognition geometric feature distance feature angle feature GoogleNet

Dynamic Hand Gesture-Based Person Identification Using Leap Motion and Machine Learning Approaches

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Computers, Materials & Continua 2024年第4期79卷 1205-1222页

作者： Jungpil Shin Md.AlMehedi Hasan Md.Maniruzzaman Taiki Watanabe Issei Jozume School of Computer science and engineering The University of AizuAizuwakamatsuFukushima965-8580Japan department of Computer science&engineering Rajshahi University of Engineering&TechnologyRajshahi6204Bangladesh

Person identification is one of the most vital tasks for network security. People are more concerned about theirsecurity due to traditional passwords becoming weaker or leaking in various attacks. In recent decades, fingerprintsand faces have been widely used for person identification, which has the risk of information leakage as a resultof reproducing fingers or faces by taking a snapshot. Recently, people have focused on creating an identifiablepattern, which will not be reproducible falsely by capturing psychological and behavioral information of a personusing vision and sensor-based techniques. In existing studies, most of the researchers used very complex patternsin this direction, which need special training and attention to remember the patterns and failed to capturethe psychological and behavioral information of a person properly. To overcome these problems, this researchdevised a novel dynamic hand gesture-based person identification system using a Leap Motion sensor. Thisstudy developed two hand gesture-based pattern datasets for performing the experiments, which contained morethan 500 samples, collected from 25 subjects. Various static and dynamic features were extracted from the handgeometry. Randomforest was used to measure feature importance using the Gini Index. Finally, the support vectormachinewas implemented for person identification and evaluate its performance using identification accuracy. Theexperimental results showed that the proposed system produced an identification accuracy of 99.8% for arbitraryhand gesture-based patterns and 99.6% for the same dynamic hand gesture-based patterns. This result indicatedthat the proposed system can be used for person identification in the field of security.

关键词： Person identification leap motion hand gesture random forest support vector machine

Machine learning for membrane design and discovery

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Green Energy & Environment 2024年第1期9卷 54-70页

作者： Haoyu Yin Muzi Xu Zhiyao Luo Xiaotian Bi Jiali Li Sui Zhang Xiaonan Wang department of Chemical engineering Tsinghua University100084BeijingChina School of Materials science&engineering Tsinghua University100084BeijingChina department of Chemical and Biomolecular engineering National University of SingaporeSingapore117576Singapore

Membrane technologies are becoming increasingly versatile and helpful today for sustainable *** Learning(ML),an essential branch of artiﬁcial intelligence(AI),has substantially impacted the research and development norm of new materials for energy and *** review provides an overview and perspectives on ML methodologies and their applications in membrane design and dis-covery.A brief overview of membrane technologies isﬁrst provided with the current bottlenecks and potential *** an appli-cations-based perspective of AI-aided membrane design and discovery,we further show how ML strategies are applied to the membrane discovery cycle(including membrane material design,membrane application,membrane process design,and knowledge extraction),in various membrane systems,ranging from gas,liquid,and fuel cell separation ***,the best practices of integrating ML methods and speciﬁc application targets in membrane design and discovery are presented with an ideal paradigm *** challenges to be addressed and prospects of AI applications in membrane discovery are also highlighted in the end.

关键词： Machine learning Membranes AI for Membrane Data-driven Design

Bayesian Optimized LightGBM model for predicting the fundamental vibrational period of masonry infilled RC frames

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Frontiers of Structural and Civil engineering 2024年第7期18卷 1084-1102页

作者： Taimur RAHMAN Pengfei ZHENG Shamima SULTANA department of Civil engineering World University of BangladeshDhaka 1230Bangladesh School of Civil engineering Zhengzhou UniversityZhengzhou 450001China department of Computer science&engineering University of Asia PacificDhaka 1205Bangladesh

The precise prediction of the fundamental vibrational period for reinforced concrete(RC)buildings with infilled walls is essential for structural design,especially earthquake-resistant *** learning models from previous studies,while boasting commendable accuracy in predicting the fundamental period,exhibit vulnerabilities due to lengthy training times and inherent dependence on pre-trained models,especially when engaging with continually evolving data *** predicament emphasizes the necessity for a model that adeptly balances predictive accuracy with robust adaptability and swift data *** latter should include consistent re-training ability as demanded by realtime,continuously updated data *** research implements an optimized Light Gradient Boosting Machine(LightGBM)model,highlighting its augmented predictive capabilities,realized through the astute use of Bayesian Optimization for hyperparameter tuning on the FP4026 research data set,and illuminating its adaptability and efficiency in predictive *** results show that the R^(2) score of LightGBM model is 0.9995 and RMSE is 0.0178,while training speed is 23.2 times faster than that offered by XGBoost and 45.5 times faster than for Gradient ***,this study introduces a practical application through a streamlit-powered,web-based dashboard,enabling engineers to effortlessly utilize and augment the model,contributing data and ensuring precise fundamental period predictions,effectively bridging scholarly research and practical applications.

关键词： masonry-infilled RC frame fundamental period LightGBM FP4026 research dataset machine learning data-driven approach Bayesian Optimization

Recent progress of self-supported air electrodes for flexible Zn-air batteries

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Journal of Energy Chemistry 2024年第2期89卷 110-136,I0004页

作者： Chen Xu Yanli Niu Vonika Ka-Man Au Shuaiqi Gong Xuan Liu Jianying Wang Deli Wu Zuofeng Chen School of Chemical science and engineering Tongji UniversityShanghai 200092China College of Environmental science&engineering Tongji UniversityShanghai 200092China department of science and Environmental Studies The Education University of Hong KongHong KongChina

Smart wearable devices are regarded to be the next prevailing technology product after smartphones and smart homes,and thus there has recently been rapid development in flexible electronic energy storage *** them,flexible solid-state zinc-air batteries have received widespread attention because of their high energy density,good safety,and *** bifunctional oxygen electrocatalysts are the primary consideration in the development of flexible solid-state zinc-air batteries,and self-supported air cathodes are strong candidates because of their advantages including simplified fabrication process,reduced interfacial resistance,accelerated electron transfer,and good *** review outlines the research progress in the design and construction of nanoarray bifunctional oxygen *** from the configuration and basic principles of zinc-air batteries and the strategies for the design of bifunctional oxygen electrocatalysts,a detailed discussion of self-supported air cathodes on carbon and metal substrates and their uses in flexible zinc-air batteries will ***,the challenges and opportunities in the development of flexible zinc-air batteries will be discussed.

关键词： Bifunctional electrocatalysts Oxygen reduction reaction Oxygen evolution reaction Self-supported air electrodes Flexible zinc-air batteries

New process for treating boron-bearing iron ore by flash reduction coupled with magnetic separation

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International Journal of Minerals,Metallurgy and Materials 2024年第3期31卷 473-484页

作者： Qipeng Bao Lei Guo Hong Yong Sohn Haibin Zuo Feng Liu Yongliang Gao Zhancheng Guo State Key Laboratory of Advanced Metallurgy University of Science and Technology BeijingBeijing 100083China department of Materials science&engineering University of UtahUtah 84112USA China ENFI engineering Corporation Beijing 100038China

Boron is an important industrial raw material often sourced from minerals containing different compounds that cocrystallize,which makes it difficult to separate the mineral phases through conventional *** study proposed a new treatment called flash reduction-melting separation(FRMS)for boron-bearing iron *** this method,the concentrates were first flash-reduced at the temperature under which the particles melt,and the slag and the reduced iron phases disengaged at the particle *** reduc-tion and melting effects were achieved above 1550℃.The B_(2)O_(3) content in the separated slag was over 18wt%,and the B content in the iron was less than 0.03wt%.The proposed FRMS method was tested to investigate the effects of factors such as ore particle size and tem-perature on the reduction and melting steps with and without pre-reducing the raw *** mineral phase transformation and morphology evolution in the ore particles during FRMS were also comprehensively analyzed.

关键词： ludwigite boron-bearing iron concentrate flash reduction melting separation boron