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harmonic aspects of wind power integration

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journal of Modern Power Systems and Clean Energy 2013年第1期1卷 14-21页

作者： math h.j.bollen Kai YANG Electric Power Engineering Lulea University of Technology93187 SkellefteaSweden

This paper discusses a number of ways in which wind power installations can impact the harmonic levels in the power *** turbines are an additional source of harmonic emission,especially when it concerns"non-characteristic harmonics."Parallel resonances can amplify the emission from individual turbines.A mathematical model is developed to quantify this *** resonances can result in high currents,driven by the background voltage distortion in the transmission grid,flowing into thewind *** of the transmission grid will increase lower order harmonics but reduce higher order harmonics.

关键词： Power quality Power system harmonics Wind power

孤岛状态下含分布式电源的配电系统可靠性分析

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电网技术 2008年第23期32卷 77-81页

作者：孙瑜 math bollen Graham Ault 华北电力科学研究院有限责任公司北京市西城区100045 瑞典输电研究院斯特拉斯克莱德大学电气工程系

分析了孤岛状态下含分布式电源的配电系统可靠性。针对配电网孤岛运行的特点,提出了可靠性分析的复合随机性负荷模型,提出了既能反映系统充裕度又体现动态特性的可靠性计算方法和衡量指标。计算结果表明,所提的模型、计算方法和衡量指... 详细信息

分析了孤岛状态下含分布式电源的配电系统可靠性。针对配电网孤岛运行的特点,提出了可靠性分析的复合随机性负荷模型,提出了既能反映系统充裕度又体现动态特性的可靠性计算方法和衡量指标。计算结果表明,所提的模型、计算方法和衡量指标能充分反映分布式电源在不同程度上提高配电系统的可靠性,为系统的规划设计提供了重要参考。

关键词：可靠性分布式电源配电网蒙特卡罗仿真

Intelligent Real-Time IoT Traffic Steering in 5G Edge Networks

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Computers, Materials & Continua 2021年第6期67卷 3433-3450页

作者： Sa math Prohim Tam Seokhoon Kim Department of Software Convergence Soonchunhyang UniversityAsan31538Korea Department of Computer Software Engineering Soonchunhyang UniversityAsan31538Korea

In the Next Generation Radio Networks(NGRN),there will be extreme massive connectivity with the heterogeneous Internet of Things(hetIoT)*** millimeter-Wave(mmWave)communications will become a potential core technology to increase the capacity of Radio Networks(RN)and enable Multiple-Input and Multiple-Output(MIMO)of Radio Remote head(RRh)***,the challenging key issues in unfair radio resource handling remain unsolved when massive requests are occurring *** imbalance of resource utilization is one of the main issues occurs when there is overloaded connectivity to the closest RRh receiving exceeding *** handle this issue effectively,Machine Learning(ML)algorithm plays an important role to tackle the requests of massive IoT devices to RRh with its obvious capacity *** paper proposed a dynamic RRh gateways steering based on a lightweight supervised learning algorithm,namely K-Nearest Neighbor(KNN),to improve the communication Quality of Service(QoS)in real-time IoT *** supervises the model to classify and recommend the user’s requests to optimal RRhs which preserves higher *** experimental dataset was generated by using computer software and the simulation results illustrated a remarkable outperformance of the proposed scheme over the conventional methods in terms of multiple significant QoS parameters,including communication reliability,latency,and throughput.

关键词： Machine learning Internet of Things traffic steering mobile edge computing

Macroalgal deep genomics illuminate multiple paths to aquatic,photosynthetic multicellularity

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Molecular Plant 2024年第5期17卷 747-771页

作者： David R.Nelson Alexandra Mystikou Ashish jaiswal Cecilia Rad-Menendez Michael j.Preston Frederik De Boever Diana C.El Assal Sarah Daakour Michael W.Lomas jean-Claude Twizere David h.Green William C.Ratcliff Kourosh Salehi-Ashtiani Division of Science and math New York University Abu DhabiAbu DhabiUAE Center for Genomics and Systems Biology(CGSB) New York University Abu DhabiAbu DhabiUAE Biotechnology Research Center Technology Innovation InstitutePO Box 9639Masdar CityAbu DhabiUAE Culture Collection of Algae and Protozoa Scottish Association for Marine ScienceObanScotlandUK National Center for Marine Algae and Microbiota Bigelow Laboratory for Ocean SciencesEast BoothbayMEUSA Laboratory of Viral Interactomes GIGA InstituteUniversity of LiegeLiegeBelgium School of Biological Sciences Georgia Institute of TechnologyAtlantaGAUSA

Macroalgae are multicellular,aquatic autotrophs that play vital roles in global climate maintenance and have diverse applications in biotechnology and eco-engineering,which are directly linked to their multicellularity ***,their genomic diversity and the evolutionary mechanisms underlying multicellularity in these organisms remain *** this study,we sequenced 110 macroalgal genomes from diverse climates and phyla,and identified key genomic features that distinguish them from their microalgal *** for cell adhesion,extracellular matrix formation,cell polarity,transport,and cell differentiation distinguish macroalgae from microalgae across all three major phyla,constituting conserved and unique gene sets supporting multicellular *** genes show phylum-and climate-specific expansions that may facilitate niche ***,our study reveals genetic determinants of convergent and divergent evolutionary trajectories that have shaped morphological diversity in macroalgae and provides genome-wide frameworks to understand photosynthetic multicellular evolution in aquatic environments.

关键词： macroalgae multicellularity comparative genomics evolution adhesome endogenous viral elements

Multi-Agent Deep Q-Networks for Efficient Edge Federated Learning Communications in Software-Defined IoT

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Computers, Materials & Continua 2022年第5期71卷 3319-3335页

作者： Prohim Tam Sa math Ahyoung Lee Seokhoon Kim Department of Software Convergence Soonchunhyang UniversityAsan31538Korea Department of Computer Science Kennesaw State UniversityMariettaGA 30060USA Department of Computer Software Engineering Soonchunhyang UniversityAsan31538Korea

Federated learning(FL)activates distributed on-device computation techniques to model a better algorithm performance with the interaction of local model updates and global model distributions in aggregation averaging ***,in large-scale heterogeneous Internet of Things(IoT)cellular networks,massive multi-dimensional model update iterations and resource-constrained computation are challenging aspects to be tackled *** paper introduces the system model of converging softwaredefined networking(SDN)and network functions virtualization(NFV)to enable device/resource abstractions and provide NFV-enabled edge FL(eFL)aggregation servers for advancing automation and ***-agent deep Q-networks(MADQNs)target to enforce a self-learning softwarization,optimize resource allocation policies,and advocate computation offloading *** gathered network conditions and resource states,the proposed agent aims to explore various actions for estimating expected longterm rewards in a particular state *** exploration phase,optimal actions for joint resource allocation and offloading decisions in different possible states are obtained by maximum Q-value ***-based virtual network functions(VNF)forwarding graph(VNFFG)is orchestrated to map VNFs towards eFL aggregation server with sufficient communication and computation resources in NFV infrastructure(NFVI).The proposed scheme indicates deficient allocation actions,modifies the VNF backup instances,and reallocates the virtual resource for exploitation *** neural network(DNN)is used as a value function approximator,and epsilongreedy algorithm balances exploration and *** scheme primarily considers the criticalities of FL model services and congestion states to optimize long-term *** results presented the outperformance of the proposed scheme over reference schemes in terms of Quality of Service(QoS)performance metrics,including packet

关键词： Deep Q-networks federated learning network functions virtualization quality of service software-defined networking

Adaptive Partial Task Offloading and Virtual Resource Placement in SDN/NFV-Based Network Softwarization

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Computer Systems Science & Engineering 2023年第5期45卷 2141-2154页

作者： Prohim Tam Sa math Seokhoon Kim Department of Software Convergence Soonchunhyang UniversityAsan31538Korea Department of Computer Software Engineering Soonchunhyang UniversityAsan31538Korea

Edge intelligence brings the deployment of applied deep learning(DL)models in edge computing systems to alleviate the core backbone network *** setup of programmable software-defined networking(SDN)control and elastic virtual computing resources within network functions virtualization(NFV)are cooperative for enhancing the applicability of intelligent edge *** offer advancement for multi-dimensional model task offloading in edge networks with SDN/NFV-based control softwarization,this study proposes a DL mechanism to recommend the optimal edge node selection with primary features of congestion windows,link delays,and allocatable bandwidth *** partial task offloading policy considered the DL-based recommendation to modify efficient virtual resource placement for minimizing the completion time and termination drop *** optimization problem of resource placement is tackled by a deep reinforcement learning(DRL)-based policy following the Markov decision process(MDP).The agent observes the state spaces and applies value-maximized action of available computation resources and adjustable resource allocation *** reward formulation primarily considers taskrequired computing resources and action-applied allocation *** defined policies of resource determination,the orchestration procedure is configured within each virtual network function(VNF)descriptor using topology and orchestration specification for cloud applications(TOSCA)by specifying the allocated *** simulation for the control rule installation is conducted using Mininet and Ryu SDN *** delay and task delivery/drop ratios are used as the key performance metrics.

关键词： Deep learning partial task offloading software-defined networking virtual machine virtual network functions

Intelligent Resource Allocations for Software-Defined Mission-Critical IoT Services

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Computers, Materials & Continua 2022年第11期73卷 4087-4102页

作者： Chaebeen Nam Sa math Prohim Tam Seokhoon Kim Department of Software Convergence Soonchunhyang UniversityAsan31538Korea Department of Computer Software Engineering Soonchunhyang UniversityAsan31538Korea

heterogeneous Internet of Things(IoT)applications generate a diversity of novelty applications and services in next-generation networks(NGN),which is essential to guarantee end-to-end(E2E)communication resources for both control plane(CP)and data plane(DP).Likewise,the heterogeneous 5th generation(5G)communication applications,including Mobile Broadband Communications(MBBC),massive Machine-Type Commutation(mMTC),and ultra-reliable low latency communications(URLLC),obligate to perform intelligent Quality-of-Service(QoS)Class Identifier(QCI),while the CP entities will be suffered from the complicated massive hIOT ***,the existing management and orchestration(MANO)models are inappropriate for resource utilization and allocation in large-scale and complicated network *** cope with the issues mentioned above,this paper presents an adopted software-defined mobile edge computing(SDMEC)with a lightweight machine learning(ML)algorithm,namely support vector machine(SVM),to enable intelligent MANO for real-time and resource-constraints IoT applications which require lightweight computation ***,the SVM algorithm plays an essential role in performing QCI ***,the software-defined networking(SDN)controller allocates and configures priority resources according to the SVM classification ***,the complementary of SVM and SDMEC conducts intelligent resource MANO for massive QCI environments and meets the perspectives of mission-critical communication with resource constraint *** on the E2E experimentation metrics,the proposed scheme shows remarkable outperformance in key performance indicator(KPI)QoS,including communication reliability,latency,and communication throughput over the various powerful reference methods.

关键词： Mobile edge computing Internet of Things software defined networks traffic classification machine learning resource allocation

Polypeptide analysis for nanopore-based protein identification

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Nano Research 2022年第11期15卷 9831-9842页

作者： Mazdak Afshar Bakshloo Safia Yahiaoui Fabien Piguet Manuela Pastoriza-Gallego Régis Daniel jérôme mathé john j.Kasianowicz Abdelghani Oukhaled CY Cergy Paris Université CNRSLAMBE95000CergyFrance UniversitéParis-Saclay Univ EvryCNRSLAMBE91025Evry-CourcouronnesFrance University of South Florida Dept.of PhysicsTampaFL 33620USA Freiburg Institute for Advanced Studies Universität FreiburgFreiburg 79104Germany

Presently,proteins are identified by cleaving them with proteases,measuring the mass to charge ratio of the fragments with a mass spectrometer,and matching the fragments to segments within known proteins in *** earlier demonstrated that a nanometer-scale pore formed by aerolysin(AeL)can discriminate between,and therefore identify,three similar size proteins from their trypsin-cleaved polypeptide *** this nanopore-protease method,the protein’s identity is instead determined from characteristic ionic current blockade patterns caused by the polypeptide fragments that enter the *** results also suggested that not all of the theoretically expected cleavage products partition into the *** better understand the mechanism by which polypeptide fragments are captured,and how different polypeptides reduce the pore’s ionic current,we studied the effects of 11 identical length polypeptides with different net charges and charge *** show that under certain experimental conditions,negative,positive,and neutral polypeptides are driven into the AeL pore by the same applied voltage *** capture rate and dwell time of polypeptides in the pore depend strongly on the ionic strength,the magnitude of the applied voltage,and the net charge and charge distribution of the *** dwell time distribution depends nonmonotonically on the applied voltage(regardless of the polymer’s net charge),and its maximum value depends on the polypeptide net charge and charge *** maximum dwell time for different polypeptides does not occur at the same applied voltage amplitude,which conceivably might complicate the detection and discrimination of some polypeptide *** additional experiments,computer simulations,and artificial intelligence research are needed to better understand how to optimize the partitioning of enzymatically cleaved fragments into the AeL nanopore,the method is still capable of accurately identifying

关键词： protein identification nanopores trypsin enzymatic degradation

UNIQUENESS OF GENERALIZED SOLUTION FOR ThE CAUChY PROBLEM OF TRANSPORTATTION EQUATIONS

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Acta mathematica Scientia 1997年第3期17卷 341-352页

作者：王振丁夏畦 Young Scientist Laboratory of math. Phys. Inst of Math. Phys. Academia Sinica Wuhan 430071 China Inst. of math. Shantou Univ. Shantou 515063 China Inst. of Appl. math. Academia Sinica Beijing 100080 China

In this paper, we prove the uniqueness of generalized solution defined by Lebesgue-Stieltjes integral for the Cauchy problem of transportation equations. Our results are based on the discussions for linear system with... 详细信息

关键词： hyperbolic system generalized solution Lebesgue-Stieltjes integral generalized potential