Local Hybrid Linear State Estimation for Electric Power Systems Using Stream Processing

The increasing penetration of renewable energy resources with highly fluctuating outputs has placed increasing concern on the accuracy and timeliness of electric power system state estimation(SE).Meanwhile,we note that only a fraction of system states fluctuate at the millisecond level and require to be updated.As such,refreshing only those states with significant variation would enhance the computational efficiency of SE and make fast-continuous update of states possible.However,this is difficult to achieve with conventional SE methods,which generally refresh states of the entire system every 4–5 s.In this context,we propose a local hybrid linear SE framework using stream processing,in which synchronized measurements received from phasor measurement units(PMUs),and trigger/timingmode measurements received from remote terminal units(RTUs)are used to update the associated local states.Moreover,the measurement update process efficiency and timeliness are enhanced by proposing a trigger measurement-based fast dynamic partitioning algorithm for determining the areas of the system with states requiring recalculation.In particular,non-iterative hybrid linear formulations with both RTUs and PMUs are employed to solve the local SE problem.The timeliness,accuracy,and computational efficiency of the proposed method are demonstrated by extensive simulations based on IEEE 118-,300-,and 2383-bus systems.

RSSI-Based 3D Wireless Sensor Node Localization Using Hybrid T Cell Immune and Lotus Optimization

Wireless Sensor Network(WSNs)consists of a group of nodes that analyze the information from surrounding regions.The sensor nodes are responsible for accumulating and exchanging information.Generally,node local-ization is the process of identifying the target node’s location.In this research work,a Received Signal Strength Indicator(RSSI)-based optimal node localization approach is proposed to solve the complexities in the conventional node localization models.Initially,the RSSI value is identified using the Deep Neural Network(DNN).The RSSI is conceded as the range-based method and it does not require special hardware for the node localization process,also it consumes a very minimal amount of cost for localizing the nodes in 3D WSN.The position of the anchor nodes is fixed for detecting the location of the target.Further,the optimal position of the target node is identified using Hybrid T cell Immune with Lotus Effect Optimization algorithm(HTCI-LEO).During the node localization process,the average localization error is minimized,which is the objective of the optimal node localization.In the regular and irregular surfaces,this hybrid algorithm effectively performs the localization process.The suggested hybrid algorithm converges very fast in the three-dimensional(3D)environment.The accuracy of the proposed node localization process is 94.25%.

Robust TDOA/FDOA estimation from emitter signals for hybrid localization using UAVs

This paper considers the time difference of arrival(TDOA)and frequency difference of arrival(FDOA)estimation problem for joint localization using unmanned aerial vehicles(UAVs),involving range migration(RM)and Doppler ambiguity within observation interval.A robust estimation method based on interpolation and resampling is proposed.Specifically,the interpolation artificially increases the pulse repetition frequency(PRF).After that,the resampling eliminates the coupling between range frequency and slow time.Finally,a coherent integration step based on inverse discrete Fourier transform(IDFT)is used to achieve parameter estimation and suppress the grating lobes caused by interpolation.The proposed method could be efficiently implemented by fast Fourier transform(FFT),inverse FFT(IFFT)and non-uniform FFT(NUFFT)without parameter searching procedures.Numerical experiments indicate that the proposed method has nearly optimal anti-noise performance but much lower computational complexity than the maximum likelihood estimator,which makes it more competitive in practical applications.

Bi-level hybrid local search approach for three-dimensional loading problem with balancing constraints

This paper presents a bi-level hybrid local search(BHLS)algorithm for the three-dimensional loading problem with balancing constraints(3DLP-B),where several rectangular boxes with even densities but different sizes are loaded into a single cubic bin to meet the requirements of the space or capacity utilization and the balance of the center of gravity.The proposed algorithm hybridizes a novel framed-layout procedure in which the concept of the core block and its generation strategy are introduced.Once the block-loading sequence has been determined,we can load one block at a time by the designed construction heuristic.Then,the double-search is introduced;its external search procedure generates a list of compact packing patterns while its internal search procedure is used to search the core-block frames and their best distribution locations.The approach is extensively tested on weakly to strongly heterogeneous benchmark data.The results show that it has better performance in improving space utilization rate and balanced condition of the placement than existed techniques:the overall averages from 79.85%to 86.45%were obtained for the balanced cases and relatively high space-usage rate of 89.44%was achieved for the unbalanced ones.

Heterosis in locally adapted sorghum genotypes and potential of hybrids for increased productivity in contrasting environments in Ethiopia

Increased productivity in sorghum has been achieved in the developed world using hybrids.Despite their yield advantage,introduced hybrids have not been adopted in Ethiopia due to the lack of adaptive traits,their short plant stature and small grain size.This study was conducted to investigate hybrid performance and the magnitude of heterosis of locally adapted genotypes in addition to introduced hybrids in three contrasting environments in Ethiopia.In total,139 hybrids,derived from introduced seed parents crossed with locally adapted genotypes and introduced R lines,were evaluated.Overall,the hybrids matured earlier than the adapted parents,but had higher grain yield,plant height,grain number and grain weight in all environments.The lowland adapted hybrids displayed a mean better parent heterosis(BPH) of19%,equating to 1160 kg ha-1and a 29% mean increase in grain yield,in addition to increased plant height and grain weight,in comparison to the hybrids derived from the introduced R lines.The mean BPH for grain yield for the highland adapted hybrids was 16% in the highland and 52%in the intermediate environment equating to 698 kg ha-1and 2031 kg ha-1,respectively,in addition to increased grain weight.The magnitude of heterosis observed for each hybrid group was related to the genetic distance between the parental lines.The majority of hybrids also showed superiority over the standard check varieties.In general,hybrids from locally adapted genotypes were superior in grain yield,plant height and grain weight compared to the high parents and introduced hybrids indicating the potential for hybrids to increase productivity while addressing farmers' required traits.

Research of Rhine Goose and Heilongjiang Local Goose Hybrid Result

[Objective]The aim is to improve the local goose in Heilongjiang Province（ Zi goose,Huo goose,Heilongjiang white sticky goose） growth rate and production performance,increase the goose economic benefits and change the resource advantage of local into commercial and economic advantages. [Methods]Rhine goose of large size,fast growth,high wool and cashmere was introduced on hybrid improvement. [Results] Improved goose 60 days of age weight was 3. 240 kg,1. 40 kg higher than that of local goose weight; Improved adult male goose weight were 4. 661 kg,female goose 4. 150 kg,0. 50 kg or 0. 80 kg higher than the local goose weight respectively; Improved goose fleece production was 110. 03 g,fleece rate 29. 17%,33. 15 g higher than the local goose prolific wool,fleece rate increased by 12. 71%. [Conclusion] Effect of using Rhine goose to improve Heilongjiang local goose obvious and economic benefit is improved.

Local Search Algorithm with Hybrid Neighborhood and Its Application to Job Shop Scheduling Problem

A new local search method with hybrid neighborhood for Job shop scheduling problem is developed. The proposed hybrid neighborhood is not only efficient in local search, but also can help overcome entrapments while search procedure get trapped at local optima and carry the search to areas of the feasible set with better prospect. New strategies used for breaking out of entrapments are presented and they are helpful for the procedure to improve local optima. A performance comparison of the proposed method with some best-performing algorithms on all 10-job, 10-machine benchmark problems and the other two problems generated by Fisher and Thompson (ie., FT6 and FT20)is made. The experiment results show the better optimal performance of the proposed algorithm.

GRAPES Hybrid-3DVar对台风苏迪罗的数值试验

为了把反映天气形势变化的背景误差协方差引入到变分分析系统中来提高分析质量,本文在GRAPES区域三维变分框架的基础上通过扩展控制变量方法实现动态与静态背景误差协方差耦合,建立混合三维变分分析系统(GRAPES Hybrid-3DVar)。通过控制变量扰动产生的集合样本进行单点观测分析试验验证Hybrid-3DVar及其局地化方案的合理性,并针对台风苏迪罗进行实际观测资料同化和数值预报试验,结果表明:用集合样本描述的背景误差协方差是随着天气流型变化的,动力场和质量场的离散度在台风中心处最大,因而混合同化的分析增量包含更多细微结构和中小尺度信息;其分析和24 h内预报要素质量优于3DVar,24 h内降水强度和落区预报也更准确,混合同化分析改善了3DVar分析的降水空报问题;同时混合同化分析的24 h内台风路径预报也最接近实况,台风强度预报在48 h之内都比3DVar更接近观测。

Solving Travelling Salesman Problem with an Improved Hybrid Genetic Algorithm

We present an improved hybrid genetic algorithm to solve the two-dimensional Eucli-dean traveling salesman problem (TSP), in which the crossover operator is enhanced with a local search. The proposed algorithm is expected to obtain higher quality solutions within a reasonable computational time for TSP by perfectly integrating GA and the local search. The elitist choice strategy, the local search crossover operator and the double-bridge random mutation are highlighted, to enhance the convergence and the possibility of escaping from the local optima. The experimental results illustrate that the novel hybrid genetic algorithm outperforms other genetic algorithms by providing higher accuracy and satisfactory efficiency in real optimization processing.

A nuclear localized protein ZCCHC9 is expressed in cerebral cortex and suppresses the MAPK signal pathway

The CCHC-type zinc finger motif has numerous biological activities （such as DNA binding and RNA binding） and can also mediate protein-protein interaction. This article gives a primary report about the human ZCCHC9 gene. Protein ZCCHC9 contains four CCHC motifs and is highly conserved in humans, mice, and rats. The whole eDNA sequence of the ZCCHC9 gene has been amplified by PCR and a number of plasmids have been constructed for further study. The results show that ZCCHC9 is localized in the nucleus, and especially concentrated in the nueleolus. It is highly expressed in the brain and testicles of the mouse. This has been confirmed by real-time reverse transcription polymerase chain reaction （RT-PCR）. In situ hybridization of the mouse brain indicates that ZCCHC9 is mainly expressed in the cerebral cortex. Reporter gene assay shows that ZCCHC9 suppresses the transcription activities of NF-kappa B and SRE, and may play roles in the Mitogen-Aetivated Protein Kinase （MAPK） signaling transduetion pathway.

A Vision-aided Localization and Geo-registration Method for Urban ARGIS Based on 2D Maps

Augmented Reality Geographic Information System(ARGIS) applications can only provide users accurate content services with a highly precise geo-registration.However,the absolute 6DOF(Degree of Freedom) pose provided by the portable sensors is usually inaccurate in urban outdoors,resulting in poorly geo-registration accuracy for ARGIS applications.Aiming at this issue,an automatic vision-aided localization method based on the 2D map is proposed to improve the initial localization accuracy of the portable sensors,and an overall geo-registration optimization framework for outdoor ARGIS is proposed.Based on the initial pose provided by the sensors,the basic principles of the vision-aided localization method are expounded in detail.The experimental results show that the proposed method can effectively correct the initial pose obtained by the pose sensors,and improve the geo-registration accuracy of outdoor ARGIS applications ultimately.

A FULLY-HYBRID MAC PROTOCOL IN LANS

In announced hybrid protocols,there are two mechanisms usually employed.One operates in aCSMA family manner and the other follows a token passing family way.However,only one ofthem works efficiently when traffic is light or heavy.This results in an inefficient redundance and aburden to the protocol implementation.In this paper,we present a new hybrid concept and its idealmodel in which risky transmissions alternate with safe transmissions in response to the dynamicchange in traffic.Being similar to virtual time CSMA in the abstract,a single control mechanism isproposed to approach this ideal model.The mechanism is rather compact,and its implementationcan be designed to be simple,efficient,reliable,robust,and fully distributed without any centralizedelement at any instant.Simulation results show that the proposed mechanism performs well overthe entire range of the traffic load from light to heavy.

An Evolutionary Algorithm with Multi-Local Search for the Resource-Constrained Project Scheduling Problem

This paper introduces a hybrid evolutionary algorithm for the resource-constrained project scheduling problem (RCPSP). Given an RCPSP instance, the algorithm identifies the problem structure and selects a suitable decoding scheme. Then a multi-pass biased sampling method followed up by a multi-local search is used to generate a diverse and good quality initial population. The population then evolves through modified order-based recombination and mutation operators to perform exploration for promising solutions within the entire region. Mutation is performed only if the current population has converged or the produced offspring by recombination operator is too similar to one of his parents. Finally the algorithm performs an intensified local search on the best solution found in the evolutionary stage. Computational experiments using standard instances indicate that the proposed algorithm works well in both computational time and solution quality.

Investigation of lower hybrid current drive during H-mode in EAST tokamak

H-mode discharges with lower hybrid current drive （LHCD） alone are achieved in EAST divertor plasma over a wide parameter range. These H-mode discharges are characterized by a sudden drop in Da emission and a spontaneous rise in main plasma density. Good lower hybrid （LH） coupling during H-mode is obtained by putting the plasma close to the antenna and by injecting D2 gas from a pipe near the grill mouse. The analysis of lower hybrid current drive properties shows that the LH deposition profile shifts off axis during H-mode, and current drive （CD） efficiency decreases due to the increase in density. Modeling results of H-mode discharges with a general ray trueing code GENRAY are reported.

Differential evolution algorithm for hybrid flow-shop scheduling problems

Aiming at the hybrid flow-shop （HFS） scheduling that is a complex NP-hard combinatorial problem with wide engineering background, an effective algorithm based on differential evolution （DE） is proposed. By using a special encoding scheme and combining DE based evolutionary search and local search, the exploration and exploitation abilities are enhanced and well balanced for solving the HFS problems. Simulation results based on some typical problems and comparisons with some existing genetic algorithms demonstrate the proposed algorithm is effective, efficient and robust for solving the HFS problems.

Application of hybrid operating rooms for treating spinal dural arteriovenous fistula

BACKGROUND A hybrid operating room(hybrid-OR)is a surgical space that combines a conventional operating room with advanced medical imaging devices.AIM To explore and summarize the technical features and effectiveness of the application of a hybrid-OR in dealing with spinal dural arteriovenous fistulas(SDAVFs).METHODS Eleven patients with SDAVFs were treated with the use of a hybrid-OR at the Department of Neurosurgery of our hospital between January 2015 and December 2018.The dual-marker localization technique was used in the hybrid-OR to locate the SDAVFs and skin incision,and the interoperative digital subtraction angiography(DSA)technique was used before and after microsurgical ligation of the fistulae in the hybrid-OR to verify the accuracy of obliteration.The patients were followed for an average of 2 years after the operation,and the preoperative American Spinal Cord Injury Association(ASIA)score and postoperative ASIA score at 6 mo after the operation were compared.RESULTS The location and skin incision of the SDAVFs were accurately obtained by using the dual-marker localization technique in the hybrid-OR in all patients,and there were no cases that required expansion of the range of the bone window in order to expose the lesions.Intraoperative error obliteration occurred and was identified in two patients by using the intraoperative DSA technique;therefore,the findings provided by the intraoperative DSA system significantly changed the surgical procedure in these two patients.With the assistance of the hybrid-OR,the feeding artery was correctly ligated in all cases,and the intraoperative error obliteration rate decreased from 18.2%(2/11)to 0%.All 11 patients were followed for an average of 2 years.The ASIA score at 6 mo after the operation was significantly improved compared with the preoperative ASIA score,and there were no patients with late recurrence during the follow-up.CONCLUSION Compared with intra-arterial embolization for the treatment of SDAVFs,hybrid-ORs can solve the problem of a higher incidence of initial failure and late recurrence.Compared with direct occlusion of SDAVFs in microsurgery,hybrid-ORs can take advantage of the intraoperative DSA system for locating the shunt and verifying the obliteration of fistulae in order to reduce the error obliteration rate.At this point,our experience suggests that the safety and ease of use make hybrid-ORs combined with microsurgery and intraoperative DSA systems an attractive modality for dealing with SDAVFs.

Decentralized PD Control for Non-uniform Motion of a Hamiltonian Hybrid System

In this paper, a decentralized proportional-derivative （PD） controller design for non-uniform motion of a Hamiltonian hybrid system is considered. A Hamiltonian hybrid system with the capability of producing a non-uniform motion is developed. The structural properties of the system are investigated by means of the theory of Hamiltonian systems. A relationship between the parameters of the system and the parameters of the proposed decentralized PD controller is shown to ensure local stability and tracking performance. Simulation results are included to show the obtained non-uniform motion.

New Hybrid Genetic Algorithm for Vertex Cover Problems

This paper presents a new hybrid genetic algorithm for the vertex cover problems in which scan-repair and local improvement techniques are used for local optimization. With the hybrid approach, genetic algorithms are used to perform global exploration in a population, while neighborhood search methods are used to perform local exploitation around the chromosomes. The experimental results indicate that hybrid genetic algorithms can obtain solutions of excellent quality to the problem instances with different sizes. The pure genetic algorithms are outperformed by the neighborhood search heuristics procedures combined with genetic algorithms.

多水源灌溉系统的管网布置与管径协同优化研究

基于多水源灌溉系统,考虑系统水资源分配并确定管网拓扑结构与连接管道尺寸,以最小化系统流量分配成本和管道安装成本之和为目标函数建立混合整数规划模型。设计一种混合启发式算法将局部搜索与精确算法结合,协同优化管网布置与管网设计两个阶段,分析各节点之间的连接情况与连接管径,并为需水节点分配流量。通过不同规模的测试算例验证协同优化算法能有效降低多水源灌溉系统的建设成本。

An Obliquely Propagating Electromagnetic Lower-Hybrid-Drift Instability in Plasmas with Negative Ions

In this study, by employing a local fluid theory for warm plasma containing negative ions, an obliquely propagating electromagnetic instability in the lower hybrid frequency range driven by cross-field currents or relative drifts between electrons and ions was investigated. It is found that the growth rate of the lower-hybrid-drift instability （LHDI） can be controlled by appropriate selection of the propagation direction, the wave number and the relative population of the negative ions.