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A Core Leader Based Label Propagation Algorithm for Community Detection

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China Communications 2016年第12期13卷 97-106页

作者： shichao liu Fuxi Zhu Huajun liu Zhiqiang Du School of Computer Wuhan University 430072 WuhanChina Hankou University 430072 Wuhan China State Key Laboratory of Information Engineering in Surveying Mapping and Remote Sensing Wuhan University 430072 Wuhan China Collaborative Innovation Center for Geospatial Technology 430072 Wuhan China

A large number of community discovery algorithms have been proposed in the last decade. Recently, the sharp increase of network scale has become a great challenge for traditional community discovery algorithms. Label propagation algorithm is a semi-supervised machine learning method, which has linear time complexity when coping with large scale networks. However, the output result has less stability and the quality of the output communities still remains to be improved. Therefore, we propose a novel coreleader based label propagation algorithm for community detection called CLBLPA. Firstly, we find core leaders of potential community by using a greedy method. Then we utilize the label influence potential to guide the process of label propagation. Thus we can accelerate the convergence of algorithm and improve the stability of the output. Experimental results on synthetic datasets and real networks show that CLBLPA can significantly improve the quality of the output communities.

关键词： network analysis community de tection label propagation coreleaders label influence potential

Impact of phase-locked loop on stability of active damped LCL-filter-based grid-connected inverters with capacitor voltage feedback

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Journal of Modern Power Systems and Clean Energy 2017年第4期5卷 574-583页

作者： Xiaoqiang GUO shichao liu Xiaoyu WANG Department of Electrical Engineering Yanshan UniversityQinhuangdaoChina School of Mechanical Electronicand Control EngineeringBeijing Jiaotong UniversityBeijingChina Department of Electronics Carleton UniversityOttawaON K1S 5B6Canada

Active damped LCL-filter-based inverters have been widely used for grid-connected distributed generation(DG) systems. In weak grids, however, the phase-locked loop(PLL) dynamics may detrimentally affect the stability of grid-connected inverters due to interaction between the PLL and the controller. In order to solve the problem, the impact of PLL dynamics on small-signal stability is investigated for the active damped LCL-filtered grid-connected inverters with capacitor voltage feedback. The system closed-loop transfer function is established based on the Norton equivalent model by taking the PLL dynamics into account. Using an established model, the system stability boundary is identified from the viewpoint of PLL bandwidth and current regulator gain. The accuracy of the ranges of stability for the PLL bandwidth and current regulator gain is verified by both simulation and experimental results.

关键词： Phase-locked loop Small-signal stability Grid-connected inverter Active damping LCL filter Transfer function

High performance solid-state thermoelectric energy conversion via inorganic metal halide perovskites under tailored mechanical deformation

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Frontiers in Energy 2022年第4期16卷 581-594页

作者： Lifu YAN Lingling ZHAO Guiting YANG shichao liu Yang liu Shangchao LIN National Engineering Research Center of Turbo-Generator Vibration School of Energy and EnvironmentSoutheast UniversityNanjing 210096China State Key Laboratory of Space Power-Sources Technology Shanghai Institute of Space Power-SourcesShanghai 200245China Key Laboratory for Power Machinery and Engineering of the Ministry of Education School of Mechanical EngineeringShanghai Jiao Tong UniversityShanghai 200240China

Solid-state thermoelectric energy conversion devices attract broad research interests because of their great promises in waste heat recycling,space power generation,deep water power generation,and temperature control,but the search for essential thermoelectric materials with high performance still remains a great *** an emerging low cost,solution-processed thermoelectric material,inorganic metal halide perovskites CsPb(I_(1–x)Br_(x))_(3) under mechanical deformation is systematically investigated using the first-principle calculations and the Boltzmann transport *** is demonstrated that halogen mixing and mechanical deformation are efficient methods to tailor electronic structures and charge transport properties in CsPb(I_(1–x)Br_(x))_(3) *** mixing leads to band splitting and anisotropic charge transport due to symmetry-breakinginduced intrinsic *** band splitting reconstructs the band edge and can decrease the charge carrier effective mass,leading to excellent charge transport *** deformation can further push the orbital energies apart from each other in a more controllable manner,surpassing the impact from intrinsic *** anisotropic charge transport properties and ZT values are sensitive to the direction and magnitude of strain,showing a wide range of variation from 20%to 400%(with a ZT value of up to 1.85)compared with unstrained *** power generation efficiency of the thermoelectric device can reach as high as approximately 12%using mixed halide perovskites under tailored mechanical deformation when the heat-source is at 500 K and the cold side is maintained at 300 K,surpassing the performance of many existing bulk thermoelectric materials.

关键词： inorganic metal halide perovskites mechanical deformation thermoelectrics first-principle calculations Boltzmann transport theory

Adaptive output regulation for cyber-physical systems under time-delay attacks

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Control Theory and Technology 2022年第1期20卷 20-31页

作者： Dan Jin Bo Chen Li Yu shichao liu College of Information Engineering Zhejiang University of TechnologyHangzhou310023ZhejiangChina Institute of Cyberspace Security Zhejiang University of TechnologyHangzhou310023ZhejiangChina Department of Electronics Carleton UniversityOttawaONK1S5B6Canada

In this paper,we present an output regulation method for unknown cyber-physical systems(CPSs)under time-delay attacks in both the sensor-to-controller(S-C)channel and the controller-to-actuator(C-A)*** proposed approach is designed using control inputs and tracking errors which are accessible *** learning is leveraged to update the control gains in real time using policy or value iterations.A thorough stability analysis is conducted and it is found that the proposed controller can sustain the convergence and asymptotic stability even when two channels are ***,comparison results with a simulated CPS verify the effectiveness of the proposed output regulation method.

关键词： Adaptive output regulation Cyber-physical systems Time-delay attacks Reinforcement learning

DeepCRBP:improved predicting function of circRNA-RBP binding sites with deep feature learning

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Frontiers of Computer Science 2024年第2期18卷 235-237页

作者： Zishan XU Linlin SONG shichao liu Wen ZHANG College of Informatics Huazhong Agricultural UniversityWuhan 430070China

1 Introduction Recently,there is growing evidence that it is essential to predict the interactions between circRNAs and RBP binding sites for diagnosing diseases and providing a potential target to treat diseases[1].Many studies have predicted the binding sites of circRNA-RBPs by using deep learning methods based on the sequence information of circRNAs for each ***,many methods focus on diversified view of sequence encoding for improving the performance of the predictive models.

关键词： learning Deep function

Growth mechanism of primary Ti_(5)Si_(3) phases in special brasses and their effect on wear resistance

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Journal of Materials Science & Technology 2021年第2期61卷 138-146页

作者： Xianlong Wang Jinchuan Jie shichao liu Zhuangzhuang Dong Guomao Yin Tingju Li Key Laboratory of Solidification Control and Digital Preparation Technology(Liaoning Province) School of Materials Science and EngineeringDalian University of TechnologyDalian116024China

In the present work, in-situ Ti_(5)Si_(3) reinforced special brasses were prepared by melt reaction method. The synthesized Ti_(5)Si_(3) phase shows various morphologies in brasses with different Ti_(5)Si_(3) content, and the3 D morphological evolution of primary Ti_(5)Si_(3)and its growth mechanism were investigated. The Ti_(5)Si_(3) crystal, which bears D8_(8) hexagonal crystal structure, grows along direction and is revealed by{1010} faces during growth. With the increase of Ti_(5)Si_(3) content in the brasses, the morphology of primary Ti_(5)Si_(3)significantly changes from fibers to hexagonal prisms to short-rods with hollow. In addition,the influence of Ti_(5)Si_(3) volume fraction and morphology on the wear behavior of special brass was also revealed. It was substantiated that the wear resistance increases with the increasing volume fraction of Ti_(5)Si_(3), and the corresponding wear mechanism changes from delamination to slight adhesive wear and abrasive wear. However, the friction coefficient shows an abnormal increase when most of the Ti_(5)Si_(3) containing hollows appears in the brass. That is mainly due to the fact that the Ti_(5)Si_(3) is easier to break and fall off resulted by the hollow as a crack source, which makes it unable to resist the plastic deformation of the contact surface during the sliding.

关键词： Ti_(5)Si_(3) Brass Morphology Growth mechanism Wear behavior

Semisolid-rolling and annealing process of woven carbon fibers reinforced Al-matrix composites

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Journal of Materials Science & Technology 2017年第7期33卷 623-629页

作者： Junjia Zhang shichao liu Yiping Lu Li Jiang Yubo Zhang Tingju Li Key Laboratory of Solidification Control and Digital Preparation Technology （Liaoning Province） School of Materials Science and Engineering Dalian University of Technology Dalian 116024 China

Semisolid-rolling method was successfully developed to prepare the Ni-coated woven carbon fibers reinforced Al-matrix composite. Due to the appropriate matrix flowability and rolling pressure, the Al-matrix could infiltrate into the woven fibers sufficiently and attach to the reinforcements closely forming a smooth interface. The rolling speed of 4 rad/min offered a subtle equilibrium between the heat transfer and the material deformation. The covering matrix should be controlled at semisolid state to provide a better infiltration behavior and a protective effect on the carbon fibers. With the addition of fibers, an improvement for more than 25% was obtained in the bending strength of the materials. Furthermore, the woven carbon fibers could strengthen the composite in multiple directions, rather than only along the fiber longitudinal directions. The annealing process promoted the Ni coating to react with and to diffuse into the matrix, resulted in an obvious increase of the bending strength.

关键词： Metal-matrix composites Woven carbon fiber Semisolid-rolling process Annealing Mechanical property

Growth and mineral nutrient analysis of teak (Tectona grandis) grown on acidic soils in south China

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Journal of Forestry Research 2017年第3期28卷 503-511页

作者： Zaizhi Zhou shichao liu Kunnan Liang Huaming Ma Guihua Huang Research Institute of Tropical Forestry Chinese Academy of Forestry

Teak （Tectona grandis L.f.） is widely planted in the world due to its high market demand, economic, ecological and social value. Its plantations have mostly been established and expanded into sites that are acidic to severely acidic in southern China. But, there are no available and specific evidence-based nutrient management techniques. To better recognize and understand the relationship between teak tree growth and nutrient content in the foliage and soil and establish nutrient norms are critical to optimally manage these young plantations. We studied the foliar nutrient and soil chemistry in 19 representative teak plantations aged 5-8 years. Regression analysis indicated that the mean annual increment of teak volume was linearly and positively correlated with foliar N, Ca, Fe and B concentrations, with soil base saturation percentage, available P and Zn concentrations, and negatively correlated with soil Al concentration. Only if the Ca and Mg contents in soil were enhanced, could the increase in soil base saturation percentage benefit teak growth. A revised classification of low-and high-yielding stands was established by using a sorting method of principal components over 6 foliar macro and 8 micro elements in a Diagnosis and Recommendation Integrated System （DRIS）. Specific DRIS norms for teak plantations in acid soils were derived. The nutrient balance of N, P, K Ca, Mg, Zn, B with Fe or A1, Ca with Mg, and Fe with AI provided a key to promote the growth of teak in acid soils. Meanwhile, soil Zn was also found as a primary trace element that affected teak growth in this study.

关键词： Acid soils DRIS diagnosis and norm Mineral nutrient relationship Plant mineral nutrition Soil properties Teak

Deep learning for drug-drug interaction prediction:A comprehensive review

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Quantitative Biology 2024年第1期12卷 30-52页

作者： Xinyue Li Zhankun Xiong Wen Zhang shichao liu College of Informatics Huazhong Agricultural UniversityWuhanChina

The prediction of drug-drug interactions(DDIs)is a crucial task for drug safety research,and identifying potential DDIs helps us to explore the mechanism behind combinatorial *** wet chemical experiments for DDI are cumbersome and time-consuming,and are too small in scale,limiting the efficiency of DDI ***,it is particularly crucial to develop improved computational methods for detecting drug *** the development of deep learning,several computational models based on deep learning have been proposed for DDI *** this review,we summarized the high-quality DDI prediction methods based on deep learning in recent years,and divided them into four categories:neural network-based methods,graph neural network-based methods,knowledge graph-based methods,and multimodal-based ***,we discuss the challenges of existing methods and future potential *** review reveals that deep learning can significantly improve DDI prediction performance compared to traditional machine *** learning models can scale to large-scale datasets and accept multiple data types as input,thus making DDI predictions more efficient and accurate.

关键词： deep learning drug-drug interactions graph neural network knowledge graph multimodal deep learning neural network