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| 1 | A new method for optimal FTU placement in distribution network under consideration of power service reliability显示文摘Modern distribution network with high penetration of intermittent renewable sources and the so-called prosumers requires more reliable distribution automation(DA) system for safe operation and control. The design of optimal feeder terminal units(FTU)placement is critical and economical for the effective DA application. Previously proposed solutions of optimal FTU placement aiming to ensure the accuracy of state estimation(SE), typically include the following two main shortcomings: 1) only to obtain the optimal FTU placement in quantity, and the analysis of FTU location is not considered yet; 2) few consider the uncertainty of intermittent power injections in the analysis of state estimation. In this paper, a modified methodology of FTU placement is proposed not only aiming to ensure the accuracy of state estimation with the minimum number of meters, but also finding those specific FTU locations to guarantee the power service reliability. Moreover, the uncertainty models of those intermittent power injections are also considered by using probability density function(PDF). The resultant optimization problem is addressed by using the covariance matrix adaptation evolution strategy(CMA-ES). Case studies demonstrate the feasibility and effectiveness of the proposed methodology. | XU JunJun WU ZaiJun YU XingHuo HU QinRan ZHU ChengZhi DOU XiaoBo GU Wei WU Zhi | 2017 | Science China(Technological Sciences)2017，60，12： | 3 |
| 2 | A Modified Self-adaptive Method for Mapping Annual 30-m Land Use/Land Cover Using Google Earth Engine:A Case Study of Yangtze River Delta显示文摘Annual Land Use/Land Cover(LULC)change information at medium spatial resolution(i.e.,at 30 m)is used in applications ranging from land management to achieving sustainable development goals related to food security.However,obtaining annual LULC information over large areas and long periods is challenging due to limitations on computational capabilities,training data,and workflow design.Using the Google Earth Engine(GEE),which provides a catalog of multi-source data and a cloud-based environment,we developed a novel methodology to generate a high accuracy 30-m LULC cover map collection of the Yangtze River Delta by integrating free and public LULC products with Landsat imagery.Our major contribution is a hybrid approach that includes three major components:1)a high-quality training dataset derived from multi-source LULC products,filtered by k-means clustering analysis;2)a yearly 39-band stack feature space,utilizing all available Landsat data and DEM data;and 3)a self-adaptive Random Forest(RF)method,introduced for LULC classification.Experimental results show that our proposed workflow achieves an average classification accuracy of 86.33%in the entire Delta.The results demonstrate the great potential of integrating multi-source LULC products for producing LULC maps of increased reliability.In addition,as the proposed workflow is based on open source data and the GEE cloud platform,it can be used anywhere by anyone in the world. | QU Le’an LI Manchun CHEN Zhenjie ZHI Junjun | 2021 | Chinese Geographical Science2021，31，5： | 2 |
| 3 | Radiation-hardened property of single-walled carbon nanotube film-based field-effect transistors under low-energy proton irradiation显示文摘Strong C-C bonds,nanoscale cross-section and low atomic number make single-walled carbon nanotubes(SWCNTs)a potential candidate material for integrated circuits(ICs)applied in outer space.However,very little work combines the simulation calculations with the electrical measurements of SWCNT field-effect transistors(FETs),which limits further understanding on the mechanisms of radiation effects.Here,SWCNT film-based FETs were fabricated to explore the total ionizing dose(TID)and displacement damage effect on the electrical performance under low-energy proton irradiation with different fluences up to 1×1015 p/cm2.Large negative shift of the threshold voltage and obvious decrease of the on-state current verified the TID effect caused in the oxide layer.The stability of the subthreshold swing and the off-state current reveals that the displacement damage caused in the CNT layer is not serious,which proves that the CNT film is radiation-hardened.Specially,according to the simulation,we found the displacement damage caused by protons is different in the source/drain contact area and channel area,leading to varying degrees of change for the contact resistance and sheet resistance.Having analyzed the simulation results and electrical measurements,we explained the low-energy proton irradiation mechanism of the CNT FETs,which is essential for the construction of radiation-hardened CNT film-based ICs for aircrafts. | Xiaorui Zhang Huiping Zhu Song’ang Peng Guodong Xiong Chaoyi Zhu Xinnan Huang Shurui Cao Junjun Zhang Yunpeng Yan Yao Yao Dayong Zhang Jingyuan Shi Lei Wang Bo Li Zhi Jin | 2021 | Journal of Semiconductors2021，42，11： | 2 |
| 4 | Mapping Soil Organic Carbon Stocks of Northeastern China Using Expert Knowledge and GIS-based Methods显示文摘The main aim of this paper was to calculate soil organic carbon stock(SOCS) with consideration of the pedogenetic horizons using expert knowledge and GIS-based methods in northeastern China.A novel prediction process was presented and was referred to as model-then-calculate with respect to the variable thicknesses of soil horizons(MCV).The model-then-calculate with fixed-thickness(MCF),soil profile statistics(SPS),pedological professional knowledge-based(PKB) and vegetation type-based(Veg) methods were carried out for comparison.With respect to the similar pedological information,nine common layers from topsoil to bedrock were grouped in the MCV.Validation results suggested that the MCV method generated better performance than the other methods considered.For the comparison of polygon based approaches,the Veg method generated better accuracy than both SPS and PKB,as limited soil data were incorporated.Additional prediction of the pedogenetic horizons within MCV benefitted the regional SOCS estimation and provided information for future soil classification and understanding of soil functions.The intermediate product,that is,horizon thickness maps were fluctuant enough and reflected many details in space.The linear mixed model indicated that mean annual air temperature(MAAT) was the most important predictor for the SOCS simulation.The minimal residual of the linear mixed models was achieved in the vegetation type-based model,whereas the maximal residual was fitted in the soil type-based model.About 95% of SOCS could be found in Argosols,Cambosols and Isohumosols.The largest SOCS was found in the croplands with vegetation of Triticum aestivum L.,Sorghum bicolor(L.) Moench,Glycine max(L.) Merr.,Zea mays L.and Setaria italica(L.) P.Beauv. | SONG Xiaodong LIU Feng JU Bing ZHI Junjun LI Decheng ZHAO Yuguo ZHANG Ganlin | 2017 | Chinese Geographical Science2017，27，4： | 2 |
| 5 | Spatio-temporal patterns and source apportionment of pollution in Qiantang River (China) using neural-based modeling and multivariate statistical techniques显示文摘 | Shiliang Su Junjun Zhi Liping Lou Fang Huang Xia Chen Jiaping Wu | 2010 | Physics and Chemistry of the Earth2010，，9： | 1 |
| 6 | Low-threshold lasing in a plasmonic laser using nanoplate InGaN/GaN显示文摘Plasmonic nanolaser as a new type of ultra-small laser,has gain wide interests due to its breaking diffraction limit of light and fast carrier dynamics characters.Normally,the main problem that need to be solved for plasmonic nanolaser is high loss induced by optical and ohmic losses,which leads to the low quality factor.In this work,InGaN/GaN nanoplate plasmonic nanolaser with large interface area were designed and fabricated,where the overlap between SPs and excitons can be enhanced.The lasing threshold is calculated to be~6.36 kW/cm^(2),where the full width at half maximum(FWHM)drops from 27 to 4 nm.And the fast decay time at 502 nm(sharp peak of stimulated lasing)is estimated to be 0.42 ns.Enhanced lasing characters are mainly attributed to the strong confinement of electromagnetic wave in the low refractive index material,which improve the near field coupling between SPs and excitons.Such plasmonic laser should be useful in data storage applications,biological application,light communication,especially for optoelectronic devices integrated into a system on a chip. | Ting Zhi Tao Tao Xiaoyan Liu Junjun Xue Jin Wang Zhikuo Tao Yi Li Zili Xie Bin Liu | 2021 | Journal of Semiconductors2021，42，12： | 0 |
| 7 | An Insight into Machine Learning Algorithms to Map the Occurrence of the Soil Mattic Horizon in the Northeastern Qinghai-Tibetan Plateau显示文摘Soil diagnostic horizons, which each have a set of quantified properties, play a key role in soil classification. However, they are difficult to predict, and few attempts have been made to map their spatial occurrence. We evaluated and compared four machine learning algorithms, namely, the classification and regression tree(CART), random forest(RF), boosted regression trees(BRT), and support vector machine(SVM), to map the occurrence of the soil mattic horizon in the northeastern Qinghai-Tibetan Plateau using readily available ancillary data. The mechanisms of resampling and ensemble techniques significantly improved prediction accuracies(measured based on area under the receiver operator characteristic curve score(AUC)) and produced more stable results for the BRT(AUC of 0.921 ± 0.012, mean ± standard deviation) and RF(0.908 ± 0.013) algorithms compared to the CART algorithm(0.784 ± 0.012), which is the most commonly used machine learning method. Although the SVM algorithm yielded a comparable AUC value(0.906 ± 0.006) to the RF and BRT algorithms, it is sensitive to parameter settings, which are extremely time-consuming.Therefore, we consider it inadequate for occurrence-distribution modeling. Considering the obvious advantages of high prediction accuracy, robustness to parameter settings, the ability to estimate uncertainty in prediction, and easy interpretation of predictor variables, BRT seems to be the most desirable method. These results provide an insight into the use of machine learning algorithms to map the mattic horizon and potentially other soil diagnostic horizons. | ZHI Junjun ZHANG Ganlin YANG Renmin YANG Fei JIN Chengwei LIU Feng SONG Xiaodong ZHAO Yuguo LI Decheng | 2018 | Pedosphere2018，28，5： | 0 |
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