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| 1 | Review of the characteristics and graded utilisation of coal gasification slag显示文摘The characteristics of the energy structure of rich coal,less oil and less gas,coupling with a high external dependence on oil and natural gas and the emphasis on the efficient and clean utilisation of coal,have brought opportunities for coal chemical industry.However,with the large-scale popularisation of coal gasification technology,the production and resulting storage of coal gasification slag continue to increase,which not only result in serious environmental pollution and a waste of terrestrial resources,but also seriously affect the sustainable development of coal chemical enterprises.Hence,the treatment of coal gasification slag is extremely important.In this paper,the production,composition,morphology,particle size structure and water holding characteristics of coal gasification slag are introduced,and the methods of carbon ash separation of gasification slag,both domestically and abroad,are summarised.In addition,the paper also summarises the research progress on gasification slag in building materials,ecological restoration,residual carbon utilisation and other high-value utilisation,and ultimately puts forward the idea of the comprehensive utilisation of gasification slag.For large-scale consumption to solve the environmental problems of enterprises and achieve high-value utilisation to increase the economic benefits of enterprises,it is urgent to zealously design a reasonable and comprehensive utilisation technologies with simple operational processes,strong adaptability and economic benefits. | Xiaodong Liu Zhengwei Jin Yunhuan Jing Panpan Fan Zhili Qi Weiren Bao Jiancheng Wang Xiaohui Yan Peng Lv Lianping Dong | 2021 | Chinese Journal of Chemical Engineering2021，34，7： | 21 |
| 2 | A surgical simulation system for predicting facial soft tissue deformation显示文摘In the field of cranio-maxillofacial(CMF)surgery, surgical simulation is becoming a very powerful tool to plan surgery and simulate surgical results before actually performing a CMF surgical procedure.Reliable prediction of facial soft tissue changes is in particular essential for better preparation and to shorten the time taken for the operation. This paper presents a surgical simulation system to predict facial soft tissue changes caused by the movement of bone segments during CMF surgery. Two experiments were designed to test the feasibility of this simulation system. The test results demonstrate the feasibility of fast and good prediction of post-operative facial appearance, with texture. Our surgical simulation system is applicable to computer-assisted CMF surgery. | Xiaodong Tang Jixiang Guo Peng Li Jiancheng Lv | 2016 | Computational Visual Media2016，2，2： | 2 |
| 3 | Fuzzy SVM with a new fuzzy membership function显示文摘 | Jiang Xiufeng Yi Zhang Lv Jiancheng | 2006 | Neural Comput and Applic2006，，15： | 1 |
| 4 | Rigid medical image registration using PCA neural network显示文摘 | SHANG LIFENG LV JIANCHENG YI ZHANG | | 0，，09： | 1 |
| 5 | Fuzzy SVM with a new fuzzy membership function显示文摘 | JIANG Xiufeng ZHANG Yi LV Jiancheng | 2006 | Neural Computation and Application2006，3，15： | 1 |
| 6 | Fuzzy SVM with a new fuzzy membership function显示文摘 | JIANG XIUFENG YI ZHANG LV JIANCHENG | 2006 | Neural Computing and Applications2006，15，34： | 1 |
| 7 | Artificial Intelligence Methods Applied to Catalytic Cracking Processes显示文摘Fluidic Catalytic Cracking(FCC)is a complex petrochemical process affected by many highly non-linear and interrelated factors.Product yield analysis,flue gas desulfurization prediction,and abnormal condition warning are several key research directions in FCC.This paper will sort out the relevant research results of the existing Artificial Intelligence(AI)algorithms applied to the analysis and optimization of catalytic cracking processes,with a view to providing help for the follow-up research.Compared with the traditional mathematical mechanism method,the AI method can effectively solve the difficulties in FCC process modeling,such as high-dimensional,nonlinear,strong correlation,and large delay.AI methods applied in product yield analysis build models based on massive data.By fitting the functional relationship between operating variables and products,the excessive simplification of mechanism model can be avoided,resulting in high model accuracy.AI methods applied in flue gas desulfurization can be usually divided into two stages:modeling and optimization.In the modeling stage,data-driven methods are often used to build the system model or rule base;In the optimization stage,heuristic search or reinforcement learning methods can be applied to find the optimal operating parameters based on the constructed model or rule base.AI methods,including data-driven and knowledge-driven algorithms,are widely used in the abnormal condition warning.Knowledge-driven methods have advantages in interpretability and generalization,but disadvantages in construction difficulty and prediction recall.While the data-driven methods are just the opposite.Thus,some studies combine these two methods to obtain better results. | Fan Yang Mao Xu Wenqiang Lei Jiancheng Lv | 2023 | Big Data Mining and Analytics2023，6，3： | 0 |
| 8 | Ultra-Short Wave Communication Squelch Algorithm Based on Deep Neural Network显示文摘The squelch problem of ultra-short wave communication under non-stationary noise and low Signal-to-Noise Ratio(SNR)in a complex electromagnetic environment is still challenging.To alleviate the problem,we proposed a squelch algorithm for ultra-short wave communication based on a deep neural network and the traditional energy decision method.The proposed algorithm first predicts the speech existence probability using a three-layer Gated Recurrent Unit(GRU)with the speech banding spectrum as the feature.Then it gets the final squelch result by combining the strength of the signal energy and the speech existence probability.Multiple simulations and experiments are done to verify the robustness and effectiveness of the proposed algorithm.We simulate the algorithm in three situations:the typical Amplitude Modulation(AM)and Frequency Modulation(FM)in the ultra-short wave communication under different SNR environments,the non-stationary burst-like noise environments,and the real received signal of the ultra-short wave radio.The experimental results show that the proposed algorithm performs better than the traditional squelch methods in all the simulations and experiments.In particular,the false alarm rate of the proposed squelch algorithm for non-stationary burst-like noise is significantly lower than that of traditional squelch methods. | Yuanxin Xiang Yi Lv Wenqiang Lei Jiancheng Lv | 2023 | Big Data Mining and Analytics2023，6，1： | 0 |
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