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| 1 | The Intelligent Control System of Traffic Light Based on Fog Computing显示文摘The continuous increase of city motors with the improvement of society has introduced extraordinary demanding situations for the traffic situation of the town.Intelligent traffic has proposed a diversity of solutions to relieve urban traffic accidents and congestion and other troubles. It cannot regulate the cycle of traffic light in real time in keeping with the occurring traffic flux which additionally, may produce the traffic jam to result in the increase for the range of automobiles and the longer of passage time. In purpose to surmount the shortcomings of traditional traffic light control, this paper is presenting a form of intelligent control system for traffic light founding on fog computing. It calculates and shares the traffic flux situation at the intersection and the surrounding intersection through fog computing platform. Regarding the traffic flow at the intersection and the traffic flow at the surrounding intersection as the parameters, the intelligent control algorithm of traffic light is designed for achieving mutual coordination and mutual influence between different intersections, so that the traffic efficiency of each intersection is improved and the traffic flow of the entire transport network is alleviated. The simulation results showed this intelligent control system progress the traffic efficiency of every intersection and relieve the traffic flow of the whole transport network. | WU Qiong HE Fanfan FAN Xiumei | 2018 | Chinese Journal of Electronics2018，27，6： | 7 |
| 2 | Alteration of heat shock protein 20 expression in preeclampticpatients and its effect in vascular and coagulation function显示文摘Preeclampsia (PE) is a pregnancy-specific, multi-system disorder and the leading cause of maternal andperinatal morbidity and mortality in obstetrics worldwide. Excessive vasoconstriction and dysregulatedcoagulation function are closely associated with PE. Heat shock protein 20 (HSP20) is ubiquitously expressedunder normal physiological conditions and has important roles in vascular dilatation and suppression of plateletaggregation. However, the role of HSP20 in the pathogenesis of PE remains unclear. In this study, we collectedchorionic plate resistance arteries (CPAs) and serum from 118 healthy pregnant women and 80 women with PEand detected the levels of HSP20 and its phosphorylated form. Both HSP20 and phosphorylated HSP20 weredownregulated in CPAs from women with PE. Comparison of the vasodilative ability of CPAs from the two groupsshowed impaired relaxation responses to acetyl choline in preeclamptic vessels. In addition to the reduced HSP20in serum from women with PE, the platelet distribution width and mean platelet volume were also decreased, andthe activated partial thromboplastin time and thromboplastin time were elevated. With regard to the vital roles ofHSP20 in mediating vasorelaxation and coagulation function, the decreased HSP20 might contribute to thepathogenesis of PE. | Fanfan Li Mengzhou He Meitao Yang Yao Fan Yun Chen Xi Xia Yin Xie Dongrui Deng | 2018 | Frontiers of Medicine2018，12，5： | 5 |
| 3 | A new coordinated backup protection scheme for distribution network containing distributed generation显示文摘This paper proposes a new backup protection scheme,named coordinated backup protection(CBP)scheme,for distribution networks containing distributed generation.The proposed protection scheme takes into account the issues faced by traditional backup protection,such as difficulty in setting parameters and complex cooperation,and considers the features of distribution networks,such as changeable power flow because of high penetration of distributed generation sources and insufficient measuring quantities.The CBP scheme includes two aspects:coordinated substation protection and regional master substation protection,who also work as nearby backup protection and remote backup protection respectively.The two protections support each other by local information coordination and regional information sharing,in order to improve the reliability of fault identification.The configuration principles and performances of the proposed backup protection scheme are addressed in the paper.Different fault conditions in the IEEE 14-node system have been used to illustrate and verify the feasibility of the CBP scheme. | Jinghan He Lin Liu Fanfan Ding Changcheng Li Dahai Zhang | 2017 | Protection and Control of Modern Power Systems2017，2，1： | 3 |
| 4 | Effect of acupuncture treatment on smoking cessation in smokers from Hong Kong显示文摘OBJECTIVE: To analyze the characteristics of smokers treated with acupuncture for smoking cessation in Hong Kong.METHODS: A total of 2051 subjects were recruited in a clinical pilot research project 'acupuncture for smoking cessation', which was conducted jointly by Institute of Acupuncture and Moxibustion, China Academy of Chinese Medical Sciences and Hong Kong Pok Oi Hospital from January of 2011 to December of 2013. The characteristics of study subjects, including baseline information, smoking background, intention to quit and influencing factors were analyzed.RESULTS: The majority of subjects treated with acupuncture for smoking cessation in Hong Kong was male(66.7%), but the proportion of female smokers in this study(33.3%) was higher than that of female smokers in Hong Kong population(13.8%, P <0.05). Subjects were at the mean age of 43.83 years old, of which the percentage of females aged 31-40 years was the highest(38.8%, P < 0.05). The mean duration of smoking was 25.49 years. The number of cigarettes smoked per day was 17.57 cigarettes.Fagerstrom Test for Nicotine Dependence(FTND)was 5.29 points. Most of the subjects had attempted quitting smoking(81.42%). The confidence index(7.44 points) and the readiness to quit smoking(8.13 points) were high. Subjects quitting smoking were mostly due to health cause(81.91%). The majority of subjects were at the level of middle school(61.63%). The higher the educational level was, the lower the tobacco dependence was and the higher the confidence in successfully quitting smoking was. 50.27% of subjects chose acupuncture for smoking cessation mainly through friends, television and network publicity. Subjects who had received acupuncture had the highest confidence index, while those who wanted to try a new method had the lower confidence index.CONCLUSION: Acupuncture for smoking cessation was more popular in female smokers, especially those aged 31-40 years. The effectiveness of acupuncture-smoking cessation was most significant in the smokers over 60. | Wang Yingying Liu Zhao Zhang Ou Chen Min Huang Lingling Wu Yuan Zhang Fanfan Wu Guanyi He Xiuqing Yang Jinsheng | 2016 | Journal of Traditional Chinese Medicine2016，36，5： | 3 |
| 5 | A low phasenoise VCO using an electronically tunable substrate integrated waveguide resonator显示文摘 | He Fanfan Wu Ke Hong Wei | 2010 | Microwave Theory and Techniques2010，58，12： | 1 |
| 6 | A planar magic-T using substrate integrated circuits concept显示文摘 | He Fanfan Wu Ke Hong Wei | 2008 | IEEE Microwave and Wireless Components Letters2008，18，38： | 1 |
| 7 | Feedback Learning Based Dead Write Termination for Energy Efficient STT-RAM Caches显示文摘Spin-torque transfer RAM(STT-RAM) is a promising candidate to replace SRAM for larger Last level cache(LLC). However, it has long write latency and high write energy which diminish the benefit of adopting STT-RAM caches. A common observation for LLC is that a large number of cache blocks have never been referenced again before they are evicted. The write operations for these blocks, which we call dead writes, can be eliminated without incurring subsequent cache misses. To address this issue, a quantitative scheme called Feedback learning based dead write termination(FLDWT) is proposed to improve energy efficiency and performance of STT-RAM based LLC. FLDWT dynamically learns the block access behavior by using data reuse distance and data access frequency, and then classifies the blocks into dead blocks and live blocks. FLDWT terminates dead write block requests and improves the estimation accuracy via feedback information. Compared with STT-RAM baseline in the lastlevel caches, experimental results show that our scheme achieves energy reduction by 44.6% and performance improvement by 12% on average with negligible overhead. | SHEN Fanfan HE Yanxiang ZHANG Jun JIANG Nan LI Qing'an LI Jianhua | 2017 | Chinese Journal of Electronics2017，26，3： | 0 |
| 8 | Rating Text Classification with Weighted Negative Supervision on Classifier Layer显示文摘Bidirectional encoder representations from transformers(BERT)gives full play to the advantages of the attention mechanism,improves the performance of sentence representation,and provides a better choice for various natural language understanding(NLU)tasks.Many methods using BERT as the pre-trained model achieve state-of-the-art performance in almost various text classification scenarios.Among them,the multitask learning framework combining the negative supervision and the pre-trained model solves the issue of the model performance degradation that occurs as the semantic similarity of texts conflicts with the classification standards.The current model does not consider the degree of difference between labels,which leads to insufficient difference information learned by the model,and affects classification performance,especially in the rating classification tasks.On the basis of the multi-task learning model,this paper fully considers the degree of difference between labels,which is expressed by using weights to solve the above problems.We supervise negative samples on the classifier layer instead of the encoder layer,so that the classifier layer can also learn the difference information between the labels.Experimental results show that our model can not only performs well in 2-class and multi-class rating text classification tasks,but also performs well in different languages. | ZHANG Jun QIU Longlong SHEN Fanfan HE Yueshun TAN Hai HE Yanxiang | 2023 | Chinese Journal of Electronics2023，32，6： | 0 |
| 9 | Compiler IR-Based Program Encoding Method for Software Defect Prediction显示文摘With the continuous expansion of software applications,people’s requirements for software quality are increasing.Software defect prediction is an important technology to improve software quality.It often encodes the software into several features and applies the machine learning method to build defect prediction classifiers,which can estimate the software areas is clean or buggy.However,the current encoding methods are mainly based on the traditional manual features or the AST of source code.Traditional manual features are difficult to reflect the deep semantics of programs,and there is a lot of noise information in AST,which affects the expression of semantic features.To overcome the above deficiencies,we combined with the Convolutional Neural Networks(CNN)and proposed a novel compiler Intermediate Representation(IR)based program encoding method for software defect prediction(CIR-CNN).Specifically,our program encoding method is based on the compiler IR,which can eliminate a large amount of noise information in the syntax structure of the source code and facilitate the acquisition of more accurate semantic information.Secondly,with the help of data flow analysis,a Data Dependency Graph(DDG)is constructed on the compiler IR,which helps to capture the deeper semantic information of the program.Finally,we use the widely used CNN model to build a software defect prediction model,which can increase the adaptive ability of the method.To evaluate the performance of the CIR-CNN,we use seven projects from PROMISE datasets to set up comparative experiments.The experiments results show that,in WPDP,with our CIR-CNN method,the prediction accuracy was improved by 12%for the AST-encoded CNN-based model and by 20.9%for the traditional features-based LR model,respectively.And in CPDP,the AST-encoded DBNbased model was improved by 9.1%and the traditional features-based TCA+model by 19.2%,respectively. | Yong Chen Chao Xu Jing Selena He Sheng Xiao Fanfan Shen | 2022 | Computers, Materials & Continua2022，，9： | 0 |
| 10 | Memory Request Priority Based Warp Scheduling for GPUs显示文摘High performance of GPGPU comes from its super massive multithreading, which makes it more and more widely used especially in the field of throughputoriented. Data locality is one of the important factors affecting the performance of GPGPU. Although GPGPU can exploit intra/inter-warp locality by itself in part, there is still large improvement space for that. In our work, we analyze the characteristics of different applications and propose memory request based warp scheduling to better exploit inter-warp spatial locality. This method can make some warps with good inter-warp locality run faster, which is beneficial to improve the whole performance. Our experimental results show that our proposed method can achieve24.7% and 11.9% average performance improvement over LRR and MRPB respectively. | ZHANG Jun HE Yanxiang SHEN Fanfan LI Qing'an TAN Hai | 2018 | Chinese Journal of Electronics2018，27，5： | 0 |
| 11 | Magnetic field enhanced thermal conductivity and origin of large thermopower in layered cobaltates显示文摘Cobalt oxide,as one of the most fascinating examples of correlated electronic system,exhibits several exotic transport characteristics,such as superconductivity,charge ordering,and topological frustration.In this study,we are reporting the observation of another intriguing transport phenomenon in calcium cobaltates.Specifically,under a large magnetic field of 7 T,we observed an anomalously enhanced thermal conductivity that was accompanied with a largely suppressed thermopower.This observation reveals a hitherto undiscovered correlation between the two transport factors.Within the premise of Heisenberg model,we have shown that the observed experimental results can be explained consistently only if the magnon excitation is taken into account.Our study offers an insight into the puzzling origin of large thermopower observed in layered cobaltates and provides a specific strategy for further optimization of thermopower. | Yinong Yin Fanfan Shi Guo-Qiang Liu Ashutosh Tiwari Jiazheng Hao Lunhua He Dan Liu Jianfeng Cai Xiaojian Tan Jun Jiang Baogen Shen | 2023 | Journal of Materiomics2023，9，6： | 0 |
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