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Top-emitting organic light-emitting devices based on silicon substrate using Delta -doping technique
Zhijun Wu,Hengqun Guo,Jiaxian Wang 한국물리학회 2011 Current Applied Physics Vol.11 No.2
We have fabricated a Top-emitting organic light-emitting device on silicon substrate Delta -doping technique. Using ultrathin quinacridone as emitting layer, the performance of Top-emitting organic lightemitting device is improved obviously. However, when increasing the thickness of the anode, the performance of device is enhanced dramatically. The max power efficiency of device is 5.9 Lm/W at 5 V corresponding to the current efficiency of 9.3 cd/A. The max current efficiency of device is also increases to 11 cd/A at 7 V.
Jun Wu,Zhijun Chen 보안공학연구지원센터 2015 International Journal of Grid and Distributed Comp Vol.8 No.2
In order to improve the service performance of mobile cloud computing, the paper strategy launched a study about switching strategy of mobile cloud computing, we propose a fused mobile cloud computing switching method based on threshold judgment and network selection .This method divided the switching strategy of mobile cloud computing process into two steps, first by a threshold judgment to determine whether to switch, followed by the use of multi-attribute decision making method to select the best candidate network for the switching .Experimental results show that the proposed switching method has more excellent switching performance than Saw method and TOPSIS method, at the three indicators of switching frequency, completion time, the energy consumption of the mobile terminal have shown outstanding advantages.
Exploring finger vein based personal authentication for secure IoT
Lu, Yu,Wu, Shiqian,Fang, Zhijun,Xiong, Naixue,Yoon, Sook,Park, Dong Sun North-Holland 2017 Future generations computer systems Vol.77 No.-
<P><B>Abstract</B></P> <P>Personal authentication is getting harder and harder in the internet of things (IoT). Existing methods used for personal authentication, such as passwords and the two-factor authentication (2FA), are inadequate and ineffective due to human error and other attacks. To support more secure IoT, this paper proposes a finger vein based personal authentication method by exploring competitive orientations and magnitudes from finger vein images. Finger vein recognition has been proven to be a reliable and promising solution for biometric-based personal authentication. The stable and rich piecewise line features in finger vein images can be used to clearly represent finger vein patterns for personal authentication. In this paper, we propose an efficient local descriptor for finger vein feature extraction, namely the histogram of competitive orientations and magnitudes (HCOM). For a finger vein image, two types of local histograms are extracted and fused together to efficiently and adequately represent the competitive information: the histogram of competitive orientations (HCO) and the local binary pattern histogram generated from the image of competitive magnitudes (named as HCMLBP). The extensive experimental results from the application of the proposed method to the public finger vein database MMCBNU_6000, demonstrate that the proposed method outperforms state-of-the-art orientation coding (OC)-based methods and other commonly used local descriptors. Additionally, the proposed method can be used for finger vein image enhancement.</P> <P><B>Highlights</B></P> <P> <UL> <LI> The proposed method can efficiently extract competitive orientations and magnitudes. </LI> <LI> The proposed method outperforms the OC-based methods and common local descriptors. </LI> <LI> The proposed method has small feature size and fast speed. </LI> <LI> The proposed method can be used for finger vein image enhancement. </LI> </UL> </P>
Physical test study on double-row long-short composite anti-sliding piles
Shen, Yongjiang,Wu, Zhijun,Xiang, Zhengliang,Yang, Ming Techno-Press 2017 Geomechanics & engineering Vol.13 No.4
The double-row long-short composite anti-sliding piles system is an effective way to control the landslides with high thrust. In this study, The double-row long-short composite anti-sliding piles with different load segment length (cantilever length) and different pile row spacing were studied by a series of physical tests, by which the influences of load segment length of rear-row piles as well as pile row spacing on the mechanical response of double-row long-short composite anti-sliding pile system were investigated. Based on the earth pressures in front of and behind the piles obtained during tests, then the maximum bending moments of the fore-row and the rear-row piles were calculated. By ensuring a equal maximum moments in the fore-row and the rear-row piles, the optimum lengths of the rear-row piles of double-row long-short composite system under different piles spacing were proposed. To investigate the validity of the reduced scale tests, the full-scale numerical models of the landside were finally conducted. By the comparisons between the numerical and the physical test results, it could be seen that the reduced scale tests conducted in this study are reliable. The results showed that the double-row long-short composite anti-sliding piles system is effective in the distribution of the landslide thrust to the rear-row and the fore-row piles.
A Novel Dataset Generating Method for Fine-Grained Vehicle Classification with CNN
Shaoyong Yu,Zhijun Song,Songzhi Su,Wei Li,Yun Wu,Wenhua Zeng 보안공학연구지원센터 2016 International Journal of Database Theory and Appli Vol.9 No.6
We focus on the issue of dataset generation for fine-grained vehicle classification with CNN. Traditionally, to build a large dataset, images must be first collected manually, and then be annotated with a lot of effort. All these work are time-consuming and cost-prohibitive. In this work we propose a novel method that can generate massive images automatically, and these generated images need no annotation. An AutoCAD 3D model of a car of specified make and model is imported into our system, and then images of different views of the car are generated, these images can describe all the details of a car. By taking these images as training dataset, we use a Convolutional Neural Network to train a model for fine-grained vehicle classification. Experimental results show that these images generated virtually by 3D model indeed work as effective as real images.
The nonlinear absorption of graphene oxide water solution in femtosecond regime
Lingling Ran,Zhijun Chai,Yachen Gao,Wenzhi Wu,Qing Chang,Degui Kong 한국물리학회 2016 Current Applied Physics Vol.16 No.9
The nonlinear absorption properties of graphene oxide water solution were investigated with femtosecond pulses using Z-scan and pump-probe techniques at 800 nm wavelength. The researching results indicated that the nonlinear absorption of graphene oxide water solution include three parts: twophoton absorption of bound electrons from valence band, excited state absorption of electrons from the low energy state in conduction band and the excited state absorption of electrons from the bottom of conduction band. By theoretically fitting the experimental results, we got the two-photon absorption coefficient about b ¼ 3 1014 m/W, and the two excited state absorption cross section in the order of 1020 m2 and 1021 m2 respectively. In addition, the excited state lifetime of electron on the low energy state of conduction band was obtained. The investigation indicated that graphene oxide water solution is a good nonlinear optical material.
Study on the International Intensive Measurements in Northeast Asia Relating to the FRIEND Project
이지이,송미정,장경순,김창혁,Zhijun Wu,Atsushi Matsuki,Amgalan Natsagdorj 한국대기환경학회 2021 한국대기환경학회 학술대회논문집 Vol.2021 No.10
Air pollution in Northeast Asia is not a problem that can be characterized and mitigated by the effort of a single country but requires an international and cross-border perspective. Therefore, the Center for Fine Particle Research Initiative in East Asia Considering National Differences (FRIEND) project has been launched since 2020 to characterize air pollution in Northeast Asia with effective collaboration. As one part of FRIEND project, this study aims to elucidate the spatio-temporal characteristics of atmospheric aerosols in Northeast Asia and provide scientific knowledge on their evolution of air pollution in the region by international intensive measurement. This will be done by creating an exceptionally strong network of key monitoring activities across the nations, including Korea, China, Mongolia, and Japan. The plan for eight intensive field campaigns regarding the high-resolution physical and chemical measurement of aerosols and precursors was also established to achieve this objective. This presentation will introduce the details on the study for the characteristics of haze formation in Northeast Asia by international intensive measurements.
Hu Hongyan,Wang Xiaowei,Wu Zhijun,Chen Mo,Chai Tuanyao,Wang Hong 한국식물학회 2022 Journal of Plant Biology Vol.65 No.6
Plants have evolved complex signaling networks that enable them to adapt to adverse environmental conditions. The dehydration-responsive element-binding (DREB) transcription factors are important for plant responses to abiotic stresses. In this study, a new member of the AP2/ERF transcription factor gene family, PcDREB2A, was cloned and characterized from Polygonum cuspidatum, a traditional Chinese medicinal herb. PcDREB2A, which includes a typical AP2 domain, was clustered in the A-2 subgroup of the DREB subfamily. At the seedling stage, PcDREB2A expression was induced by cold, salt, and drought stresses. A yeast one-hybrid assay and an analysis of transiently transformed tobacco revealed that PcDREB2A can specifically bind to the DRE motif and transactivate reporter gene expression. Following 200 and 250 mM mannitol treatments, the PcDREB2A-overexpressing Arabidopsis thaliana lines had longer roots and a significantly higher fresh weight than the wild-type plants. Furthermore, under drought stress conditions, the PcDREB2A-overexpressing A. thaliana plants accumulated less malondialdehyde than the control plants. These results indicate that PcDREB2A encodes a novel DREB transcription factor in P. cuspidatum. Furthermore, the data generated in this study may be useful for researchers and breeders interested in genetically engineering plants to increase drought tolerance without inhibiting growth.