Solution-Processed Nanowire Coating for Light Management in Organic Solar Cells by K. Tsuboi, T. Fukawa, Y. Konosu, H. Matsumoto, A. Tanioka

“…We report a novel light management approach based on solution-processed nanowire (NW) coating for enhancing organic solar cell efficiency. …”
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Observation of ultraviolet photothermoelectric bipolar impulse in gallium-based heterostructure nanowires by Jinjie Zhu, Qing Cai, Pengfei Shao, Shengjie Zhang, Haifan You, Hui Guo, Jin Wang, Junjun Xue, Bin Liu, Hai Lu, Youdou Zheng, Rong Zhang, Dunjun Chen

“…Here, we introduce a GaON/GaN heterostructure-nanowire ultraviolet electrochemical cell of observing a photothermoelectric bipolar impulse characteristic. …”
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Phase Transition and Optical Properties for Ultrathin KNbO3 Nanowires by Shulin Yang, Yongming Hu, Shengfu Wang, Haoshuang Gu, Yu Wang

“…Fascicular KNbO3 nanowires with tetragonal perovskite structures and ultrasmall diameters are synthesized by hydrothermal route at about 150°C for 24 hours. …”
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Mesoporous SnO2 Nanowires: Synthesis and Ethanol Sensing Properties by Shan-Hong Li, Fang-Fang Meng, Zhong Chu, Tao Luo, Fu-Min Peng, Zhen Jin

“…XRD, SEM, and HRTEM were used to characterize the synthesized mesoporous SnO2 nanowires. The sensing property of the mesoporous SnO2 nanowires in ethanol detection also has been studied. …”
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Breaking the wire: the impact of critical length on melting pathways in silver nanowires by K M Ridings, E E L Vaka’uta, S M Croot

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Preparation and photoelectric properties of Si:B nanowires with thermal evaporation method. by Yang Feng, Ping Liang, Ziwen Xia, Weiye Yang, Hongyan Peng, Shihua Zhao

“…We have successfully prepared a significant number of nanowires from non-toxic silicon sources. Compared to the SiO silicon source used in most other articles, our preparation method is much safer. …”
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DECREASE IN LABOR INPUT OF PRODUCTION DUE TO RATIONAL USE OF A MANPOWER by E. V. Korneevets, A. V. Burchak

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Behavior Intention Derivation of Android Malware Using Ontology Inference by Jian Jiao, Qiyuan Liu, Xin Chen, Hongsheng Cao

“…Previous researches on Android malware mainly focus on malware detection, and malware’s evolution makes the process face certain hysteresis. …”
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HTTP behavior characteristics generation and extraction approach for Android malware by Yaling LUO, Wenwei LI, Xin SU

“…Growing of Android malware，not only seriously endangered the security of the Android market，but also brings challenges for detection.A generation and extraction approach of automatic Android malware behavioral signatures was proposed based on HTTP traffic.Firstly，the behavioral signatures were extracted from the traffic traces generated by Android malware.Then，network behavioral characteristics were extracted from the generated network traffic.Finally，these behavioral signatures were used to detect Android malware.The experimental results show that the approach is able to extract Android malware network traffic behavioral signature with accuracy and efficiency.…”
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Research on the reverse analyses and monitoring data of Mirai malware botnet by Ya-liang CHEN, Qin-yun DAI, Hai-yan WU, Zheng WEI

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Android malware detection based on APK signature information feedback by Xin-yu LIU, Jian WENG, Yue ZHANG, Bing-wen FENG, Jia-si WENG

“…A new malware detection method based on APK signature of information feedback (SigFeedback) was proposed.Based on SVM classification algorithm,the method of eigenvalue extraction adoped heuristic rule learning to sig APK information verify screening,and it also implemented the heuristic feedback,from which achieved the purpose of more accurate detection of malicious software.SigFeedback detection algorithm enjoyed the advantage of the high detection rate and low false positive rate.Finally the experiment show that the SigFeedback algorithm has high efficiency,making the rate of false positive from 13% down to 3%.…”
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Online analytical model of massive malware based on feature clusting by Xiao-lin XU, Xiao-chun YUN, Yong-lin ZHOU, Xue-bin KANG

Subjects: “…malware…”
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Android malware detection method based on deep neural network by Fan CHAO, Zhi YANG, Xuehui DU, Yan SUN

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A Data Mining Classification Approach for Behavioral Malware Detection by Monire Norouzi, Alireza Souri, Majid Samad Zamini

“…In this paper we present a data mining classification approach to detect malware behavior. We proposed different classification methods in order to detect malware based on the feature and behavior of each malware. …”
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Method of anti-confusion texture feature descriptor for malware images by Yashu LIU, Zhihai WANG, Hanbing YAN, Yueran HOU, Yukun LAI

Subjects: “…malware visualization…”
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Active-probing based distributed malware master detection system by Cheng-xiang SI, Bo SUN, Wen-han YANG, Hui-lin ZHANG, Xiao-nan XUE

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Malware classification method based on static multiple-feature fusion by Bo-wen SUN, Yan-yi HUANG, Qiao-kun WEN, Bin TIAN, Peng WU, Qi LI

Subjects: “…malware…”
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HD-SEIRS Malware Propagation Model in Heterogeneous Complex Networks by Elham Asadi, Soodeh Hosseini

Subjects: “…malware propagation modeling…”
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Multi-granularity Android malware fast detection based on opcode by Xuetao ZHANG, Meng SUN, Jinshuang WANG

“…The detection method based on opcode is widely used in Android malware detection,but it still contains some problems such as complex feature extraction method and low efficiency.In order to solve these problems,a multi-granularity fast detection method based on opcode for Android malware was proposed.Multi-granularity refers to the feature based on the bag of words model,and with the function as basic unit to extract features.By step-by-level aggregation feature,the APK multi-level information is obtained.The log length characterizes the scale of the function.And feature can be compressed and mapped to improve the efficiency and construct the corresponding classification model based on the semantic similarity of the Dalvik instruction set.Tests show that the proposed method has obvious advantages in performance and efficiency.…”
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A Malware Detection Scheme Based on Mining Format Information by Jinrong Bai, Junfeng Wang, Guozhong Zou

“…Malware has become one of the most serious threats to computer information system and the current malware detection technology still has very significant limitations. …”
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