作者机构：
[Xiang, Lingyun] Changsha Univ Sci & Technol, Hunan Prov Key Lab Intelligent Proc Big Data Tran, Changsha 410114, Peoples R China.;[Yang, Shuanghui; Xiang, Lingyun; Liu, Yuhang] Changsha Univ Sci & Technol, Sch Comp & Commun Engn, Changsha 410114, Peoples R China.;[Xiang, Lingyun] Changsha Univ Sci & Technol, Hunan Prov Key Lab Smart Roadway & Cooperat Vehic, Changsha 410114, Peoples R China.;[Li, Qian] Univ Technol Sydney, Fac Engn & Informat Technol, Ultimo, NSW 2007, Australia.;[Zhu, Chengzhang] Acad Mil Med Sci, Beijing 100091, Peoples R China.
通讯机构：
[Zhu, Chengzhang] A;Acad Mil Med Sci, Beijing 100091, Peoples R China.
关键词：
linguistic steganography;LSTM;automatic text generation;character-level language model
摘要：
With the development of natural language processing, linguistic steganography has become a research hotspot in the field of information security. However, most existing linguistic steganographic methods may suffer from the low embedding capacity problem. Therefore, this paper proposes a character-level linguistic steganographic method (CLLS) to embed the secret information into characters instead of words by employing a long short-term memory (LSTM) based language model. First, the proposed method utilizes the LSTM model and large-scale corpus to construct and train a character-level text generation model. Through training, the best evaluated model is obtained as the prediction model of generating stego text. Then, we use the secret information as the control information to select the right character from predictions of the trained character-level text generation model. Thus, the secret information is hidden in the generated text as the predicted characters having different prediction probability values can be encoded into different secret bit values. For the same secret information, the generated stego texts vary with the starting strings of the text generation model, so we design a selection strategy to find the highest quality stego text from a number of candidate stego texts as the final stego text by changing the starting strings. The experimental results demonstrate that compared with other similar methods, the proposed method has the fastest running speed and highest embedding capacity. Moreover, extensive experiments are conducted to verify the effect of the number of candidate stego texts on the quality of the final stego text. The experimental results show that the quality of the final stego text increases with the number of candidate stego texts increasing, but the growth rate of the quality will slow down.
摘要：
Abstract Objective: Traffic deaths involving e-bike (electric bike) riders are increasing in China. This study aims to quantitatively investigate the association between e-bike rider casualty and impact speed in electric bike-passenger vehicle collisions based on China in-depth accident study data. Methods: According to the collision location and driving direction of the e-bike and the vehicle, electric bike-passenger vehicle collisions are divided into five collision types: frontal collision, e-bike side collision, vehicle side collision, scrape collision and rear-end collision. Since e-bike side collision (the side of e-bike impacted with the front of vehicle) is the leading type and has the highest likelihood of severe or fatal injury in all collision types, e-bike side collisions are further selected to build the casualty risk functions of e-bike rider in relation to the rider age and the impact speed (vehicle impact speed and e-bike impact speed). Results: The analysis results show that, as for e-bike side collisions and e-bike impact speed is 20 km/h, the fatality risk of riders is approximately 2.9% at vehicle impact speed of 30 km/h, 23% at 50 km/h, 50% at 60 km/h, and 90% at 80 km/h. Rider age is also significantly associated with a higher risk of severe and fatality injury. The e-bike impact speed is not significantly associated with the severe and fatality risk in e-bike side collisions. Conclusions: The findings of this study provide meaningful insights to formulate effective policies especially for speed limit management to improve the safety of e-bikes.
摘要：
In order to predict the resilient modulus of compacted clays, the material indicator tests, repeated load triaxial test, and pressure plate test for compacted clays from South China were carried out. The soil–water characteristic curve (SWCC) was described using the Fredlund and Xing’s model. And a logarithmic function between the soil suction and resilient modulus was built. Then, a new variable named the minimum bulk stress was defined to separate the shear effect of soil samples from the bulk stress, which avoids the bulk stress reflects two contrary effects, namely hardening effect and softening effect. Subsequently, the influences of the degree of compaction, soil suction, minimum bulk stress, and octahedral shear stress on the resilient modulus were analysed. In the following, a new resilient modulus prediction model of compacted clays, which took the soil suction, minimum bulk stress, and octahedral shear stress as the model variables, was developed and verified using the data of different cohesive soils from this study and existing literatures. The results show that the new model matched these data well and have a high prediction accuracy, which indicates that this new model is reasonable and widely applicable.
通讯机构：
[Qin, JH; Xiang, XY] C;[Xiang, Xuyu] U;Cent South Univ Forestry & Technol, Coll Comp Sci & Informat Technol, Changsha, Peoples R China.;Univ Alabama, Coll Commun & Informat Sci, Tuscaloosa, AL 35487 USA.
关键词：
Coverless information hiding;Data hiding;Deep learning;DCT;DenseNet;Real-time image processing
摘要：
Information security has become a key issue of public concern recently. In order to radically resist the decryption and analysis in the field of image information hiding and significantly improve the security of the secret information, a novel coverless information hiding approach based on deep learning is proposed in this paper. Deep learning can select the appropriate carrier according to requirements to achieve real-time image data hiding and the high-level semantic features extracted by CNN are more accurate than the low-level features. This method does not need to employ the designated image for embedding the secret data but transfer a set of real-time stego-images which share one or several visually similar blocks with the given secret image. In this approach, a group of real-time images searched online are segmented according to specific requirements. Then, the DenseNet is used to extract the high-level semantic features of each similar block. At the same time, a robust hash sequence with feature sequence, DC and location is generated by DCT. The inverted index structure based on the hash sequence is constructed to attain real-time image matching efficiently. At the sending end, the stego-images are matched and sent through feature retrieval. At the receiving end, the secret image can be recovered by extracting similar blocks through the received stego-images and stitching the image blocks according to the location information. Experimental results demonstrate that the proposed method without any modification traces provides better robustness and has higher retrieval accuracy and capacity when compared with some existing coverless image information hiding.
摘要：
In the IoT (Internet of Things) environment, smart homes, smart grids, and telematics constantly generate data with complex attributes. These data have low heterogeneity and poor interoperability, which brings difficulties to data management and value mining. The promising combination of blockchain and the Internet of things as BCoT (blockchain of things) can solve these problems. This paper introduces an innovative method DCOMB (dual combination Bloom filter) to firstly convert the computational power of bitcoin mining into the computational power of query. Furthermore, this article uses the DCOMB method to build blockchain-based IoT data query model. DCOMB can implement queries only through mining hash calculation. This model combines the data stream of the IoT with the timestamp of the blockchain, improving the interoperability of data and the versatility of the IoT database system. The experiment results show that the random reading performance of DCOMB query is higher than that of COMB (combination Bloom filter), and the error rate of DCOMB is lower. Meanwhile, both DCOMB and COMB query performance are better than MySQL (My Structured Query Language).
期刊：
Journal of Materials Chemistry C,2020年8(9):3029-3039 ISSN：2050-7526
通讯作者：
Liu, Chunzhao;Fan, Runhua;Guo, Zhanhu
作者机构：
[Xie, Peitao; Liu, Chunzhao; Sui, Kunyan] Qingdao Univ, Coll Mat Sci & Engn, Inst Biochem Engn, State Key Lab Biofibers & Ecotext, Qingdao 266071, Peoples R China.;[Fu, Xueyan; Li, Yifan] Shandong Univ, Minist Educ, Key Lab Liquid Solid Struct Evolut & Proc Mat, Jinan 250061, Peoples R China.;[Hou, Qing] UCL, Dept Chem, Kathleen Lonsdale Mat Chem, 20 Gordon St, London WC1H 0AJ, England.;[Zhang, Jiaoxia] Jiangsu Univ Sci & Technol, Sch Mat Sci & Engn, Zhenjiang 212003, Jiangsu, Peoples R China.;[Murugadoss, Vignesh] Zhengzhou Univ, Natl Engn Res Ctr Adv Polymer Proc Technol, Minist Educ, Key Lab Mat Proc & Mold, Zhengzhou, Peoples R China.
通讯机构：
[Liu, Chunzhao] Q;[Fan, Runhua] S;[Guo, Zhanhu] U;Qingdao Univ, Coll Mat Sci & Engn, Inst Biochem Engn, State Key Lab Biofibers & Ecotext, Qingdao 266071, Peoples R China.;Shanghai Maritime Univ, Coll Ocean Sci & Engn, Shanghai 201306, Peoples R China.
摘要：
One-dimensional wires are the most common building blocks in metamaterials. In this study, zero-dimensional nanoparticles connected by tunneling networks were used to construct metamaterials, thus providing a more flexible alternative for designing the geometrical configuration of metamaterials, particularly in nanodevices. The composites with nickel nanoparticles@MnO were prepared by a bio-gel derived strategy. Nickel nanoparticles were not connected geometrically, but the conductive network had been already formed, which was a tunneling-dominated percolative phenomenon demonstrated by the first-principles calculation. Negative permittivity was achieved in the composites, as the low-frequency plasmonic state could be generated in the tunneling nickel-networks. At the same time, negative susceptibility was observed due to the diamagnetism of the tunneling current loops. Electromagnetic simulations indicate that the composites have the potential for electromagnetic shielding (only 0.25 mm in thickness). It is believed that this study not only fills up the research gap in the influence of the tunneling effect on negative electromagnetic parameters but also opens up another way of preparing metamaterials by using zero-dimensional nanoparticles instead of one-dimensional wires.
