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Articles by Tao LI
Total Records ( 9 ) for Tao LI
  Tao Li , Kaijin Hu , Libo Cheng , Yin Ding , Yuxiang Ding , Jinling Shao and Liang Kong
  This study aimed to evaluate continuous and simultaneous variations of dental implant diameter and length, and to identify their relatively optimal ranges in the posterior mandible under biomechanical consideration. A 3D finite element model of a posterior mandibular segment with dental implant was created. Implant diameter ranged from 3.0 to 5.0 mm, and implant length ranged from 6.0 to 16.0 mm. The results showed that under axial load, the maximum Von Mises stresses in cortical and cancellous bones decreased by 76.53% and 72.93% respectively, with the increasing of implant diameter and length; and under buccolingual load, by 83.97% and 84.93%, respectively. Under both loads, the maximum displacements of implant-abutment complex decreased by 58.09% and 75.53%, respectively. The results indicate that in the posterior mandible, implant diameter plays more significant roles than length in reducing cortical bone stress and enhancing implant stability under both loads. Meanwhile, implant length is more effective than diameter in reducing cancellous bone stress under both loads. Moreover, biomechanically, implant diameter exceeding 4.0 mm and implant length exceeding 12.0 mm is a relatively optimal combination for a screwed implant in the posterior mandible with poor bone quality.
  Ting Zhang , Cheng Xu , Tao Li , Yunchuan Qin and Min Nie
  Matrix multiplication is a kernel and fundamental operation in many applications including image, robotic and digital signal processing. The key component of matrix multiplication is Multiplier Accumulator (MAC) which is a decisive component for the performance of matrix multiplication. This study proposes a pipelined floating-point MAC architecture on Field Programmable Gate Array (FPGA) using a novel accumulating method. By adding the last N-stage results of the pipelined adder, the accumulation of the multiplier products can be obtained. Then, a matrix multiplication is implemented by employing parallel systolic structure based on the proposed MAC. Experimental results demonstrate that the proposed MAC architecture achieves higher clock speed and consumes less hardware resources than previous designs and the matrix multiplier has a good performance and scalability. It also can be concluded that the efficiency of the matrix multiplier is even higher when the matrices are larger.
  Yi Zhu , Xingming Sun , Zhihua Xia , Li Chen , Tao Li and Daxing Zhang
  With the growing popularity of cloud computing, more and more users are willing to outsource their private data to the cloud. To ensure the security of data, data owners usually encrypted their private data before outsourcing them to the cloud server. Though data encryption improves the security of data, it increases the difficulty of data operating. This study focuses on the search of encrypted images in the cloud and proposes an efficient similarity retrieval scheme over encrypted images. The proposed scheme enables data owners to outsource their personal images and the content-based image retrieval service to the cloud without revealing the actual content of the image database to the cloud. The proposed scheme in this study supports the global feature based image retrieval methods under the Euclidean distance metric. Besides, rigorous security analysis and extensive experiments show that the proposed scheme is secure and efficient.
  Tao Li and Kikuhito Kawasue
  Infrared (IR) thermography is device that can measure the distribution of infrared energy emitted from the surface of these objects. Since two-dimensional thermal images can be easily obtained without making contact with the object, the thermography has been used in fields such as agriculture, medicine, engineering and architecture. This study presents calibration methods that enable combining three-dimensional (3D) scanning technology with thermography. Three types of image measurement systems are introduced. The proposed systems can detect not only the 3D shape of a target object but also its temperature distribution. Application technology based on infrared thermography can make great strides in biological and medical fields by acquiring the 3D temperature distribution. In addition, a new Iterative Closest Point (ICP) algorithm is introduced. The feasibility of the proposed systems was confirmed by experiment.
  Huan Liu , Baowei Wang , Xingming Sun , Tao Li , Qi Liu and Yunbiao Guo
  The technology of Wireless Sensor Network (WSN) has facilitated the meteorological parameter monitoring. To reduce the cost, most monitoring systems collect desired data through cheap, unprofessional meteorological equipments, so do our system. However, due to the low cost of equipments and the poor package, the data collected by unprofessional equipments is inaccurate. In this study, we propose a Data Correction Scheme for Cheap Sensor (DCSCS) to improve data accuracy. The Discrete Wavelet Transform algorithm is used to filter the collected data to clear the noise and find the data pattern. Then we use Back Propagation neural network to establish a data correction model. Finally, we use the model to correct the other data. Our experiment shows that the meteorological data corrected by our method performs a very good result both in maximum error, mean error and correlation coefficient.
  Tao Li , Cheng Xu and Youqi Cai
  Road detection is one of the most important technologies in the vision-based intelligent navigation system. In this study, a fast and robust unstructured road detection method is proposed. In order to ensure the robustness of the algorithm, BP (Back Propagation) Neural Network is employed to learn the color features from a set of sample of both road region and off-road region and then to classify a new pixel. And a heuristic fitting approach based on Conditional Destiny Propagation is employed to fit the boundaries of the lanes with the Least Square Method. Taking the advantages of these properties, the proposed implementation works out with high performance of detection in various environments. Meanwhile it is robust against noise, shadows and illumination variations.
  Tao Li , Ji-Fan Hu , Xinwen Qiu , Jianqun Ling , Huiling Chen , Shukui Wang , Aiju Hou , Thanh H. Vu and Andrew R. Hoffman
  CTCF is a zinc finger DNA-binding protein that regulates the epigenetic states of numerous target genes. Using allelic regulation of mouse insulin-like growth factor II (Igf2) as a model, we demonstrate that CTCF binds to the unmethylated maternal allele of the imprinting control region (ICR) in the Igf2/H19 imprinting domain and forms a long-range intrachromosomal loop to interact with the three clustered Igf2 promoters. Polycomb repressive complex 2 is recruited through the interaction of CTCF with Suz12, leading to allele-specific methylation at lysine 27 of histone H3 (H3-K27) and to suppression of the maternal Igf2 promoters. Targeted mutation or deletion of the maternal ICR abolishes this chromatin loop, decreases allelic H3-K27 methylation, and causes loss of Igf2 imprinting. RNA interference knockdown of Suz12 also leads to reactivation of the maternal Igf2 allele and biallelic Igf2 expression. CTCF and Suz12 are coprecipitated from nuclear extracts with antibodies specific for either protein, and they interact with each other in a two-hybrid system. These findings offer insight into general epigenetic mechanisms by which CTCF governs gene expression by orchestrating chromatin loop structures and by serving as a DNA-binding protein scaffold to recruit and bind polycomb repressive complexes.
  Tao Li , Shu-min Fei and Qing Zhu
  In this letter, the delay-dependent state estimation problem for recurrent neural networks with both time-varying and distributed time-varying delays is investigated. Through available output measurements, a delay-dependent criterion is established to estimate the neuron states such that the dynamics of the estimation error is globally exponentially stable. The derivative of a time-varying delay can take any value and the activation functions are assumed to be neither monotonic, nor differentiable, which are more general than the recently commonly used Lipschitz conditions. Finally, two illustrative examples are given to demonstrate the usefulness of the obtained condition.
  Tao LI , LIU Run-Jin , HE Xin-Hua and WANG Bao-Shan
  Arbuscular mycorrhizal (AM)-mediated plant physiological activities could contribute to plant salt tolerance. However, the biochemical mechanism by which AM fungi enhance salt tolerance of halophytic plants is unclear. A pot experiment was conducted to determine whether salt tolerance of the C3 halophyte Suaeda salsa was enhanced by the AM fungus Glomus mosseae. When 60-day-old S. salsa seedlings were subjected to 400 mmol L−1 NaCl stress for 35 days, plant height, number of leaves and branches, shoot and root biomass, and root length of G. mosseae-colonized seedlings were significantly greater than those of the nonmycorrizal seedlings. Leaf superoxide dismutase (SOD) activity at all sampling times (weekly for 35 days after salt stress was initiated) and leaf catalase (CAT) activity at 2 and 3 weeks after salt stress was initiated were also significantly enhanced in G. mosseae-colonized S. salsa seedlings, while the content of leaf malondialdehyde (MDA), a product of membrane lipid peroxidation, was significantly reduced, indicating an alleviation of oxidative damage. The corresponding leaf isoenzymes of SOD (Fe-SOD, Cu/Zn-SOD1, and Cu/Zn-SOD2) and CAT (CAT1 and CAT2) were also significantly increased in the mycorrhizal seedlings after 14 days of 400 mmol L−1 NaCl stress. Our results suggested that G. mosseae increased salt tolerance by increasing SOD and CAT activities and forming SOD and CAT isoforms in S. salsa seedlings.
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