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Zhichao Yang,Shuqiang Liu,Jingjing Li,Gaihong Wu,Man Zhang,Fu Li,Lu Jia,Yujing Zhang,Huimin Li,Xia Liu,Jingjing Zhao,Huiqin Zhang,Shiyu Li 한국섬유공학회 2023 Fibers and polymers Vol.24 No.12
Polylactic acid (PLA) surgical suture is considered to be one of the most ideal materials for tissue closure due to its rich raw materials and excellent biological properties. However, surgical sutures face great challenges due to problems such as wound infection and tissue reaction in practical applications. In order to improve the clinical applicability of surgical sutures, we constructed a new drug-loading system for core-spun surgical sutures. The shell was composed of nanofibrous membranes composed of polyglycolic acid (PGA) and polycaprolactone (PCL) and ciprofloxacin (CIP) antibacterial drugs, and the core layer adopts PLA filament. By adjusting the composition ratio of PGA and PCL in the shell, a new mode of regulating the release rate and release cycle of the suture was constructed. According to different wound healing time, different drug release cycles of surgical suture were selected. In the study, the structure of the core-spun yarn can be clearly observed by scanning electron microscope, the higher the shell PGA content and drug loading, the faster the drug release rate. When the carrier ratio PGA/PCL was 80/20 and the drug loading was 3%, the drug release rate was the fastest and the drug release was high; finally, antibacterial experiments showed that the suture had excellent antibacterial effect and could effectively kill Staphylococcus aureus and Escherichia coli. The successful preparation of core-spun yarn surgical suture provides a new idea for the study of new antibacterial surgical suture.
A Feature Selection Algorithm based on Hoeffding Inequality and Mutual Information
Chunyong Yin,Lu Feng,Luyu Ma,Zhichao Yin,Jin Wang 보안공학연구지원센터 2015 International Journal of Signal Processing, Image Vol.8 No.11
With the rapid development of the Internet, the application of data mining in the Internet is becoming more and more extensive. However, the data source’s complex feature redundancy leads that data mining process becomes very inefficient and complex. So feature selection research is essential to make data mining more efficient and simple. In this paper, we propose a new way to measure the correlation degree of internal features of dataset which is a mutation of mutual information. Additionally we also introduce Hoeffding inequality as constraint of constructing algorithm. During the experiments, we use C4.5 classification algorithm as test algorithm and compare HSF with BIF(feature selection algorithm based on mutual information). Experiments results show that HSF performances better than BIF[1] in TP and FP rate, what’s more the feature subset obtained by HSF can significantly improve the TP, FP and memory usage of C4.5 classification algorithm.
A Feature Selection Algorithm towards Efficient Intrusion Detection
Chunyong Yin,Luyu Ma,Lu Feng,Zhichao Yin,Jin Wang 보안공학연구지원센터 2015 International Journal of Multimedia and Ubiquitous Vol.10 No.11
Feature selection algorithm plays a crucial role in intrusion detection, data mining and pattern recognition. According to some evaluation criteria, it gets optimal feature subset by deleting unrelated and redundant features of the original data set. Aiming at solving the problems about the low accuracy, the high false positive rate and the long detection time of the existing feature selection algorithm. In this paper, we come up with a feature selection algorithm towards efficient intrusion detection, this algorithm combines the correlation algorithm and redundancy algorithm to chooses the optimal feature subset. Experimental results show that the algorithm shows almost and even better than the traditional feature selection algorithm on the different classifiers.
Fabrication and Magnetic Properties of A New Fe-based Amorphous Compound Powder Cores
Wang Xiangyue,Guo Feng,Lu Caowei,Lu Zhichao,Li Deren,Zhou Shaoxiong 한국자기학회 2011 Journal of Magnetics Vol.16 No.3
A new Fe-based amorphous compound powder was prepared from Fe-Si-B amorphous powder by crushing amorphous ribbons as the first magnetic component and Fe-Cr-Mo metallic glassy powder by water atomization as the second magnetic component. Subsequently by adding organic and inorganic binders to the compound powder and cold pressing, the new Fe-based amorphous compound powder cores were fabricated. This new Fe-based amorphous compound powder cores combine the superior DC-Bias properties and the excellent core loss. The core loss of 500 ㎾/㎥ at Bm = 0.1T and f = 100 ㎑ was obtained When the mass ratio of FeSiB/FeCrMo equals 3:2, and meanwhile the DC-bias properties of the new Fe-based amorphous compound powder cores just decreased by 10% compared with that of the FeSiB powder cores. In addition, with the increasing of the content of the FeCrMo metallic glassy powder, the core loss tends to decrease.