Analysis and Design of Surgical Instrument Localization Algorithm

With the help of surgical navigation system,doctors can operate on patients more intuitively and accurately.The positioning accuracy and real-time performance of surgical instruments are very important to the whole system.In this paper,we analyze and design the detection algorithm of surgical instrument location mark,and estimate the posture of surgical instrument.In addition,we optimized the pose by remapping.Finally,the algorithm of location mark detection proposed in this paper and the posture analysis data of surgical instruments are verified and analyzed through experiments.The final result shows a high accuracy.

An Optimized Chinese Filtering Model Using Value Scale Extended Text Vector

With the development of Internet technology,the explosive growth of Internet information presentation has led to difficulty in filtering effective information.Finding a model with high accuracy for text classification has become a critical problem to be solved by text filtering,especially for Chinese texts.This paper selected the manually calibrated Douban movie website comment data for research.First,a text filtering model based on the BP neural network has been built;Second,based on the Term Frequency-Inverse Document Frequency(TF-IDF)vector space model and the doc2vec method,the text word frequency vector and the text semantic vector were obtained respectively,and the text word frequency vector was linearly reduced by the Principal Component Analysis(PCA)method.Third,the text word frequency vector after dimensionality reduction and the text semantic vector were combined,add the text value degree,and the text synthesis vector was constructed.Experiments show that the model combined with text word frequency vector degree after dimensionality reduction,text semantic vector,and text value has reached the highest accuracy of 84.67%.

The enantioselective enhancing effect and mechanistic insights of chiral enhancers in transdermal drug delivery

Overlook of chiral consideration in transdermal drug delivery increases administrated dose and risk of side effects,decreasing therapeutical effects.To improve the transdermal delivery efficiency of eutomer,this work focused on investigating the law and mechanism of enantioselective enhancing effects of chiral permeation enhancers on drug enantiomers.Chiral nonsteroidal anti-inflammatory drugs and terpene permeation enhancers were selected as model drug and enhancers.The results indicated that the L-isomer of permeation enhancers increased the skin absorption of S-enantiomer of drug and D-isomer improve the permeation of R-enantiomer,in which the enhancement effect(ER)of Lmenthol on S-enantiomer(ER=3.23)was higher than that on R-enantiomer(ER=1.49).According to the pharmacokinetics results,L-menthol tended to enhance the permeation of S-enantiomer better than R-enantiomer(2.56 fold),and showed excellent in vitro/in vivo correlations.The mechanism study showed that L-isomer of permeation enhancers improved the permeation of S-enantiomer by increasing the retention,but the D-isomer by improving partition for better permeation.Enantioselective mechanism indicated that the weaker chiral H-bond interaction between drug-chiral enhancers was caused by the enantiomeric conformation.Additionally,stronger chiral enhancers-skin interaction between L-isomer and S-conformation of ceramide produced better enhancing effects.In conclusion,enantioselective interaction of chiral drug-chiral enhancers and chiral enhancers-chiral skin played a critical role in transdermal drug delivery,rational utilization of which contributed to improving the uptake of eutomer and inhibiting distomers to decrease a half of dose and side effects,increasing transdermal therapeutical efficiency.

Improved Blending Attention Mechanism in Visual Question Answering

Visual question answering(VQA)has attracted more and more attention in computer vision and natural language processing.Scholars are committed to studying how to better integrate image features and text features to achieve better results in VQA tasks.Analysis of all features may cause information redundancy and heavy computational burden.Attention mechanism is a wise way to solve this problem.However,using single attention mechanism may cause incomplete concern of features.This paper improves the attention mechanism method and proposes a hybrid attention mechanism that combines the spatial attention mechanism method and the channel attention mechanism method.In the case that the attention mechanism will cause the loss of the original features,a small portion of image features were added as compensation.For the attention mechanism of text features,a selfattention mechanism was introduced,and the internal structural features of sentences were strengthened to improve the overall model.The results show that attention mechanism and feature compensation add 6.1%accuracy to multimodal low-rank bilinear pooling network.

Soft Tissue Feature Tracking Based on Deep Matching Network

Research in the field ofmedical image is an important part of themedical robot to operate human organs.Amedical robot is the intersection ofmulti-disciplinary research fields,in whichmedical image is an important direction and has achieved fruitful results.In this paper,amethodof soft tissue surface feature tracking basedonadepthmatching network is proposed.This method is described based on the triangular matching algorithm.First,we construct a self-made sample set for training the depth matching network from the first N frames of speckle matching data obtained by the triangle matching algorithm.The depth matching network is pre-trained on the ORL face data set and then trained on the self-made training set.After the training,the speckle matching is carried out in the subsequent frames to obtain the speckle matching matrix between the subsequent frames and the first frame.From this matrix,the inter-frame feature matching results can be obtained.In this way,the inter-frame speckle tracking is completed.On this basis,the results of this method are compared with the matching results based on the convolutional neural network.The experimental results show that the proposed method has higher matching accuracy.In particular,the accuracy of the MNIST handwritten data set has reached more than 90%.

Spatial and temporal temperature variations in Xinjiang,China during 1961-2008

This study examines spatial and temporal changes in 16 extreme temperature indices at 37 weather stations in Xinjiang and their associations with changes in climate means during 1961-2008. Linear regression analyses reveal that significant increas- ing trends in temperature were observed over Xinjiang, with the rate of 0.13 ~C/decade, 0.24 ~C/decade, and 0.52 ~C/decade for annual mean temperature, annual maximum, and minimum temperature, respectively. Annual fi＇equency of cool nights （days） has decreased by -2.45 days/decade （-0.86 days/decade）, whereas the frequency of warm nights （days） has increased by 4.85 days/decade （1.62 days/decade）. Seasonally, the frequencies of summer warm nights and days are changing more rap- idly than the corresponding frequencies for cool nights and days. However, normalization of the extreme and mean series shows that the rate of changes in extreme temperature events are generally less than those of mean temperatures, except for winter cold nights which are changing as rapidly as the winter mean minimum temperatures. These results indicate that there have been seasonally and diurnally asymmetric changes in extreme temperature events relative to recent increases in tempera- ture means in Xinjiang.

A Blockchain-Based Authentication Protocol for WLAN Mesh Security Access

In order to deploy a secure WLAN mesh network,authentication of both users and APs is needed,and a secure authentication mechanism should be employed.However,some additional configurations of trusted third party agencies are still needed on-site to deploy a secure authentication system.This paper proposes a new block chain-based authentication protocol for WLAN mesh security access,to reduce the deployment costs and resolve the issues of requiring key delivery and central server during IEEE 802.11X authentication.This method takes the user’s authentication request as a transaction,considers all the authentication records in the mesh network as the public ledger and realizes the effective monitoring of the malicious attack.Finally,this paper analyzes the security of the protocol in detail,and proves that the new method can solve the dependence of the authentication node on PKI and CA.

Experimental investigation of inflow-outflow asymmetry in induced-charge electro-osmosis

Induced-charge electro-osmosis(ICEO)is a research hotspot in bioengineering and analytical chemistry.Inflow-outflow asymmetry of ICEO was reported in the existing literatures,but systematic study on this phenomenon is insufficient.In this experimental study,we found that in strong electric fields,not only the velocity magnitude but also the vortex positions of ICEO are asymmetrical along the inflow and outflow directions because of the pronounced non-uniform surface electrokinetic transport.On the inflow and outflow directions,the amplitudes of velocities are unequal,ICEO maximum velocity positions change depending on the electric field intensity and sodium chloride(NaCl)concentration.Additionally,the distances between vortex centers are different.At NaCl solution concentration of 0.001 mol⋅L^(-1),the outflow velocity almost vanishes.The asymmetry rises with the increasing electric field intensity.The new discoveries can direct the application of microscale devices.

Aerosol optical absorption by dust and black carbon in Taklimakan Desert,during no-dust and dust-storm conditions

Aerosol absorption coefficient σap involves the additive contribution of both black carbon aerosol （BC） and dust aerosol. The linear statistical regression analysis approach introduced by Fialho et al. （2005） is used to estimate the absorption exponents of BC and dust aerosol absorption coefficients, and further to separate the contributions of these two types of aerosols from the total light absorption coefficient measured in the hinterland of Taklimakan Desert in the spring of 2006. Absorption coefficients are measured by means of a 7-wavelength Aethalometer from 1 March to 31 May and from 1 November to 28 December, 2006. The absorption exponent of BC absorption coefficient α is estimated as （-0.95 ± 0.002） under background weather （supposing the observed absorption coefficient is due only to BC）; the estimated absorption exponent of dust aerosol absorption coefficient/5 during the 6 dust storm periods （strong dust storm） is （-2.55 ± 0.009）. Decoupling analysis of the measured light absorption coefficients demonstrates that, on average, the light absorptions caused by dust aerosol and BC make up about 50.5% and 49.5% respectively of the total light absorption at 520 nm; during dust weather process periods （dust storm, floating dust, blowing dust）, the contribution of dust aerosol to absorption extinction is 60.6% on average; in the hin- terland of desert in spring, dust aerosol is also the major contributor to the total aerosol light absorption, more than that of black carbon aerosol.