Adaptive admittance control for dual-arm surgical robot using radial basis function neural network / 中国医学物理学杂志

Aiming at the problem of large force tracking errors caused by environmental stiffness changes when dual-arm robot is assisting in opening soft tissues in head and neck surgery,an adaptive admittance control strategy based on radial basis function(RBF)neural network is proposed for reducing force tracking error and improving system response speed.By using RBF neural network to adjust admittance parameters online during surgery,the adaptability of the robotic arm to different contact conditions and operation requirements is improved,thereby realizing fast and accurate force tracking.The simulation experiment introduces the adaptive admittance control strategy based on RBF neural network into the dual-arm force synchronous admittance control system and compares it with the traditional fixed-parameter admittance control to prove its contact force control effect under the condition of variable contact environment parameters.The results demonstrate that the adaptive admittance control strategy based on RBF neural network can effectively improve the force tracking accuracy,response speed and anti-interference capability of dual-arm surgical robot.

Establishment of Feedforward Control Model for Dry Granulation of Polysaccharide Components Based on Quality by Design / 中国实验方剂学杂志

ObjectiveA feedforward control model for dry granulation of polysaccharide components was established to guide the adjustment and optimization of critical process parameters （CPPs） in the design space， so as to reduce the impact of fluctuations in raw materials properties on the quality of medicines. MethodTaking Astragali Radix extract powder as the model drug， the design space of dry granulation CPPs was determined by Box-Behnken design. Astragali Radix mixed powder with different powder properties were prepared by mixture design， the variance inflation factor （VIF） was used to diagnose the multicollinearity of the powder properties， and principal component analysis （PCA） was used to extract the characteristic data of the model. Radial basis function neural network （RBFNN） was used to establish a feedforward control model for reflecting the relationship between the powder properties of polysaccharide components， dry granulation CPPs and one-time molding rate. ResultThe design space for dry granulation CPPs of polysaccharide components was 16-35 Hz for feeding speed， 10-23 Hz for roller speed， and 10-46 kg·cm-2 for roller pressure. The established RBFNN feedforward control model had a good predictive effect on the one-time molding rate of dry granulation of polysaccharide components， which could be used to guide the adjustment and optimization of CPPs in the design space， the relative error was 0.38%-6.73%， and the average relative error was 3.42%. ConclusionThe established feedforward control model can well reflect the relationship between the powder properties of the polysaccharide components， the dry granulation CPPs and the one-time molding rate of the granules， which can be used to guide the adjustment and optimization of CPPs in the design space， reduce the impact of material property fluctuation on product quality， and provide ideas for promoting the quality of traditional Chinese medicine from passive control to active control.

Rapid determination of nine components in the first extraction process of Xingnaojing injection by using ultraviolet spectroscopy / 中国中药杂志

In this study, an analytical method based on ultraviolet spectroscopy was established for the rapid determination of nine components including isophorone, 4-methylene-isophorone, curcumenone, curcumenol, curdione, curzerenone, furanodienone, curcumol and germacrone in the first extraction process of Xingnaojing injection. 166 distillate samples of Gardeniae Fructus and Radix Curcumae were collected in the first extraction process of Xingnaojing injection. The ultraviolet spectra of these samples were collected, and the contents of the nine components in these samples were determined by high performance liquid chromatography. Least squares support vector machine and radial basis function artificial neural network were used to establish the multivariate calibration models between the ultraviolet spectra and the contents of the nine components. The results showed that the established ultraviolet spectrum analysis method can determine the contents of the nine components in the distillates accurately, with root mean square error of prediction of 0.068, 0.147, 0.215, 0.319, 1.01, 1.27, 0.764, 0.147, 0.610 mg•L⁻¹, respectively. This proposed method is a rapid, simple and low-cost tool for the monitoring and endpoint determination of the extraction process of Xingnaojing injection to reduce quality defects and variations.

Application of RBF and RSM in Optimizing the Processing Conditions of Manchurian Dutchmanspipe Stem with Alkali / 医药导报

Objective To optimize the processing conditions of Manchuiran Dutchmanspipe Stem with alkali. Methods The combination of radial basis function ( RBF) and response surface methodology ( RSM) was used to investigate the influence of NaHCO3 , concentration, duration and cycles of processing on the content of aristolochic acid. Results The optimal process was achieved when Manchuiran Dutchmanspipe Stem was soaked for 3 cycles in 0. 05 mol·L-1 NaHCO3 solution, for 24 hours in each cycle. The removal rate of total aristolochic acid approached to 83. 74%. Conclusion The combination of RBF and RSM provided a new method and good guidance for further toxicity attenuation for Manchuiran Dutchmanspipe Stem.

Aproximação fisionômica pericial através de função de base radial hermitiana / Forensic facial approximation through hermitian radial basis functions

A aproximação fisionômica é o método que busca, a partir do crânio, simular a fotografia de um indivíduo quando em vida. Deve ser empregada como último recurso, na busca de desaparecidos, quando não houver possibilidade de aplicação de um método válido de identificação. O objetivo deste estudo foi obter a aproximação fisionômica, a partir de um crânio seco e de tomografia computadorizada multislice de indivíduos vivos, através da função de base radial hermitiana (FBRH). Constituiu-se também em avaliar o resultado da mesma quanto ao reconhecimento. Na primeira etapa do estudo, foi utilizada a imagem escaneada de um crânio seco, de origem desconhecida, com o intuito de avaliar se a quantidade de pontos obtidos seria suficiente para aplicação da FBRH e consequente reconstrução da superfície facial. Na segunda fase, foram utilizadas três tomografias de indivíduos vivos, para análise da semelhança alcançada entre a face escaneada e as aproximações faciais. Nesta etapa, foi aplicada uma associação de diferentes metodologias já publicadas, para reconstrução de uma mesma região da face, a partir de um mesmo crânio. Na última etapa, foram simuladas situações de reconhecimento com familiares e amigos dos indivíduos doadores das tomografias. Observou-se que a metodologia de FBRH pode ser empregada em aproximação fisionômica. Houve reconhecimento positivo nos três sujeitos estudados, sendo que, em dois deles, os resultados foram ainda mais significativos. Desta forma, conclui-se que a metodologia é rápida, objetiva e proporciona o reconhecimento. Esta permite a criação de múltiplas versões de aproximações fisionômicas a partir do mesmo crânio, o que amplia as possibilidades de reconhecimento. Observou-se ainda que a técnica não exige habilidade artística do profissional.

Facial approximation works by building the visual face up from the skull. This method should be performed as last resort, to carry out for missing persons, when there is no other primary identification method avaliable. The purpose of this study was to introduce a new computerized method with hermite radial basis function (HRBF) for facial approximation using dry skull and computed tomography (CT). The same was also evaluated as a result of the recognition. Firstly, a scan of a dry unidentified skull image was used in order to assess if the amount of points would be sufficient for HRBF methodology and subsequent reconstruction of the facial surface. In second, three CT scans of living individuals were used to evaluate the similarity achieved between the real face scanned and facial approximations. An association of different facial structures reconstruction techniques already published for the same region of the face was applied for the same skull. Moreover, some situations from developed facial approximations were simulated, as recognition by a relative or parent, on a face pool-test. Results from the study showed that the purposed methodology can be used for facial approximation. At the three cases a correct approximation identification as one of a few possible matches to the missing person happened. In two of them, the results were consistently better at identifying the correct approximation. In conclusion, the proposed methodology is fast, objective and reaches visual identification. It is possible to perform multiple versions of the same skull, changing the selected data into the system, which maximizes the chances of establishing recognition of the target face. It was also observed that the technique does not need artistic interpretation.

Aproximação fisionômica pericial através de função de base radial hermitiana / Forensic facial approximation through hermitian radial basis functions

A aproximação fisionômica é o método que busca, a partir do crânio, simular a fotografia de um indivíduo quando em vida. Deve ser empregada como último recurso, na busca de desaparecidos, quando não houver possibilidade de aplicação de um método válido de identificação. O objetivo deste estudo foi obter a aproximação fisionômica, a partir de um crânio seco e de tomografia computadorizada multislice de indivíduos vivos, através da função de base radial hermitiana (FBRH). Constituiu-se também em avaliar o resultado da mesma quanto ao reconhecimento. Na primeira etapa do estudo, foi utilizada a imagem escaneada de um crânio seco, de origem desconhecida, com o intuito de avaliar se a quantidade de pontos obtidos seria suficiente para aplicação da FBRH e consequente reconstrução da superfície facial. Na segunda fase, foram utilizadas três tomografias de indivíduos vivos, para análise da semelhança alcançada entre a face escaneada e as aproximações faciais. Nesta etapa, foi aplicada uma associação de diferentes metodologias já publicadas, para reconstrução de uma mesma região da face, a partir de um mesmo crânio. Na última etapa, foram simuladas situações de reconhecimento com familiares e amigos dos indivíduos doadores das tomografias. Observou-se que a metodologia de FBRH pode ser empregada em aproximação fisionômica. Houve reconhecimento positivo nos três sujeitos estudados, sendo que, em dois deles, os resultados foram ainda mais significativos. Desta forma, conclui-se que a metodologia é rápida, objetiva e proporciona o reconhecimento. Esta permite a criação de múltiplas versões de aproximações fisionômicas a partir do mesmo crânio, o que amplia as possibilidades de reconhecimento. Observou-se ainda que a técnica não exige habilidade artística do profissional...

Facial approximation works by building the visual face up from the skull. This method should be performed as last resort, to carry out for missing persons, when there is no other primary identification method avaliable. The purpose of this study was to introduce a new computerized method with hermite radial basis function (HRBF) for facial approximation using dry skull and computed tomography (CT). The same was also evaluated as a result of the recognition. Firstly, a scan of a dry unidentified skull image was used in order to assess if the amount of points would be sufficient for HRBF methodology and subsequent reconstruction of the facial surface. In second, three CT scans of living individuals were used to evaluate the similarity achieved between the real face scanned and facial approximations. An association of different facial structures reconstruction techniques already published for the same region of the face was applied for the same skull. Moreover, some situations from developed facial approximations were simulated, as recognition by a relative or parent, on a face pool-test. Results from the study showed that the purposed methodology can be used for facial approximation. At the three cases a correct approximation identification as one of a few possible matches to the missing person happened. In two of them, the results were consistently better at identifying the correct approximation. In conclusion, the proposed methodology is fast, objective and reaches visual identification. It is possible to perform multiple versions of the same skull, changing the selected data into the system, which maximizes the chances of establishing recognition of the target face. It was also observed that the technique does not need artistic interpretation...

Rapid Identification of Traditional Chinese Medicine Using Electronic Nose Based on RBF-RF Cascade Classifier / 世界科学技术-中医药现代化

This study was aimed to apply the electronic nose (E-nose) in the research of traditional Chinese medicine (TCM). The discussion was made on difficulties of using E-nose. The solution plan was proposed and the discrimination model was established. It provided a simple, rapid and effective analysi method in the identification of TCM. It also provided new ideas for the research and application of gas sensor arrays. E-nose was used in the ex-traction of TCM scent characteristics. Based on ion mobility spectrometry of MOS sensor, the fingerprint of TCM scent was established. The maximum response value of the sensor was used as analysis index. According to the diffi-culties of identification, two solution plans were proposed. Firstly, different detectors were employed to complete the classification. Secondly, radial basis function (RBF) and random forests (RF) were combined and then a cascade classifier was constructed in order to achieve the maximum of information obtained in conditions where the number of measurements, metal oxide semiconductor sensors in E-nose was limited. The results showed that both plans were accurate and practical with relatively high upper correct judge rate and better cross-validation (The highest upper correct judge rates were 95% and 100%, 96% and 80%, respectively). It was concluded that this study firstly ap-plied cascade classifier in the establishment of TCM identification by E-nose. With limited amount of sensors, the maximum information was received through data mining. Using E-nose in the identification of TCM was rapid and accurate. The established pattern recognition method was maneuverable with accurate identification rate and stability compared to conventional sensory identification method. It provided a simple and rapid analysis method for the iden-tification of TCM.

A metabonomic approach to the early prognostic evaluation of sepsis using HPLC/MS in rat model / 中华急诊医学杂志

Objective To innovate an early, rapid and efficient approach to the pmgnestic evaluation of sep-sis in order to lower the mortality. Method Forty-five septic rats, induced by cecal ligation and puncture, were divided into surviving group (n=23) and non-survival group (n=22) on six days after onset of sepsis. Serum samples were taken from septic and sham-operated rats (n=25) at 12 hours after surgery. HPLC/MS assays were performed to acquire the serum metabolic profiles, and radial basis function neural network (RBFNN) was em-ployed to build predictive model for prognostic evaluation of sepsis. Results The principal component analysis al-lows differentiating the rots of survive,non-survive and sham-operated from one another in respect of the pathologic characteristics. Six metabolites, linolenic acid, linoleic acid, oleic acid, stearic acid, docosahexaenoic acid and do-cosapentaenoic acid, related to the outcomes of septic rats were then structurally identified. A RBFNN model for outcome predication was built based upon the metabolic profile data from rat sera with the sensitivity of (96.1 ±3.6)% (n=10) and specificity of (91.0±4.3)% (n=10). Condusions HPLC/MS-based metabonomic approach combined with pattern recognition permits accurate outcome prediction of septic rats in the early stage. The proposed approach has advantages of rapid, low-cost and efficiency, and is isph-ing to be applied in clinical prognostic evaluation of septic patients.

Medical Image Segmentation Method Based on Texture Character and GRBF Network / 医疗卫生装备

Objective To get a better medical image segmentation result by studing a new image segmentation method. Methods Medical images were segmented using image segmentation method based on texture character and generalized radial basis function neural networks. The texture character parameters were obtained according to gray level co-occurrence matrix. The parameters were input to the generalized radial basis function neural networks to train the network. Results Comparatively, perfect binary images were obtained by using this new image segmentation method. Conclusion The emulational results show that the method is an effective medical image segmentation method.