Bioautomation

Volume 21, Issue 4
Special Issue on Advanced Bioinformatics and Bionics Algorithms Guest Editor: Liu Qi, Huazhong University of Science and Technology
Modeling and Development of Medical Information System Based on Support Vector Machine in Web Network	283-292
Chuanfu Hu, Caichang Ding, Lu Dai [ +/- abstract ][ full text ]
This paper aims at improving and utilizing the ontology information in ontology design of FOAF and vCard in real time, and the application of open relational data technology, SPARQL query information results and sending RDF/JSON data format. In addition, improve the effectiveness and efficiency of patient information extraction from the medical information website. This article includes two web search engines that are used to inform patients about medical care information. The experiment uses Drupal as the main software tool, and the Drupal RDF extension module provides some meaningful mapping. In the evaluation part, the structure of the experimental test platform is established and the system function test is carried out. The evaluation results include consumers or patients retrieving the latest doctor information and comparing search capabilities and techniques, between our system and existing systems.
Accuracy and Applicability Analysis of Anatomical Landmarks Point Registration Image Guided Surgery of Neurosurgery	293-304
Zhenzhen Huang, Xiaoqing Liu, Xuelin Liu [ +/- abstract ][ full text ]
Image guided neurosurgery system is currently an interesting and active topic for research that covers a wide ranges of knowledge related to medical sciences, image and signal processing and computer programming. Therefore, we are providing an analysis for the accuracy when using different sets of Anatomical Landmarks (ALs) as well as the applicability of the corresponding surgical fields. In addition, one of the significant factors that influence the registration accuracy at the target point is the distribution of the fiducially points. The optimal distribution may be difficult to achieve either due to the limited number of distinct anatomical features on head surface or even due to the poor planning of skin adhesive markers. The simulation experiment of the accuracy analysis showed that, by incorporating a Fiducially Registration Error (FRE) of 3.5 mm measured in the clinical setting, the expected Target Registration Error (TRE) in the whole skull was less than 2.5 mm, and the expected TRE in the whole brain was less than 1.75 mm when using the configuration with all the nine ALs. Results showed an improvement in registration quality in the targeted area in all cases by this kind of correction.
Intelligent Fusion Method Based on BP Neural Network for Robot Suit Pressure Sensing Array Data	305-316
Bing Guo, Xinli Deng [ +/- abstract ][ full text ]
In order to eliminate the crosstalk influence existed among temperature, voltage fluctuation and sensor signal of robot tactile sensor array unit, the paper presented a sort of information fusion method in large scale sensor array based on BP neural network. By means of learning training with weight for neural network, the method can effectively eliminate the crosstalk influence for output characteristics of pressure sensing array sensor among non-target parameters and large scale sensor signals such as the environment temperature, voltage disturbance and so on, and thereby it improves the stability and reliability of robot tactile sensing suit system. Laboratory tests demonstrated that the error of the suit pressure sensor array data is less than 5%. The experimental results show that the intelligent fusion method presented in this paper can be accepted in engineering application, and the method is be propitious to improve intelligent judgment and information utilization ratio of robot system.
Quantitative Simulation of Damage Roots on Inoculated Alfalfa by Arbuscular Mycorrhiza Fungi	317-324
Ying Liu, Hui Yue [ +/- abstract ][ full text ]
Underground mining would cause ground subsidence damage and large amounts of cracks, which would result a loss of surface moisture and nutrient and intensifying drought. There are a few reports about damage to plant roots caused by coal mining. The irregular distribution of plant roots in soil and the different forces generated in process of surface subsidence are difficult to study comprehensively. The technologies to repair damaged plant roots have not been completely perfected yet. Based on quantitative simulation of alfalfa root cut-repair experiment, this paper discusses the influences of inoculated Arbuscular Mycorrhiza Fungi on alfalfa root and the mitigation effects of an inoculation on the growth of alfalfa. Root injured alfalfa were investigated by soil pot experiments. The result indicated that at the same cut degree, the growth situation of inoculated alfalfa is better than the contrast. Compared with the Olsen-P content, at cut level of 0 and 1/3, the sand of inoculated alfalfa has less Olsen-P than contrast, at cut degree of 1/2 and 2/3, the sand of inoculated alfalfa has more Olsen-P than contrast, at degree of 3/4, the sand of inoculated alfalfa has less Olsen-P than contrast, the change trend of Olsen-P content is concerned with the relative strength size of absorb Olsen-P by alfalfa root and dissolve Olsen-P by root exudates and hyphae interstate.
The Research on Automatic Test System of Human-death-time Based on Virtual Instrument Technology	325-330
Sheng Li [ +/- abstract ][ full text ]
The automatic test system (ATS) is widely used in the field of industrial production, scientific research and national defense construction. This paper introduces an ATS for time estimation of human death, in which the host computer runs the detecting software to do data analysis and drive the hardware taking acquisition, and makes the use of forensic temperature estimating algorithm to calculate the death time. The temperature sensing module adopts rope shape design which is convenient for requirements of detecting scenarios, and the communication between host computer and temperature sensing module is realized through 1-Wire bus protocol. The system can estimate the body's time of death quickly and conveniently which plays a key role in the forensic laboratory and criminal scene of the death time measurement, and the temperature sensing module has the advantages of small size for convenient carrying.
Study on Prediction of Grain Yield Based on Grey Theory and Fuzzy Neutral Network Model	331-338
Hui-yun Zhang [ +/- abstract ][ full text ]
In order to improve the prediction precision of grain yield, the grey system theory and the fuzzy neutral network are combined to construct the combined prediction model, which is applied in predicting the grain yield. Firstly, the basic theory of the grey system theory is analyzed. Secondly, the mathematical model of fuzzy neutral network is studied, and the corresponding algorithm procedure is designed. Finally, the grain yields in China are used as the researching object, and the corresponding prediction analysis is carried out, and the prediction results of grain yield are agreed with real values, results show that the combined prediction model can be applied in predicting the grain yield effectively.
Research on the Prediction of Carbon Emission Based on the Chaos Theory and Neural Network	339-348
Yingshi Liu, Yinhua Tian, Min Chen [ +/- abstract ][ full text ]
In this paper, carbon emissions and the related problems are studied based on carbon emission time series data and the chaos theory, in order to make clear the relationship among the data, and we reconstruct the time series by phase space reconstruction. Finally, the predicting model of the carbon emission is established with BP neural network. The simulation results show that the hybrid of chaos theory and BP neural network can be used to fit and predict the carbon emissions time series without considering other factors, which is easier and more accurate than other predicting method.
The Use of Adaptive Genetic Algorithm for Detecting Kiwifruit’s Variant Subculture Seedling	349-356
Jun Zeng, Yong Li [ +/- abstract ][ full text ]
In order to reduce the possible economic loss brought by variant seedlings in tissue culture, we propose a pattern recognition approach using fitness to dynamically monitor subculture seedlings of kiwifruit based on adaptive Genetic Algorithm. By coding, selection, mutation and crossover the selected primer pairs of the subculture seedlings, we simulate the process of optimizing the kiwifruit’s genomic DNA polymorphism. The result shows that fitness values of kiwifruit’s subculture seedlings can better maintain their genetic stability from the first to the ninth generation in the simulation. But from the tenth generation, the rapid change of the fitness values of subculture seedlings happen. It is in accord with the experimentation, which uses optimized AFLP system for analyzing genetic diversity of 75 samples of seventh to eleventh 5 generations of kiwifruit subculture seedlings.