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Xiaoyan Zhao,Xiaowei Zhang,Hongkai Liu,Haitao Zhu,Yunping Zhu 한국식품과학회 2019 Food Science and Biotechnology Vol.28 No.6
The release of bioactive pigments could bepotentially improved by enzyme degradation of plant cellwall polysaccharides. In this study, the objective was toevaluate enzyme type (cellulase and pectinase), pH values,hydrolysis temperature and time on the release of astaxanthinfrom Haematococcus pluvialis (H. pluvialis). Theresults showed that pre-treated H. pluvialis with enzymescould improve the separation yield of astaxanthin. Pectinaserelease rate of astaxanthin from H. pluvialis wassignificantly higher than cellulase (p\0.05), and enzymehydrolysis time was also shorter. The stability study ofastaxanthin oleoresin and microcapsule during storage atdifferent temperature, oxygen and illumination was foundthat the degradation rate of astaxanthin rose with increasingtemperature and illumination time, and the retention inoxygen environment decreased. The stability of astaxanthinmicrocapsules was better than astaxanthin oleoresin.
A Method for Mapping Sensor Data to SSN Ontology
Xiaoming Zhang,Yunping Zhao,Wanming Liu 보안공학연구지원센터 2015 International Journal of u- and e- Service, Scienc Vol.8 No.9
Along with the continuous development of the sensor network technology, sensors from all over the world are constantly producing sensor data. However, the sensor data from different source is hard to work together for lack of semantic. Fortunately, SSN ontology provide a way to represent sensor data semantically, but how to transform sensor data into the instance of SSN ontology conveniently is still an issue to be considered. This paper proposed a solution to map sensor data to SSN ontology automatically based on a predefined XML-based document. We design a mapping language SASML (Sensors Annotation and Semantic Mapping Language) which provide a schema to annotate sensors and sources so as to generate a XML document for mapping. Then, an algorithm (namely SDRM) is designed to automatically transform sensor data, which described by SASML, to RDF conforming to SSN ontology, according to the mapping document and the element correspondences between the SASML and SSN ontology. Further, a case study about sensor data from greenhouse is presented to illustrate our method, and a prototype is also developed to demonstrate the feasibility and effectiveness.