The Clinical E-Science Framework (CLEF) project was used to extract important information from medical texts by building a system for the purpose of clinical research, evidence-based healthcare and genotype-meets-phenotype informatics. The system is
divided into two parts, one part concerns with the identification of relationships between clinically important entities in the text. The full parses and domain-specific grammars had been used to apply many approaches to extract the relationship. In the second part of the system, statistical machine learning (ML) approaches are applied to extract relationship. A corpus of oncology narratives that hand annotated with clinical relationships can be used to train and test a system that has been designed and implemented by supervised machine learning (ML) approaches. Many features can be extracted from these texts that are used to build a model by the classifier. Multiple supervised machine learning algorithms can be applied for relationship extraction. Effects of adding the features, changing the size of the corpus, and changing the type of the algorithm on relationship extraction are examined. Keywords: Text mining; information extraction; NLP; entities; and relations.
Radio Frequency Identification (RFID) technology one of the most promising technologies in the field of ubiquitous computing. Indeed, RFID technology may well replace barcode technology. Although it offers many advantages over other identification sy
stems, there are also associated security risks that are not easy to be addressed. When designing a real lightweight authentication protocol for low cost RFID tags, a number of challenges arise due to the extremely limited computational, storage and communication abilities of Low-cost RFID tags. This paper proposes a real mutual authentication protocol for low cost RFID tags. The proposed protocol prevents passive attacks as active attacks are discounted when designing a protocol to meet the requirements of low cost RFID tags. However the implementation of the protocol meets the limited abilities of low cost RFID tags.
Almost all existing RFID authentication schemes (tag/reader) are vulnerable to relay attacks, because of their inability to estimate the distance to the tag. These attacks are very serious since it can be mounted without the notice of neither the rea
der nor the tag and cannot be prevented by cryptographic protocols that operate at the application layer. Distance bounding protocols represent a promising way to thwart relay attacks, by measuring the round trip time of short authenticated messages. All the existing distance bounding protocols use random number generator and hash functions at the tag side which make them inapplicable at low cost RFID tags. This paper proposes a lightweight distance bound protocol for low cost RFID tags. The proposed protocol based on modified version of Gossamer mutual authentication protocol. The implementation of the proposed protocol meets the limited abilities of low-cost RFID tags.
