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In heterogeneous service environment, E-learning, especially for learning content service, poses many opportunities and challengers of which the focus is that the service is even not able to be provided if the content can not be consumed in the service environment, termed service context also, which consists of the current state of networks, terminals, users, natural circumstance etc. To face the music, ISO/IEC proposes new standard, MPEG-21, in which content adaptation technology is employed to solve the problem of mismatch between content and service context. In content adaptation technology, service context model is a key point because it is the premise of other operations. Though service context modeling has been studied extensively recently and some models are created even standardized, there are some problems left still. One is that most of models are lack of ability of inference or the ability is weak because they are based on extensive makeup language (XML) or resource description framework (RDF). The other is that they are not capable of describing rules. However, it is necessary for service context model to reason and rule coding because those abilities will be helpful for datasize deceasing, context mining and subsequent processing, e.g. adaptation decision-taking, In this paper, we propose a novel model in the basis of ontology, whose property is to reason and describe rules. By ontology modeling software, protege, the model is performed. Based on the result of implementation, it is proven that the model is feasible.

A Multi-Cyclic Redundancy Check (CRC) selective Hybrid Automatic-Repeat-reQuest (HARQ) scheme for improving the throughput efficiency of Multiple Input Multiple Output (MIMO) systems is proposed in this paper. According to different feedback information from the receiver, the proposed HARQ scheme employs two strategies, referred to as retransmission frame selection and space diversity. These two strategies decrease the successive frame errors upon retransmission. Theoretic analysis and computer simulation results show that this HARQ scheme achieves higher throughput than the existing HARQ schemes even in poor conditions of low signal-to-noise ratio.

Due to the rapid development of electronic technologies, it tends to be diverse to access networks besides personal computers. Thanks to the technologies, it is possible for us to learn on the net anytime and anywhere, which propels the progress in e-learning dramatically, and some new research issues arise at the same time. Firstly, owing to the differences in processing power, storage and display resolution of terminals, it will lead to some problems that the same content is sent to heterogeneous terminals. Secondly, since the personalized learning pattern is popular in modern education, it is unsuitable to send the same media type of content to the different learners. With respect to the problems, it is needed to adapt content to characteristics of terminals and preferences of learners. In this paper, we will propose a novel content adaptation model under e-learning environment employing the expert control mode in control engineering. On the basis of the theory analysis and experiment results, it is proved that content adaptation under e-learning environment can be achieved by the model effectively.