Soft measurement for component content based on adaptive model of Pr/Nd color features

For measurement of component content in the extraction and separation process of praseodymium/neodymium(Pr/Nd), a soft measurement method was proposed based on modeling of ion color features, which is suitable for fast estimation of component content in production field. Feature analysis on images of the solution is conducted,which are captured from Pr/Nd extraction/separation field. H/S components in the HSI color space are selected as model inputs, so as to establish the least squares support vector machine(LSSVM) model for Nd(Pr) content,while the model parameters are determined with the GA algorithm. To improve the adaptability of the model,the adaptive iteration algorithm is used to correct parameters of the LSSVM model, on the basis of model correction strategy and new sample data. Using the field data collected from rare earth extraction production, predictive methods for component content and comparisons are given. The results indicate that the proposed method presents good adaptability and high prediction precision, so it is applicable to the fast detection of element content in the rare earth extraction.

Hop-by-hop Content Distribution with Network Coding in Multihop Wireless Networks

The predominant use of today＇s networks is content access and distribution. Network Coding （NC） is an innovative technique that has potential to improve the efficiency of multicast content distribution over multihop Wireless Mesh Networks （WMNs） by allowing intermediate Forwarding Nodes （FNs） to encode and then forward data packets. Practical protocols are needed to realize the benefits of the NC technique. However, the existing NC-based multicast protocols cannot accurately determine the minimum number of coded packets that a FN should send in order to ensure successful data delivery to the destinations, so that many redundant packets are injected into the network, leading to performance degradation. In this paper, we propose HopCaster, a novel reliable multicast protocol that incorporates network coding with hop-by-hop transport. HopCaster completely eliminates the need for estimating the number of coded packets to be transmitted by a FN, and avoids redundant packet transmissions. It also effectively addresses the challenges of heterogeneous mulficast receivers. Moreover, a cross-layer multicast rate adaptation mechanism is proposed, which enables HopCaster to optimize multicast throughput by dynamically adjusting wireless transmission rate based on the changes in the receiver population and channel conditions during the course of mulficasting a coded data chunk. Our evaluations show that HopCaster significantly outperforms the existing NC-based multicast protocols.

An Aggregation Cache Replacement Algorithm Based on Ontology Clustering

This paper describes the theory, implementation, and experimental evaluation of an Aggregation Cache Replacement （ ACR ） algorithm. By considering application background, carefully choosing weight values, using a special formula to calculate the similarity, and clustering ontologies by similarity for getting more embedded deep relations, ACR combines the ontology similarity with the value of object and decides which object is to be replaced. We demonstrate the usefulness of ACR through experiments. （a） It is found that the aggregation tree is created wholly differently according to the application cases. Therefore, clustering can direct the content adaptation more accurately according to the user perception and can satisfy the user with different preferences. （b） After comparing this new method with widely-used algorithm Last-Recently-Used （LRU） and First-in-First-out （FIFO） method, it is found that ACR outperforms the later two in accuracy and usability. （c） It has a better semantic explanation and makes adaptation more personalized and more precise.