Are the contributions of China and Korea upsetting the world system of science?
SummaryInstitutions and their aggregates are not the right units of analysis for developing a science policy with cognitive goals in view. Institutions, however, can be compared in terms of their performance with reference to their previous stages. King's (2004) 'The scientific impact of nations' has provided the data for this comparison. Evaluation of the data from this perspective along the time axis leads to completely different and hitherto overlooked conclusions: a new dynamic can be revealed which points to a group of emerging nations. These nations do not increase their contributions marginally, but their national science systems grow endogenously. In addition to publications, their citation rates keep pace with the exponential growth patterns, albeit with a delay. The center of gravity of the world system of science may be changing accordingly.

title: A comparison between the China Scientific and Technical Papers and Citations Database and the Science Citation Index in terms of journal hierarchies and interjournal citation relations
abstract: The journal structure in the China Scientific and Technical Papers and Citations Database (CSTPCD) is analysed from three perspectives: the database level, the specialty level and the institutional level (i.e., university journals versus journals issued by the Chinese Academy of Sciences). The results are compared with those for (Chinese) journals included in the Science Citation Index. The frequency of journal-journal citation relations in the CSTPCD is an order of magnitude lower than in the SCI. Chinese journals, especially high-quality journals, prefer to cite international journals rather than domestic ones. However, Chinese journals do not get an equivalent reception from their international counterparts. The international visibility of Chinese journals is low, but varies among fields of science. Journals of the Chinese Academy of Sciences (CAS) have a better reception in the international scientific community than university journals.

title: Hybrid Intelligent System for Supervisory Control of Mineral Grinding Process
abstract: The particle size is the important technical performance index of the grinding process, which closely related to the overall performance of the mineral processing. In this paper, we mainly concern on the determination of the particle size for the supervisory control of the grinding process by the technical performance index decision system. The overall structure of the system and introduce of every part are given briefly. The experiment results and its compare with the neural network method show its validity and efficiency

title: Local Elastic Registration of Multimodal Medical Image Using Robust Point Matching and Compact Support RBF
abstract: A novel local elastic registration of multimodal medical image method is proposed in this paper. At first, local deformation regions are detected by evaluating the variation of mutual information in re-quantified gray space of images. The re-quantified image retains anatomical structure of the organ well and reduces the gray levels greatly. Mutual information performs better in the quantification space and can be used to detect whether the deformation happens in small sampling images. Next, edges of the local deformation regions are detected. Fuzzy clustering method is performed on edge points and the clustering centers are chosen as candidate landmarks. Robust point matching is used to estimate landmarks correspondence in the local deformation regions. Finally, a new compact support radial basis function CSTPF has been adopted to deform image, which cost less bending energy than other RBFs. Local registration experiments of multimodal medical images show the feasibility of our method.

title: Adaptive Buffer Management for Efficient Code Dissemination in Multi-Application Wireless Sensor Networks
abstract: Future wireless sensor networks (WSNs) are projected to run multiple applications in the same network infrastructure. While such multi-application WSNs (MA-WSNs) are economically more efficient and adapt better to the changing environments than traditional single-application WSNs, they usually require frequent code redistribution on wireless sensors, making it critical to design energy efficient post-deployment code dissemination protocols in MA-WSNs. Different applications in MA-WSNs often share some common code segments. Therefore when there is a need to disseminate a new application from the sink node, it is possible to disseminate its shared code segments from peer sensors instead of disseminating everything from the sink node. While dissemination protocols have been proposed to handle code of each single type, it is challenging to achieve energy efficiency when the code contains both types and needs simultaneous dissemination. In this paper we utilize an adaptive buffer management approach to achieve efficient code dissemination in MA-WSNs. Our experimental results show that adaptive buffer management can reduce the completion time and the message overhead up to 10% and 20% respectively.

title: A Binary Correlation Matrix Memory k-NN Classifier with Hardware Implementation
abstract: This paper describes a generic and fast classifier that uses a binary CMM (Correlation Matrix Memory) neural network for storing and matching a large amount of patterns efficiently, and a k-NN rule for classification. To meet CMM input requirements, a robust encoding method is proposed to convert numerical inputs into binary ones with the maximally achievable uniformity. To reduce the execution bottleneck, a hardware implementation of the CMM is described, which shows the network with on-board training and testing operates at over 200 times the speed of a current mid-range workstation, and is scaleable to very large problems. The CMM classifier has been tested on several benchmarks and, comparing with a simple k-NN classifier, it gave less than 1% lower accuracy and over 4 and 12 times speed-ups in software and hardware respectively.

title: A Fuzzy Logic Expert System for Fault Diagnosis and Security Assessment of Power Transformers