Acxiom (United States)

분자량이 다른 세종류 히알루론산(HA)에 1,4-butanediol diglycidyl ether(BDDE)가 가교된 hyaluronic acid(HA)를 첨가하여 하이드로겔을 제조하고 HA 분자량에 따른 팽윤도와 탄성계수의 효과를 조사하였다. 최종 투석 후 잔류 BDDE 양은 0.5 ppm 이하이었다. 비가교된 분자량이 큰 HA에서 최대 팽윤도가 관찰되었다. 팽윤도는 비가교 HA 양과 가교도에 각각 비례와 반비례하였다. 1.0 w/v% BDDE 가교 HA와 HA(1368 kDa)를 혼합한 monophasic 하이드로젤의 탄성계수는 152~325 ㎩이었다. 15% 가교 HA(687 kDa)과 85% HA(1368 kDa)로 구성된 biphasic 하이드로젤의 탄성계수는 178 Pa이었다.

Record linkage deals with finding records that identify the same real world entity, such as an individual or a business, from a given file or set of files. Record linkage problem is also referred to as the entity resolution or record recognition problem. To locate those records identifying the same real world entity, in principle, pairwise record analyses have to be performed among all records. Analytical operations between two records vary from comparing corresponding fields to enhancing records through large knowledge bases and querying large databases. Hence, these operations are complex and take time. To reduce the number of pairwise record comparisons, blocking techniques are introduced to partition the records into blocks. After that records in each block are analyzed against one and another. One of the effective blocking methods is the closure approach, where a “related” equivalence relation is used to partition the records into equivalence classes. This paper introduces the closure problem and describes the design and implementation of a parallel and distributed closure prototype system running in an enterprise grid.

Many systems in sciences, engineering and nature can be modeled as networks. Examples include the internet, WWW and social networks. Finding hidden structures is important for making sense of complex networked data. In this paper we present a new network clustering method that can find clusters in an agglomerative fashion using structural similarity of vertices in the given network. Experiments conducted on real datasets demonstrate promising performance of the new method.

In this paper, we propose a novel rate control scheme for H.264/AVC standard, including a new coding complexity measure for intra-frames, a new rate-complexity-quantization (R-C-Q) model, an accurate quantization parameter (QP) estimation for intra-frames, an incremental-control-based QP calculation for inter-frames, and a bit-allocation-balancing technique. Our experimental results demonstrate that, the proposed scheme outperforms the JVT-G012 solution by providing more accurate QP prediction, reducing frame skipping, depressing quality fluctuations, and finally, improving coding quality.

The purpose of this panel is to discuss the importance of mathematics and mathematical thinking as applied to well-established disciplines of computing namely: computer science, computer engineering, information systems, software engineering, and computational science. The new ACM/IEEE Computing Curricula 2001 has listed discrete structures, for the first time, as one of the many othe core sub-areas of computer science---this means discrete mathematics topics are more than just another mathematics requirements. In fact, with the importance of so many mathematical topics as relevant to computing, a two-semester sequence in discrete structures is recommended. The panelists will present their views on how mathematics can be utilized as one of the most valuable tools applied to the modern field of computing.