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Fast Discovery of Frequent Itemsets through Clustering and Decomposition
Tsui-Ping Chang 한국산학기술학회 2012 SmartCR Vol.2 No.6
In a previous paper, we proposed a technique called the top-down mining (TDM) algorithm to speed up the task of mining hybrid sequential patterns. TDM has a unique feature that examines database itemsets in a top-down manner using decomposition. This method, however, may incur a space problem during decomposition transactions from the database. In this paper, therefore, we propose a new algorithm called transaction decomposition with clustering (TDC) to alleviate the space problem associated with the decomposition method. We use TDC to derive frequent itemsets from a large database. The major feature of TDC is that it divides a database into several smaller projected databases such that each portion can be solved with the decomposition method independently. Since a large amount of information does not have to be stored in memory, the TDC method can efficiently mine frequent itemsets. We compare experimental results for the proposed method and existing algorithms. The results show that TDC can solve the space problem of TDM, and TDC outperforms its counterpart algorithms in many cases. Even when the data set is large or the user-specified minimum support is low, the TDC method still exhibits high performance in mining frequent itemsets. This makes the TDC method suitable for mining frequent itemsets in very large databases.
Tsui, Jonathan H.,Janebodin, Kajohnkiart,Ieronimakis, Nicholas,Yama, David M. P.,Yang, Hee Seok,Chavanachat, Rakchanok,Hays, Aislinn L.,Lee, Haeshin,Reyes, Morayma,Kim, Deok-Ho American Chemical Society 2017 ACS NANO Vol.11 No.12
<P>Despite possessing substantial regenerative capacity, skeletal muscle can suffer from loss of function due to catastrophic traumatic injury or degenerative disease. In such cases, engineered tissue grafts hold the potential to restore function and improve patient quality of life. Requirements for successful integration of engineered tissue grafts with the host musculature include cell alignment that mimics host tissue architecture and directional functionality, as well as vascularization to ensure tissue survival. Here, we have developed biomimetic nanopatterned poly(lactic-<I>co</I>-glycolic acid) substrates conjugated with sphingosine-1-phosphate (S1P), a potent angiogenic and myogenic factor, to enhance myoblast and endothelial maturation. Primary muscle cells cultured on these functionalized S1P nanopatterned substrates developed a highly aligned and elongated morphology and exhibited higher expression levels of myosin heavy chain, in addition to genes characteristic of mature skeletal muscle. We also found that S1P enhanced angiogenic potential in these cultures, as evidenced by elevated expression of endothelial-related genes. Computational analyses of live-cell videos showed a significantly improved functionality of tissues cultured on S1P-functionalized nanopatterns as indicated by greater myotube contraction displacements and velocities. In summary, our study demonstrates that biomimetic nanotopography and S1P can be combined to synergistically regulate the maturation and vascularization of engineered skeletal muscles.</P><P><B>Graphic Abstract</B> <IMG SRC='http://pubs.acs.org/appl/literatum/publisher/achs/journals/content/ancac3/2017/ancac3.2017.11.issue-12/acsnano.7b00186/production/images/medium/nn-2017-001868_0008.gif'></P><P><A href='http://pubs.acs.org/doi/suppl/10.1021/nn7b00186'>ACS Electronic Supporting Info</A></P>