Maximality in the ⍺-C.A. Degrees

<p>In [4], Downey and Greenberg define the notion of totally ⍺-c.a. for appropriately small ordinals ⍺, and discuss the hierarchy this notion begets on the Turing degrees. The hierarchy is of particular interest because it has already given rise to several natural definability results, and provides a definable antichain in the c.e. degrees. Following on from the work of [4], we solve problems which are left open in the aforementioned relating to this hierarchy. Our proofs are all constructive, using strategy trees to build c.e. sets, usually with some form of permitting. We identify levels of the hierarchy where there is absolutely no collapse above any totally ⍺-c.a. c.e. degree, and construct, for every ⍺ ≼ ε0, both a totally ⍺-c.a. c.e. minimal cover and a chain of totally ⍺-c.a. c.e. degrees cofinal in the totally ⍺-c.a. c.e. degrees in the cone above the chain's least member.</p>

Maximality in the ⍺-C.A. Degrees

<p>In [4], Downey and Greenberg define the notion of totally ⍺-c.a. for appropriately small ordinals ⍺, and discuss the hierarchy this notion begets on the Turing degrees. The hierarchy is of particular interest because it has already given rise to several natural definability results, and provides a definable antichain in the c.e. degrees. Following on from the work of [4], we solve problems which are left open in the aforementioned relating to this hierarchy. Our proofs are all constructive, using strategy trees to build c.e. sets, usually with some form of permitting. We identify levels of the hierarchy where there is absolutely no collapse above any totally ⍺-c.a. c.e. degree, and construct, for every ⍺ ≼ ε0, both a totally ⍺-c.a. c.e. minimal cover and a chain of totally ⍺-c.a. c.e. degrees cofinal in the totally ⍺-c.a. c.e. degrees in the cone above the chain's least member.</p>

Using a Generalized Statistically Optimal Method of Solution for Minimum Weighted Cover Task

Statistically optimal algorithm for finding minimal cover of 0.1-matrices for the unweighted matrix has been proposed in the works of O. V. German. The algorithm is based on iterative addition of new columns (columns-resolvent)to the matrix, which are built according to the authors' formulated the principle of group resolution (PGR). They have the following property. Under the assumption that optimal cover has not been obtained yet, each such cover contains at least one row from among those that cover the column - resolvent. After adding each new column, considered as a random 0.1-vector, analytical evaluation of mathematical expectation of the number of minimal covers with a given number of rows is made. The evaluation concludes the need to continue the iterations or termination of the algorithm. After evaluation it can be concluded about the necessity to continue the iterations or termination of the algorithm.The algorithm is tested for 600 randomly generated problems with a subsequent comparison with the exact solution. It can be concluded that analytical estimates for mathematical expectation of the number of covers with specified size are stable for matrices of large dimension. On the contrary, with a decrease in the number of columns these estimates become less stable. Doubtless, in our opinion, advantage of this method is its high speed. Thus, in the vast majority of cases, the algorithm concludes by finding the exact solution, which makes to consider it statistically optimal one. The advantage of this method is its speed, but it is empirically proven that increase in the dimension of the problem leads to unpredictable failures.

Covering the Monitoring Network: A Unified Framework to Protect E-Commerce Security

Multimedia applications in smart electronic commerce (e-commerce), such as online trading and Internet marketing, always face security in storage and transmission of digital images and videos. This study addresses the problem of security in e-commerce and proposes a unified framework to analyze the security data. First, to allocate the definite security resources optimally, we build our e-commerce monitoring model as an undirected network, where a monitored node is a vertex of the graph and a connection between vertices is an undirected edge. Moreover, we aim to find a minimal cover for the monitoring network as the optimal solution of resource allocation, which is defined as the network monitoring minimization problem (NMM). This problem is proved to be NP-hard. Second, by analyzing the latent threats, we design a novel and trusted monitoring system that can integrate incident monitoring, data analysis, risk assessment, and security warnings. This system does not touch users’ privacy data. Third, we propose a sequential model-based risk assessment method, which can predict the risk according to the text semantics. Our experimental results on web scale data demonstrate that our system is flexible enough when monitoring, which also verify the effectiveness and efficiency of our system.