A related degree-based frequent pattern mining algorithm for railway fault data

It is of great significance to improve the efficiency of railway production and operation by realizing the fault knowledge association through the efficient data mining algorithm.However,high utility quantitative frequent pattern mining algorithms in the field of data mining still suffer from the problems of low time-memory performance and are not easy to scale up.In the context of such needs,we propose a related degree-based frequent pattern mining algorithm,named Related High Utility Quantitative Item set Mining(RHUQI-Miner),to enable the effective mining of railway fault data.The algorithm constructs the item-related degree structure of fault data and gives a pruning optimization strategy to find frequent patterns with higher related degrees,reducing redundancy and invalid frequent patterns.Subsequently,it uses the fixed pattern length strategy to modify the utility information of the item in the mining process so that the algorithm can control the length of the output frequent pattern according to the actual data situation and further improve the performance and practicability of the algorithm.The experimental results on the real fault dataset show that RHUQI-Miner can effectively reduce the time and memory consumption in the mining process,thus providing data support for differentiated and precise maintenance strategies.

Secure Network Coding Based on Lattice Signature

To provide a high-security guaran- tee to network coding and lower the comput- ing complexity induced by signature scheme, we take full advantage of homomorphic prop- erty to build lattice signature schemes and sec- ure network coding algorithms. Firstly, by means of the distance between the message and its sig- nature in a lattice, we propose a Distance-bas- ed Secure Network Coding （DSNC） algorithm and stipulate its security to a new hard problem Fixed Length Vector Problem （FLVP）, which is harder than Shortest Vector Problem （SVP） on lattices. Secondly, considering the bound- ary on the distance between the message and its signature, we further propose an efficient Bo- undary-based Secure Network Coding （BSNC） algorithm to reduce the computing complexity induced by square calculation in DSNC. Sim- ulation results and security analysis show that the proposed signature schemes have stronger unforgeability due to the natural property of lattices than traditional Rivest-Shamir-Adleman （RSA）-based signature scheme. DSNC algo- rithm is more secure and BSNC algorithm greatly reduces the time cost on computation.

Analysis of Cavitation Performance of a 2-D Hydrofoil Based on Mixed-iterative Method

In order to study cavitation characteristics of a 2-D hydrofoil, the method that combines nonlinear cavitation model and mixed-iteration is used to predict and analyze the cavitation performance of hydrofoils. The cavitation elements are nonlinearly disposed based on the Green formula and perturbation potential panel method. At the same time, the method that combines cavity shape for fixed cavity length （CSCL） iteration and cavity shape for fixed cavitation number （CSCN） iteration is used to work out the thickness and length of hydrofoil cavitations. Through analysis of calculation results, it can be concluded that the jump of pressure and velocity potentially exist between cavitation end area and non-cavitations area on suction surface when cavitation occurs on hydrofoil. In certain angles of attack, the cavitation number has a negative impact on the length of cavitations. And under the same angle of attack and cavitation number, the bigger the thickness of the hydrofoil, the shorter the cavitations length.

On the Performance of Fixed Burst Length OBS

In this paper, we propose a new OBS scheme, named Fixed Burst Length OBS. The FBL-OBS networks, combined with the extra-offset time scheme, can guarantee the QoS of OBS networks in a more efficient way.