A helical drive in-pipe robot based on compound planetary gearing

The modern society is fuelled by very comprehensive grids of gas and liquid pipelines. In recent years, various in-pipe robots have been developed for inspection and maintenance tasks inside such pipes. In this paper, a novel in-pipe robot is proposed and developed for gas/oil well interventions at thousands of meters downhole. Due to the nature of such intervention, in-pipe robot design must be capable of carrying a very large payload, as large as 2500?N inside a pipe with diameter as small as 54?mm. The proposed design concept is based on a compound planetary gearing system. One of the major novelties of this design is the use of pipe wall as a ring gear for one stage of the compound planetary gear system; the other novelty is the generation of helical angle when the planetary gears are expanded to press on the pipe wall. The proposed concept is compact, efficient, and has never been reported before. In this paper, the helical angle, the velocity, and load capability of the proposed system will be analyzed. The load transportation capability of the proposed robot is also measured based on an experiment. Initial data have shown great potential in carrying large payloads.     

Bounds on multipartite concurrence and tangle

We present an analytical lower bound of multipartite concurrence based on the generalized Bloch representations of density matrices. It is shown that the lower bound can be used as an effective entanglement witness of genuine multipartite entanglement. Tight lower and upper bounds for multipartite tangles are also derived. Since the lower bounds depend on just part of the correlation tensors, the result is experimentally feasible.     

FTIR,DTA and XRD study of sphene (CaTiSiO5) crystallization in a ceramic frit and a non-borate base glass

The primary objective of this study has been the application of Fourier transform infrared (FTi.r.) absorption spectroscopy for both qualitative and quantitative characterization of sphene (CaTiSiO₅) crystallization in test materials; namely, a CaO-TiO₂-B₂O₃ bearing ceramic frit-S and a similar non-borate base glass-S. Differential thermal analysis (DTA), X-ray diffraction (XRD) and scanning electron microscope/electron probe X-ray microanalysis (SEM/EPMA) techniques have also been used. FTi.r. absorption spectra have been shown to be capable of providing both qualitative and quantitative characterizations of crystal nucleation and growth in a frit-S and glass-S, being annealed between 800–1100° C. CaTiSiO₅ appears as the dominant phase and-cristobalite as the transitional phase in frit-S; whereas, -CaSiO₃ is dominant, CaTiSiO₅ being a minor phase in the non-borate glass-S. As given by DTA data, the intense stage of crystal growth for frit-S is about 120–125° C lower than that of glass-S. B₂O₃ content and the relative amounts of CaO and TiO₂ in the test specimens have been shown to give different modes of phase evolution and the onset temperature of nucleation. The activation energies,E _c, of crystal nucleation/growth was estimated by two different methods, namely, via DTA data and FTi.r. absorption spectra under the dominant surface nucleation mode for powder pellet specimens.E _c for CaTiSiO₅, -CaSiO₃ and-cristobalite in the frit-S and the non-borate base glass-S were estimated to be 219.6, 107.2 and 51.5 kJ mol^–1, respectively, parallel to the decreasing order of chemical complexity of the glass-forming system. Similar quantitative FTi.r. studies in the determination ofE _c for a broader scope of glass compositions, and compared with that based on XRD and DTA data, are to be encouraged so that the application of FTi.r. spectroscopy in glass-ceramics may be advanced.     

An adaptive interference alignment scheme based on the dynamic selection of desired transmitters for unmanned ship network

Wireless Networks - In the unmanned ship networking scenario, the position of the unmanned ship changes continuously, leading to the result that the desired transmitters and the interference...     

A rough set approach to feature selection based on power set tree

Feature selection is viewed as an important preprocessing step for pattern recognition, machine learning and data mining. Traditional hill-climbing search approaches to feature selection have difficulties to find optimal reducts. And the current stochastic search strategies, such as GA, ACO and PSO, provide a more robust solution but at the expense of increased computational effort. It is necessary to investigate fast and effective search algorithms. Rough set theory provides a mathematical tool to discover data dependencies and reduce the number of features contained in a dataset by purely structural methods. In this paper, we define a structure called power set tree (PS-tree), which is an order tree representing the power set, and each possible reduct is mapped to a node of the tree. Then, we present a rough set approach to feature selection based on PS-tree. Two kinds of pruning rules for PS-tree are given. And two novel feature selection algorithms based on PS-tree are also given. Experiment results demonstrate that our algorithms are effective and efficient.     

Industrial architectural assessment using TARA

Scenario based architectural assessment is a well-established approach for assessing architectural designs. However scenario-based methods are not always usable in an industrial context, where in our experience, they can be perceived as complicated and expensive to use. In this paper we explore why this may be the case and define a simpler technique called TARA, which has been designed for use in situations where scenario based methods are unlikely to be successful. The method is illustrated through an experience report that explains how it was applied to the assessment of two quantitative financial analysis systems, and its strengths, weaknesses and relationship to other methods are briefly discussed.