Robust H_∞ directional control for a sampled-data autonomous airship

A robust H∞ directional controller for a sampled-data autonomous airship with polytopic parameter uncertainties was proposed. By input delay approach, the linearized airship model was transformed into a continuous-time system with time-varying delay. Sufficient conditions were then established based on the constructed Lyapunov-Krasovskii functional, which guarantee that the system is mean-square exponentially stable with H∞ performance. The desired controller can be obtained by solving the obtained conditions. Simulation results show that guaranteed minimum H∞ performance γ=1.4037 and fast response of attitude for sampled-data autonomous airship are achieved in spite of the existence of parameter uncertainties.

An Efficient Accurate Direct Solution of Poisson's Equation for Computation of Meteorological Parameters

Poisson's equation is solved numerically by two direct methods, viz. Block Cyclic Reduction (BCR) method and Fourier Method. Qualitative and quantitative comparison between the numerical solutions obtained by two methods indicates that BCR method is superior to Fourier method in terms of speed and accuracy. Therefore. BCR method is applied to solve (?)2(?)= ζ and (?)2X= D from observed vorticity and divergent values. Thereafter the rotational and divergent components of the horizontal monsoon wind in the lower troposphere are reconstructed and are com pared with the results obtained by Successive Over-Relaxation (SOR) method as this indirect method is generally in more use for obtaining the streamfunction ((?)) and velocity potential (X) fields in NWP models. It is found that the results of BCR method are more reliable than SOR method.

Calculate Joint Probability Distribution of Steady Directed Cyclic Graph with Local Data and Domain Casual Knowledge

It is desired to obtain the joint probability distribution(JPD) over a set of random variables with local data, so as to avoid the hard work to collect statistical data in the scale of all variables. A lot of work has been done when all variables are in a known directed acyclic graph(DAG). However, steady directed cyclic graphs(DCGs) may be involved when we simply combine modules containing local data together, where a module is composed of a child variable and its parent variables. So far, the physical and statistical meaning of steady DCGs remain unclear and unsolved. This paper illustrates the physical and statistical meaning of steady DCGs, and presents a method to calculate the JPD with local data, given that all variables are in a known single-valued Dynamic Uncertain Causality Graph(S-DUCG), and thus defines a new Bayesian Network with steady DCGs. The so-called single-valued means that only the causes of the true state of a variable are specified, while the false state is the complement of the true state.

Dosimetric evaluation of CR, 3DCRT and two types of IMRT for breast cancer after conservative surgery

Objective: The purpose of this study was to compare the dose distribution and dose volume histogram (DVH) of the planning target volume (PTV) and organs at risk (OARs) among conventional radiation therapy (CR), three-dimensional conformal radiation therapy (3DCRT), two-step intensity-modulated radiation therapy (TS-IMRT) and direct machine parameter optimization intensity-modulated radiation therapy (DMPO-IMRT) after breast-conserving surgery. Methods: For each of 20 randomly chosen patients, 4 plans were designed using 4 irradiation techniques. The prescribed dose was 50 Gy/2 Gy/25 f, 95% of the planning target volume received this dose. The cumulated DVHs and 3D dose distributions of CR, 3DCRT, TS-IMRT and DMPO-IMRT plans were compared. Results: For the homogeneity indices, no statistically significant difference was observed among CR, 3DCRT, TS-IMRT and DMPO-IMRT while the difference of the conformality indices were statistically significant. With regard to the organs at risk, IMRT and 3DCRT showed a significantly fewer exposure dose to the ipsilateral lung than CR in the high-dose area while in the low-dose area, IMRT demonstrated a significant increase of exposure dose to ipsilateral lung, heart and contralateral breast compared with 3DCRT and CR. In addition, the monitor units (MUs) for DMPO-IMRT were approximately 26% more than those of TS-IMRT and the segments of the former were approximately 24% less than those of the latter. Conclusion: Compared with CR, 3DCRT and IMRT improved the homogeneity and conformity of PTV, reduced the irradiated volume of OARs in high dose area but IMRT increased the irradiated volume of OARs in low dose area. DMPO-IMRT plan has fewer delivery time but more MUs than TS-IMRT.

Social Choice Meets Graph Drawing: How to Get Subexponential Time Algorithms for Ranking and Drawing Problems

We analyze a common feature of p-Kemeny AGGregation（p-KAGG） and p-One-Sided Crossing Minimization（p-OSCM） to provide new insights and findings of interest to both the graph drawing community and the social choice community. We obtain parameterized subexponential-time algorithms for p-KAGG—a problem in social choice theory—and for p-OSCM—a problem in graph drawing. These algorithms run in time O＊（2O（√k log k））,where k is the parameter, and significantly improve the previous best algorithms with running times O.1.403k/and O.1.4656k/, respectively. We also study natural ＂above-guarantee＂ versions of these problems and show them to be fixed parameter tractable. In fact, we show that the above-guarantee versions of these problems are equivalent to a weighted variant of p-directed feedback arc set. Our results for the above-guarantee version of p-KAGG reveal an interesting contrast. We show that when the number of ＂votes＂ in the input to p-KAGG is odd the above guarantee version can still be solved in time O＊（2O（√k log k））, while if it is even then the problem cannot have a subexponential time algorithm unless the exponential time hypothesis fails（equivalently, unless FPT D M[1]）.