948 research outputs found

    Efficient Approximation Algorithms for Multi-Antennae Largest Weight Data Retrieval

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    In a mobile network, wireless data broadcast over mm channels (frequencies) is a powerful means for distributed dissemination of data to clients who access the channels through multi-antennae equipped on their mobile devices. The δ\delta-antennae largest weight data retrieval (δ\deltaALWDR) problem is to compute a schedule for downloading a subset of data items that has a maximum total weight using δ\delta antennae in a given time interval. In this paper, we propose a ratio 11eϵ1-\frac{1}{e}-\epsilon approximation algorithm for the δ\delta-antennae largest weight data retrieval (δ\deltaALWDR) problem that has the same ratio as the known result but a significantly improved time complexity of O(21ϵ1ϵm7T3.5L)O(2^{\frac{1}{\epsilon}}\frac{1}{\epsilon}m^{7}T^{3.5}L) from O(ϵ3.5m3.5ϵT3.5L)O(\epsilon^{3.5}m^{\frac{3.5}{\epsilon}}T^{3.5}L) when δ=1\delta=1 \cite{lu2014data}. To our knowledge, our algorithm represents the first ratio 11eϵ1-\frac{1}{e}-\epsilon approximation solution to δ\deltaALWDR for the general case of arbitrary δ\delta. To achieve this, we first give a ratio 11e1-\frac{1}{e} algorithm for the γ\gamma-separated δ\deltaALWDR (δ\deltaAγ\gammaLWDR) with runtime O(m7T3.5L)O(m^{7}T^{3.5}L), under the assumption that every data item appears at most once in each segment of δ\deltaAγ\gammaLWDR, for any input of maximum length LL on mm channels in TT time slots. Then, we show that we can retain the same ratio for δ\deltaAγ\gammaLWDR without this assumption at the cost of increased time complexity to O(2γm7T3.5L)O(2^{\gamma}m^{7}T^{3.5}L). This result immediately yields an approximation solution of same ratio and time complexity for δ\deltaALWDR, presenting a significant improvement of the known time complexity of ratio 11eϵ1-\frac{1}{e}-\epsilon approximation to the problem

    A discrete dynamic convexized method for nonlinear integer programming

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    AbstractIn this paper, we consider the box constrained nonlinear integer programming problem. We present an auxiliary function, which has the same discrete global minimizers as the problem. The minimization of the function using a discrete local search method can escape successfully from previously converged discrete local minimizers by taking increasing values of a parameter. We propose an algorithm to find a global minimizer of the box constrained nonlinear integer programming problem. The algorithm minimizes the auxiliary function from random initial points. We prove that the algorithm can converge asymptotically with probability one. Numerical experiments on a set of test problems show that the algorithm is efficient and robust

    The Study of Xintan Landslide\u27s Sterescopic Monitoring in the Changjiang River Three Gorges

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    This paper emphatically introduces a new landslide’s stereoscopic monitoring system that was builded in Xintan slope after failed. The movement in the underground different level can be decided through monitoring of surface by the system. The system can provide a basis to master the slope gliding regulartion so that a new prediction method may be worked out in the future

    Prediction-Forecast and Slip-Control for One Slope

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    Firstly, combining the engineering geological conditions of the slope, this paper analyses the forms and main causes of the slope possible slip, and predicts the slope\u27s stability in the different construction periods of the gully at the bottom of slope. In the basis of these, the work plan of quick cutting quick erecting for the gully is emphatically discussed. Then, the paper presents the slope monitoring method and monitoring results. At last, the paper re-analyses the site-monitoring data. The results of monitoring and re-analysis prove that work plan of quick cutting and quick erecting is correct and the poured concrete improves the state of the force on the slope and takes really effect on pressing the slope\u27s bottom in time

    PeF: Poisson's Equation Based Large-Scale Fixed-Outline Floorplanning

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    Floorplanning is the first stage of VLSI physical design. An effective floorplanning engine definitely has positive impact on chip design speed, quality and performance. In this paper, we present a novel mathematical model to characterize non-overlapping of modules, and propose a flat fixed-outline floorplanning algorithm based on the VLSI global placement approach using Poisson's equation. The algorithm consists of global floorplanning and legalization phases. In global floorplanning, we redefine the potential energy of each module based on the novel mathematical model for characterizing non-overlapping of modules and an analytical solution of Poisson's equation. In this scheme, the widths of soft modules appear as variables in the energy function and can be optimized. Moreover, we design a fast approximate computation scheme for partial derivatives of the potential energy. In legalization, based on the defined horizontal and vertical constraint graphs, we eliminate overlaps between modules remained after global floorplanning, by modifying relative positions of modules. Experiments on the MCNC, GSRC, HB+ and ami49\_x benchmarks show that, our algorithm improves the average wirelength by at least 2\% and 5\% on small and large scale benchmarks with certain whitespace, respectively, compared to state-of-the-art floorplanners

    Analytical Solution of Poisson's Equation with Application to VLSI Global Placement

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    Poisson's equation has been used in VLSI global placement for describing the potential field caused by a given charge density distribution. Unlike previous global placement methods that solve Poisson's equation numerically, in this paper, we provide an analytical solution of the equation to calculate the potential energy of an electrostatic system. The analytical solution is derived based on the separation of variables method and an exact density function to model the block distribution in the placement region, which is an infinite series and converges absolutely. Using the analytical solution, we give a fast computation scheme of Poisson's equation and develop an effective and efficient global placement algorithm called Pplace. Experimental results show that our Pplace achieves smaller placement wirelength than ePlace and NTUplace3. With the pervasive applications of Poisson's equation in scientific fields, in particular, our effective, efficient, and robust computation scheme for its analytical solution can provide substantial impacts on these fields

    Generation of Biotechnology-Derived Flavobacterium columnare Ghosts by PhiX174 Gene E-Mediated Inactivation and the Potential as Vaccine Candidates against Infection in Grass Carp

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    Flavobacterium columnare is a bacterial pathogen causing high mortality rates for many freshwater fish species. Fish vaccination with a safe and effective vaccine is a potential approach for prevention and control of fish disease. Here, in order to produce bacterial ghost vaccine, a specific Flavobacterium lysis plasmid pBV-E-cat was constructed by cloning PhiX174 lysis gene E and the cat gene with the promoter of F. columnare into the prokaryotic expression vector pBV220. The plasmid was successfully electroporated into the strain F. columnare G4cpN22 after curing of its endogenous plasmid. F. columnare G4cpN22 ghosts (FCGs) were generated for the first time by gene E-mediated lysis, and the vaccine potential of FCG was investigated in grass carp (Ctenopharyngodon idellus) by intraperitoneal route. Fish immunized with FCG showed significantly higher serum agglutination titers and bactericidal activity than fish immunized with FKC or PBS. Most importantly, after challenge with the parent strain G4, the relative percent survival (RPS) of fish in FCG group (70.9%) was significantly higher than FKC group (41.9%). These results showed that FCG could confer immune protection against F. columnare infection. As a nonliving whole cell envelope preparation, FCG may provide an ideal alternative to pathogen-based vaccines against columnaris in aquaculture

    A Tabu Search-Based Memetic Algorithm for Hardware/Software Partitioning

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    Hardware/software (HW/SW) partitioning is to determine which components of a system are implemented on hardware and which ones on software. It is one of the most important steps in the design of embedded systems. The HW/SW partitioning problem is an NP-hard constrained binary optimization problem. In this paper, we propose a tabu search-based memetic algorithm to solve the HW/SW partitioning problem. First, we convert the constrained binary HW/SW problem into an unconstrained binary problem using an adaptive penalty function that has no parameters in it. A memetic algorithm is then suggested for solving this unconstrained problem. The algorithm uses a tabu search as its local search procedure. This tabu search has a special feature with respect to solution generation, and it uses a feedback mechanism for updating the tabu tenure. In addition, the algorithm integrates a path relinking procedure for exploitation of newly found solutions. Computational results are presented using a number of test instances from the literature. The algorithm proves its robustness when its results are compared with those of two other algorithms. The effectiveness of the proposed parameter-free adaptive penalty function is also shown
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