948 research outputs found
Efficient Approximation Algorithms for Multi-Antennae Largest Weight Data Retrieval
In a mobile network, wireless data broadcast over 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
-antennae largest weight data retrieval (ALWDR) problem is to
compute a schedule for downloading a subset of data items that has a maximum
total weight using antennae in a given time interval. In this paper,
we propose a ratio approximation algorithm for the
-antennae largest weight data retrieval (ALWDR) problem that
has the same ratio as the known result but a significantly improved time
complexity of from
when
\cite{lu2014data}. To our knowledge, our algorithm represents the first ratio
approximation solution to ALWDR for the
general case of arbitrary . To achieve this, we first give a ratio
algorithm for the -separated ALWDR
(ALWDR) with runtime , under the assumption
that every data item appears at most once in each segment of
ALWDR, for any input of maximum length on channels in
time slots. Then, we show that we can retain the same ratio for
ALWDR without this assumption at the cost of increased time
complexity to . This result immediately yields an
approximation solution of same ratio and time complexity for ALWDR,
presenting a significant improvement of the known time complexity of ratio
approximation to the problem
A discrete dynamic convexized method for nonlinear integer programming
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
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
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
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
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
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
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
Multiphase MCM-CAPRAM modeling of the formation and processing of secondary aerosol constituents observed during the Mt. Tai summer campaign in 2014
Despite the high abundance of secondary aerosols in the atmosphere, their formation mechanisms remain poorly understood. In this study, the Master Chemical Mechanism (MCM) and the Chemical Aqueous-Phase Radical Mechanism (CAPRAM) are used to investigate the multiphase formation and processing of secondary aerosol constituents during the advection of air masses towards the measurement site of Mt. Tai in northern China. Trajectories with and without chemical–cloud interaction are modeled. Modeled radical and non-radical concentrations demonstrate that the summit of Mt. Tai, with an altitude of ∼1.5 km a.m.s.l., is characterized by a suburban oxidants budget. The modeled maximum gas-phase concentrations of the OH radical are 3.2×106 and 3.5×106 molec. cm−3 in simulations with and without cloud passages in the air parcel, respectively. In contrast with previous studies at Mt. Tai, this study has modeled chemical formation processes of secondary aerosol constituents under day vs. night and cloud vs. non-cloud cases along the trajectories towards Mt. Tai in detail. The model studies show that sulfate is mainly produced in simulations where the air parcel is influenced by cloud chemistry. Under the simulated conditions, the aqueous reaction of HSO−3 with H2O2 is the major contributor to sulfate formation, contributing 67 % and 60 % in the simulations with cloud and non-cloud passages, respectively. The modeled nitrate formation is higher at nighttime than during daytime. The major pathway is aqueous-phase N2O5 hydrolysis, with a contribution of 72 % when cloud passages are considered and 70 % when they are not. Secondary organic aerosol (SOA) compounds, e.g., glyoxylic, oxalic, pyruvic and malonic acid, are found to be mostly produced from the aqueous oxidations of hydrated glyoxal, hydrated glyoxylic acid, nitro-2-oxopropanoate and hydrated 3-oxopropanoic acid, respectively. Sensitivity studies reveal that gaseous volatile organic compound (VOC) emissions have a huge impact on the concentrations of modeled secondary aerosol compounds. Increasing the VOC emissions by a factor of 2 leads to linearly increased concentrations of the corresponding SOA compounds. Studies using the relative incremental reactivity (RIR) method have identified isoprene, 1,3-butadiene and toluene as the key precursors for glyoxylic and oxalic acid, but only isoprene is found to be a key precursor for pyruvic acid. Additionally, the model investigations demonstrate that an increased aerosol partitioning of glyoxal can play an important role in the aqueous-phase formation of glyoxylic and oxalic acid. Overall, the present study is the first that provides more detailed insights in the formation pathways of secondary aerosol constituents at Mt. Tai and clearly emphasizes the importance of aqueous-phase chemical processes on the production of multifunctional carboxylic acids
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