30 research outputs found
Weighted Cache Location Problem with Identical Servers
This paper extends the well-known p-CLP with one server to p-CLP with m≥2 identical servers, denoted by (p,m)-CLP. We propose the closest server orienting protocol (CSOP), under which every client connects to the closest server to itself via a shortest route on given network. We abbreviate (p,m)-CLP under CSOP to (p,m)-CSOP CLP and investigate that (p,m)-CSOP CLP on a general network is equivalent to that on a forest and further to multiple CLPs on trees. The case of m=2 is the focus of this paper. We first devise an improved O(ph2+n)-time parallel exact algorithm for p-CLP on a tree and then present a parallel exact algorithm with at most O((4/9)p2n2) time in the worst case for (p,2)-CSOP CLP on a general network. Furthermore, we extend the idea of parallel algorithm to the cases of m>2 to obtain a worst-case O((4/9)(n-m)2((m+p)p/p-1!))-time exact algorithm. At the end of the paper, we first give an example to illustrate our algorithms and then make a series of numerical experiments to compare the running times of our algorithms
Space-Time-Controlled Multi-Stage Pulsed Magnetic Field Forming
Electromagnetic forming (EMF) is a high strain-rate forming method where a pulsed
electromagnetic force is applied to a conductive metallic workpiece. To improve the
performance of the EMF system, the current problems which restrict its extensive
application have been analyzed. To this end, a space-time-controlled EMF technology
with multi-stage and multi-direction coils system has been developed. In our new EMF
system, the magnetic field generated by driving coils is much higher than in conventional
EMF due to introducing design methods developed for non-destructive pulsed high field
magnets. This technology enables the forming of complex, large-scale sheets and tubes
that may be difficult to deform by conventional methods, as well as controlling particular
properties of the work pieces
Robust estimation of bacterial cell count from optical density
Optical density (OD) is widely used to estimate the density of cells in liquid culture, but cannot be compared between instruments without a standardized calibration protocol and is challenging to relate to actual cell count. We address this with an interlaboratory study comparing three simple, low-cost, and highly accessible OD calibration protocols across 244 laboratories, applied to eight strains of constitutive GFP-expressing E. coli. Based on our results, we recommend calibrating OD to estimated cell count using serial dilution of silica microspheres, which produces highly precise calibration (95.5% of residuals <1.2-fold), is easily assessed for quality control, also assesses instrument effective linear range, and can be combined with fluorescence calibration to obtain units of Molecules of Equivalent Fluorescein (MEFL) per cell, allowing direct comparison and data fusion with flow cytometry measurements: in our study, fluorescence per cell measurements showed only a 1.07-fold mean difference between plate reader and flow cytometry data
A Novel Switched-Capacitor Inverter with Reduced Capacitance and Balanced Neutral-Point Voltage
A novel three-phase switched-capacitor multilevel inverter (SCMLI) with reduced capacitance and balanced neutral-point voltage is proposed in this paper. Applying only one DC source, the three-phase seven-level topology possessing voltage-boosting capability is accomplished without the high-voltage stress of power switches. Owing to the inherent redundant switching states of the proposed topology, two charging approaches that can effectively limit the voltage ripples and path selection for capacitors can be realized. This provides the presented topology with reduced capacitance, balanced neutral-point voltage, good performance in not only the three-phase four-wire system but also the three-phase three-wire system, and low total harmonic distortion (THD) of the output voltage. A comprehensive comparison with previous SCMLIs in various aspects is conducted to validate the merits mentioned above. The simulation results accord with theoretical analyses, confirming the feasibility of the proposed three-phase SCMLI
Risk-Based Probabilistic Voltage Stability Assessment in Uncertain Power System
The risk-based assessment is a new approach to the voltage stability assessment in power systems. Under several uncertainties, the security risk of static voltage stability with the consideration of wind power can be evaluated. In this paper, we first build a probabilistic forecast model for wind power generation based on real historical data. Furthermore, we propose a new probability voltage stability approach based on Conditional Value-at-Risk (CVaR) and Quasi-Monte Carlo (QMC) simulation. The QMC simulation is used to speed up Monte Carlo (MC) simulation by improving the sampling technique. Our CVaR-based model reveals critical characteristics of static voltage stability. The distribution of the local voltage stability margin, which considers the security risk at a forecast operating time interval, is estimated to evaluate the probability voltage stability. Tested on the modified IEEE New England 39-bus system and the IEEE 118-bus system, results from the proposal are compared against the result of the conventional proposal. The effectiveness and advantages of the proposed method are demonstrated by the test results
Collecting Multidimensional Numerical Data and Estimating Mean with Personalized Local Differential Privacy
Collecting and analyzing data can generate a wealth of knowledge, but it can also raise privacy concerns. Local differential privacy (LDP) is the latest privacy standard to address this issue and has been implemented on platforms such as Chrome, iOS, and macOS. In the LDP solution, users first perturb their own data on the user side and then upload the perturbed data to the server. This not only protects against background attacks but also against untrusted servers. However, existing multidimensional solutions ignore the personalized privacy needs of users. In this paper, we meet the personalized privacy needs of users while reducing the mean square error of the perturbed data. Specifically, we first designed a personalized privacy budget allocation within a certain range, which meets the personalized privacy needs of users. Then, we optimized the sampling dimension of the existing solution, which resulted in a smaller mean square error of the perturbed data. Finally, we proposed our solution for collecting multidimensional numerical data and estimating the mean. In addition, we conducted experiments on two real datasets. The results demonstrate that the mean square error of our solution is lower than the existing solutions
On the 2-MRS Problem in a Tree with Unreliable Edges
This paper extends the well-known most reliable source (1-MRS) problem in unreliable graphs to the 2-most reliable source (2-MRS) problem. Two kinds of reachable probability models of node pair in unreliable graphs are considered, that is, the superior probability and united probability. The 2-MRS problem aims to find a node pair in the graph from which the expected number of reachable nodes or the minimum reachability is maximized. It has many important applications in large-scale unreliable computer or communication networks. The #P-hardness of the 2-MRS problem in general graphs follows directly from that of the 1-MRS problem. This paper deals with four models of the 2-MRS problem in unreliable trees where every edge has an independent working probability and devises a cubic-time and quadratic-space dynamic programming algorithm, respectively, for each model
Multi-Objective Demand Response Model Considering the Probabilistic Characteristic of Price Elastic Load
Demand response (DR) programs provide an effective approach for dealing with the challenge of wind power output fluctuations. Given that uncertain DR, such as price elastic load (PEL), plays an important role, the uncertainty of demand response behavior must be studied. In this paper, a multi-objective stochastic optimization problem of PEL is proposed on the basis of the analysis of the relationship between price elasticity and probabilistic characteristic, which is about stochastic demand models for consumer loads. The analysis aims to improve the capability of accommodating wind output uncertainty. In our approach, the relationship between the amount of demand response and interaction efficiency is developed by actively participating in power grid interaction. The probabilistic representation and uncertainty range of the PEL demand response amount are formulated differently compared with those of previous research. Based on the aforementioned findings, a stochastic optimization model with the combined uncertainties from the wind power output and the demand response scenario is proposed. The proposed model analyzes the demand response behavior of PEL by maximizing the electricity consumption satisfaction and interaction benefit satisfaction of PEL. Finally, a case simulation on the provincial power grid with a 151-bus system verifies the effectiveness and feasibility of the proposed mechanism and models