16,543 research outputs found
New Approach to Estimating the Standard Deviations of Lognormal Cost Variables in the Monte Carlo Analysis of Construction Risks
If soundly conducted, risk assessment could yield considerable savings for project investors. Monte Carlo Simulation (MCS) has been widely embraced by risk management guides as an instrumental tool for this purpose. This research aims to develop a new method to improve the rigor of MCS by establishing the link between parameter estimation and assessment of individual risk sources. The method is validated by virtue of its predictive power for the likelihood of a project being successful in securing investors. Eight Taiwanese sewerage Build-Operate-Transfer projects are investigated. Compared to the discounted cash flow approach, this new method can provide a more accurate prediction using the expert’s assessment as input of financial impact and occurrence likelihood of individual risks. This finding furnishes solid empirical evidence for the value MCS might add to project appraisal
Probing isospin- and momentum-dependent nuclear effective interactions in neutron-rich matter
The single-particle potentials for nucleons and hyperons in neutron-rich
matter generally depends on the density and isospin asymmetry of the medium as
well as the momentum and isospin of the particle. It further depends on the
temperature of the matter if the latter is in thermal equilibrium. We review
here the extension of a Gogny-type isospin- and momentum-dependent interaction
in several aspects made in recent years and their applications in studying
intermediate-energy heavy ion collisions, thermal properties of asymmetric
nuclear matter and properties of neutron stars. The importance of the isospin-
and momentum-dependence of the single-particle potential, especially the
momentum dependence of the isovector potential, is clearly revealed throughout
these studies.Comment: 27 pages, 19 figures, 1 table, accepted version to appear in EPJA
special volume on Nuclear Symmetry Energ
The Information Of The Milky Way From 2MASS Whole Sky Star Count: The Bimodal Color Distributions
The J-Ks color distribution (CD) with a bin size of 0.05 magnitude for the
entire Milky Way has been carried out by using the Two Micron All Sky Survey
Point Source Catalog (2MASS PSC). The CDs are bimodal, which has a red peak at
0.8 < J-Ks < 0.85 and a blue peak at 0.3 < J-Ks < 0.4. The colors of the red
peak are more or less the same for the whole sky, but that of the blue peak
depend on Galactic latitude, (J-Ks ~ 0.35 at low Galactic latitudes and 0.35 <
J-Ks < 0.4 for other sky areas). The blue peak dominates the bimodal CDs at low
Galactic latitudes and becomes comparable with the red peak in other sky
regions. In order to explain the bimodal distribution and the global trend
shown by the all sky 2MASS CDs, we assemble an empirical HR diagram, which is
composed by observational-based near infrared HR diagrams and color magnitude
diagrams, and incorporate a Milky Way model. In the empirical HR diagram, the
main sequence stars turnoff the thin disk is relatively bluer, (J-Ks)0 = 0.31,
when we compare with the thick disk which is (J-Ks)0 = 0.39. The age of the
thin/thick disk is roughly estimated to be around 4-5/8-9 Gyr according to the
color-age relation of the main sequence turnoff. In general, the 2MASS CDs can
be treated as a tool to census the age of stellar population of the Milky Way
in a statistical manner and to our knowledge this is a first attempt to measure
the age.Comment: Accepted by ApJ on Sept. 11 201
NETWORK DESIGN FOR THE TEMPORAL AND SPATIAL COLLABORATION WITH SERVICE CLASS IN DELIVERY SERVICES
The COVID-19 pandemic has significantly impacted e-commerce and the delivery service sector. As lockdowns and social distancing measures were put in place to slow the spread of the virus, many brick-and-mortar stores were forced to close, leading to an increase in online shopping. This situation led to a surge in demand for delivery services as more people turned to the internet to purchase goods. However, this increase in demand also created several challenges for delivery companies. They experienced delays in delivering packages due to increased volume, limited staff, and disruptions to supply chains. It led to more competition and increased pressure on delivery companies to improve their services and delivery times. To overcome such competition, collaboration among small and medium-sized delivery companies can be a good way to compete with larger delivery companies. By working together, small and medium-sized companies can combine their resources and expertise to offer more extensive coverage and competitive prices than they could individually. This can help them to gain market share and expand their customer base. This study proposes a network design model for collaboration with service class in delivery services considering multi-time horizon. The problem to be considered is deciding which company is dedicated to delivering certain types of items, such as regular or refrigerated items, in designated regions in each time horizon. During the agreed-upon timeframe, the companies operate, using each other's infrastructure (such as vehicles and facilities) and sharing delivery centers for the coalition's benefit to improve efficiency and reduce costs. We also propose a multi-objective, nonlinear programming model that maximizes the incremental profit of participating companies and a linearization methodology to solve it. The max-sum criterion and Shapley value allocation methods are applied to find the best solution and ensure a fair distribution of profits among the collaborating group. The efficiency of the suggested model is shown through a numerical illustration
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