# Search Results

###### Influence of seasonal factors in the earned value of construction

calendars bring to light in those countries where laws protect the right of holiday choice. In these cases, the calendar factor is no longer deterministic. On the other hand, other authors (e.g., Tucker & Rahilly, 1982 [ 19 ]; Koehn & Brown, 1985 [ 14 ]; Chan & Kumaraswamy, 1995 [ 6 ]; El-Rayes & Mosehli 2001 [ 9 ];Wiliams, 2008 [ 21 ]; Odabasi, 2009 [ 15 ]) have explored the climatic factor giving rise to some predictive models with varying success. Nevertheless, we have not found any studies measuring the influence of all the seasonal factors in the construction

###### Five Years of Phase Space Dynamics of the Standard & Poor’s 500

and roughness of the stock, and the market state corresponds to a certain distribution of stock in phase space. The novelty of our approach is twofold. First, in Sec. 4.1 , we have developed the novel concept of predictability of states in phase space. Our approach is based on the idea that with some probability a state might be a t -day precursor of another state in phase space. The introduced measure of t -day predictability of a state is a sum of all information components from its t-day precursors. From such a point of view, Markov chains are

###### Affine Transformation Based Ontology Sparse Vector Learning Algorithm

-59. 10.7763/IJAPM.2011.V1.11 Huang X. Xu T. Gao W. Jia Z. 2011 Ontology Similarity Measure and Ontology Mapping Via Fast Ranking Method, International Journal of Applied Physics and Mathematics 1 1 54 59 10.7763/IJAPM.2011.V1.11 [30] W. Gao and L. Liang, (2011), Ontology Similarity Measure by Optimizing NDCG Measure and Application in Physics Education , Future Communication, Computing, Control and Management, Vol 142 of the series Lecture Notes in Electrical Engineering pp 415-421. 10.1007/978-3-642-27314-8_56 Gao W. Liang L. 2011 Ontology Similarity Measure by

###### Ontology optimization tactics via distance calculating

Physics and Mathematics 1 1 54 59 10.7763/IJAPM.2011.V1.11 [14] W. Gao, L. Liang. (2011), Ontology similarity measure by optimizing NDCG measure and application in physics education, Future Communication, Computing, Control and Management, 142, 415-421. Gao W. Liang L. 2011 Ontology similarity measure by optimizing NDCG measure and application in physics education Future Communication, Computing, Control and Management 142 415 421 [15] C. McDiarmid. (1989), On the method of bounded differences, in Surveys in Combinatorics, Cambridge University Press, 1989, pp. 148

###### Complex Network Theory and Its Application Research on P2P Networks

networks have the characteristics of power-low, clustering and small world. Through statistic and analysis of the networks, these studies focused on testifying existed models on the P2P networks. 3.2 User behavior With the deepening of the study, users, resources and their relationships with each other in P2P network were analyzed; especially users’ inner interests have been excavated in-depth. By measuring user behavior characteristics in a large number of network, the literature [ 7 ] found user behavior was distinguish between different network, for example

###### Simulation analysis of resource-based city development based on system dynamics: A case study of Panzhihua

2010, the total sulfur dioxide emissions in Panzhihua City should be controlled within 81,000 tons. To achieve these goals, Panzhihua City has adopted a series of important measures, including the establishment of emission reduction implementation plans and action plans, such as the “Panzhihua Main Pollutant Total Emission Reduction and Implementation Plan” and Panzhihua City’s “Main Pollutant Total Emission Reduction Action Plan” in 2008 and 2009. In addition, the total amount of major pollutants control indicators was further decomposed and implemented to

###### Research on relationship between tourism income and economic growth based on meta-analysis

results [ 9 ]. 2 Theoretical basis and research hypothesis 2.1 Relation between tourism income and economic growth Tourism income is one of the important indicators for measuring economic activity. It can also directly reflect the regional economic performance [ 10 ]. To a certain extent, the increase in tourism income can promote economic development and promote economic growth. The more tourism income, the more obvious the economic growth is. Hou and Lang (2016) conducted an empirical research on the relationship between Zhangjiajie’s tourism income and

###### Applied mathematics and nonlinear sciences in the war on cancer

incorporating such approaches into biomedical models of disease (see e.g. the reviews [ 3 – 12 ]). Mathematical “dynamical” models have already been the basis of many theoretical proposals including: tumor control [ 13 – 15 ], adaptive therapies [ 16 ], metronomic [ 17 , 18 ] or protracted [ 19 ] therapies, implementing concepts from evolutionary dynamics [ 20 – 22 ], non-Darwinian dynamics [ 23 ], therapy personalization [ 24 – 28 ], to cite a few of very many examples. In addition, the definition of quantitative measures of the disease such as novel imaging biomarkers

###### Designing optimal trajectories for a skimmer ship to clean, recover and prevent the oil spilled on the sea from reaching the coast

function considering OPT-0- (4) ) was approximately 2.413e+10. The optimal trajectories found at the end of these experiments and the distribution c w ( x ) = ∫ 0 T $\begin{array}{} \int_0^{T} \end{array}$ coef( x ) c ( τ , x )d τ , are shown in Figures 7 and 8 . c w ( x ) is a parameter that measures the weighted concentration which have been at point x through the time interval [0, T ]. The final values of the objective function (4) and the reduction in percentage of this value with respect to the scenario without pumping are given in Table 2 . In

###### A model for the operations to render epidemic-free a hog farm infected by the Aujeszky disease

transmission between herds has been described [ 3 ]. Several risk factors resulted associated with the infection in different studies. These risk factors are related to management and herd characteristics such as pig production cycle, gilts replacement, herd size, animal density, vaccination schemes, biosecurity measures. Other risk factors are related to the geographic area such as AD occurrence, animal and herd density, pig transports, pork industry, feral pigs presence [ 1 , 8 , 9 , 10 , 11 , 14 , 16 , 17 , 18 ]. The infection causes severe economic losses to