11351 research outputs found
Sort by
Efficiently discovering users connectivity with local information in online social networks
No full textPeople\u27s activities in Online Social Networks (OSNs) have generated a massive volume of data to which tremendous attention has been paid in academia and industry. With such data, researchers and third-parties can analyze human beings’ behaviors in social communities and develop more user-friendly services and applications to meet people\u27s needs. However, often times, they face a big challenge of acquiring the data, as the access to such data is restricted by their collectors (e.g., Facebook and Twitter), due to various reasons, such as their user\u27s privacy. In this paper, we intend to shed light on leveraging limited local social network topological properties to effectively and efficiently conduct search in OSNs. The problem we focus on is to discover the connectivity of a group of target users in an OSN, particularly from the perspective of a third-party analyst who does not have full access to the network. For the analyst, even discovering a user\u27s local connections requires issuing a query through OSN APIs (e.g., Facebook Friendlist API or Twitter Followerlist API). We develop searching techniques which demand only a few number of queries for the connectivity discovery. After conducting an intensive set of experiments on both real-world and synthetic data sets, we found that our proposed techniques perform as well as the centralized detection algorithm, which assumes the availability of the entire data set, in terms of the size of the discovered subgraph connecting all target users as well as the number of queries made in the search. The experiment results demonstrate the effectiveness of incorporating topological properties of social networks into searching in the OSNs
Evaluating planning strategies for prioritizing projects in sustainability improvement programs
No full textPrograms to improve the sustainability of building infrastructures often consist of project portfolios that need to be prioritized in an appropriate chronological fashion to maximize the program’s benefits. This is particularly important when a revolving-fund approach is used to leverage savings from the initial projects to pay for later improvements. The success of the revolving-fund approach is dependent on the appropriate prioritization of projects. Competing performance measures and scarce resources make this task of project prioritization during the planning stage a complex and challenging endeavour. The current study examined the impact of different project prioritization strategies for revolving-fund sustainability program performance. A novel modeling approach for sustainability decision-analysis was developed using the system dynamics method, and the model was calibrated using a campus sustainability improvement program at a major university. The model was applied to evaluate the effects of five common project-prioritization strategies on three program-performance measures, across a wide range of initial investment levels. For the university case study, we found that the strategy of prioritizing projects according to decreasing benefit/cost ratio performed best. The research demonstrated that using a system dynamics model can allow sustainability program managers to make better-informed sequencing decisions, leading to a financially and environmentally successful program implementations
Energy of a finite three-dimensional electron gas of spinless electrons
No full textWe study a finite three-dimensional electron gas system consisting of an arbitrary number of electrons embedded in a finite cubic domain. The electrons are treated as spinless particles implying that the system under consideration represents a fully spin-polarized Fermi quantum phase of electrons. The cubic region is uniformly filled with a positive background that ensures overall charge neutrality. We apply a Hartree-Fock approach that starts with a Slater determinant wave function of normalized plane wave orbitals. The treatment enables us to obtain the energy per particle of the finite system at any given number of electrons. The potential (exchange) energy is conveniently obtained by simplifying the calculation of the ensuing two-particle integrals over the finite cubic domain in terms of expressions that involve compact analytic auxiliary functions. Results are provided for both the kinetic and potential energy per particle for various numbers of electrons. It is shown that the kinetic and the potential energy per particle converge towards their bulk thermodynamic limit values in a non-monotonic way as a function of the number of particles. The results derived may apply to finite systems of delocalized electrons in alkali metal nanoclusters in which the positive ionic core is approximated as a cubic jellium region
Identification of Phytotoxic Levels of Copper and Nickel in Commercial Organic Soil Amendments Recycled from Poultry Farms and Municipal Wastes
No full textCommercial-scale recycling of agricultural and municipal wastes into organic soil amendments facilitates safe disposal of waste and reduces environmental contamination. However, phytotoxicity of commercial organic amendments to crops is a major concern to farmers. Consistent with this, commercial chicken manure and Milorganite (recycled from municipal waste) were found to be phytotoxic. Chicken manure aqueous extract contains 10.8 ppm Cu and 0.7 ppm Ni. The level of Cu and Ni in Milorganite is lower. The current study identified an aqueous solution containing 5 ppm Cu, lower than in chicken manure aqueous extract, was highly phytotoxic to mustard seeds germination. Therefore, phytotoxicity of chicken manure is in part due to Cu. An aqueous solution containing 1 ppm Ni was not phytotoxic; whereas 0.125 ppm Ni was phytotoxic when 62.5 ppm Na, which is nontoxic, was added to the solution. Therefore, synergistic effects of chemicals in the organic amendments may induce phytotoxicity
Soil CO2 emission in response to organic amendments, temperature, and rainfall
No full textVegetated land surfaces play an important role in determining the fate of carbon in the global carbon cycle. However, our understanding of the terrestrial biosphere on a global scale is subject to considerable uncertainty, especially concerning the impacts of climatic variables on the carbon cycle. Soil is a source and also a sink of CO2 exchange and helps in carbon sequestration. Agricultural management practices influence soil water dynamics, as well as carbon cycling by changing soil CO2 emission and uptake rates. The rate of soil CO2 emission varies for different crops and different organic amendments. The major goal of this study was to assess the impacts of the type and rate of organic amendment on soil CO2 emission in a collard greens crop grown in the southeast Texas environment. Thirty-six plots were developed to grow collard greens on Prairie View A&M University’s Research Farm. Three types of organic amendments (Chicken manure, Dairy manure, and Milorganite), at four levels of application (0, 168, 336, and 672 kg N/ha) were used and replicated three times. Each organic amendment type was applied to nine randomly selected plots. Three random plots were used as a control in each row. We measured daily soil CO2 emission for the first two weeks and every other day in a week during the experiment. We evaluated the effects of organic amendments and the application rates on soil CO2 emission for collard greens during two growing seasons. The results showed higher the application rates for each organic amendment, higher the CO2 emissions from the soil. The results also showed higher cumulative CO2 emissions for the soils amended with chicken manure and milorganite, but lowest for the soils amended with dairy manure. This field experiment and analyses help better understand the temporal and spatial variations of soil CO2 emission, and also help to develop best management practices to maximize carbon sequestration and to minimize soil CO2 emissions during the growth periods of collard greens under changing temperatures using different organic amendments, and application rates
The Binomial Transform of P-Recursive Sequences And the Dilogarithm Function
Get PDFUsing a generalized binomial transform and a novel binomial coefficient identity, we will show that the set of p-recursive sequences is closed under the binomial transform. Using these results, we will derive a new series representation for the dilogarithm function that converges on its domain of analyticity. Finally, we will show that this series representation results in a scheme for numerical evaluation of the dilogarithm function that is accurate, efficient, and stable
Estimation of Transmission Dynamics of COVID-19 in India: The Influential Saturated Incidence Rate
Get PDFA non-linear SEIR mathematical model for coronavirus disease in India has been proposed, by incorporating the saturated incidence rate on the occurrence of new infections. In the model, the threshold quantity known as the reproduction number is evaluated which determines the stability of disease-free equilibrium and the endemic equilibrium points. The disease-free equilibrium point becomes globally asymptotically stable when the corresponding reproduction number is less than unity, whereas, if it is greater than unity then the endemic equilibrium point comes into existence, which is locally asymptotically stable under certain restrictions on the parameters value in the model. The impact of various parameters on the threshold quantity is signified by the sensitivity analysis. Numerical results imply that by implementing and strictly following the prevention measures a rapid reduction in the reproduction number for COVID-19 can be observed, through which the coronavirus disease can be controlled
An Efficient Algorithm for Numerical Inversion of System of Generalized Abel Integral Equations
Get PDFIn this article a direct method is introduced, which is based on orthonormal Bernstein polynomials, to present an efficient and stable algorithm for numerical inversion of the system of singular integral equations of Abel type. The appropriateness of earlier numerical inversion methods was restricted to the one portion of singular integral equations of Abel type. The proposed method is absolutely accurate, and numerical illustrations are given to show the convergence and utilization of the suggested method and comparisons are made with some other existing numerical solution
On Higher-order Duality in Nondifferentiable Minimax Fractional Programming
Get PDFIn this paper, we consider a nondifferentiable minimax fractional programming problem with continuously differentiable functions and formulated two types of higher-order dual models for such optimization problem.Weak, strong and strict converse duality theorems are derived under higherorder generalized invexity
Integrated Farm Model for Optimal Allocation of Resources- A Linear Programming Approach
Get PDFThe mathematical model for optimal allocation of farm resources, especially land and water are proposed to optimize the resources that contribute to increase farm revenues. A study is being carried out, to analyze the cropping practice adopted by growers, depending on availability and accessibility of resources. Different crop-combinations and cropping patterns are being analyzed in districts of Rajasthan. Rajasthan has arid topography with varying weather conditions. Thus, a diverse crop variety is being cultivated in a region. Being a state with inadequate water resources, the formulated model proposed different crop combinations alternatives. A crop-mix model is developed to reduce the input cost and maximize farm revenues. The Multi-Objective Linear Programming approach is applied to determine the feasibility of decision variables. The model solution lies within the feasible region; hence, it must be in the convex hull of previous year planting decisions. Consequently, the model finds an optimal crop combination to optimize the objective function under prevailing climatic conditions. To avoid the uncertainties involved in sector some of the farm parameters such as climatic and market fluctuations were kept constant. The model solution is achieved by imposing constraints, that limit the decision variables within the feasible range. LINGO 18.0 Software is used to determine the optimal values of the decision variables