A Hybrid Model for Improving Software Cost Estimation in Global Software Development

Accurate software cost estimation in Global Software Development(GSD)remains challenging due to reliance on historical data and expert judgments.Traditional models,such as the Constructive Cost Model(COCOMO II),rely heavily on historical and accurate data.In addition,expert judgment is required to set many input parameters,which can introduce subjectivity and variability in the estimation process.Consequently,there is a need to improve the current GSD models to mitigate reliance on historical data,subjectivity in expert judgment,inadequate consideration of GSD-based cost drivers and limited integration of modern technologies with cost overruns.This study introduces a novel hybrid model that synergizes the COCOMO II with Artificial Neural Networks(ANN)to address these challenges.The proposed hybrid model integrates additional GSD-based cost drivers identified through a systematic literature review and further vetted by industry experts.This article compares the effectiveness of the proposedmodelwith state-of-the-artmachine learning-basedmodels for software cost estimation.Evaluating the NASA 93 dataset by adopting twenty-six GSD-based cost drivers reveals that our hybrid model achieves superior accuracy,outperforming existing state-of-the-artmodels.The findings indicate the potential of combining COCOMO II,ANN,and additional GSD-based cost drivers to transform cost estimation in GSD.

Resource Management in UAV Enabled MEC Networks

Mobile edge cloud networks can be used to offload computationally intensive tasks from Internet of Things(IoT)devices to nearby mobile edge servers,thereby lowering energy consumption and response time for ground mobile users or IoT devices.Integration of Unmanned Aerial Vehicles(UAVs)and the mobile edge computing(MEC)server will significantly benefit small,battery-powered,and energy-constrained devices in 5G and future wireless networks.We address the problem of maximising computation efficiency in U-MEC networks by optimising the user association and offloading indicator(OI),the computational capacity(CC),the power consumption,the time duration,and the optimal location planning simultaneously.It is possible to assign some heavy tasks to the UAV for faster processing and small ones to the mobile users(MUs)locally.This paper utilizes the k-means clustering algorithm,the interior point method,and the conjugate gradient method to iteratively solve the non-convex multi-objective resource allocation problem.According to simulation results,both local and offloading schemes give optimal solution.

A Reliable Stochastic Numerical Analysis for Typhoid Fever Incorporating With Protection Against Infection

In this paper,a reliable stochastic numerical analysis for typhoid fever incorporating with protection against infection has been considered.We have compared the solutions of stochastic and deterministic typhoid fever model.It has been shown that the stochastic typhoid fever model is more realistic as compared to the deterministic typhoid fever model.The effect of threshold number T*hold in stochastic typhoid fever model.The proposed framework of the stochastic non-standard finite difference scheme(SNSFD)preserves all dynamical properties like positivity,bounded-ness and dynamical consistency defined by Mickens,R.E.The stochastic numerical simulation of the model showed that increase in protection leads to low disease prevalence in a population.

Numerical Simulations for Stochastic Computer Virus Propagation Model

We are presenting the numerical simulations for the stochastic computer virus propagation model in this manuscript.We are comparing the solutions of stochastic and deterministic computer virus models.Outcomes of a threshold number R0 hold in stochastic computer virus model.If R_(0)<1 then in such a condition virus controlled in the computer population while R_(0)>1 shows virus rapidly spread in the computer population.Unfortunately,stochastic numerical techniques fail to cope with large step sizes of time.The suggested structure of the stochastic non-standard finite difference technique can never violate the dynamical properties.On this basis,we can suggest a collection of strategies for removing virus’s propagation in the computer population.