A Differential Privacy Budget Allocation Method Combining Privacy Security Level

Trajectory privacy protection schemes based on suppression strategies rarely take geospatial constraints into account,which is made more likely for an attacker to determine the user’s true sensitive location and trajectory.To solve this problem,this paper presents a privacy budget allocation method based on privacy security level(PSL).Firstly,in a custom map,the idea of P-series is contributed to allocate a given total privacy budget reasonably to the initially sensitive locations.Then,the size of privacy security level for sensitive locations is dynamically adjusted by comparing it with the customized initial level threshold parameterµ.Finally,the privacy budget of the initial sensitive location is allocated to its neighbors based on the relationship between distance and degree between nodes.By comparing the PSL algorithm with the traditional allocation methods,the results show that it is more flexible to allocate a privacy budget without compromising location privacy under the same preset conditions.

Optimal Budget Spending for Software Testing under the Condition of Nonlinear Constraint

Software testing is a very important phase of the software development process. It is a very difficult job for a software manager to allocate optimally the financial budget to a software project during testing. In this paper the problem of optimal allocation of the software testing cost is studied. There exist several models focused on the development of software costs measuring the number of software errors remaining in the software during testing. The purpose of this paper is to use these models to formulate the optimization problems of resource allocation: Minimization of the total number of software errors remaining in the system. On the assumption that a software project consists of some independent modules, the presented approach extends previous work by defining new goal functions and extending the primary assumption and precondition.

Financing Disaster Risk Reduction:Exploring the Opportunities,Challenges,and Threats Within the Southern African Development Community Region

The Southern African Development Community(SADC)region,a regional economic body comprised of 16 member states,is one of our planet's most vulnerable regions to natural hazards,and has a complex disaster risk profile.The region has sustained several disasters over the past decades.These events include annual floods in 2004-2019 and extreme droughts(1990-1993);other climate-induced disasters,such as cyclones,also have had devastating impacts,particularly on the Indian Ocean island states and east coast countries.To reduce the risk and impacts of dis asters,governments must invest in disaster risk reduction(DRR).However,interventions aimed at reducing social and economic vulnerability and investing in longterm mitigation activities are often few,poorly funded,and insignificant in comparison with money spent on humanitarian assistance,dis aster relief,and post-disaster reconstruction.This study investigated whether DRR is adequately funded within SADC member states in light of the high stakes in human life,infrastructure,and economic losses and the potential savings involved.The study applied a qualitative research design with data collected through semistructured interviews and focus group discussions.Respondents were selected purposefully and through snowball sampling with a total of 67 respondents from Botswana,Eswatini,Namibia,South Africa,and Zimbabwe participating in the study.The study findings reveal that DRR is inadequately funded in all the member states consulted in comparison to funding allocated to disaster response.In light of the underfunding experienced by DRR activities,this study provides a platform for lobbying and advocacy for adequate funding for DRR.

Different challenges,different approaches and related expenditures of communitybased tuberculosis activities by international non-governmental organizations in Myanmar

Background:International non-governmental organizations(INGOs)have been implementing community-based tuberculosis(TB)care(CBTBC)in Myanmar since 2011.Although the National TB Programme(NTP)ultimately plans to take over CBTBC,there have been no evaluations of the models of care or of the costs of providing CBTBC in Myanmar by INGOs.Methods:This was a descriptive study using routinely-collected programmatic and financial data from four INGOs during 2013 and 2014,adjusted for inflation.Data analysis was performed from the provider perspective.Costs for sputum examination were not included as it was provided free of charge by NTP.We calculated the average cost per year of each programme and cost per patient completing treatment.Results:Four INGOs assisted the NTP by providing CBTBC in areas where access to TB services was challenging.Each INGO faced different issues in their contexts and responded with a diversity of strategies.The total costs ranged from US$140754 to US$550221 during the study period.The cost per patient completing treatment ranged from US$215 to US$1076 for new cases and US$354 to US$1215 for retreatment cases,depending on the targeted area and the package of services offered.One INGO appeared less costly,more sustainable and patient oriented than others.Conclusions:This study revealed a wide variety of models of care and associated costs for implementing CBTBC in diverse and challenging populations and contexts in Myanmar.Consequently,we recommend a more comprehensive evaluation,including development of a cost model,to estimate the costs of scaling up CBTBC country-wide,and cost-effectiveness studies,to best inform the NTP as it prepares to takeover CBTBC activities from INGOs.While awaiting evidence from these studies,model of CBTBC that have higher sustainability potential and allocate more resources to patient-centered care should be given priority support.

Stochastic systems simulation optimization

With the advance of new computational technology,stochastic systems simulation and optimization has become increasingly a popular subject in both academic research and industrial applications.This paper presents some of recent developments about the problem of optimizing a performance function from a simulation model.We begin by classifying different types of problems and then provide an overview of the major approaches,followed by a more in-depth presentation of two specific areas:optimal computing budget allocation and the nested partitions method.