Total Number Of Resources Research Articles

Socioecological determinants of community resource utilisation among low-income women in Mexico City who experienced male-to-female intimate partner violence

ABSTRACT Women who experience intimate partner violence (IPV) face multiple barriers to seeking help from community resources, but little research has examined the impact of ecological influences on community resource utilisation among women living in low- and middle-income countries. The current study investigated individual-, relationship-, family-, and community-level influences on community resource utilisation among Mexican women experiencing IPV. Using baseline data from 950 women in Mexico City enrolled in a clinic-based randomised controlled trial, multilevel regressions were performed to assess associations between socioecological factors and women’s community resource utilisation. 41.3% women used at least one resource. At the individual-level, every additional resource that women were aware of, was associated with a 20% increase in the total number of resources used (p < .001). Every additional lethal risk factor was associated with a 5% increase in the total number of resources used (p = .004). At the family-level, women who reported having an in-law encourage IPV used 46% more resources (p < .001). At the community-level, stronger supportive norms around community resource utilisation was associated with a 6% increase in the total number of resources (p = .01). These findings suggest the importance of addressing family and community factors in the broader ecological context of Mexican women’s help-seeking behaviours.

Quicker solution for interference reduction in wireless networks

In this study, a closed-form solution is presented for the constrained water-filling problem (CWFP) where in powers allocated to the user resources maximise the user's capacity under an interference constraint and a total power constraint. Total power constraint in CWFP is to save the energy in wireless network. To solve CWFP, erstwhile algorithms compute powers for all the resources iteratively. Unlike existing algorithms, the proposed method calculates the number of resources that gets positive (or non-zero) powers using the concepts of traditional water-filling problem. Later, powers are allocated to the resolved resources (that gets positive powers) alone using the closed-form solution, which reduces the number of computations. It can be discerned that the computational complexity of the given solution is of the order of , where is the total number of resources; which is remarkably lower than that of the prior algorithms specified by an order of .

An Efficient Direct Solution of Cave-Filling Problems

Waterfilling problems subjected to peak power constraints are solved, which are known as cave-filling problems (CFP). The proposed algorithm finds both the optimum number of positive powers and the number of resources that are assigned the peak power before finding the specific powers to be assigned. The proposed solution is non-iterative and results in a computational complexity, which is of the order of M, O(M), where M is the total number of resources, which is significantly lower than that of the existing algorithms given by an order of M <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> , O(M <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> ), under the same memory requirement and sorted parameters. The algorithm is then generalized both to weighted CFP (WCFP) and WCFP requiring the minimum power. These extensions also result in a computational complexity of the order of M, O(M). Finally, simulation results corroborating the analysis are presented.

A Scalable Solution to the Wireless Personal Cloud Service Providers to Allocate Maximize Resources to Users

Cloud service providers face challenges regarding performance and pricing. Cloud service consumers need to minimize the execution time without exceeding a given budget. This leads to umpteen numbers of challenges that includes choosing a job to admit, the time t which to run them, to accomplish them in a single or multiple systems and the total number of resources to be rented to the service providers. In this paper, a three-tier cloud structures such as infrastructures vendors, service providers and consumers with Software as a Service (SaaS) are considered. The proposed algorithm is intended in such a way that it can confirm that the SaaS providers can attain the modification that takes place dynamically for customers and also mapping the client's needs to that of the parameters of the infrastructure level. A numerous service request from a number of clients has been emphasized in this paper which is called as the scheduling. A service provider takes up the wanted resources from the infrastructure of cloud vendors and makes those resources as an established service. This is done by the technique of virtual machine (VM) image. Then the instances from these VM images are created dynamically by the providers.

Design and implementing a software tool to ensure undeadlock state by perfect distribution of resources' instances among competing processes

In computer operating systems books, they explain and solve deadlock problems by declaring in advance the maximum needs of resources and their instances for each process, the total number of resources' instances, and the allocation of the resources' instances for each process. In this paper, we introduce an effective software tool to prove that it is not necessary to declare in advance the allocation of resources' instances for each process since we suggested and implement in the tool some equations to calculate and discover a suitable allocation of resources' instances to be distributed among competing processes in such a way that the computer system will never enter a deadlock state. In fact, the only necessary and sufficient conditions to solve deadlock problems are the total number of resources and their instances besides the maximum needs of resources and their instances for each process. The theory and details are explained with some examples in the contents.

Optimizing individual resource assignment using genetic algorithm

Construction activities are mostly determined by the technique known as critical path method (CPM) based on technical relationships and by resource allocation techniques which is used to examine daily resource requirement. These resource allocation techniques analyze the overall resource profile of a project without considering working timetable of any individual resource. Generally, in practice, an assigned foreman designated by a project manager will be responsible for assigning resources to a particular activity. Most of the time, this assignment is done when an activity is about to start. Therefore, working timetables of an individual resource cannot be known in advance. Although most foremen can allocate resources at low cost, there are many occasions that workers are forced to be idle between jobs or to suddenly change to different tasks. These could result in inefficiency as they affect workers’ income and their learning process. This paper proposes the use of genetic algorithm technique to assist in the search for a work plan resulting in the most cost-effective working timetable of an individual resource in a construction project with unlimited resources. In this study, the efficiency is measured in three dimensions including: the number of releases and re-hires, the number of resource idle days and the total number of resources required. To identify the most cost-effective schedule, five different schedules of a project example were generated. They are 1) early start schedule 2) late start schedule 3) min Mx schedule 4) min RRH schedule and 5) min RID schedule. Then the respective resource allocations are compared. The results show that, in the case that idle days were considered unpaid days, the Mx schedule delivered the lowest cost as well as the lowest number of resource requirement. In the case that resources were paid on idle days, the RID schedule was found to incur the lowest cost while RRH & RID schedules required the least number of total resources. Based on the study’s findings, it is recommended that, schedule analysis should be carried out with the planning of the individual resource timetable to be able to manage project resource efficiently and cost-effectively.