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The purpose of this paper is to test the capability of a new population‐based optimization algorithm for solving an NP‐hard problem, called “Multiple Knapsack Problem”, or MKP.

Here, the intelligent water drops (IWD) algorithm, which is a population‐based optimization algorithm, is modified to include a suitable local heuristic for the MKP. Then, the proposed algorithm is used to solve the MKP.

The proposed IWD algorithm for the MKP is tested by standard problems and the results demonstrate that the proposed IWD‐MKP algorithm is trustable and promising in finding the optimal or near‐optimal solutions. It is proved that the IWD algorithm has the property of the convergence in value.

This paper introduces the new optimization algorithm, IWD, to be used for the first time for the MKP and shows that the IWD is applicable for this NP‐hard problem. This research paves the way to modify the IWD for other optimization problems. Moreover, it opens the way to get possibly better results by modifying the proposed IWD‐MKP algorithm.

The purpose of this paper is to calculate the back scattering response from single, finite and infinite arrays of nonlinear antennas like the case where the antennas are exposed to high-value signals such as lightning strokes.

In this paper, the authors have used a recently introduced optimization technique called intelligent water drop.

The results exhibit that the method used by the authors is faster and more accurate than other conventional optimization algorithms, i.e. particle swarm optimization and genetic algorithm.

A new optimization algorithm is used to solve nonlinear problem accurately and sufficiently. Although the technique is not confined to the mentioned examples in the paper, it can be applied to other nonlinear circuits.

User requests over the cloud are not achievable with one single service, multiple services need to be executed to fulfill what a user asks for. Typically, such services are composed and presented as one global service. Moreover, the same operation can be achieved by multiple services available at different clouds, which can result in different possibilities in composing them. This paper aims to decrease the number of clouds involved in the composition process, so that user requests are satisfied with minimal cost (communication costs, execution time and financial charges).

This paper investigates the use of an intelligent water drops (IWDs) optimization-based algorithm, and an integer linear programming model to optimize the number of cloud bases involved in the composition process. A comparison of the solutions found by these two techniques is presented in the paper.

The obtained results show that the number of cloud bases can be decreased without affecting user satisfaction.

The paper is a first attempt to use the IWDs algorithm for service composition, tested with big-size data.

This chapter reflects on xCHANGE, a month-long festival marking International Women's Day (IWD) at Birmingham City University, UK. The author first problematizes expectations of IWD and then outlines the origins of the festival, detailing both practical aspects and program content. The chapter then considers the festival through a lens of “power geometry” (Massey, 1993) in which female academics are positioned in distinct ways in relation to flows and interconnections of power within the university. Does the xCHANGE festival disrupt or merely reflect this power geometry? Does it create conditions for women to thrive in academia?

The concept of business process (BP) as a service is a new solution in enterprises for the purpose of using specific BPs. BPs represent combinations of software services that must be properly executed by the resources provided by a company’s information technology infrastructure. As the policy requirements are different in each enterprise, processes are constantly evolving and demanding new resources in terms of computation and storage. To support more agility and flexibility, it is common today for enterprises to outsource their processes to clouds and, more recently, to cloud federation environment. Ensuring the optimal allocation of cloud resources to process service during the execution of workflows in accordance with user policy requirements is a major concern. Given the diversity of resources available in a cloud federation environment and the ongoing process changes required based on policies, reallocating cloud resources for service processing may lead to high computational costs and increased overheads in communication costs.

This paper presents a new adaptive resource allocation approach that uses a novel algorithm extending the natural-based intelligent water drops (IWD) algorithm that optimizes the resource allocation of workflows on the cloud federation which can estimate and optimize final deployment costs. The proposed algorithm is implemented and embedded within the WokflowSim simulation toolkit and tested in different simulated cloud environments with different workflow models.

The algorithm showed noticeable enhancements over the classical workflow deployment algorithms taking into account the challenges of data transfer. This paper made a comparison between the proposed IWD-based workflow deployment (IWFD) algorithm with other proposed algorithms. IWFD presented considerable improvements in the makespan, cost and data transfer in most situations in the cloud federation environment.

An extension for WorkflowSim to support the implementation of BPs in a federation cloud space regarding BP policy. Optimize workflow execution performance in Federated clouds by means of IWFD algorithm.

This paper aims to predict the traffic and helps to find a solution. Unpredictable traffic leads more vehicles on the road. The result of which is one of the factors that aggravate traffic congestion. Traffic congestion occurs when the available transport resources are less when compared to the number of vehicles that share the resource. As the number of vehicles increases the resources become scarce and congestion is more.

The population of the urban areas keeps increasing as the people move toward the cities in search of jobs and a better lifestyle. This leads to an increase in the number of vehicles on the road. However, the transport network, which is accessible to the citizens is less when compared to their demand.

The demand for resources is higher than the actual capacity of the roads and the streets. There are some circumstances, which will aggravate traffic congestion. The circumstances can be the road condition (pot holes and road repair), accidents and some natural calamities.

There is a lot of research being done to predict the traffic and model it to find a solution, which will make the condition better. However, still, it is an open issue. The accuracy of the predictions done is less.

In this chapter, we examine historical and contemporary debates about the position and situation of women in Myanmar (and to a lesser extent gender and sexual minorities). Specific reference is made to the patriarchal character of the military coup of February 1, 2021, and the emergent forms of feminist resistance that turned social norms inside out in protest against lethal repression. The way women, as well as sexual and gender minorities, are unequally positioned and face structural and social discrimination in society serves to contextualize our presentation of the findings of a collaborative case-study conducted in 2018 on issues pertaining to gender and imprisonment in Myanmar, based mainly on interviews with former prisoners in three research sites. The aim was to generate field-based knowledge about the carceral experiences of women and LGBTQIA+ persons in Myanmar – focusing on their needs and vulnerabilities, their capacities and rights, their relationships and identities, and their modes of survival as they encounter penal regimes. Findings are summarized focusing on former prisoners’ experiences of legal bias; perspectives on encounters with the criminal justice system; the inadequacy of health provision (posed as lethal neglect); and the way certain behaviors and identities are criminalized. The chapter concludes with some reflections on the degree to which there might still be space for critical scholarship in the post-coup world and poses some questions for future research.

Distribution. The purpose of this study is to obtain the modified maximum likelihood estimator of stress–strength model using the ranked set sampling, to obtain the asymptotic and bootstrap confidence interval of P[Y < X], to compare the performance of author’s estimates with the estimates under simple random sampling and to apply author’s estimates on head and neck cancer.

The maximum likelihood estimator of R = P[Y < X], where X and Y are two independent inverse Weibull random variables common shape parameter that affect the shape of the distribution, and different scale parameters that have an effect on the distribution dispersion are given under ranked set sampling. Together with the asymptotic and bootstrap confidence interval, Monte Carlo simulation shows that this estimator performs better than the estimator under simple random sampling. Also, the asymptotic and bootstrap confidence interval under ranked set sampling is better than these interval estimators under simple random sampling. The application to head and neck cancer disease data shows that the estimator of R = P[Y < X] that shows the treatment with radiotherapy is more efficient than the treatment with a combined radiotherapy and chemotherapy under ranked set sampling that is better than these estimators under simple random sampling.

The ranked set sampling is more effective than the simple random sampling for the inference of stress-strength model based on inverse Weibull distribution.

This study sheds light on the author’s estimates on head and neck cancer.