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This chapter investigates the impacts of households’ residential self-selection, parents’ perceptions and travel patterns on their children’s daily travel mode shares, among single parent households.

To capture the complexity of the relationships between parent and children daily travel mode choices, an integrated model structure is introduced and the model estimated with simultaneous equation modelling.

The results show that, beside the daily activity-travel engagements of the parent, both parent’s perceptions and his/her residential self-selection reasons play significant roles in influencing their children daily travel mode shares. The parent’s perceptions play more significant roles in influencing children’s travel modes shares, whilst the residential self-selection reasons have more significant influence on the parent’s travel mode choice.

The finding of this study reveals a fact that wherever the children live, their travel behaviour tend to be ‘neutral’ and open to influence by their parents throughout their childhood.

This study adds to our understanding of the interactions between parents’ attitudes and behaviours with their children’s travel patterns. This study focuses on single parent households, on which there is very little literature.

Drawing on accounts from 22 lesbian couples with children conceived using donor insemination, this chapter explores how the respondents’ selection of parent terms, such as “momma” and “mommy,” influences day-to-day negotiation of parenthood. Term selection was affected by personal meanings respondents associated with terms as well as how they anticipated terms would be publicly received. Couples utilized personalized meanings associated with terms, such as terms used by families of origin or reflected in a parent’s cultural background, to help non-biological mothers feel comfortable and secure in their parenting identities. Some families also avoided terms that non-biological mothers associated too strongly with biological motherhood and felt uncomfortable using for themselves. Families also considered whether parent terms, and subsequently their relationships to their children, would be recognizable to strangers or cause undue scrutiny to their family. However, not all of the families selected terms that were easily decipherable by strangers and had to negotiate moments in which the personal meanings and public legibility of terms came into conflict. Overall, these accounts illustrate the importance of parent terms for lesbian-parent families, and other nontraditional families, as a family practice negotiating both deeply personal meanings surrounding parent–child relationships and how these terms, and the families, are normatively recognizable in public spaces.

Routing protocol for low-power lossy network (RPL) being the de facto routing protocol used by low power lossy networks needs to provide adequate routing service to mobile nodes (MNs) in the network. As RPL is designed to work under constraint power requirements, its route updating frequency is not sufficient for MNs in the network. The purpose of this study is to ensure that MNs enjoy seamless connection throughout the network with minimal handover delay.

This study proposes a load balancing mobility aware secure hybrid – RPL in which static node (SN) identifies route using metrics like expected transmission count, and path delay and parent selection are further refined by working on remaining energy for identifying the primary route and queue availability for secondary route maintenance. MNs identify route with the help of smart timers and by using received signal strength indicator sampling of parent and neighbor nodes. In this work, MNs are also secured against rank attack in RPL.

This model produces favorable result in terms of packet delivery ratio, delay, energy consumption and number of living nodes in the network when compared with different RPL protocols with mobility support. The proposed model reduces packet retransmission in the network by a large margin by providing load balancing to SNs and seamless connection to MNs.

In this work, a novel algorithm was developed to provide seamless handover for MNs in network. Suitable technique was developed to provide load balancing to SNs in network by maintaining appropriate secondary route.

This paper considers a so far unappreciated sector of the labour market – lone parents. The number of lone parents has increased dramatically in recent years. Consideration of lone parents allows for a discussion of two key issues within the contemporary labour market: the attempts by government to increase the number of lone parents in work; and relatedly, governmental initiatives which have sought to reform the tax and benefit system to make work more attractive and also address the need for work‐life balance for parents. The paper considers these issues by reporting a small‐scale piece of research that sought to address the viability of the supermarket sector as a suitable employer for lone parents. The results suggest that the increasing numbers of students entering the labour market means that supermarkets are unlikely to consider lone parents as an important, discrete source of labour.

Genetic algorithms are a class of non‐deterministic algorithms that derive from Darwinian evolution and that provide good, though not necessarily optimal, solutions to combinatorial problems. We describe their application to the identification of characteristics that occur approximately equifrequently in a database, using two different methods for the creation of the chromosome data structures that lie at the heart of a genetic algorithm. Experiments with files of English and Turkish text suggest that the genetic algorithm developed here can produce results superior to those produced by existing non‐deterministic algorithms; however, the results are inferior to those produced by an existing deterministic algorithm.

The purpose of this paper is to investigate the predicting roles of extension naming strategies and categorical fit on the transfer of brand personality from a parent brand to its extension brand. Extension naming strategies include direct and indirect naming, while categorical fit is the similarity between an extended product and its parent brand's cognitive category. Further, the interaction effect and the relative effectiveness of various combinations of the two predictors when determining brand personality transfer are also explored.

A 2×2 factorial between‐subject experimental design with one covariate is used to test the proposed hypotheses. The experiment involves 242 participants from a university in Taiwan.

The findings show that consumers perceive higher brand personality transfer when a direct naming strategy is applied or when the parent brand extends to a high perceived fit product. The former is the dominant predictor of brand personality transfer. There also exists an interaction effect between extension naming strategies and categorical fit. Specifically, consumers perceive the highest brand personality transfer when a direct naming strategy is applied for a high fit extended product. Moreover, the use of a direct naming strategy for an extended product with a low categorical fit still leads to a higher degree of parent brand personality than both the other cases in which an indirect naming strategy is applied for either high or low fit extended products. Furthermore, irrespective of the degree of categorical fit, the transfer of brand personality is low when an indirect naming strategy is applied.

The current research is pioneer work in identifying the determinants of brand personality transfer. It also notes the interaction effect and the relative effectiveness of the determinants.

In this paper, we propose that the “powerful and privileged” sustain their way of life through greed and they sustain the lives of others through trickledown sharing. Greed provides the powerful and privileged a buffer against famine. Trickledown sharing provides them a buffer against predation or war. The inspiration for this integration of greed and trickledown sharing as self-preservation strategies is a multi-selection model called skew selection. According to skew selection, when perennial organisms are subjected to cycles of famine and predation, greed and trickledown sharing increases the organism’s survival relative to a greed-only strategy. Skew selection is extended to explain greed and trickledown sharing among humans through the introduction of mogul games. The results of mogul games reported herein suggest that inequality is an emergent property of self-organizing systems and potentially an essential precursor to the evolution of social behavior. In the future, it is our hope that mogul game simulations will be employed by others to explore the effect of variation in cycles of predation and resource abundance on the rules of greed (resource acquisition) and trickledown sharing (resources redistribution).

A reproductive plan is a type of adaptive procedure devised by Holland which embodies many principles found in the adaptation of natural systems through evolution. This study develops a reproductive meta‐plan, an adaptive procedure that controls the modification of parameter values in a reproductive plan. After a brief review of Holland's formalization of reproductive plans, a non‐reproductive meta‐plan devised by Cavicchio is discussed. In response to some of the limitations of Cavicchio's approach, a reproductive meta‐plan is developed. Experiments with computer implementations of both meta‐plans show improvement in a reproductive plan's utility gain when the reproductive meta‐plan is used.

This paper aims to provide a prolonging network lifetime and optimizing energy consumption in mobile wireless sensor networks (MWSNs). MWSNs have characteristics of dynamic topology due to the factors such as energy consumption and node movement that lead to create a problem in lifetime of the sensor network. Node clustering in wireless sensor networks (WSNs) helps in extending the network life time by reducing the nodes’ communication energy and balancing their remaining energy. It is necessary to have an effective clustering algorithm for adapting the topology changes and improve the network lifetime.

This work consists of two centralized dynamic genetic algorithm-constructed algorithms for achieving the objective in MWSNs. The first algorithm is based on improved Unequal Clustering-Genetic Algorithm, and the second algorithm is Hybrid K-means Clustering-Genetic Algorithm.

Simulation results show that improved genetic centralized clustering algorithm helps to find the good cluster configuration and number of cluster heads to limit the node energy consumption and enhance network lifetime.

In this work, each node transmits and receives packets at the same energy level throughout the solution. The proposed approach was implemented in centralized clustering only.

The main reason for the research efforts and rapid development of MWSNs occupies a broad range of circumstances in military operations.

The research highly gains impacts toward mobile-based applications.

A new fitness function is proposed to improve the network lifetime, energy consumption and packet transmissions of MWSNs.

Wireless sensor networks are expected to be an integral part of any pervasive computing environment. This implies an ever‐increasing need for efficient energy and resource management of both the sensor nodes, as well as the overall sensor network, in order to meet the expected quality of data and service requirements. There have been numerous studies that have looked at the routing of data in sensor networks with the sole intention of reducing communication power consumption. However, there has been comparatively little prior art in the area of multi‐criteria based routing that exploit both the semantics of queries and the state of sensor nodes to improve network service longevity. In this paper, we look at routing in sensor networks from this perspective and propose an adaptive multi‐criteria routing protocol. Our algorithm offers automated reconfiguration of the routing tree as demanded by variations in the network state to meet application service requirements. Our experimental results show that our approach consistently outperforms, in terms of Network Lifetime and Coverage, the leading semantic‐based routing algorithm which reconfigures the routing tree at fixed periods.