QoS guarantee with adaptive transmit power and message rate control for DSRC vehicle network based road safety applications

Quality of services (QoS) support is critical for dedicated short range communications (DSRC) vehicle networks based collaborative road safety applications. In this paper we propose an adaptive power and message rate control method for DSRC vehicle networks at road intersections. The design objective is to provide high availability and low latency channels for high priority emergency safety applications while maximizing channel utilization for low priority routine safety applications. In this method an offline simulation based approach is used to find out the best possible configurations of transmit power and message rate for given numbers of vehicles in the network. The identified best configurations are then used online by roadside access points (AP) according to estimated number of vehicles. Simulation results show that this adaptive method significantly outperforms a fixed control method. © 2011 Springer-Verlag.

Disabling a family? Emotional dilemmas experienced in becoming a parent of a child with learning disabilities

Becoming the parent of a child diagnosed with learning disabilities can have a dramatic impact. Chrissie Rogers, the author of this article, is both a lecturer in education studies at Keele University and the mother of a daughter who has learning disabilities. She argues here that the pressures on mothers to produce ‘perfect’ babies and to meet all their needs are immense. These pressures arise from both internalised norms and societal expectations and, in the face of these pressures, parents may feel shock, loss and disappointment. These feelings may lead, in turn, to denial, anxiety and conflict affecting both the parents and the professionals involved with the family. Drawing on a series of in-depth interviews and personal narratives, Chrissie Rogers makes a powerful case for the importance of support, whether that support is formal or informal. She suggests that, without the right levels of support and understanding, having a child with a diagnosis of learning disability can disable the whole family.

Networks of Evolutionary Processors (NEP) as Decision Support Systems

This paper presents the application of Networks of Evolutionary Processors to Decision Support Systems, precisely Knowledge-Driven DSS. Symbolic information and rule-based behavior in Networks of Evolutionary Processors turn out to be a great tool to obtain decisions based on objects present in the network. The non-deterministic and massive parallel way of operation results in NP-problem solving in linear time. A working NEP example is shown.

Indirect ties in knowledge networks:a social network analysis with ordered weighted averaging operators

This PhD thesis analyses networks of knowledge flows, focusing on the role of indirect ties in the knowledge transfer, knowledge accumulation and knowledge creation process. It extends and improves existing methods for mapping networks of knowledge flows in two different applications and contributes to two stream of research. To support the underlying idea of this thesis, which is finding an alternative method to rank indirect network ties to shed a new light on the dynamics of knowledge transfer, we apply Ordered Weighted Averaging (OWA) to two different network contexts. Knowledge flows in patent citation networks and a company supply chain network are analysed using Social Network Analysis (SNA) and the OWA operator. The OWA is used here for the first time (i) to rank indirect citations in patent networks, providing new insight into their role in transferring knowledge among network nodes; and to analyse a long chain of patent generations along 13 years; (ii) to rank indirect relations in a company supply chain network, to shed light on the role of indirectly connected individuals involved in the knowledge transfer and creation processes and to contribute to the literature on knowledge management in a supply chain. In doing so, indirect ties are measured and their role as means of knowledge transfer is shown. Thus, this thesis represents a first attempt to bridge the OWA and SNA fields and to show that the two methods can be used together to enrich the understanding of the role of indirectly connected nodes in a network. More specifically, the OWA scores enrich our understanding of knowledge evolution over time within complex networks. Future research can show the usefulness of OWA operator in different complex networks, such as the on-line social networks that consists of thousand of nodes.

A decision support system for waste collection management and its potential improvement with Radio-Frequency Identification Technology (RFID)

Due to vigorous globalisation and product proliferation in recent years, more waste has been produced by the soaring manufacturing activities. This has contributed to the significant need for an efficient waste management system to ensure, with all efforts, the waste is properly treated for recycling or disposed. This paper presents a Decision Support System (DSS) framework, based on Constraint Logic Programming (CLP), for the collection management of industrial waste (of all kinds) and discusses the potential employment of Radio-Frequency Identification Technology (RFID) to improve several critical procedures involved in managing waste collection. This paper also demonstrates a widely distributed and semi-structured network of waste producing enterprises (e.g. manufacturers) and waste processing enterprises (i.e. waste recycling/treatment stations) improving their operations planning by means of using the proposed DSS. The potential RFID applications to update and validate information in a continuous manner to bring value-added benefits to the waste collection business are also presented. © 2012 Inderscience Enterprises Ltd.

An empirical examination of emotional and cognitive responses to threat appeals

Advertising and other forms of communications are often used by government bodies, non-government organisations, and other institutions to try to influence the population to either a) reduce some form of harmful behaviour (e.g. smoking, drunk- driving) or b) increase some more healthy behaviour (e.g. eating healthily). It is common for these messages to be predicated on the chances of some negative event occurring if the individual does not either a) stop the harmful behaviour, or b) start / increase the healthy behaviour. This design of communication is referred to by many names in the relevant literature, but for the purposes of this thesis, will be termed a ‘threat appeal’. Despite their widespread use in the public sphere, and concerted academic interest since the 1950s, the effectiveness of threat appeals in delivering their objective remains unclear in many ways. In a detailed, chronological and thematic examination of the literature, two assumptions are uncovered that have either been upheld despite little evidence to support them, or received limited attention at all, in the literature. Specifically, a) that threat appeal characteristics can be conflated with their intended responses, and b) that a threat appeal always and necessarily evokes a fear response in the subject. A detailed examination of these assumptions underpins this thesis. The intention is to take as a point of departure the equivocality of empirical results, and deliver a novel approach with the objective of reducing the confusion that is evident in existing work. More specifically, the present thesis frames cognitive and emotional responses to threat appeals as part of a decision about future behaviour. To further develop theory, a conceptual framework is presented that outlines the role of anticipated and anticipatory emotions, alongside subjective probabilities, elaboration and immediate visceral emotions, resultant from manipulation of the intrinsic message characteristics of a threat appeal (namely, message direction, message frame and graphic image). In doing so, the spectrum of relevant literature is surveyed, and used to develop a theoretical model which serves to integrate key strands of theory into a coherent model. In particular, the emotional and cognitive responses to the threat appeal manipulations are hypothesised to influence behaviour intentions and expectations pertaining to future behaviour. Using data from a randomised experiment with a sample of 681 participants, the conceptual model was tested using analysis of covariance. The results for the conceptual framework were encouraging overall, and also with regard to the individual hypotheses. In particular, empirical results showed clearly that emotional responses to the intrinsic message characteristics are not restricted to fear, and that different responses to threat appeals were clearly attributed to specific intrinsic message characteristics. In addition, the inclusion of anticipated emotions alongside cognitive appraisals in the framework generated interesting results. Specifically, immediate emotions did not influence key response variables related to future behaviour, in support of questioning the assumption of the prominent role of fear in the response process that is so prevalent in existing literature. The findings, theoretical and practical implications, limitations and directions for future research are discussed.

Semantic enabled sensor network design

Wireless Sensor Network (WSN) systems have become more and more popular in our modern life. They have been widely used in many areas, such as smart homes/buildings, context-aware devices, military applications, etc. Despite the increasing usage, there is a lack of formal description and automated verification for WSN system design. In this paper, we present an approach to support the rigorous verification of WSN modeling using the Semantic Web technology We use Web Ontology Language (OWL) and Semantic Web Rule Language (SWRL) to define a meta-ontology for the modeling of WSN systems. Furthermore, we apply ontology reasoners to perform automated verification on customized WSN models and their instances. We demonstrate and evaluate our approach through a Light Control System (LCS) as the case study.

Understanding inter-firm networks and types of innovation in SMEs:a social network perspective

Innovation is one of the key drivers for gaining competitive advantages in any firms. Understanding knowledge transfer through inter-firm networks and its effects on types of innovation in SMEs is very important in improving SMEs innovation. This study examines relationships between characteristics of inter-firm knowledge transfer networks and types of innovation in SMEs. To achieve this, social network perspective is adopted to understand inter-firm knowledge transfer networks and its impact on innovation by investigating how and to what extend ego network characteristics are affecting types of innovation. Therefore, managers can develop the firms'network according to their strategies and requirements. First, a conceptual model and research hypotheses are proposed to establish the possible relationship between network properties and types of innovation. Three aspects of ego network are identified and adopted for hypotheses development: 1) structural properties which address the potential for resources and the context for the flow of resources, 2) relational properties which reflect the quality of resource flows, and 3) nodal properties which are about quality and variety of resources and capabilities of the ego partners. A questionnaire has been designed based on the hypotheses. Second, semistructured interviews with managers of five SMEs have been carried out, and a thematic qualitative analysis of these interviews has been performed. The interviews helped to revise the questionnaire and provided preliminary evidence to support the hypotheses. Insights from the preliminary investigation also helped to develop research plan for the next stage of this research.

Advanced predictive-analysis-based decision support for collaborative logistics networks

Purpose – The purpose of this paper is to examine challenges and potential of big data in heterogeneous business networks and relate these to an implemented logistics solution. Design/methodology/approach – The paper establishes an overview of challenges and opportunities of current significance in the area of big data, specifically in the context of transparency and processes in heterogeneous enterprise networks. Within this context, the paper presents how existing components and purpose-driven research were combined for a solution implemented in a nationwide network for less-than-truckload consignments. Findings – Aside from providing an extended overview of today’s big data situation, the findings have shown that technical means and methods available today can comprise a feasible process transparency solution in a large heterogeneous network where legacy practices, reporting lags and incomplete data exist, yet processes are sensitive to inadequate policy changes. Practical implications – The means introduced in the paper were found to be of utility value in improving process efficiency, transparency and planning in logistics networks. The particular system design choices in the presented solution allow an incremental introduction or evolution of resource handling practices, incorporating existing fragmentary, unstructured or tacit knowledge of experienced personnel into the theoretically founded overall concept. Originality/value – The paper extends previous high-level view on the potential of big data, and presents new applied research and development results in a logistics application.

Teacher-student relationships and the link to academic adjustment and emotional well-being in early adolescence

The role of support from teachers on the academic and emotional adjustment of a ethnically and economically diverse sample of adolescents was examined. Analyses were conducted on data from a larger study examining social networks across the transition to junior high school. Participants in the current study included 694 African-American, Hispanic-American and European-American students in grades 6 and 8 from public elementary schools in South Florida. Some of these schools are located in economically distressed areas and some are in middle income areas. Children were interviewed, and information on teacher social support resources, school stressors, risk and academic and emotional adjustment was obtained. Several significant findings emerged from the analyses. First, overall teacher support was a significant predictor of a wide range of academic and emotional adjustment outcomes. Second, teacher support compensated for low peer support on teacher rated behavior problems. Third, teacher support interacted with school stress to predict depressed affect and self esteem. Fourth, teacher support interacted with low ecological risk conditions to predict feelings of loneliness. ^

Social support, risk, and adjustment of immigrant preadolescents

The current study was designed to explore the salience of social support, immigrant status, and risk in middle childhood and early adolescence across two time periods as indicated by measures of school adjustment and well-being. Participants included 691 children of public elementary schools in grades 4 and 6 who were interviewed in 1997 (Time 1) and reinterviewed two years later (Time 2); 539 were U.S.-born, and 152 were foreign-born. ^ Repeated measures multivariate analyses of variance (MANOVA's) were conducted to assess the effects of immigrant status and risk on total support, well-being, and school adjustment from Time 1 to Time 2. Follow-up analyses, including Student-Newman-Keuls post hoc tests, were used to test the significance of the differences among the means of support categories (low and high), immigrant status (U.S. born and non-U.S. born), risk (low and high) and time (time 1 and time 2). ^ Results showed that immigrant participants in the high risk group reported significantly lower levels of support than their peers. Further, children of low risk at Time 2 indicated the highest levels of support. Second, immigrant preadolescents, preadolescents who reported low levels of social support, and preadolescents of the high risk reported lower levels of emotional well-being. There was also an interaction of support by risk by time, indicating that children who are at risk and had low levels of social support reported more emotional problems at Time 1. Finally, preadolescents who are at risk and preadolescents who reported lower levels of support were more likely to show school adaptation problems. Findings from this study highlight the importance of a multivariable approach to the study of support, emotional adjustment, and academic adjustment of immigrant preadolescents. ^

Parent emotional functioning, parent responsiveness, and child adjustment

Over the past two decades, interest in the psychological development of children has steadily increased (Beg, Casey, & Saunders, 2007), presumably because statistics describing childhood psychological illness are alarming. Certain parent interaction styles or behaviors are known to influence child adjustment. According to attachment theory, the reason for these findings is that interaction with a caregiver informs an individual’s construction of an internal working model (IWM) of the self in relation to others in the environment. The purpose of this study was to gain a greater understanding of the factors contributing to child adjustment by examining the influence of parents’ emotional functioning and parent responsiveness to children’s bids for interaction. This dissertation tested a multivariate model of attachment-related processes and outcomes with an ethnically diverse sample. Results partially supported the model, in that parent emotional intelligence predicted some aspects of child adjustment. Overall, the study adds to knowledge about how parent characteristics influence child adjustment and provides support for conceptualizing emotional intelligence as a concrete and observable manifestation of the nonconscious attachment IWM.

Abstractions to support dynamic adaptation of communication frameworks for user-centric communication

The convergence of data, audio and video on IP networks is changing the way individuals, groups and organizations communicate. This diversity of communication media presents opportunities for creating synergistic collaborative communications. This form of collaborative communication is however not without its challenges. The increasing number of communication service providers coupled with a combinatorial mix of offered services, varying Quality-of-Service and oscillating pricing of services increases the complexity for the user to manage and maintain ‘always best’ priced or performance services. Consumers have to manually manage and adapt their communication in line with differences in services across devices, networks and media while ensuring that the usage remain consistent with their intended goals. This dissertation proposes a novel user-centric approach to address this problem. The proposed approach aims to reduce the aforementioned complexity to the user by (1) providing high-level abstractions and a policy based methodology for automated selection of the communication services guided by high-level user policies and (2) providing services through the seamless integration of multiple communication service providers and providing an extensible framework to support the integration of multiple communication service providers. The approach was implemented in the Communication Virtual Machine (CVM), a model-driven technology for realizing communication applications. The CVM includes the Network Communication Broker, the layer responsible for providing a network-independent API to the upper layers of CVM. The initial prototype for the NCB supported only a single communication framework which limited the number, quality and types of services available. Experimental evaluation of the approach show the additional overhead of the approach is minimal compared to the individual communication services frameworks. Additionally the automated approach proposed out performed the individual communication services frameworks for cross framework switching.

Control of MNC environmental performance and the challenges of subsidiary network dimensions

The trend of green consumerism and increased standardization of environmental regulations has driven multinational corporations (MNCs) to seek standardization of environmental practices or at least seek to be associated with such behavior. In fact, many firms are seeking to free ride on this global green movement, without having the actual ecological footprint to substantiate their environmental claims. While scholars have articulated the benefits from such optimization of uniform global green operations, the challenges for MNCs to control and implement such operations are understudied. For firms to translate environmental commitment to actual performance, the obstacles are substantial, particularly for the MNC. This is attributed to headquarters' (HQ) control challenges (1) in managing core elements of the corporate environmental management (CEM) process and specifically matching verbal commitment and policy with ecological performance and by (2) the fact that the MNC operates in multiple markets and the HQ is required to implement policy across complex subsidiary networks consisting of diverse and distant units. Drawing from the literature on HQ challenges of MNC management and control, this study examines (1) how core components of the CEM process impact optimization of global environmental performance (GEP) and then uses network theory to examine how (2) a subsidiary network's dimensions can present challenges to the implementation of green management policies. It presents a framework for CEM which includes (1) MNCs' Verbal environmental commitment, (2) green policy Management which guides standards for operations, (3) actual environmental Performance reflected in a firm's ecological footprint and (4) corporate environmental Reputation (VMPR). Then it explains how an MNC's key subsidiary network dimensions (density, diversity, and dispersion) create challenges that hinder the relationship between green policy management and actual environmental performance. It combines content analysis, multiple regression, and post-hoc hierarchal cluster analysis to study US manufacturing MNCs. The findings support a positive significant effect of verbal environmental commitment and green policy management on actual global environmental performance and environmental reputation, as well as a direct impact of verbal environmental commitment on green policy management. Unexpectedly, network dimensions were not found to moderate the relationship between green management policy and GEP.

Emotions and Learning in Support Groups of Female Breast Cancer Patients

The understanding of emotions and learning in the participants of breast cancer support groups will assist in better preparation of how to cope with the disease these patients face. It is in working through emotional experiences that participants are able to learn and grow in support groups.