Sierra : cooperative request-response for resource management in disasters using semantic web principles

Disasters cause widespread harm and disrupt the normal functioning of society, and effective management requires the participation and cooperation of many actors. While advances in information and networking technology have made transmission of data easier than it ever has been before, communication and coordination of activities between actors remain exceptionally difficult. This paper employs semantic web technology and Linked Data principles to create a network of intercommunicating and inter-dependent on-line sites for managing resources. Each site publishes available resources openly and a lightweight opendata protocol is used to request and respond to requests for resources between sites in the network.

e-Business in supply chain management

E-business is concerned with the use of the Internet to link companies with their suppliers, customers and other trading partners. As a business concept, it has evolved significantly since its introduction in the 1990’s in parallel with the rapid rate of development of information technology (IT) during this period. Supply chain management (SCM) is fundamentally concerned with integration of activities both with and between organisations. IT plays a crucial role in SCM as a key enabler of supply chain integration (SCI). This chapter sets out the role of e-business concepts in the context of the supply chain challenges faced by firms. It specifically explores the role of e-procurement as an example of how e-business concepts have been applied to one key SCM activity, namely purchasing and procurement. In this context, the chapter examines the nature and evolution of e-marketplaces and goes on to identify key adoption drivers and benefits based on recent research. This research identifies key adoption drivers and benefits but also recognises that there are many barriers that ongoing research needs to address if the potential of e-business is to be fulfilled.

Exploring the relationships between network change and network learning

This paper relates the concept of network learning - learning by a group of organizations as a group - to change and notions of change management. Derived initially from a review of literature on organizational learning (OL) and interorganizational networks, and secondary cases of network learning, the concept was evaluated and developed through empirical investigation of five network learning episodes in the group of organizations that comprises the English prosthetics service. We argue that the notion of network learning enables a richer understanding of developments in networks over extended periods of time than can be afforded through more established concepts of change and change management alone.

Learning and change in interorganizational networks:the case for network learning and network change

The ALBA 2002 Call for Papers asks the question ‘How do organizational learning and knowledge management contribute to organizational innovation and change?’. Intuitively, we would argue, the answer should be relatively straightforward as links between learning and change, and knowledge management and innovation, have long been commonly assumed to exist. On the basis of this assumption, theories of learning tend to focus ‘within organizations’, and assume a transfer of learning from individual to organization which in turn leads to change. However, empirically, we find these links are more difficult to articulate. Organizations exist in complex embedded economic, political, social and institutional systems, hence organizational change (or innovation) may be influenced by learning in this wider context. Based on our research in this wider interorganizational setting, we first make the case for the notion of network learning that we then explore to develop our appreciation of change in interorganizational networks, and how it may be facilitated. The paper begins with a brief review of lite rature on learning in the organizational and interorganizational context which locates our stance on organizational learning versus the learning organization, and social, distributed versus technical, centred views of organizational learning and knowledge. Developing from the view that organizational learning is “a normal, if problematic, process in every organization” (Easterby-Smith, 1997: 1109), we introduce the notion of network learning: learning by a group of organizations as a group. We argue this is also a normal, if problematic, process in organizational relationships (as distinct from interorganizational learning), which has particular implications for network change. Part two of the paper develops our analysis, drawing on empirical data from two studies of learning. The first study addresses the issue of learning to collaborate between industrial customers and suppliers, leading to the case for network learning. The second, larger scale study goes on to develop this theme, examining learning around several major change issues in a healthcare service provider network. The learning processes and outcomes around the introduction of a particularly controversial and expensive technology are described, providing a rich and contrasting case with the first study. In part three, we then discuss the implications of this work for change, and for facilitating change. Conclusions from the first study identify potential interventions designed to facilitate individual and organizational learning within the customer organization to develop individual and organizational ‘capacity to collaborate’. Translated to the network example, we observe that network change entails learning at all levels – network, organization, group and individual. However, presenting findings in terms of interventions is less meaningful in an interorganizational network setting given: the differences in authority structures; the less formalised nature of the network setting; and the importance of evaluating performance at the network rather than organizational level. Academics challenge both the idea of managing change and of managing networks. Nevertheless practitioners are faced with the issue of understanding and in fluencing change in the network setting. Thus we conclude that a network learning perspective is an important development in our understanding of organizational learning, capability and change, locating this in the wider context in which organizations are embedded. This in turn helps to develop our appreciation of facilitating change in interorganizational networks, both in terms of change issues (such as introducing a new technology), and change orientation and capability.

Perspectives of carers on medication management in dementia:lessons from collaboratively developing a research proposal

Background: The need for carers to manage medication-related problems for people with dementia living in the community raises dilemmas, which can be identified by carers and people with dementia as key issues for developing carer-relevant research projects.A research planning Public Patient Involvement (PPI) workshop using adapted focus group methodology was held at the Alzheimer's Society's national office, involving carers of people with dementia who were current members of the Alzheimer's Society Research Network (ASRN) in dialogue with health professionals aimed to identify key issues in relation to medication management in dementia from the carer viewpoint. The group was facilitated by a specialist mental health pharmacist, using a topic guide developed systematically with carers, health professionals and researchers. Audio-recordings and field notes were made at the time and were transcribed and analysed thematically. The participants included nine carers in addition to academics, clinicians, and staff from DeNDRoN (Dementias and Neurodegenerative Diseases Research Network) and the Alzheimer's Society. Findings. Significant themes, for carers, which emerged from the workshop were related to: (1) medication usage and administration practicalities, (2) communication barriers and facilitators, (3) bearing and sharing responsibility and (4) weighing up medication risks and benefits. These can form the basis for more in-depth qualitative research involving a broader, more diverse sample. Discussion. The supported discussion enabled carer voices and perspectives to be expressed and to be linked to the process of identifying problems in medications management as directly experienced by carers. This was used to inform an agenda for research proposals which would be meaningful for carers and people with dementia. © 2014 Poland et al.; licensee BioMed Central Ltd.

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 cloud-based farm management system:architecture and implementation

Recent technological advances have paved the way for developing and offering advanced services for the stakeholders in the agricultural sector. A paradigm shift is underway from proprietary and monolithic tools to Internet-based, cloud hosted, open systems that will enable more effective collaboration between stakeholders. This new paradigm includes the technological support of application developers to create specialized services that will seamlessly interoperate, thus creating a sophisticated and customisable working environment for the end users. We present the implementation of an open architecture that instantiates such an approach, based on a set of domain independent software tools called "generic enablers" that have been developed in the context of the FI-WARE project. The implementation is used to validate a number of innovative concepts for the agricultural sector such as the notion of a services' market place and the system's adaptation to network failures. During the design and implementation phase, the system has been evaluated by end users, offering us valuable feedback. The results of the evaluation process validate the acceptance of such a system and the need of farmers to have access to sophisticated services at affordable prices. A summary of this evaluation process is also presented in this paper. © 2013 Elsevier B.V.

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.

Supply chain management resources, capabilities and execution

This paper identifies inter- and intra-organisational management resources that determine the level of execution of inter-firm alliance supply chain management (SCM). By drawing on network and resource-based view theories, a conceptual model proposes the effects of SCM resources and capabilities as influencing factors on SCM execution. The model was tested using survey data from studies conducted in two European supply chain environments. Variance-based structural equation modelling confirmed the hypothesised hierarchical order of three proposed antecedents: internal SCM resources affect joint SCM resources, which in turn influence collaborative SCM-related processes and finally SCM execution. An importance-performance analysis for both settings shows that providing and investing in internal SCM resources should be a priority when aiming to increase SCM execution. The theoretical contribution of this paper lies in confirming that the improvement of SCM execution follows a clear pathway featuring internal supply chain resources as one of the main drivers. The practical implications of this research include the development of a prioritisation list of measures that elevate SCM execution in the two country settings. © 2014 © 2014 Taylor & Francis.

Self-organising zooms for decentralised redundancy management in visual sensor networks

When visual sensor networks are composed of cameras which can adjust the zoom factor of their own lens, one must determine the optimal zoom levels for the cameras, for a given task. This gives rise to an important trade-off between the overlap of the different cameras’ fields of view, providing redundancy, and image quality. In an object tracking task, having multiple cameras observe the same area allows for quicker recovery, when a camera fails. In contrast having narrow zooms allow for a higher pixel count on regions of interest, leading to increased tracking confidence. In this paper we propose an approach for the self-organisation of redundancy in a distributed visual sensor network, based on decentralised multi-objective online learning using only local information to approximate the global state. We explore the impact of different zoom levels on these trade-offs, when tasking omnidirectional cameras, having perfect 360-degree view, with keeping track of a varying number of moving objects. We further show how employing decentralised reinforcement learning enables zoom configurations to be achieved dynamically at runtime according to an operator’s preference for maximising either the proportion of objects tracked, confidence associated with tracking, or redundancy in expectation of camera failure. We show that explicitly taking account of the level of overlap, even based only on local knowledge, improves resilience when cameras fail. Our results illustrate the trade-off between maintaining high confidence and object coverage, and maintaining redundancy, in anticipation of future failure. Our approach provides a fully tunable decentralised method for the self-organisation of redundancy in a changing environment, according to an operator’s preferences.

Reliability modelling and verification of manufacturing processes based on process knowledge management

Reliability modelling and verification is indispensable in modern manufacturing, especially for product development risk reduction. Based on the discussion of the deficiencies of traditional reliability modelling methods for process reliability, a novel modelling method is presented herein that draws upon a knowledge network of process scenarios based on the analytic network process (ANP). An integration framework of manufacturing process reliability and product quality is presented together with a product development and reliability verification process. According to the roles of key characteristics (KCs) in manufacturing processes, KCs are organised into four clusters, that is, product KCs, material KCs, operation KCs and equipment KCs, which represent the process knowledge network of manufacturing processes. A mathematical model and algorithm is developed for calculating the reliability requirements of KCs with respect to different manufacturing process scenarios. A case study on valve-sleeve component manufacturing is provided as an application example of the new reliability modelling and verification procedure. This methodology is applied in the valve-sleeve component manufacturing processes to manage and deploy production resources.

Progmosis:evaluating risky individual behavior during epidemics using mobile network data

The possibility to analyze, quantify and forecast epidemic outbreaks is fundamental when devising effective disease containment strategies. Policy makers are faced with the intricate task of drafting realistically implementable policies that strike a balance between risk management and cost. Two major techniques policy makers have at their disposal are: epidemic modeling and contact tracing. Models are used to forecast the evolution of the epidemic both globally and regionally, while contact tracing is used to reconstruct the chain of people who have been potentially infected, so that they can be tested, isolated and treated immediately. However, both techniques might provide limited information, especially during an already advanced crisis when the need for action is urgent. In this paper we propose an alternative approach that goes beyond epidemic modeling and contact tracing, and leverages behavioral data generated by mobile carrier networks to evaluate contagion risk on a per-user basis. The individual risk represents the loss incurred by not isolating or treating a specific person, both in terms of how likely it is for this person to spread the disease as well as how many secondary infections it will cause. To this aim, we develop a model, named Progmosis, which quantifies this risk based on movement and regional aggregated statistics about infection rates. We develop and release an open-source tool that calculates this risk based on cellular network events. We simulate a realistic epidemic scenarios, based on an Ebola virus outbreak; we find that gradually restricting the mobility of a subset of individuals reduces the number of infected people after 30 days by 24%.

Performance evaluation of adaptive context aware rate selection algorithm (ACARS) for road safety applications in vehicular network

One of the major drawbacks for mobile nodes in wireless networks is power management. Our goal is to evaluate the performance power control scheme to be used to reduce network congestion, improve quality of service and collision avoidance in vehicular network and road safety application. Some of the importance of power control (PC) are improving spatial reuse, and increasing network capacity in mobile wireless communications. In this simulation we have evaluated the performance of existing rate algorithms compared with context Aware Rate selection algorithm (ACARS) and also seen the performance of ACARS and how it can be applied to road safety, improve network control and power management. Result shows that ACARS is able to minimize the total transmit power in the presence of propagation processes and mobility of vehicles, by adapting to the fast varying channels conditions with the Path loss exponent values that was used for that environment which is shown in the network simulation parameter. Our results have shown that ACARS is a very robust algorithm which performs very well with the effect of propagation processes that is prone to every transmitted signal in mobile networks. © 2013 IEEE.

Balancing push and pull information management within the supply chain

The aim of this paper is to explore the management of information in an aerospace manufacturer's supply chain by analysing supply chain disruption risks. The social network perspective will be used to examine the flows of information in the supply chain. The examination of information flows will also be explored in terms of push and pull information management. The supply chain risk management (SCRM) strategy is to assess the management of information that allows companies to gather information which will allow them to mitigate that risk before any disruption to the supply chain occurs. There is a shortage of models in analysing the supply chain risk associated with information flows, possibly due to the omission of appropriate modelling techniques in this area (Tang and Nurmaya, 2011). This paper uses an exploratory case study consisting of a multi method qualitative approach using fifteen interviews and four focus groups.

Practitioner perspectives on supply chain management and logistics:a study from the United Kingdom

Purpose: The focus of this paper is the evolution of supply chain management (SCM) and logistics, as well as of the relationship between them. Its purpose is to generate deep insights into practice, particularly in relation to the fundamental issue of how practitioners define these key terms and phrases. Research approach: A largely qualitative study which involved in depth interviews with managers from two third party logistics providers (3PLs)/distributors, two retailers and two manufacturers from the United Kingdom. This interview protocol is based on the template used in a previous study published over a decade ago. Findings and originality: The data collected during the focussed interviews in the United Kingdom is contrasted with results from the earlier study. The findings suggest that there is variation between practitioners particularly in relation to what SCM is specifically concerned with. This variation mirrors to a large extent the differing orientations and emphases evident in the many theoretical definitions of SCM that have been proposed in recent decades. Research impact: The authors introduced the concept of refined replication in SCM research. This allows previous research to be built upon in order to test understanding of SCM theory and its practical implementation among SCM professionals in the United Kingdom. Practical impact: A profile of SCM understanding and adoption by firms in the United Kingdom is presented .