The Role of Family/Friend Social Support in Diabetes Self-Management for Minorities with Type 2 Diabetes

This study investigated how ethnicity, perceived family/friend social support (FSS), and health behaviors are associated with diabetes self-management (DSM) in minorities. The participants were recruited by community outreach methods and included 174 Cuban-, 121 Haitian- and 110 African-Americans with type 2 diabetes. The results indicated that ethnicity and FSS were associated with DSM. Higher FSS scores were associated with higher DSM scores, independent of ethnicity. There were ethnic differences in several elements of FSS. DSM was highest in Haitian- as compared to African-Americans; yet Haitian Americans had poorer glycemic control. The findings suggest FSS together with ethnicity may influence critical health practices. Studies are needed that further investigate the relationships among minorities with diabetes, their intimate network (family and friends) and the diabetes care process.

Management of remote field instrumentation via the Internet

Supervisory Control & Data Acquisition (SCADA) systems are used by many industries because of their ability to manage sensors and control external hardware. The problem with commercially available systems is that they are restricted to a local network of users that use proprietary software. There was no Internet development guide to give remote users out of the network, control and access to SCADA data and external hardware through simple user interfaces. To solve this problem a server/client paradigm was implemented to make SCADAs available via the Internet. Two methods were applied and studied: polling of a text file as a low-end technology solution and implementing a Transmission Control Protocol (TCP/IP) socket connection. Users were allowed to login to a website and control remotely a network of pumps and valves interfaced to a SCADA. This enabled them to sample the water quality of different reservoir wells. The results were based on real time performance, stability and ease of use of the remote interface and its programming. These indicated that the most feasible server to implement is the TCP/IP connection. For the user interface, Java applets and Active X controls provide the same real time access.

Defense Against Node Compromise in Sensor Network Security

Recent advances in electronic and computer technologies lead to wide-spread deployment of wireless sensor networks (WSNs). WSNs have wide range applications, including military sensing and tracking, environment monitoring, smart environments, etc. Many WSNs have mission-critical tasks, such as military applications. Thus, the security issues in WSNs are kept in the foreground among research areas. Compared with other wireless networks, such as ad hoc, and cellular networks, security in WSNs is more complicated due to the constrained capabilities of sensor nodes and the properties of the deployment, such as large scale, hostile environment, etc. Security issues mainly come from attacks. In general, the attacks in WSNs can be classified as external attacks and internal attacks. In an external attack, the attacking node is not an authorized participant of the sensor network. Cryptography and other security methods can prevent some of external attacks. However, node compromise, the major and unique problem that leads to internal attacks, will eliminate all the efforts to prevent attacks. Knowing the probability of node compromise will help systems to detect and defend against it. Although there are some approaches that can be used to detect and defend against node compromise, few of them have the ability to estimate the probability of node compromise. Hence, we develop basic uniform, basic gradient, intelligent uniform and intelligent gradient models for node compromise distribution in order to adapt to different application environments by using probability theory. These models allow systems to estimate the probability of node compromise. Applying these models in system security designs can improve system security and decrease the overheads nearly in every security area. Moreover, based on these models, we design a novel secure routing algorithm to defend against the routing security issue that comes from the nodes that have already been compromised but have not been detected by the node compromise detecting mechanism. The routing paths in our algorithm detour those nodes which have already been detected as compromised nodes or have larger probabilities of being compromised. Simulation results show that our algorithm is effective to protect routing paths from node compromise whether detected or not.

Design Strategies for an Artificial Neural Network Based Algorithm for Automatic Incident Detection on Major Arterial Streets

Traffic incidents are non-recurring events that can cause a temporary reduction in roadway capacity. They have been recognized as a major contributor to traffic congestion on our national highway systems. To alleviate their impacts on capacity, automatic incident detection (AID) has been applied as an incident management strategy to reduce the total incident duration. AID relies on an algorithm to identify the occurrence of incidents by analyzing real-time traffic data collected from surveillance detectors. Significant research has been performed to develop AID algorithms for incident detection on freeways; however, similar research on major arterial streets remains largely at the initial stage of development and testing. This dissertation research aims to identify design strategies for the deployment of an Artificial Neural Network (ANN) based AID algorithm for major arterial streets. A section of the US-1 corridor in Miami-Dade County, Florida was coded in the CORSIM microscopic simulation model to generate data for both model calibration and validation. To better capture the relationship between the traffic data and the corresponding incident status, Discrete Wavelet Transform (DWT) and data normalization were applied to the simulated data. Multiple ANN models were then developed for different detector configurations, historical data usage, and the selection of traffic flow parameters. To assess the performance of different design alternatives, the model outputs were compared based on both detection rate (DR) and false alarm rate (FAR). The results show that the best models were able to achieve a high DR of between 90% and 95%, a mean time to detect (MTTD) of 55-85 seconds, and a FAR below 4%. The results also show that a detector configuration including only the mid-block and upstream detectors performs almost as well as one that also includes a downstream detector. In addition, DWT was found to be able to improve model performance, and the use of historical data from previous time cycles improved the detection rate. Speed was found to have the most significant impact on the detection rate, while volume was found to contribute the least. The results from this research provide useful insights on the design of AID for arterial street applications.

Optimization of three-dimensional branching networks of microchannels for thermal management of microelectronics

The aim of this work is to present a methodology to develop cost-effective thermal management solutions for microelectronic devices, capable of removing maximum amount of heat and delivering maximally uniform temperature distributions. The topological and geometrical characteristics of multiple-story three-dimensional branching networks of microchannels were developed using multi-objective optimization. A conjugate heat transfer analysis software package and an automatic 3D microchannel network generator were developed and coupled with a modified version of a particle-swarm optimization algorithm with a goal of creating a design tool for 3D networks of optimized coolant flow passages. Numerical algorithms in the conjugate heat transfer solution package include a quasi-ID thermo-fluid solver and a steady heat diffusion solver, which were validated against results from high-fidelity Navier-Stokes equations solver and analytical solutions for basic fluid dynamics test cases. Pareto-optimal solutions demonstrate that thermal loads of up to 500 W/cm2 can be managed with 3D microchannel networks, with pumping power requirements up to 50% lower with respect to currently used high-performance cooling technologies.

Predicting delay reductions from freeway traffic diversion for incident management

Traffic incidents are a major source of traffic congestion on freeways. Freeway traffic diversion using pre-planned alternate routes has been used as a strategy to reduce traffic delays due to major traffic incidents. However, it is not always beneficial to divert traffic when an incident occurs. Route diversion may adversely impact traffic on the alternate routes and may not result in an overall benefit. This dissertation research attempts to apply Artificial Neural Network (ANN) and Support Vector Regression (SVR) techniques to predict the percent of delay reduction from route diversion to help determine whether traffic should be diverted under given conditions. The DYNASMART-P mesoscopic traffic simulation model was applied to generate simulated data that were used to develop the ANN and SVR models. A sample network that comes with the DYNASMART-P package was used as the base simulation network. A combination of different levels of incident duration, capacity lost, percent of drivers diverted, VMS (variable message sign) messaging duration, and network congestion was simulated to represent different incident scenarios. The resulting percent of delay reduction, average speed, and queue length from each scenario were extracted from the simulation output. The ANN and SVR models were then calibrated for percent of delay reduction as a function of all of the simulated input and output variables. The results show that both the calibrated ANN and SVR models, when applied to the same location used to generate the calibration data, were able to predict delay reduction with a relatively high accuracy in terms of mean square error (MSE) and regression correlation. It was also found that the performance of the ANN model was superior to that of the SVR model. Likewise, when the models were applied to a new location, only the ANN model could produce comparatively good delay reduction predictions under high network congestion level.

Patterns of dynamic changes in supply management – a triadic approach

Research has followed a network perspective of supply management from as early as the publication of Krajlic matrix. This portfolio approach is still static. Recently the triad is interpreted as the smallest unit of a network through which dynamics can be studied. Analyzing triads seems to be a promising way through which a deeper insight into the dynamics of supplier development can be gained. Using case study approach the paper investigates this dynamics with a special emphasis on coopetitive behavior. Analyzing a triadic sourcing setting operating in a make to engineer (and order) environment we show the importance of governance.

The importance of realistic dispersal models in planning for conservation : application of a novel modelling platform to evaluate management scenarios in an Afrotropical biodiversity hotspot

Funded by European Union's Horizon 2020 Marie Sklodowska-Curie. Grant Number: 661211 Research Foundation Flanders (FWO). Grant Numbers: G.0055.08, G.0149.09, G.0308.13 FWO Research Network on Eco-Evolutionary dynamics French Ministère de l'Energie de l'Ecologie du Développement Durable et de la Mer through the EU FP6 BiodivERsA Eranet NERC. Grant Number: NE/J008001/1

A framework for modelling mobile radio access networks for intelligent fault management

Postprint

From ‘poor parenting’ to micro-management:coalition governance and the sponsorship of arm’s-length bodies in the United Kingdom, 2010–13

The delegation of public tasks to arm’s-length bodies remains a central feature of contemporary reform agendas within both developed and developing countries. The role and capacity of political and administrative principals (i.e. ministers and departments of state) to control the vast network of arm’s-length bodies for which they are formally responsible is therefore a critical issue within and beyond academe. In the run-up to the 2010 General Election in the United Kingdom, the ‘quango conundrum’ emerged as an important theme and all three major parties committed themselves to shift the balance of power back towards ministers and sponsor departments. This article presents the results of the first major research project to track and examine the subsequent reform process. It reveals a stark shift in internal control relationships from the pre-election ‘poor parenting’ model to a far tighter internal situation that is now the focus of complaints by arm’s-length bodies of micro-management. This shift in the balance of power and how it was achieved offers new insights into the interplay between different forms of governance and has significant theoretical and comparative relevance. Points for practitioners: For professionals working in the field of arm’s-length governance, the article offers three key insights. First, that a well-resourced core executive is critical to directing reform given the challenges of implementing reform in a context of austerity. Second, that those implementing reform will also need to take into account the diverse consequences of centrally imposed reform likely to result in different departments with different approaches to arm’s-length governance. Third, that reforming arm’s-length governance can affect the quality of relationships, and those working in the field will need to mitigate these less tangible challenges to ensure success.

Implementation of supply chain management theory in practice:a questionnaire survey in the United Kingdom

Purpose: The purpose of the research described in this paper is to disentangle the rhetoric from the reality in relation to supply chain management (SCM) adoption in practice. There is significant evidence of a divergence between theory and practice in the field of SCM. Research Approach: The authors’ review of the extant SCM literature highlighted a lack of replication studies in SCM, leading to the concept of refined replication being developed. The authors conducted a refined replication of the work of Sweeney et al. (2015) where a new SCM definitional construct – the Four Fundamentals – was proposed. The work presented in this article refines the previous study but adopts the same three-phase approach: focussed interviews, a questionnaire survey, and focus groups. This article covers the second phase of the refined replication study and describes an integrated research design of a questionnaire research to be undertaken in Britain. Findings and Originality: The article presents an integrated research design of a questionnaire research with emphases on the refined replication of previous work of Sweeney et al. (2015) carried out in Ireland and adapting it to the British context. Research Impact: The authors introduce 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 - based on the Four Fundamentals construct - among SCM professionals in Britain. Practical Impact: The article presents the integrated research design of a questionnaire research that may be used in similar studies.

Management of adult attention deficit hyperactivity disorder in UK primary care: a survey of general practitioners

Background: Compared to existing literature on childhood attention deficit hyperactivity disorder (ADHD), little published adult data are available, particularly outside of the United States. Using General Practitioner (GP) questionnaires from the United Kingdom, this study aimed to examine a number of issues related to ADHD in adults, across three cohorts of patients, adults who received ADHD drug treatment in childhood/adolescence but stopped prior to adulthood; adults who received ADHD drug treatment in childhood/adolescence and continued treatment into adulthood and adults who started ADHD drug treatment in adulthood.Methods: Patients with a diagnosis of ADHD and prescribed methylphenidate, dexamfetamine or atomoxetine were identified using data from The Health Improvement Network (THIN). Dates when these drugs started and stopped were used to classify patients into the three cohorts. From each cohort, 50 patients were randomly selected and questionnaires were sent via THIN to their GPs.GPs returned completed questionnaires to THIN who forwarded anonymised copies to the researchers. Datasets were analysed using descriptive statistics.Results: Overall response rate was 89% (133/150). GPs stated that in 19 cases, the patient did not meet the criteria of that group; the number of valid questionnaires returned was 114 (76%). The following broad trends were observed: 1) GPs were not aware of the reason for treatment cessation in 43% of cases, 2) patient choice was the most common reason for discontinuation (56%), 3) 7% of patients who stopped pharmacological treatment subsequently reported experiencing ADHD symptoms, 4) 58% of patients who started pharmacological treatment for ADHD in adulthood received pharmacological treatment for other mental health conditions prior to the ADHD being diagnosed.Conclusion: This study presents some key findings relating to ADHD; GPs were often not aware of the reason for patients stopping ADHD treatment in childhood or adolescence. Patient choice was identified as the most common reason for treatment cessation. For patients who started pharmacological treatment in adulthood, many patients received pharmacological treatment for comorbidities before a diagnosis of ADHD was made.

Problematizing practice: MacIntyre and management

Alasdair MacIntyre’s distinction between institutions and practices helps illuminate how powerful institutional forces frame and constrain the practice of organizational research as well as the output and positioning of scholarly journals like Organization. Yet his conceptual frame is limited, not least because it is unclear whether the activity of managing is, or is not, a practice. This article builds on MacIntyre’s ideas by incorporating Aristotle’s concepts of poíēsis, praxis, téchnē and phrónēsis. Rather than ask, following MacIntyre, whether management is a practice, this wider network of concepts provides a richer frame for understanding the nature of managing and the appropriate role for academia. The article outlines a phronetic paradigm for organizational inquiry, and concludes by briefly examining the implications of such a paradigm for research and learning.

Applying complexity science to air traffic management

Complexity science is the multidisciplinary study of complex systems. Its marked network orientation lends itself well to transport contexts. Key features of complexity science are introduced and defined, with a specific focus on the application to air traffic management. An overview of complex network theory is presented, with examples of its corresponding metrics and multiple scales. Complexity science is starting to make important contributions to performance assessment and system design: selected, applied air traffic management case studies are explored. The important contexts of uncertainty, resilience and emergent behaviour are discussed, with future research priorities summarised.

Measuring the Diversity and the Integration of Film Production in Mercosur: A Social Network Analysis

Based on an original and comprehensive database of all feature fiction films produced in Mercosur between 2004 and 2012, the paper analyses whether the Mercosur film industry has evolved towards an integrated and culturally more diverse market. It provides a summary of policy opportunities in terms of integration and diversity, emphasizing the limiter role played by regional policies. It then shows that although the Mercosur film industry remains rather disintegrated, it tends to become more integrated and culturally more diverse. From a methodological point of view, the combination of Social Network Analysis and the Stirling Model opens up interesting research tracks to analyse creative industries in terms of their market integration and their cultural diversity.