Understanding institutional conversion:the case of the National Reporting and Learning System

This article focuses on one type of institutional change: conversion. One innovative approach to institutional change, the “political-coalitional approach”, acknowledges that: institutions can have unintended effects, which may privilege certain groups over others; institutions are often created and sustained through compromise with external actors; and institutions’ external context can vary significantly over time, as different coalitions’ power waxes and wanes. This approach helps explain the conversion of one institution drawn from the UK National Health Service, the National Reporting and Learning System. However, the shift of this system from producing formative information to facilitate learning to promote safer care, towards producing summative information to support resource allocation decisions, cannot be explained merely by examining the actions of external power coalitions. An internal focus, which considers factors that are normally viewed as “organisational” (such as leadership and internal stability), is also required.

A review of research and practice for the industrial networks of the future

Academic researchers have followed closely the interest of companies in establishing industrial networks by studying aspects such as social interaction and contractual relationships. But what patterns underlie the emergence of industrial networks and what support should research provide for practitioners? First, it appears that manufacturing is becoming a commodity rather than a unique capability, which accounts especially for low-technology approaches in downstream parts of the network, for example, in assembly operations. Second, the increased tendency towards specialisation has forced other, upstream, parts of industrial networks to introduce advanced manufacturing technologies for niche markets. Third, the capital market for investments in capacity, and the trade in manufacturing as a commodity, dominates resource allocation to a larger extent than was previously the case. Fourth, there is becoming a continuous move towards more loosely connected entities that comprise manufacturing networks. Finally, in these networks, concepts for supply chain management should address collaboration and information technology that supports decentralised decision-making, in particular to address sustainable and green supply chains. More traditional concepts, such as the keiretsu and chaibol networks of some Asian economies, do not sufficiently support the demands now being placed on networks. Research should address these five fundamental challenges to prepare for the industrial networks of 2020 and beyond. © 2010 Springer-Verlag London.

Entrepreneurial profile of the UK in the light of the Global Entrepreneurship and Development Index

In this research summary, we provide a novel look into the entrepreneurial profile of the UK in an international context. We use a new method – the Global Entrepreneurship and Development Index GEDI – to identify the entrepreneurial strengths and weaknesses of the UK economy, as well as to identify potential bottlenecks that hold back the performance of the UK relative to other advanced economies. We perform a Penalty for Bottleneck analysis to identify the bottlenecks in the UK's entrepreneurial profile. We also explore optimal resource allocation for UK's policy for National Systems of Entrepreneurship.

Industrial networks of the future:a critical commentary on research and practice

Academia has followed the interest by companies in establishing industrial networks by studying aspects such as social interaction and contractual relationships. But what patterns underlie the emergence of industrial networks and what support should research provide for practitioners? Firstly, it seems that manufacturing is becoming a commodity rather than a unique capability, which accounts especially for low-technology approaches in downstream parts of the network, for example in assembly operations. Secondly, the increased tendency to specialize forces other parts of industrial networks to introduce advanced manufacturing technologies for niche markets. Thirdly, the capital market for investments in capacity and the trade in manufacturing as a commodity dominates resource allocation to a larger extent. Fourthly, there will be a continuous move toward more loosely connected entities forming manufacturing networks. More traditional concepts, like keiretsu and chaibol networks, do not sufficiently support this transition. Research should address these fundamental challenges to prepare for the industrial networks of 2020 and beyond.

The multiple pheromone ant clustering algorithm and its application to real world domains

The Multiple Pheromone Ant Clustering Algorithm (MPACA) models the collective behaviour of ants to find clusters in data and to assign objects to the most appropriate class. It is an ant colony optimisation approach that uses pheromones to mark paths linking objects that are similar and potentially members of the same cluster or class. Its novelty is in the way it uses separate pheromones for each descriptive attribute of the object rather than a single pheromone representing the whole object. Ants that encounter other ants frequently enough can combine the attribute values they are detecting, which enables the MPACA to learn influential variable interactions. This paper applies the model to real-world data from two domains. One is logistics, focusing on resource allocation rather than the more traditional vehicle-routing problem. The other is mental-health risk assessment. The task for the MPACA in each domain was to predict class membership where the classes for the logistics domain were the levels of demand on haulage company resources and the mental-health classes were levels of suicide risk. Results on these noisy real-world data were promising, demonstrating the ability of the MPACA to find patterns in the data with accuracy comparable to more traditional linear regression models. © 2013 Polish Information Processing Society.

Message-passing for inference and optimization of real variables on sparse graphs

The inference and optimization in sparse graphs with real variables is studied using methods of statistical mechanics. Efficient distributed algorithms for the resource allocation problem are devised. Numerical simulations show excellent performance and full agreement with the theoretical results. © Springer-Verlag Berlin Heidelberg 2006.

State advances and private retreats? Evidence from the decomposition of the Chinese manufacturing aggregate productivity decomposition in China

This paper is motivated by the recent debate on the existence and scale of China's 'Guo Jin Min Tui' phenomenon, which is often translated as 'the state sector advances and the private sector retreats'. We argue that the profound implication of an advancing state sector is not the size expansion of the state ownership in the economy per se, but the likely retardation of the development of the already financially constrained private sector and the issues around the sustainability of the already weakening Chinese economy growth. Drawing on recent methodological advances, we provide a critical analysis of the contributions of the state and non-state sectors in the aggregate Total Factor Productivity and its growth over the period of 1998-2007 to verify the existence of GJMT and its possible impacts on Chinese economic growth. Overall, we find strong and consistent evidence of a systematic and worsening resource misallocation within the state sector and/or between the state sectors and private sectors over time. This suggests that non-market forces allow resources to be driven away from their competitive market allocation and towards the inefficient state sector. Crown Copyright © 2014.

A framework for automated construction of resource space based on background knowledge

Resource Space Model is a kind of data model which can effectively and flexibly manage the digital resources in cyber-physical system from multidimensional and hierarchical perspectives. This paper focuses on constructing resource space automatically. We propose a framework that organizes a set of digital resources according to different semantic dimensions combining human background knowledge in WordNet and Wikipedia. The construction process includes four steps: extracting candidate keywords, building semantic graphs, detecting semantic communities and generating resource space. An unsupervised statistical language topic model (i.e., Latent Dirichlet Allocation) is applied to extract candidate keywords of the facets. To better interpret meanings of the facets found by LDA, we map the keywords to Wikipedia concepts, calculate word relatedness using WordNet's noun synsets and construct corresponding semantic graphs. Moreover, semantic communities are identified by GN algorithm. After extracting candidate axes based on Wikipedia concept hierarchy, the final axes of resource space are sorted and picked out through three different ranking strategies. The experimental results demonstrate that the proposed framework can organize resources automatically and effectively.©2013 Published by Elsevier Ltd. All rights reserved.

Quality-driven resource utilization methods for video streaming in wireless communication networks

This research is focused on the optimisation of resource utilisation in wireless mobile networks with the consideration of the users’ experienced quality of video streaming services. The study specifically considers the new generation of mobile communication networks, i.e. 4G-LTE, as the main research context. The background study provides an overview of the main properties of the relevant technologies investigated. These include video streaming protocols and networks, video service quality assessment methods, the infrastructure and related functionalities of LTE, and resource allocation algorithms in mobile communication systems. A mathematical model based on an objective and no-reference quality assessment metric for video streaming, namely Pause Intensity, is developed in this work for the evaluation of the continuity of streaming services. The analytical model is verified by extensive simulation and subjective testing on the joint impairment effects of the pause duration and pause frequency. Various types of the video contents and different levels of the impairments have been used in the process of validation tests. It has been shown that Pause Intensity is closely correlated with the subjective quality measurement in terms of the Mean Opinion Score and this correlation property is content independent. Based on the Pause Intensity metric, an optimised resource allocation approach is proposed for the given user requirements, communication system specifications and network performances. This approach concerns both system efficiency and fairness when establishing appropriate resource allocation algorithms, together with the consideration of the correlation between the required and allocated data rates per user. Pause Intensity plays a key role here, representing the required level of Quality of Experience (QoE) to ensure the best balance between system efficiency and fairness. The 3GPP Long Term Evolution (LTE) system is used as the main application environment where the proposed research framework is examined and the results are compared with existing scheduling methods on the achievable fairness, efficiency and correlation. Adaptive video streaming technologies are also investigated and combined with our initiatives on determining the distribution of QoE performance across the network. The resulting scheduling process is controlled through the prioritization of users by considering their perceived quality for the services received. Meanwhile, a trade-off between fairness and efficiency is maintained through an online adjustment of the scheduler’s parameters. Furthermore, Pause Intensity is applied to act as a regulator to realise the rate adaptation function during the end user’s playback of the adaptive streaming service. The adaptive rates under various channel conditions and the shape of the QoE distribution amongst the users for different scheduling policies have been demonstrated in the context of LTE. Finally, the work for interworking between mobile communication system at the macro-cell level and the different deployments of WiFi technologies throughout the macro-cell is presented. A QoEdriven approach is proposed to analyse the offloading mechanism of the user’s data (e.g. video traffic) while the new rate distribution algorithm reshapes the network capacity across the macrocell. The scheduling policy derived is used to regulate the performance of the resource allocation across the fair-efficient spectrum. The associated offloading mechanism can properly control the number of the users within the coverages of the macro-cell base station and each of the WiFi access points involved. The performance of the non-seamless and user-controlled mobile traffic offloading (through the mobile WiFi devices) has been evaluated and compared with that of the standard operator-controlled WiFi hotspots.

Enhanced connectivity and QoE through LTE-WiFi interworking in Smart Cities

Mobile communication and networking infrastructures play an important role in the development of smart cities, to support real-time information exchange and management required in modern urbanization. Mobile WiFi devices that help offloading data traffic from the macro-cell base station and serve the end users within a closer range can significantly improve the connectivity of wireless communications between essential components including infrastructural and human devices in a city. However, this offloading function through interworking between LTE and WiFi systems will change the pattern of resource distributions operated by the base station. In this paper, a resource allocation scheme is proposed to ensure stable service coverage and end-user quality of experience (QoE) when offloading takes place in a macro-cell environment. In this scheme, a rate redistribution algorithm is derived to form a parametric scheduler to meet the required levels of efficiency and fairness, guided by a no-reference quality assessment metric. We show that the performance of resource allocation can be regulated by this scheduler without affecting the service coverage offered by the WLAN access point. The performances of different interworking scenarios and macro-cell scheduling policies are also compared.

Comparative analysis of the relationship between phenological phenomena and meteorological indicators based on insect and plant monitoring

Climate change is one of the biggest environmental problems of the 21st century. The most sensitive indicators of the effects of the climatic changes are phenological processes of the biota. The effects of climate change which were observed the earliest are the remarkable changes in the phenology (i.e. the timing of the phenophases) of the plants and animals, which have been systematically monitored later. In our research we searched for the answer: which meteorological factors show the strongest statistical relationships with phenological phenomena based on some chosen plant and insect species (in case of which large phenological databases are available). Our study was based on two large databases: one of them is the Lepidoptera database of the Hungarian Plant Protection and Forestry Light Trap Network, the other one is the Geophytes Phenology Database of the Botanical Garden of Eötvös Loránd University. In the case of butterflies, statistically defined phenological dates were determined based on the daily collection data, while in the case of plants, observation data on blooming were available. The same meteorological indicators were applied for both groups in our study. On the basis of the data series, analyses of correlation were carried out and a new indicator, the so-called G index was introduced, summing up the number of correlations which were found to be significant on the different levels of significance. In our present study we compare the significant meteorological factors and analyse the differences based on the correlation data on plants and butterflies. Data on butterflies are much more varied regarding the effectiveness of the meteorological factors.

Matching human resource and corporate strategies

Increasing use of the term, Strategic Human Resource Management (SHRM), reflects the recognition of the interdependencies between corporate strategy, organization and human resource management in the functioning of the firm. Dyer and Holder (1988) proposed a comprehensive Human Resource Strategic Typology consisting of three strategic types--inducement, investment and involvement. This research attempted to empirically validate their typology and also test the performance implications of the match between corporate strategy and HR strategy. Hypotheses were tested to determine the relationships between internal consistency in HRM sub-systems, match between corporate strategy and HR strategy, and firm performance. Data were collected by a mail survey of 998 senior HR executives of whom 263 returned the completed questionnaire. Financial information on 909 firms was collected from secondary sources like 10-K reports and CD-Disclosure. Profitability ratios were indexed to industry averages. Confirmatory Factor Analysis using LISREL provided support in favor of the six-factor HR measurement model; the six factors were staffing, training, compensation, appraisal, job design and corporate involvement. Support was also found for the presence of a second-order factor labeled "HR Strategic Orientation" explaining the variations among the six factors. LISREL analysis also supported the congruence hypothesis that HR Strategic Orientation significantly affects firm performance. There was a significant associative relationship between HR Strategy and Corporate Strategy. However, the contingency effects of the match between HR and Corporate strategies were not supported. Several tests were conducted to show that the survey results are not affected by non-response bias nor by mono-method bias. Implications of these findings for both researchers and practitioners are discussed. ^

Short and long hydroperiod Everglades periphyton mats: Community characterization and experimental hydroperiod manipulation

Hydroperiod, or the distribution, duration and timing of flooding affects both plant and animal distributions. The Florida Everglades is currently undergoing restoration that will result in altered hydroperiods. This study was conducted in Everglades National Park to document the variability in periphyton community structure and function between long and short hydroperiod Everglades marshes. Periphyton is an important primary producer and important food resource in the Everglades. Periphyton is also involved in marl soil formation and nutrient cycling. Although periphyton is an important component of the Everglades landscape, little is known about periphyton structural-functional variation between hydroperiods. ^ For this study diatoms, as well as fresh algae slides of diatoms, cyanobacteria and green algae were identified and enumerated. Short verse long hydroperiod soil and water column nutrients were compared. Short and long hydroperiod algal periphyton mat productivity rates were compared using BOD incubations. Experimental manipulations were performed to determine the effects of desiccation duration and rewetting on periphyton productivity, community structure, and nutrient flux. ^ Variation in periphyton community structure was significantly greater between hydroperiods than within hydroperiods. Short and long hydroperiod periphyton mats have the same algal species, it is the distribution and abundance that varies between hydroperiods. Long hydroperiod mats have greater diatom abundance while short hydroperiod mats have greater relative filamentous cyanobacterial abundance. ^ Long hydroperiod mats had greater net primary production (npp) than short hydroperiod mats. Short hydroperiod mats respond to rewetting more rapidly than do long hydroperiod mats. Dry short hydroperiod mats became net primary producers within 24 hours of rehydration. Increasing desiccation duration led to greater cyanobacterial abundance in long hydroperiod mats and decreased diatom abundance in both long and short hydroperiod mats. ^

Ecosystem structure in disturbed and restored subtropical seagrass meadows

Shallow seagrass ecosystems frequently experience physical disturbance from vessel groundings. Specific restoration methods that modify physical, chemical, and biological aspects of disturbances are used to accelerate recovery. This study evaluated loss and recovery of ecosystem structure in disturbed seagrass meadows through plant and soil properties used as proxies for primary and secondary production, habitat quality, benthic metabolism, remineralization, and nutrient storage and exchange. The efficacy of common seagrass restoration techniques in accelerating recovery was also assessed. Beyond removal of macrophyte biomass, disturbance to seagrass sediments resulted in loss of organic matter and stored nutrients, and altered microbial and infaunal communities. Evidence of the effectiveness of restoration actions was variable. Fill placement prevented additional erosion, but the resulting sediment matrix had different physical properties, low organic matter content and nutrient pools, reduced benthic metabolism, and less primary and secondary production relative to the undisturbed ecosystem. Fertilization was effective in increasing nitrogen and phosphorus availability in the sediments, but concurrent enhancement of seagrass production was not detected. Seagrass herbivores removed substantial seagrass biomass via direct grazing, suggesting that leaf loss to seagrass herbivores is a spatially variable but critically important determinant of seagrass transplanting success. Convergence of plant and sediment response variables with levels in undisturbed seagrass meadows was not detected via natural recovery of disturbed sites, or through filling and fertilizing restoration sites. However, several indicators of ecosystem development related to primary production and nutrient accumulation suggest that early stages of ecosystem development have begun at these sites. This research suggests that vessel grounding disturbances in seagrass ecosystems create more complex and persistent resource losses than previously understood by resource managers. While the mechanics of implementing common seagrass restoration actions have been successfully developed by the restoration community, expectations of consistent or rapid recovery trajectories following restoration remain elusive.

Host and network optimizations for performance enhancement and energy efficiency in data center networks

Modern data centers host hundreds of thousands of servers to achieve economies of scale. Such a huge number of servers create challenges for the data center network (DCN) to provide proportionally large bandwidth. In addition, the deployment of virtual machines (VMs) in data centers raises the requirements for efficient resource allocation and find-grained resource sharing. Further, the large number of servers and switches in the data center consume significant amounts of energy. Even though servers become more energy efficient with various energy saving techniques, DCN still accounts for 20% to 50% of the energy consumed by the entire data center. The objective of this dissertation is to enhance DCN performance as well as its energy efficiency by conducting optimizations on both host and network sides. First, as the DCN demands huge bisection bandwidth to interconnect all the servers, we propose a parallel packet switch (PPS) architecture that directly processes variable length packets without segmentation-and-reassembly (SAR). The proposed PPS achieves large bandwidth by combining switching capacities of multiple fabrics, and it further improves the switch throughput by avoiding padding bits in SAR. Second, since certain resource demands of the VM are bursty and demonstrate stochastic nature, to satisfy both deterministic and stochastic demands in VM placement, we propose the Max-Min Multidimensional Stochastic Bin Packing (M3SBP) algorithm. M3SBP calculates an equivalent deterministic value for the stochastic demands, and maximizes the minimum resource utilization ratio of each server. Third, to provide necessary traffic isolation for VMs that share the same physical network adapter, we propose the Flow-level Bandwidth Provisioning (FBP) algorithm. By reducing the flow scheduling problem to multiple stages of packet queuing problems, FBP guarantees the provisioned bandwidth and delay performance for each flow. Finally, while DCNs are typically provisioned with full bisection bandwidth, DCN traffic demonstrates fluctuating patterns, we propose a joint host-network optimization scheme to enhance the energy efficiency of DCNs during off-peak traffic hours. The proposed scheme utilizes a unified representation method that converts the VM placement problem to a routing problem and employs depth-first and best-fit search to find efficient paths for flows.