1,552 research outputs found
Trust and control interrelations: New perspectives on the trust control nexus
This article is the post-print version of the published article that may be accessed at the link below. Copyright @ 2007 Sage Publications.This article introduces the special issue on New Perspectives on the Trust-Control Nexus in Organizational Relations. Trust and control are interlinked processes commonly seen as key to reach effectiveness in inter- and intraorganizational relations. The relation between trust and control is, however, a complex one, and research into this relation has given rise to various and contradictory interpretations of how trust and control relate. A well-known discussion is directed at whether trust and control are better conceived as substitutes, or as complementary mechanisms of governance. The articles in this special issue bring the discussion on the relationship between both concepts a step further by identifying common factors, distinctive mechanisms, and key implications relevant for theory building and empirical research. By studying trust and control through different perspectives and at different levels of analysis, the articles provide new theoretical insights and empirical evidence on the foundations of the trust-control interrelations
A Human Development Framework for CO2 Reductions
Although developing countries are called to participate in CO2 emission
reduction efforts to avoid dangerous climate change, the implications of
proposed reduction schemes in human development standards of developing
countries remain a matter of debate. We show the existence of a positive and
time-dependent correlation between the Human Development Index (HDI) and per
capita CO2 emissions from fossil fuel combustion. Employing this empirical
relation, extrapolating the HDI, and using three population scenarios, the
cumulative CO2 emissions necessary for developing countries to achieve
particular HDI thresholds are assessed following a Development As Usual
approach (DAU). If current demographic and development trends are maintained,
we estimate that by 2050 around 85% of the world's population will live in
countries with high HDI (above 0.8). In particular, 300Gt of cumulative CO2
emissions between 2000 and 2050 are estimated to be necessary for the
development of 104 developing countries in the year 2000. This value represents
between 20% to 30% of previously calculated CO2 budgets limiting global warming
to 2{\deg}C. These constraints and results are incorporated into a CO2
reduction framework involving four domains of climate action for individual
countries. The framework reserves a fair emission path for developing countries
to proceed with their development by indexing country-dependent reduction rates
proportional to the HDI in order to preserve the 2{\deg}C target after a
particular development threshold is reached. Under this approach, global
cumulative emissions by 2050 are estimated to range from 850 up to 1100Gt of
CO2. These values are within the uncertainty range of emissions to limit global
temperatures to 2{\deg}C.Comment: 14 pages, 7 figures, 1 tabl
Machine learning based IoT Intrusion Detection System:an MQTT case study (MQTT-IoT-IDS2020 Dataset)
The Internet of Things (IoT) is one of the main research fields in the Cybersecurity domain. This is due to (a) the increased dependency on automated device, and (b) the inadequacy of general-purpose Intrusion Detection Systems (IDS) to be deployed for special purpose networks usage. Numerous lightweight protocols are being proposed for IoT devices communication usage. One of the distinguishable IoT machine-to-machine communication protocols is Message Queuing Telemetry Transport (MQTT) protocol. However, as per the authors best knowledge, there are no available IDS datasets that include MQTT benign or attack instances and thus, no IDS experimental results available. In this paper, the effectiveness of six Machine Learning (ML) techniques to detect MQTT-based attacks is evaluated. Three abstraction levels of features are assessed, namely, packet-based, unidirectional flow, and bidirectional flow features. An MQTT simulated dataset is generated and used for the training and evaluation processes. The dataset is released with an open access licence to help the research community further analyse the accompanied challenges. The experimental results demonstrated the adequacy of the proposed ML models to suit MQTT-based networks IDS requirements. Moreover, the results emphasise on the importance of using flow-based features to discriminate MQTT-based attacks from benign traffic, while packet-based features are sufficient for traditional networking attacks
Half Life of the Doubly-magic r-Process Nucleus 78Ni
Nuclei with magic numbers serve as important benchmarks in nuclear theory. In
addition, neutron-rich nuclei play an important role in the astrophysical rapid
neutron-capture process (r-process). 78Ni is the only doubly-magic nucleus that
is also an important waiting point in the r-process, and serves as a major
bottleneck in the synthesis of heavier elements. The half-life of 78Ni has been
experimentally deduced for the first time at the Coupled Cyclotron Facility of
the National Superconducting Cyclotron Laboratory at Michigan State University,
and was found to be 110 (+100 -60) ms. In the same experiment, a first
half-life was deduced for 77Ni of 128 (+27 -33) ms, and more precise half-lives
were deduced for 75Ni and 76Ni of 344 (+20 -24) ms and 238 (+15 -18) ms
respectively.Comment: 4 pages, 3 figure
Investigating the missing data mechanism in quality of life outcomes: a comparison of approaches
Background: Missing data is classified as missing completely at random (MCAR), missing at
random (MAR) or missing not at random (MNAR). Knowing the mechanism is useful in identifying
the most appropriate analysis. The first aim was to compare different methods for identifying this
missing data mechanism to determine if they gave consistent conclusions. Secondly, to investigate
whether the reminder-response data can be utilised to help identify the missing data mechanism.
Methods: Five clinical trial datasets that employed a reminder system at follow-up were used.
Some quality of life questionnaires were initially missing, but later recovered through reminders.
Four methods of determining the missing data mechanism were applied. Two response data
scenarios were considered. Firstly, immediate data only; secondly, all observed responses
(including reminder-response).
Results: In three of five trials the hypothesis tests found evidence against the MCAR assumption.
Logistic regression suggested MAR, but was able to use the reminder-collected data to highlight
potential MNAR data in two trials.
Conclusion: The four methods were consistent in determining the missingness mechanism. One
hypothesis test was preferred as it is applicable with intermittent missingness. Some inconsistencies between the two data scenarios were found. Ignoring the reminder data could potentially give a distorted view of the missingness mechanism. Utilising reminder data allowed the possibility of MNAR to be considered.The Chief Scientist Office of the Scottish Government Health Directorate.
Research Training Fellowship (CZF/1/31
Combining estimates of interest in prognostic modelling studies after multiple imputation: current practice and guidelines
Background: Multiple imputation (MI) provides an effective approach to handle missing covariate
data within prognostic modelling studies, as it can properly account for the missing data
uncertainty. The multiply imputed datasets are each analysed using standard prognostic modelling
techniques to obtain the estimates of interest. The estimates from each imputed dataset are then
combined into one overall estimate and variance, incorporating both the within and between
imputation variability. Rubin's rules for combining these multiply imputed estimates are based on
asymptotic theory. The resulting combined estimates may be more accurate if the posterior
distribution of the population parameter of interest is better approximated by the normal
distribution. However, the normality assumption may not be appropriate for all the parameters of
interest when analysing prognostic modelling studies, such as predicted survival probabilities and
model performance measures.
Methods: Guidelines for combining the estimates of interest when analysing prognostic modelling
studies are provided. A literature review is performed to identify current practice for combining
such estimates in prognostic modelling studies.
Results: Methods for combining all reported estimates after MI were not well reported in the
current literature. Rubin's rules without applying any transformations were the standard approach
used, when any method was stated.
Conclusion: The proposed simple guidelines for combining estimates after MI may lead to a wider
and more appropriate use of MI in future prognostic modelling studies
The epidemiology of patellar luxation in dogs attending primary-care veterinary practices in England
Visualisation of trust and quality information for geospatial dataset selection and use:Drawing trust presentation comparisons with B2C e-Commerce
The evaluation of geospatial data quality and trustworthiness presents a major challenge to geospatial data users when making a dataset selection decision. Part of the problem arises from the inconsistent and patchy nature of data quality information, which makes intercomparison very difficult. Over recent years, the production and availability of geospatial data has significantly increased, facilitated by the recent explosion of Web-based catalogues, portals, standards and services, and by initiatives such as INSPIRE and GEOSS. Despite this significant growth in availability of geospatial data and the fact that geospatial datasets can, in many respects, be considered commercial products that are available for purchase online, consumer trust has to date received relatively little attention in the GIS domain. In this paper, we discuss how concepts of trust, trust models, and trust indicators (largely derived from B2C e-Commerce) apply to the GIS domain and to geospatial data selection and use. Our research aim is to support data users in more efficient and effective geospatial dataset selection on the basis of quality, trustworthiness and fitness for purpose. To achieve this, we propose a GEO label – a decision support mechanism that visually summarises availability of key geospatial data informational aspects. We also present a Web service that was developed to support generation of dynamic GEO label representations for datasets by combining producer metadata (from standard catalogues or other published locations) with structured user feedback
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