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GREAT Deliverable 6.2. Dissemination and exploitation plan
Full text linkThis document provides detail of the instruments, tools and processes to be deployed by the Games
Realising Effective Affective Transformation (GREAT) project partners and associates to engage
stakeholders, raise awareness and leverage the project outcomes, outputs, findings and results.
In conjunction with the supporting, associated, dynamic ‘activity plan’ the document will be used by the
project to inform, manage and operationalise dissemination and exploitation activities.
The core elements of the plan are:
● To provide an integrated and consistent external profile for the project, to facilitate recognition,
raise awareness and engage identified target groups.
● To ensure visibility of the project’s actions, activities, outcomes, research findings, and events.
● To disseminate extensively and intensively the achievements of the project and the effectiveness
of the GREAT approach to targeted audiences.
● To leverage the international networks that are linked to consortium members.
● To provide a roadmap for successful commercial and non-commercial exploitation of the project
outcomes.
This first version of the deliverable (D6.2) will be updated and revised with a second iteration at a later
point of the project in month 30. The updated version (D6.4) will incorporate specific details of activities
undertaken, strategic updates and reflections informed by the emergent experience of the project as it
progresse
Fast capture and efficient removal of bloom algae based on improved dielectrophoresis process
Full text linkA dielectrophoresis (DEP) method for direct capture and fast removal of Anabaena was established in this work. The factors affecting the removal efficiency of Anabaena were investigated systematically, leading to optimized experimental conditions and improved DEP process equipment. The experimental results showed that our improved DEP method could directly capture Anabaena in eutrophic water with much enhanced removal efficiency of Anabaena from high-concentration algal bloom-eutrophication-simulated solution. The removal rate could increase by more than 20% after applying DEP at 15 V compared with a pure filtration process. Moreover, the removal rate could increase from 38.76% to 80.18% in optimized experimental conditions (the initial concentration of 615 μg/L, a flow rate of 0.168 L/h, an AC voltage of 15 V, and frequency of 100 kHz). Optical microscopic images showed that the structure of the captured algae cells was intact, indicating that the DEP method could avoid the secondary pollution caused by the addition of reagents and the release of phycotoxins, providing a new practical method for emergent treatment of water bloom outbreaks
A new AI-based approach for rental tax evasion management in Iran(ethical consideration)
No full textIn any nation, some parts of society are unsatisfied with the idea of
paying taxes. Some authorities have tried to fill the gaps in law by adopting
techniques to discourage tax evasion and tax fraud. In this case, technology,
especially big data have been used to enable tax collection and regulation. This
paper studied the pivotal role of big data in rental tax evasion management in
different countries. In order to solve the issues, this paper investigates tax evasion
in the rental era and then applies the GIS approach in describing geo-behaviours,
social connections, and the interaction between taxpayers and properties. The
idea is to reduce evasion and fraud in Tax Management in Iran by applying the
‘National Licensing Schema’ for landlords, using Tax Profiling System
combined with GIS and GraphDB. This is to identify the landlord’s and tenants’
relationship
Design and implementation of camera-based security system (CBSS) for detecting missing persons
No full textAn efficient AI-based Camera security system is
important for locating missing persons. In simple words, if
any suspicious face is detected by the system, it sends an
alert to the authorized people. Thus, this eliminates the risk
of a certain theft from the organization. The focus in our
project is implementing and designing a camera-based security
system (CBSS) for locating missing persons. The CBSS system is
designed using a high resolution camera for detection and several
facial recognition features were implemented in the model. In
the end, the experiments of our program showed that the system
had a more accurate detection notwithstanding the proximity of
detection and in almost all the angular positions of detection
Reference values for wrist-worn accelerometer physical activity metrics in England children and adolescents
Full text linkBackground: Over the last decade use of raw acceleration metrics to assess physical activity has increased. Metrics such as Euclidean Norm Minus One (ENMO), and Mean Amplitude Deviation (MAD) can be used to generate metrics which describe physical activity volume (average acceleration), intensity distribution (intensity gradient), and intensity of the most active periods (MX metrics) of the day. Presently, relatively little comparative data for these metrics exists in youth. To address this need, this study presents age- and sex-specific reference percentile values in England youth and compares physical activity volume and intensity profiles by age and sex. Methods: Wrist-worn accelerometer data from 10 studies involving youth aged 5 to 15 y were pooled. Weekday and weekend waking hours were first calculated for youth in school Years (Y) 1&2, Y4&5, Y6&7, and Y8&9 to determine waking hours durations by age-groups and day types. A valid waking hours day was defined as accelerometer wear for ≥ 600 min·d−1 and participants with ≥ 3 valid weekdays and ≥ 1 valid weekend day were included. Mean ENMO- and MAD-generated average acceleration, intensity gradient, and MX metrics were calculated and summarised as weighted week averages. Sex-specific smoothed percentile curves were generated for each metric using Generalized Additive Models for Location Scale and Shape. Linear mixed models examined age and sex differences. Results: The analytical sample included 1250 participants. Physical activity peaked between ages 6.5–10.5 y, depending on metric. For all metrics the highest activity levels occurred in less active participants (3rd-50th percentile) and girls, 0.5 to 1.5 y earlier than more active peers, and boys, respectively. Irrespective of metric, boys were more active than girls (p < .001) and physical activity was lowest in the Y8&9 group, particularly when compared to the Y1&2 group (p < .001). Conclusions: Percentile reference values for average acceleration, intensity gradient, and MX metrics have utility in describing age- and sex-specific values for physical activity volume and intensity in youth. There is a need to generate nationally-representative wrist-acceleration population-referenced norms for these metrics to further facilitate health-related physical activity research and promotion
Resource orchestration in Indian ethnic entrepreneurial enterprises through generation change in Malaysia
No full textEthnic entrepreneurial enterprises are continuously evolving, especially when generations change. As these changes take place, resources are also orchestrated differently. However, research gap exists on how resources are orchestrated in ethnic entrepreneurial enterprises through generational change. We answer this question by adopting a qualitative approach based on data from eleven ethnic entrepreneurial enterprises that have experienced generational succession. The data was then analysed by adopting a novel approach of artificial intelligence. Our results suggest that the orchestration in class and ethnic resources has equipped the later generation ethnic entrepreneurs with capabilities to expand and develop their ethnic entrepreneurial enterprises. We emphasize the importance of orchestrating resources in ethnic entrepreneurial enterprises for product innovation, market growth and business development as generations change. The use of artificial intelligence technique enables underlying patterns in ethnic entrepreneurship to be discovered, which assist practitioners in making the best decisions concerning entrepreneurial efforts. This study invites entrepreneurs to comprehend the importance of orchestrating resources for entrepreneurial decision-making in business expansion and development, especially in ethnic entrepreneurial enterprises. With novelty in the methodological application, we extend a cordial invitation to erudite scholars to apply artificial intelligence technique within qualitative research to achieve precision and nuances
Understanding advance care planning for children and young people: a survey of health professionals
No full textBackground:
A range of polices, documentation, and practices are associated with advance care planning. However, there is a shortage of research to understand advance care planning from a professional viewpoint.
Aims:
To explore the views and experiences of health professionals of the advance care planning process with children and young people.
Methods:
An online questionnaire was used to collect data, which were analysed thematically.
Findings:
Key findings related to barriers and facilitators to initiating and documenting advance care planning: understanding the process and the condition of the patient; how advance care planning works in practice; and access to relevant, affordable training options.
Conclusion:
Additional training and standardised documentation can help support the initiation and use of advance care planning, reduce misperceptions, and generate greater confidence in participating in the process. A larger multidisciplinary team, with better communication, will support improved relationships between professionals which will filter down to the families
The potential of trustful leadership : an examination of its impact on stress and performance in the modern workplace
Full text linkTrust is a vital element of effective leadership, especially in high-stress work
environments. While a single positive occurrence may create short-term trust,
sustainable trust can only be established when an individual meets the criteria and
indications of a trustworthy person. Trustful leadership is generally assumed to be
positively related to employee performance in a stressed work environment.
However, ambiguity surrounding empirical evidence on trust or trustworthiness,
coupled with the existence of theoretical predictions and differences, underscores the
complexity of these constructs. This research introduces a comprehensive exploration
of the interplay between trustful leadership and employee performance, emphasizing the
pivotal role of specific leadership strategies in high-stress contexts. By bridging the gap
between theoretical predictions and empirical evidence, this study offers a novel
perspective, enriching the discourse on trustful leadership and its tangible impacts in
organizational settings.
Using Interpretative Phenomenological Analysis (IPA), this paper investigates the
relationship between trustful leadership and performance, examining the moderating
effect of five strategies and behaviours — recognition, empowerment, reinforcement,
communication, and mindful leadership behaviour.
The study found that among these strategies, mindful leadership behaviour and
empowerment had the most significant impact in enhancing the positive relationship
between trustful leadership and employee performance in high-stress environments
Development of a conceptual framework for strategic implementation of health, safety and environmental management in the UAE construction industry
Full text linkThe study critically evaluates strategic implementation of health and safety (H&S) and its effect on Environmental Management in the United Arab Emirates (UAE) construction industry. Previous research indicates that the construction industry, while improving its injury rates, is not making up sufficient ground on all industry-specific average performances. In a modernising construction industry, it must be asked why there is no bold commitment to lowering these rates by high percentages? Perhaps it is time for responsible authorities to step up and do their job. Construction workers comprise a significant percentage of the Gulf Cooperation Council’s (GCC) migrant workforces. The study adopted mixed research methods. Qualitative data collected were analysed using thematic analysis has been performed for qualitative data collected by six interviews, and for the quantitative approach in a survey of 106 UAE construction professionals and has been conducted to support the findings.
The findings indicate that reviews and audits and evaluations are integral for projects to sustain their specialist competence. These mechanisms assist project heads in navigating the evolving landscape of the industry by leveraging accumulated expertise. Traditional engineering guidance seems insufficient for today's construction project overseers. Construction project outcomes are often gauged by work efficiency, which gets swayed by the effectiveness of construction practices. Given the labour centric nature of construction, the workforce emerges as a primary asset. Common challenges include a lack of clarity and executing tasks in an unordered manner, which can impede construction effectiveness. Reward structures appear to have a positive influence on job contentment, organizational allegiance, and worker output. Tech-driven solutions have been embraced to bolster workplace safety and enhance service standards. Boosting service excellence involves refining operations and sidestepping missteps
An effective analysis of palm print detection using Resnet framework in comparison with Recurrent Neural Network to improve classification accuracy
Full text linkThe goal of the proposed study is to use
ResNet rather than a novel recurrent neural network
to identify plant diseases with greater classification
accuracy. Materials and Methods: The detection of
plant disease is performed using ResNet and
Recurrent Neural Network algorithms. The sample
size for each sample is considered as 10 which is
performed with a G power calculator. Results: The
ResNet algorithm exhibited better results with
classification accuracy of 95% compared to that of
Novel Recurrent Neural Network with accuracy of
85%. The insignificant accuracy value of p=0.139
(p>0.05) is attained through SPSS Statistical Analysis.
Conclusion: The classification of plant disease using
ResNet is better than the Novel Recurrent Neural
Network