365 research outputs found
A Critical Review Of Post-Secondary Education Writing During A 21st Century Education Revolution
Educational materials are effective instruments which provide information and report new discoveries uncovered by researchers in specific areas of academia. Higher education, like other education institutions, rely on instructional materials to inform its practice of educating adult learners. In post-secondary education, developmental English programs are tasked with meeting the needs of dynamic populations, thus there is a continuous need for research in this area to support its changing landscape. However, the majority of scholarly thought in this area centers on K-12 reading and writing. This paucity presents a phenomenon to the post-secondary community. This research study uses a qualitative content analysis to examine peer-reviewed journals from 2003-2017, developmental online websites, and a government issued document directed toward reforming post-secondary developmental education programs. These highly relevant sources aid educators in discovering informational support to apply best practices for student success. Developmental education serves the purpose of addressing literacy gaps for students transitioning to college-level work. The findings here illuminate the dearth of material offered to developmental educators. This study suggests the field of literacy research is fragmented and highlights an apparent blind spot in scholarly literature with regard to English writing instruction. This poses a quandary for post-secondary literacy researchers in the 21st century and establishes the necessity for the literacy research community to commit future scholarship toward equipping college educators teaching writing instruction to underprepared adult learners
Data ethics : building trust : how digital technologies can serve humanity
Data is the magic word of the 21st century. As oil in the 20th century and electricity in the 19th century:
For citizens, data means support in daily life in almost all activities, from watch to laptop, from kitchen to car,
from mobile phone to politics. For business and politics, data means power, dominance, winning the race. Data can be used for good and bad,
for services and hacking, for medicine and arms race. How can we build trust in this complex and ambiguous data world?
How can digital technologies serve humanity? The 45 articles in this book represent a broad range of ethical reflections and recommendations
in eight sections: a) Values, Trust and Law, b) AI, Robots and Humans, c) Health and Neuroscience, d) Religions for Digital Justice, e) Farming, Business, Finance, f) Security, War, Peace, g) Data Governance, Geopolitics, h) Media, Education, Communication.
The authors and institutions come from all continents.
The book serves as reading material for teachers, students, policy makers, politicians, business, hospitals, NGOs and religious organisations alike. It is an invitation for dialogue, debate and building trust!
The book is a continuation of the volume “Cyber Ethics 4.0” published in 2018 by the same editors
Recent trends in robot learning and evolution for swarm robotics
Swarm robotics is a promising approach to control large groups of robots. However, designing the individual behavior of the robots so that a desired collective behavior emerges is still a major challenge. In recent years, many advances in the automatic design of control software for robot swarms have been made, thus making automatic design a promising tool to address this challenge. In this article, I highlight and discuss recent advances and trends in offline robot evolution, embodied evolution, and offline robot learning for swarm robotics. For each approach, I describe recent design methods of interest, and commonly encountered challenges. In addition to the review, I provide a perspective on recent trends and discuss how they might influence future research to help address the remaining challenges of designing robot swarms
Weather or not? The role of international sanctions and climate on food prices in Iran
IntroductionThe scarcity of resources have affected food production, which has challenged the ability of Iran to provide adequate food for the population. Iterative and mounting sanctions on Iran by the international community have seriously eroded Iran's access to agricultural technology and resources to support a growing population. Limited moisture availability also affects Iran's agricultural production. The aim of this study was to analyze the influence of inflation, international sanctions, weather disturbances, and domestic crop production on the price of rice, wheat and lentils from 2010 to 2021 in Iran.MethodData were obtained from the statistical yearbooks of the Ministry of Agriculture in Iran, Statistical Center of Iran, and the Central Bank of Iran. We analyzed econometric measures of food prices, including CPI, food inflation, subsidy reform plan and sanctions to estimate economic relationships. After deflating the food prices through CPI and detrending the time series to resolve the non-linear issue, we used monthly Climate Hazards group Infrared Precipitation with Stations (CHIRPS) precipitation data to analyze the influence of weather disturbances on food prices.Results and discussionThe price of goods not only provides an important indicator of the balance between agricultural production and market demand, but also has strong impacts on food affordability and food security. This novel study used a combination of economic and climate factors to analyze the food prices in Iran. Our statistical modeling framework found that the monthly precipitation on domestic food prices, and ultimately food access, in the country is much less important than the international sanctions, lowering Iran's productive capability and negatively impacting its food security
Managing healthcare transformation towards P5 medicine (Published in Frontiers in Medicine)
Health and social care systems around the world are facing radical organizational, methodological and technological paradigm changes to meet the requirements for improving quality and safety of care as well as efficiency and efficacy of care processes. In this they’re trying to manage the challenges of ongoing demographic changes towards aging, multi-diseased societies, development of human resources, a health and social services consumerism, medical and biomedical progress, and exploding costs for health-related R&D as well as health services delivery. Furthermore, they intend to achieve sustainability of global health systems by transforming them towards intelligent, adaptive and proactive systems focusing on health and wellness with optimized quality and safety outcomes.
The outcome is a transformed health and wellness ecosystem combining the approaches of translational medicine, 5P medicine (personalized, preventive, predictive, participative precision medicine) and digital health towards ubiquitous personalized health services realized independent of time and location. It considers individual health status, conditions, genetic and genomic dispositions in personal social, occupational, environmental and behavioural context, thus turning health and social care from reactive to proactive. This requires the advancement communication and cooperation among the business actors from different domains (disciplines) with different methodologies, terminologies/ontologies, education, skills and experiences from data level (data sharing) to concept/knowledge level (knowledge sharing). The challenge here is the understanding and the formal as well as consistent representation of the world of sciences and practices, i.e. of multidisciplinary and dynamic systems in variable context, for enabling mapping between the different disciplines, methodologies, perspectives, intentions, languages, etc. Based on a framework for dynamically, use-case-specifically and context aware representing multi-domain ecosystems including their development process, systems, models and artefacts can be consistently represented, harmonized and integrated. The response to that problem is the formal representation of health and social care ecosystems through an system-oriented, architecture-centric, ontology-based and policy-driven model and framework, addressing all domains and development process views contributing to the system and context in question.
Accordingly, this Research Topic would like to address this change towards 5P medicine. Specifically, areas of interest include, but are not limited:
• A multidisciplinary approach to the transformation of health and social systems
• Success factors for sustainable P5 ecosystems
• AI and robotics in transformed health ecosystems
• Transformed health ecosystems challenges for security, privacy and trust
• Modelling digital health systems
• Ethical challenges of personalized digital health
• Knowledge representation and management of transformed health ecosystems
Table of Contents:
04 Editorial: Managing healthcare transformation towards P5
medicine
Bernd Blobel and Dipak Kalra
06 Transformation of Health and Social Care Systems—An
Interdisciplinary Approach Toward a Foundational
Architecture
Bernd Blobel, Frank Oemig, Pekka Ruotsalainen and Diego M. Lopez
26 Transformed Health Ecosystems—Challenges for Security,
Privacy, and Trust
Pekka Ruotsalainen and Bernd Blobel
36 Success Factors for Scaling Up the Adoption of Digital
Therapeutics Towards the Realization of P5 Medicine
Alexandra Prodan, Lucas Deimel, Johannes Ahlqvist, Strahil Birov,
Rainer Thiel, Meeri Toivanen, Zoi Kolitsi and Dipak Kalra
49 EU-Funded Telemedicine Projects – Assessment of, and
Lessons Learned From, in the Light of the SARS-CoV-2
Pandemic
Laura Paleari, Virginia Malini, Gabriella Paoli, Stefano Scillieri,
Claudia Bighin, Bernd Blobel and Mauro Giacomini
60 A Review of Artificial Intelligence and Robotics in
Transformed Health Ecosystems
Kerstin Denecke and Claude R. Baudoin
73 Modeling digital health systems to foster interoperability
Frank Oemig and Bernd Blobel
89 Challenges and solutions for transforming health ecosystems
in low- and middle-income countries through artificial
intelligence
Diego M. López, Carolina Rico-Olarte, Bernd Blobel and Carol Hullin
111 Linguistic and ontological challenges of multiple domains
contributing to transformed health ecosystems
Markus Kreuzthaler, Mathias Brochhausen, Cilia Zayas, Bernd Blobel
and Stefan Schulz
126 The ethical challenges of personalized digital health
Els Maeckelberghe, Kinga Zdunek, Sara Marceglia, Bobbie Farsides
and Michael Rigb
Recommended from our members
Proceedings of the 33rd Annual Workshop of the Psychology of Programming Interest Group
This is the Proceedings of the 33rd Annual Workshop of the Psychology of Programming Interest Group (PPIG). This was the first PPIG to be held physically since 2019, following the two online-only PPIGs in 2020 and 2021, both during the Covid pandemic. It was also the first PPIG conference to be designed specifically for hybrid attendance. Reflecting the theme, it was hosted by Music Computing Lab at the Open University in Milton Keynes
Critical analysis from an international law perspective of the United Kingdom's regulatory framework of Space and High-Altitude Activities in the context of changing technology and evolving geopolitical tensions.
This thesis addresses the absence of a comprehensive critical analysis of UK space policy and law. The central research question is to determine whether the UK’s legal and regulatory structure can achieve the government’s objective of growing the UK space economy. This has been addressed by using the concept of regulatory competition to determine how effective the UK’s space strategy is, and whether the policies pursued, and the laws and regulations put in place, are consistent with that strategy. Subsidiary research questions focus on the potential and motivation for regulatory competition; the critical path that provides the framework for UK space policy; the competitiveness of the UK space economy; and the policies required for effective regulatory competition. Although UK space law is derived from the UN space treaties, those obligations are loosely defined which creates the opportunity for regulatory competition. Optimistic economic forecasts provide the motivation for regulatory competition. A Strength Weakness Opportunity Threat analysis concludes that the UK is in a weak position to achieve its space economy aspirations. The UK’s space policy from 1967 to 2009 was characterised by parsimony expressed through opposition to the formation of a space agency, human space flight programs, and a national launch capability. Parsimony reflected a lack of financial resources, which is why the UK focused on the practical exploitation of space applications. These three pillars of UK space policy were abandoned after 2010 due to the influence of public relations concerns on policy. This resulted in the Space Industry Act 2018 and the Space Industry Regulations 2021. Though the core regulatory framework for the licencing of spaceport, range control and launch licences, raise no concerns as to clarity, certainty, complexity, or cost, there is inadequate detail for the licensing of orbital space-activities. The research identified that the Civil Aviation Authority’s (CAA) approach to risk, to process, and timing, were problematical. The legislation and the associated regulations are too complex, and too many organisations are involved in the process. There is also a lack of clarity in the regulations as to the interpretation of key words and phrases. In addition, the regulations give the regulator wide, discretionary powers, and the appeals process lacks transparency and independence. The adoption of an ‘adaptable, outcomes-based regulatory regime’ does not address critical gaps in the CAA’s competence. The scope of national security law, and the risk of broadening of environmental policy in pursuit of ‘thought leadership’, further undermine the attractions of the UK space economy. The CAA lacks the flexibility and authority to balance the requirements needed to prioritise growth over other policy objectives. Though these regulatory weaknesses could be addressed over time, international entrepreneurs are unlikely to finance the CAA’s learning curve. The failure to develop critical Space Domain Awareness capabilities further undermines the claim of competing through regulation. Since 2010, the UK has aspired to securing 10% of the global space economy by 2030. The research concludes that the regulatory framework is not competitive, and so the UK will not achieve that target
Contributions to deconfliction advanced U-space services for multiple unmanned aerial systems including field tests validation
Unmanned Aerial Systems (UAS) will become commonplace, the number of UAS
flying in European airspace is expected to increase from a few thousand to hundreds
of thousands by 2050. To prepare for this approaching, national and international
organizations involved in aerial traffic management are now developing new laws
and restructuring the airspace to incorporate UAS into civil airspace. The Single
European Sky ATM Research considers the development of the U-space, a crucial
step to enable the safe, secure, and efficient access of a large set of UAS into airspace.
The design, integration, and validation of a set of modules that contribute to our
UTM architecture for advanced U-space services are described in this Thesis. With
an emphasis on conflict detection and resolution features, the architecture is flexible,
modular, and scalable. The UTM is designed to work without the need for human
involvement, to achieve U-space required scalability due to the large number of expected
operations. However, it recommends actions to the UAS operator since, under
current regulations, the operator is accountable for carrying out the recommendations
of the UTM. Moreover, our development is based on the Robot Operating System
(ROS) and is open source.
The main developments of the proposed Thesis are monitoring and tactical deconfliction
services, which are in charge of identifying and resolving possible conflicts
that arise in the shared airspace of several UAS. By limiting the conflict search to a
local search surrounding each waypoint, the proposed conflict detection method aims
to improve conflict detection. By splitting the issue down into smaller subproblems
with only two waypoints, the conflict resolution method tries to decrease the deviation
distance from the initial flight plan. The proposed method for resolving potential threats is based on the premise that
UAS can follow trajectories in time and space properly. Therefore, another contribution
of the presented Thesis is an UAS 4D trajectory follower that can correct space
and temporal deviations while following a given trajectory. Currently, commercial autopilots
do not offer this functionality that allows to improve the airspace occupancy
using time as an additional dimension.
Moreover, the integration of onboard detect and avoid capabilities, as well as the
consequences for U-space services are examined in this Thesis. A module capable
of detecting large static unexpected obstacles and generating an alternative route to
avoid the obstacle online is presented.
Finally, the presented UTM architecture has been tested in both software-in-theloop
and hardware-in-the-loop development enviroments, but also in real scenarios
using unmanned aircraft. These scenarios were designed by selecting the most relevant
UAS operation applications, such as the inspection of wind turbines, power lines
and precision agriculture, as well as event and forest monitoring. ATLAS and El
Arenosillo were the locations of the tests carried out thanks to the European projects
SAFEDRONE and GAUSS.Los sistemas aéreos no tripulados (UAS en inglés) se convertirán en algo habitual. Se prevé que el
número de UAS que vuelen en el espacio aéreo europeo pase de unos pocos miles a cientos de
miles en 2050. Para prepararse para esta aproximación, las organizaciones nacionales e
internacionales dedicadas a la gestión del tráfico aéreo están elaborando nuevas leyes y
reestructurando el espacio aéreo para incorporar los UAS al espacio aéreo civil. SESAR (del inglés
Single European Sky ATM Research) considera el desarrollo de U-space, un paso crucial para
permitir el acceso seguro y eficiente de un gran conjunto de UAS al espacio aéreo.
En esta Tesis se describe el diseño, la integración y la validación de un conjunto de módulos que
contribuyen a nuestra arquitectura UTM (del inglés Unmanned aerial system Traffic Management)
para los servicios avanzados del U-space. Con un énfasis en las características de detección y
resolución de conflictos, la arquitectura es flexible, modular y escalable. La UTM está diseñada para
funcionar sin necesidad de intervención humana, para lograr la escalabilidad requerida por U-space
debido al gran número de operaciones previstas. Sin embargo, la UTM únicamente recomienda
acciones al operador del UAS ya que, según la normativa vigente, el operador es responsable de las
operaciones realizadas. Además, nuestro desarrollo está basado en el Sistema Operativo de Robots
(ROS en inglés) y es de código abierto.
Los principales desarrollos de la presente Tesis son los servicios de monitorización y evitación de
conflictos, que se encargan de identificar y resolver los posibles conflictos que surjan en el espacio
aéreo compartido de varios UAS. Limitando la búsqueda de conflictos a una búsqueda local
alrededor de cada punto de ruta, el método de detección de conflictos pretende mejorar la detección
de conflictos. Al dividir el problema en subproblemas más pequeños con sólo dos puntos de ruta, el
método de resolución de conflictos intenta disminuir la distancia de desviación del plan de vuelo
inicial.
El método de resolución de conflictos propuesto se basa en la premisa de que los UAS pueden
seguir las trayectorias en el tiempo y espacio de forma adecuada. Por tanto, otra de las aportaciones
de la Tesis presentada es un seguidor de trayectorias 4D de UAS que puede corregir las
desviaciones espaciales y temporales mientras sigue una trayectoria determinada. Actualmente, los
autopilotos comerciales no ofrecen esta funcionalidad que permite mejorar la ocupación del espacio
aéreo utilizando el tiempo como una dimensión adicional.
Además, en esta Tesis se examina la capacidad de integración de módulos a bordo de detección y
evitación de obstáculos, así como las consecuencias para los servicios de U-space. Se presenta un
módulo capaz de detectar grandes obstáculos estáticos inesperados y capaz de generar una ruta
alternativa para evitar dicho obstáculo.
Por último, la arquitectura UTM presentada ha sido probada en entornos de desarrollo de simulación,
pero también en escenarios reales con aeronaves no tripuladas. Estos escenarios se diseñaron
seleccionando las aplicaciones de operación de UAS más relevantes, como la inspección de
aerogeneradores, líneas eléctricas y agricultura de precisión, así como la monitorización de eventos y
bosques. ATLAS y El Arenosillo fueron las sedes de las pruebas realizadas gracias a los proyectos
europeos SAFEDRONE y GAUSS
WiFi-Based Human Activity Recognition Using Attention-Based BiLSTM
Recently, significant efforts have been made to explore human activity recognition (HAR) techniques that use information gathered by existing indoor wireless infrastructures through WiFi signals without demanding the monitored subject to carry a dedicated device. The key intuition is that different activities introduce different multi-paths in WiFi signals and generate different patterns in the time series of channel state information (CSI). In this paper, we propose and evaluate a full pipeline for a CSI-based human activity recognition framework for 12 activities in three different spatial environments using two deep learning models: ABiLSTM and CNN-ABiLSTM. Evaluation experiments have demonstrated that the proposed models outperform state-of-the-art models. Also, the experiments show that the proposed models can be applied to other environments with different configurations, albeit with some caveats. The proposed ABiLSTM model achieves an overall accuracy of 94.03%, 91.96%, and 92.59% across the 3 target environments. While the proposed CNN-ABiLSTM model reaches an accuracy of 98.54%, 94.25% and 95.09% across those same environments
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