11,527 research outputs found
Towards Autonomous Selective Harvesting: A Review of Robot Perception, Robot Design, Motion Planning and Control
This paper provides an overview of the current state-of-the-art in selective
harvesting robots (SHRs) and their potential for addressing the challenges of
global food production. SHRs have the potential to increase productivity,
reduce labour costs, and minimise food waste by selectively harvesting only
ripe fruits and vegetables. The paper discusses the main components of SHRs,
including perception, grasping, cutting, motion planning, and control. It also
highlights the challenges in developing SHR technologies, particularly in the
areas of robot design, motion planning and control. The paper also discusses
the potential benefits of integrating AI and soft robots and data-driven
methods to enhance the performance and robustness of SHR systems. Finally, the
paper identifies several open research questions in the field and highlights
the need for further research and development efforts to advance SHR
technologies to meet the challenges of global food production. Overall, this
paper provides a starting point for researchers and practitioners interested in
developing SHRs and highlights the need for more research in this field.Comment: Preprint: to be appeared in Journal of Field Robotic
Satellite Image Based Cross-view Localization for Autonomous Vehicle
Existing spatial localization techniques for autonomous vehicles mostly use a
pre-built 3D-HD map, often constructed using a survey-grade 3D mapping vehicle,
which is not only expensive but also laborious. This paper shows that by using
an off-the-shelf high-definition satellite image as a ready-to-use map, we are
able to achieve cross-view vehicle localization up to a satisfactory accuracy,
providing a cheaper and more practical way for localization. While the
utilization of satellite imagery for cross-view localization is an established
concept, the conventional methodology focuses primarily on image retrieval.
This paper introduces a novel approach to cross-view localization that departs
from the conventional image retrieval method. Specifically, our method develops
(1) a Geometric-align Feature Extractor (GaFE) that leverages measured 3D
points to bridge the geometric gap between ground and overhead views, (2) a
Pose Aware Branch (PAB) adopting a triplet loss to encourage pose-aware feature
extraction, and (3) a Recursive Pose Refine Branch (RPRB) using the
Levenberg-Marquardt (LM) algorithm to align the initial pose towards the true
vehicle pose iteratively. Our method is validated on KITTI and Ford Multi-AV
Seasonal datasets as ground view and Google Maps as the satellite view. The
results demonstrate the superiority of our method in cross-view localization
with median spatial and angular errors within meter and ,
respectively.Comment: Accepted by ICRA202
The Metaverse: Survey, Trends, Novel Pipeline Ecosystem & Future Directions
The Metaverse offers a second world beyond reality, where boundaries are
non-existent, and possibilities are endless through engagement and immersive
experiences using the virtual reality (VR) technology. Many disciplines can
benefit from the advancement of the Metaverse when accurately developed,
including the fields of technology, gaming, education, art, and culture.
Nevertheless, developing the Metaverse environment to its full potential is an
ambiguous task that needs proper guidance and directions. Existing surveys on
the Metaverse focus only on a specific aspect and discipline of the Metaverse
and lack a holistic view of the entire process. To this end, a more holistic,
multi-disciplinary, in-depth, and academic and industry-oriented review is
required to provide a thorough study of the Metaverse development pipeline. To
address these issues, we present in this survey a novel multi-layered pipeline
ecosystem composed of (1) the Metaverse computing, networking, communications
and hardware infrastructure, (2) environment digitization, and (3) user
interactions. For every layer, we discuss the components that detail the steps
of its development. Also, for each of these components, we examine the impact
of a set of enabling technologies and empowering domains (e.g., Artificial
Intelligence, Security & Privacy, Blockchain, Business, Ethics, and Social) on
its advancement. In addition, we explain the importance of these technologies
to support decentralization, interoperability, user experiences, interactions,
and monetization. Our presented study highlights the existing challenges for
each component, followed by research directions and potential solutions. To the
best of our knowledge, this survey is the most comprehensive and allows users,
scholars, and entrepreneurs to get an in-depth understanding of the Metaverse
ecosystem to find their opportunities and potentials for contribution
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Ensuring Access to Safe and Nutritious Food for All Through the Transformation of Food Systems
Corporate Social Responsibility: the institutionalization of ESG
Understanding the impact of Corporate Social Responsibility (CSR) on firm performance as it relates to industries reliant on technological innovation is a complex and perpetually evolving challenge. To thoroughly investigate this topic, this dissertation will adopt an economics-based structure to address three primary hypotheses. This structure allows for each hypothesis to essentially be a standalone empirical paper, unified by an overall analysis of the nature of impact that ESG has on firm performance. The first hypothesis explores the evolution of CSR to the modern quantified iteration of ESG has led to the institutionalization and standardization of the CSR concept. The second hypothesis fills gaps in existing literature testing the relationship between firm performance and ESG by finding that the relationship is significantly positive in long-term, strategic metrics (ROA and ROIC) and that there is no correlation in short-term metrics (ROE and ROS). Finally, the third hypothesis states that if a firm has a long-term strategic ESG plan, as proxied by the publication of CSR reports, then it is more resilience to damage from controversies. This is supported by the finding that pro-ESG firms consistently fared better than their counterparts in both financial and ESG performance, even in the event of a controversy. However, firms with consistent reporting are also held to a higher standard than their nonreporting peers, suggesting a higher risk and higher reward dynamic. These findings support the theory of good management, in that long-term strategic planning is both immediately economically beneficial and serves as a means of risk management and social impact mitigation. Overall, this contributes to the literature by fillings gaps in the nature of impact that ESG has on firm performance, particularly from a management perspective
Minimum income support systems as elements of crisis resilience in Europe: Final Report
Mindestsicherungssysteme dienen in den meisten entwickelten Wohlfahrtsstaaten als Sicherheitsnetz letzter Instanz. Dementsprechend spielen sie gerade in wirtschaftlichen Krisenzeiten eine besondere Rolle. Inwieweit Mindestsicherungssysteme in Zeiten der Krise beansprucht werden, hängt auch von der Ausprägung vorgelagerter Sozialschutzsysteme ab. Diese Studie untersucht die Bedeutung von Systemen der Mindestsicherung sowie vorgelagerter Systeme wie Arbeitslosenversicherung, Kurzarbeit und arbeitsrechtlichem Bestandsschutz für die Krisenfestigkeit in Europa. Im Kontext der Finanzkrise von 2008/2009 und der Corona-Krise wird die Fähigkeit sozialpolitischer Maßnahmen untersucht, Armut und Einkommensverluste einzudämmen und gesellschaftliche Ausgrenzung zu vermeiden. Die Studie setzt dabei auf quantitative und qualitative Methoden, etwa multivariate Analysen, Mikrosimulationsmethoden sowie eingehende Fallstudien der Länder Dänemark, Frankreich, Irland, Polen und Spanien, die für unterschiedliche Typen von Wohlfahrtsstaaten stehen.The aim of this study is to analyse the role of social policies in different European welfare states regarding minimum income protection and active inclusion. The core focus lies on crisis resilience, i.e. the capacity of social policy arrangements to contain poverty and inequality and avoid exclusion before, during and after periods of economic shocks. To achieve this goal, the study expands its analytical focus to include other tiers of social protection, in particular upstream systems such as unemployment insurance, job retention and employment protection, as they play an additional and potentially prominent role in providing income and job protection in situations of crisis. A mixed-method approach is used that combines quantitative and qualitative research, such as descriptive and multivariate quantitative analyses, microsimulation methods and in-depth case studies. The study finds consistent differences in terms of crisis resilience across countries and welfare state types. In general, Nordic and Continental European welfare states with strong upstream systems and minimum income support (MIS) show better outcomes in core socio-economic outcomes such as poverty and exclusion risks. However, labour market integration shows some dualisms in Continental Europe. The study shows that MIS holds particular importance if there are gaps in upstream systems or cases of severe and lasting crises
Semantic Segmentation Enhanced Transformer Model for Human Attention Prediction
Saliency Prediction aims to predict the attention distribution of human eyes
given an RGB image. Most of the recent state-of-the-art methods are based on
deep image feature representations from traditional CNNs. However, the
traditional convolution could not capture the global features of the image well
due to its small kernel size. Besides, the high-level factors which closely
correlate to human visual perception, e.g., objects, color, light, etc., are
not considered. Inspired by these, we propose a Transformer-based method with
semantic segmentation as another learning objective. More global cues of the
image could be captured by Transformer. In addition, simultaneously learning
the object segmentation simulates the human visual perception, which we would
verify in our investigation of human gaze control in cognitive science. We
build an extra decoder for the subtask and the multiple tasks share the same
Transformer encoder, forcing it to learn from multiple feature spaces. We find
in practice simply adding the subtask might confuse the main task learning,
hence Multi-task Attention Module is proposed to deal with the feature
interaction between the multiple learning targets. Our method achieves
competitive performance compared to other state-of-the-art methods
Exploring the Training Factors that Influence the Role of Teaching Assistants to Teach to Students With SEND in a Mainstream Classroom in England
With the implementation of inclusive education having become increasingly valued over the years, the training of Teaching Assistants (TAs) is now more important than ever, given that they work alongside pupils with special educational needs and disabilities (hereinafter SEND) in mainstream education classrooms. The current study explored the training factors that influence the role of TAs when it comes to teaching SEND students in mainstream classrooms in England during their one-year training period. This work aimed to increase understanding of how the training of TAs is seen to influence the development of their personal knowledge and professional skills. The study has significance for our comprehension of the connection between the TAs’ training and the quality of education in the classroom. In addition, this work investigated whether there existed a correlation between the teaching experience of TAs and their background information, such as their gender, age, grade level taught, years of teaching experience, and qualification level.
A critical realist theoretical approach was adopted for this two-phased study, which involved the mixing of adaptive and grounded theories respectively. The multi-method project featured 13 case studies, each of which involved a trainee TA, his/her college tutor, and the classroom teacher who was supervising the trainee TA. The analysis was based on using semi-structured interviews, various questionnaires, and non-participant observation methods for each of these case studies during the TA’s one-year training period. The primary analysis of the research was completed by comparing the various kinds of data collected from the participants in the first and second data collection stages of each case. Further analysis involved cross-case analysis using a grounded theory approach, which made it possible to draw conclusions and put forth several core propositions. Compared with previous research, the findings of the current study reveal many implications for the training and deployment conditions of TAs, while they also challenge the prevailing approaches in many aspects, in addition to offering more diversified, enriched, and comprehensive explanations of the critical pedagogical issues
Central-provincial Politics and Industrial Policy-making in the Electric Power Sector in China
In addition to the studies that provide meaningful insights into the complexity of technical and economic issues, increasing studies have focused on the political process of market transition in network industries such as the electric power sector. This dissertation studies the central–provincial interactions in industrial policy-making and implementation, and attempts to evaluate the roles of Chinese provinces in the market reform process of the electric power sector. Market reforms of this sector are used as an illustrative case because the new round of market reforms had achieved some significant breakthroughs in areas such as pricing reform and wholesale market trading. Other policy measures, such as the liberalization of the distribution market and cross-regional market-building, are still at a nascent stage and have only scored moderate progress. It is important to investigate why some policy areas make greater progress in market reforms than others. It is also interesting to examine the impacts of Chinese central-provincial politics on producing the different market reform outcomes. Guangdong and Xinjiang are two provinces being analyzed in this dissertation. The progress of market reforms in these two provinces showed similarities although the provinces are very different in terms of local conditions such as the stages of their economic development and energy structures. The actual reform can be understood as the outcomes of certain modes of interactions between the central and provincial actors in the context of their particular capabilities and preferences in different policy areas. This dissertation argues that market reform is more successful in policy areas where the central and provincial authorities are able to engage mainly in integrative negotiations than in areas where they engage mainly in distributive negotiations
Examples of works to practice staccato technique in clarinet instrument
Klarnetin staccato tekniğini güçlendirme aşamaları eser çalışmalarıyla uygulanmıştır. Staccato
geçişlerini hızlandıracak ritim ve nüans çalışmalarına yer verilmiştir. Çalışmanın en önemli amacı
sadece staccato çalışması değil parmak-dilin eş zamanlı uyumunun hassasiyeti üzerinde de
durulmasıdır. Staccato çalışmalarını daha verimli hale getirmek için eser çalışmasının içinde etüt
çalışmasına da yer verilmiştir. Çalışmaların üzerinde titizlikle durulması staccato çalışmasının ilham
verici etkisi ile müzikal kimliğe yeni bir boyut kazandırmıştır. Sekiz özgün eser çalışmasının her
aşaması anlatılmıştır. Her aşamanın bir sonraki performans ve tekniği güçlendirmesi esas alınmıştır.
Bu çalışmada staccato tekniğinin hangi alanlarda kullanıldığı, nasıl sonuçlar elde edildiği bilgisine
yer verilmiştir. Notaların parmak ve dil uyumu ile nasıl şekilleneceği ve nasıl bir çalışma disiplini
içinde gerçekleşeceği planlanmıştır. Kamış-nota-diyafram-parmak-dil-nüans ve disiplin
kavramlarının staccato tekniğinde ayrılmaz bir bütün olduğu saptanmıştır. Araştırmada literatür
taraması yapılarak staccato ile ilgili çalışmalar taranmıştır. Tarama sonucunda klarnet tekniğin de
kullanılan staccato eser çalışmasının az olduğu tespit edilmiştir. Metot taramasında da etüt
çalışmasının daha çok olduğu saptanmıştır. Böylelikle klarnetin staccato tekniğini hızlandırma ve
güçlendirme çalışmaları sunulmuştur. Staccato etüt çalışmaları yapılırken, araya eser çalışmasının
girmesi beyni rahatlattığı ve istekliliği daha arttırdığı gözlemlenmiştir. Staccato çalışmasını yaparken
doğru bir kamış seçimi üzerinde de durulmuştur. Staccato tekniğini doğru çalışmak için doğru bir
kamışın dil hızını arttırdığı saptanmıştır. Doğru bir kamış seçimi kamıştan rahat ses çıkmasına
bağlıdır. Kamış, dil atma gücünü vermiyorsa daha doğru bir kamış seçiminin yapılması gerekliliği
vurgulanmıştır. Staccato çalışmalarında baştan sona bir eseri yorumlamak zor olabilir. Bu açıdan
çalışma, verilen müzikal nüanslara uymanın, dil atış performansını rahatlattığını ortaya koymuştur.
Gelecek nesillere edinilen bilgi ve birikimlerin aktarılması ve geliştirici olması teşvik edilmiştir.
Çıkacak eserlerin nasıl çözüleceği, staccato tekniğinin nasıl üstesinden gelinebileceği anlatılmıştır.
Staccato tekniğinin daha kısa sürede çözüme kavuşturulması amaç edinilmiştir. Parmakların
yerlerini öğrettiğimiz kadar belleğimize de çalışmaların kaydedilmesi önemlidir. Gösterilen azmin ve
sabrın sonucu olarak ortaya çıkan yapıt başarıyı daha da yukarı seviyelere çıkaracaktır
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