14,911 research outputs found

    Towards Autonomous Selective Harvesting: A Review of Robot Perception, Robot Design, Motion Planning and Control

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    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

    The Metaverse: Survey, Trends, Novel Pipeline Ecosystem & Future Directions

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    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

    Conditional Adapters: Parameter-efficient Transfer Learning with Fast Inference

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    We propose Conditional Adapter (CoDA), a parameter-efficient transfer learning method that also improves inference efficiency. CoDA generalizes beyond standard adapter approaches to enable a new way of balancing speed and accuracy using conditional computation. Starting with an existing dense pretrained model, CoDA adds sparse activation together with a small number of new parameters and a light-weight training phase. Our experiments demonstrate that the CoDA approach provides an unexpectedly efficient way to transfer knowledge. Across a variety of language, vision, and speech tasks, CoDA achieves a 2x to 8x inference speed-up compared to the state-of-the-art Adapter approach with moderate to no accuracy loss and the same parameter efficiency

    HR Analytics: Concept, Application, and Impact on Talent Management, Branding, and Challenges

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    Purpose: Making wiser decisions about employees to improve performance at the individual and/or organizational levels is the process of HR analytics. HR analytics is a method for determining the correlation between HR practices and organizational performance outcomes such as sales volume or customer satisfaction. Human Resource Analytics was established in 1978 by Jac Fitz-Enz, the pioneer of human capital strategic analysis and performance benchmarking. In this paper, the researcher wants to discuss the concept of HR analytics, its application, impact on talent management, branding, and challenges in its application.Design/methodology/approach: The researcher examines secondary data and conducts a thorough literature review to understand the concept and its application across industries and nations, as well as to identify any challenges encountered during deployment and any benefits perceived by various industry professionals. Findings: The study's findings indicate that using HR analytics can help businesses build their brand and gain a competitive edge in today's fiercely competitive business environment while also enhancing workforce and employee productivity.Originality/value: This study has significant implications for both literature and HR analytics. Researchers will know more about the factors that contribute to and the mechanisms by which HR analytics improve organisational performance. The author's second claim is that having access to HR technology both facilitates and precedes HR analytics. Finally, concrete data from the literature demonstrates its influence on branding and organisational success. Keywords: Human resource (HR) analytics, People analytics, Branding, Talent Management, Organizational performance. Paper type: Research paper JEL Code: M12, M15 & M51 DOI: 10.7176/EJBM/15-8-06 Publication date: April 30th 202

    Changes in soil fertility and microbial communities following cultivation of native grassland in Horqin Sandy Land, China: a 60-year chronosequence

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    Background: Grassland conversion to cropland is a prevailing change of land use in traditionally nomadic areas, especially in the Mongolian Plateau. We investigated the effects of grassland conversion followed by continuous cultivation on soil properties and microbial community characteristics in Horqin Sandy Land, a typical agro-pastoral transition zone of Northern China. Soil samples were collected from the topsoil (upper 20 cm) across a 60-year cultivation chronosequence (5, 15, 25, 35 and 60 years) and unconverted native grassland. Soil physico-chemical properties were determined and high-throughput sequencing was used to assess microbial community diversity and composition. Results: Grassland cultivation resulted in changes to soil properties in both the short and longer term. Initially, it significantly increased soil bulk density (BD), electrical conductivity (EC), soil total nitrogen (TN), available phosphorus (AP) and available potassium (AK) concentrations, while reducing soil water content (SWC) and soil organic carbon content (SOC). Over the next 35–55 years of continuous cultivation, the trend for most of these characteristics was of reversion towards values nearer to those of native grassland, except for SOC which remained highly depleted. Cultivation of grassland substantially altered soil microbial communities at phylum level but there was no significant difference in microbial α-diversity between native grassland and any cropland. However, soil bacterial and fungal community structures at phylum level in the croplands of all cultivation years were different from those in the native grasslands. Heatmaps further revealed that bacterial and fungal structures in cropland tended to become more similar to native grassland after 15 and 25 years of cultivation, respectively. Redundancy analysis indicated that SOC, EC and BD were primary determinants of microbial community composition and diversity. Conclusions: These findings suggest that agricultural cultivation of grassland has considerable effects on soil fertility and microbial characteristics of Horqin Sandy Land. Intensive high-yield forage grass production is proposed as an alternative to avoid further native grassland reclamation, while meeting the grazing development needs in the ethnic minority settlements of eco-fragile regions

    Hospitality Employers and Employees’ Perceptions Regarding Covid-19 Support Measures: The Case of the Algarve Region (Portugal)

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    This paper aims at investigating hospitality employers and employees’ perceptions regarding governmental policies and measures implemented during Covid 19 crisis, in the Algarve, one of the most tourist regions of Portugal. The methodological framework is associated with a case study based on a set of 51 interviews to Algarvean hospitality employers and employees. A content analysis of interviews on the effects of the pandemic on hospitality was carried using the software QSR NVivo 12. Covid 19 employment impacts were considered as ‘very high’ and ‘high’ in the Algarvean hospitality. Portuguese governmental intervention was classified as good, but more support should be enhanced, namely associated with four main policy areas such as ‘income-generating support measures’, ‘cost reductions’, ‘legal framework’, and ‘health and safety’

    A spatial explicit vulnerability assessment for a coastal socio-ecological Natura 2000 site

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    In line with the global trend, the Ria de Aveiro coastal lagoon is subjected to multiple co-occurring pressures threatening vital benefits flowing from nature to people. The main objective of this research was to assess the status of habitats important for ecosystem services in the Ria de Aveiro by identifying vulnerable areas to anthropogenic threats. The pressures from seven relevant human activities (recreation, services, aquaculture, agriculture, commercial development, unintended impacts from management, and invasive alien species) were analysed based on their spatiotemporal distribution (exposure) and impact over the EUNIS habitats (EUNIS codes A2.2, A2.22 – sand flats and beaches; A2.3 – mud flats; A2.61 – seagrasses; A2.5, A2.53C, A2.535, A2.545, A2.554 – salt marshes; and, X10 – ‘Bocage,’ a landscape of small-hedged fields) in seven distinct landscape units. A prospective scenario, co-developed for the year 2030, was evaluated using a map-based risk assessment tool and brought forward the near-term vulnerability of the seagrass biotope. The highest risks posed to intertidal habitats (mud flats and salt marshes) were driven mainly by environmental management activities that support critical socio-economic sectors. Our methodology evaluated plausible threats to habitats in the near term, established baseline knowledge for the adaptive management process in Ria de Aveiro Natura 2000 site, and showcased how future assessments can inform the operationalization of ecosystem-based management as new information becomes available

    Évaluation de l'impact du changement climatique sur la défoliation de l'épinette noire par la tordeuse des bourgeons de l'épinette

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    Les modèles écologiques actuels prévoient de profonds effets des changements climatiques sur les régimes de perturbations naturelles des forêts. La tordeuse des bourgeons de l'épinette (Choristoneura fumiferana) (TBE) est le principal insecte défoliateur dans l'est de l'Amérique du Nord. Les épidémies de TBE ont un impact majeur sur la structure et la fonction de la forêt boréale canadienne puisque la défoliation entraîne une diminution de la croissance des arbres, une augmentation de la mortalité et une baisse de la productivité forestière. Les épidémies de TBE sont devenues plus sévères au cours du dernier siècle à cause des changements climatiques; cependant, nous savons peu de choses sur la manière dont l'effet intégré du climat et du TBE modifie la croissance des espèces hôtes. Nous évaluons ici comment l’interaction entre le climat et la gravité de l'épidémie affecte la croissance de l'épinette noire (Picea mariana) pendant l'épidémie de TBE qui a eu lieu entre 1968-1988 et 2006-2017. Nous avons compilé des séries dendrochronologiques (2271 arbres), des données de sévérité de l'épidémie (estimée par la défoliation aérienne observée) et des données climatiques pour 164 sites au Québec, Canada. Nous avons utilisé un modèle linéaire à effets mixtes pour déterminer l'impact des paramètres climatiques, de la défoliation cumulative (des cinq années précédentes) et de leur effet couplé sur la croissance en surface terrière. À la gravité maximale de l'épidémie, la croissance en surface terrière de l'épinette noire a été réduite de 14 à 18 % sur les cinq années en raison de l'effet TBE. Cette croissance a été affectée par le climat : des températures minimales estivales précédentes plus élevées et un indice d'humidité climatique estival plus élevé ont réduit la croissance de 11 % et 4 % respectivement. En revanche, l'effet négatif de la défoliation a été atténué de 9% pour une température minimale plus élevée au printemps précédent et de 7% pour une température maximale plus élevée l'été précédent. Cette étude améliore notre compréhension des effets combinés de la TBE et du climat et aide à prévoir les dommages futurs causés par cet insecte dans les peuplements forestiers afin de soutenir la gestion durable des forêts. Nous recommandons également que les projections des écosystèmes dans la forêt boréale incluent plusieurs classes de défoliation de la TBE et plusieurs scénarios climatiques

    A Design Science Research Approach to Smart and Collaborative Urban Supply Networks

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    Urban supply networks are facing increasing demands and challenges and thus constitute a relevant field for research and practical development. Supply chain management holds enormous potential and relevance for society and everyday life as the flow of goods and information are important economic functions. Being a heterogeneous field, the literature base of supply chain management research is difficult to manage and navigate. Disruptive digital technologies and the implementation of cross-network information analysis and sharing drive the need for new organisational and technological approaches. Practical issues are manifold and include mega trends such as digital transformation, urbanisation, and environmental awareness. A promising approach to solving these problems is the realisation of smart and collaborative supply networks. The growth of artificial intelligence applications in recent years has led to a wide range of applications in a variety of domains. However, the potential of artificial intelligence utilisation in supply chain management has not yet been fully exploited. Similarly, value creation increasingly takes place in networked value creation cycles that have become continuously more collaborative, complex, and dynamic as interactions in business processes involving information technologies have become more intense. Following a design science research approach this cumulative thesis comprises the development and discussion of four artefacts for the analysis and advancement of smart and collaborative urban supply networks. This thesis aims to highlight the potential of artificial intelligence-based supply networks, to advance data-driven inter-organisational collaboration, and to improve last mile supply network sustainability. Based on thorough machine learning and systematic literature reviews, reference and system dynamics modelling, simulation, and qualitative empirical research, the artefacts provide a valuable contribution to research and practice
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