8,005 research outputs found

    Exploiting Symmetry and Heuristic Demonstrations in Off-policy Reinforcement Learning for Robotic Manipulation

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    Reinforcement learning demonstrates significant potential in automatically building control policies in numerous domains, but shows low efficiency when applied to robot manipulation tasks due to the curse of dimensionality. To facilitate the learning of such tasks, prior knowledge or heuristics that incorporate inherent simplification can effectively improve the learning performance. This paper aims to define and incorporate the natural symmetry present in physical robotic environments. Then, sample-efficient policies are trained by exploiting the expert demonstrations in symmetrical environments through an amalgamation of reinforcement and behavior cloning, which gives the off-policy learning process a diverse yet compact initiation. Furthermore, it presents a rigorous framework for a recent concept and explores its scope for robot manipulation tasks. The proposed method is validated via two point-to-point reaching tasks of an industrial arm, with and without an obstacle, in a simulation experiment study. A PID controller, which tracks the linear joint-space trajectories with hard-coded temporal logic to produce interim midpoints, is used to generate demonstrations in the study. The results of the study present the effect of the number of demonstrations and quantify the magnitude of behavior cloning to exemplify the possible improvement of model-free reinforcement learning in common manipulation tasks. A comparison study between the proposed method and a traditional off-policy reinforcement learning algorithm indicates its advantage in learning performance and potential value for applications

    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

    Norsk rÄ kumelk, en kilde til zoonotiske patogener?

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    The worldwide emerging trend of eating “natural” foods, that has not been processed, also applies for beverages. According to Norwegian legislation, all milk must be pasteurized before commercial sale but drinking milk that has not been heat-treated, is gaining increasing popularity. Scientist are warning against this trend and highlights the risk of contracting disease from milkborne microorganisms. To examine potential risks associated with drinking unpasteurized milk in Norway, milk- and environmental samples were collected from dairy farms located in south-east of Norway. The samples were analyzed for the presence of specific zoonotic pathogens; Listeria monocytogenes, Campylobacter spp., and Shiga toxin-producing Escherichia coli (STEC). Cattle are known to be healthy carriers of these pathogens, and Campylobacter spp. and STEC have a low infectious dose, meaning that infection can be established by ingesting a low number of bacterial cells. L. monocytogenes causes one of the most severe foodborne zoonotic diseases, listeriosis, that has a high fatality rate. All three pathogens have caused milk borne disease outbreaks all over the world, also in Norway. During this work, we observed that the prevalence of the three examined bacteria were high in the environment at the examined farms. In addition, 7% of the milk filters were contaminated by STEC, 13% by L. monocytogenes and 4% by Campylobacter spp. Four of the STEC isolates detected were eaepositive, which is associated with the capability to cause severe human disease. One of the eae-positive STEC isolates were collected from a milk filter, which strongly indicate that Norwegian raw milk may contain potential pathogenic STEC. To further assess the possibilities of getting ill by STEC after consuming raw milk, we examined the growth of the four eae-positive STEC isolates in raw milk at different temperatures. All four isolates seemed to have ability to multiply in raw milk at 8°C, and one isolate had significant growth after 72 hours. Incubation at 6°C seemed to reduce the number of bacteria during the first 24 hours before cell death stopped. These findings highlight the importance of stable refrigerator temperatures, preferable < 4°C, for storage of raw milk. The L. monocytogenes isolates collected during this study show genetic similarities to isolates collected from urban and rural environmental locations, but different clones were predominant in agricultural environments compared to clinical and food environments. However, the results indicate that the same clone can persist in a farm over time, and that milk can be contaminated by L. monocytogenes clones present in farm environment. Despite testing small volumes (25 mL) of milk, we were able to isolate both STEC and Campylobacter spp. directly from raw milk. A proportion of 3% of the bulk tank milk and teat milk samples were contaminated by Campylobacter spp. and one STEC was isolated from bulk tank milk. L monocytogenes was not detected in bulk tank milk, nor in teat milk samples. The agricultural evolvement during the past decades have led to larger production units and new food safety challenges. Dairy cattle production in Norway is in a current transition from tie-stall housing with conventional pipeline milking systems, to modern loose housing systems with robotic milking. The occurrence of the three pathogens in this project were higher in samples collected from farms with loose housing compared to those with tiestall housing. Pasteurization of cow’s milk is a risk reducing procedure to protect consumers from microbial pathogens and in most EU countries, commercial distribution of unpasteurized milk is legally restricted. Together, the results presented in this thesis show that the animal housing may influence the level of pathogenic bacteria in the raw milk and that ingestion of Norwegian raw cow’s milk may expose consumers to pathogenic bacteria which can cause severe disease, especially in children, elderly and in persons with underlying diseases. The results also highlight the importance of storing raw milk at low temperatures between milking and consumption.Å spise mat som er mindre prosessert og mer «naturlig» er en pĂ„gĂ„ende trend i Norge og i andre deler av verden. Interessen for Ă„ drikke melk som ikke er varmebehandlet, sĂ„kalt rĂ„ melk, er ogsĂ„ Ăžkende. I Norge er det pĂ„budt Ă„ pasteurisere melk fĂžr kommersielt salg for Ă„ beskytte forbrukeren mot sykdomsfremkallende mikroorganismer. Fagfolk advarer mot Ă„ drikke rĂ„ melk, og pĂ„peker risikoen for Ă„ bli syk av patogene bakterier som kan finnes i melken. I denne avhandlingen undersĂžker vi den potensielle risikoen det medfĂžrer Ă„ drikke upasteurisert melk fra Norge. I tillegg til Ă„ samle inn tankmelk- og speneprĂžver fra melkegĂ„rder i sĂžrĂžst Norge, samlet vi ogsĂ„ miljĂžprĂžver fra de samme gĂ„rdene for Ă„ kartlegge forekomst og for Ă„ identifisere potensielle mattrygghetsrisikoer i melkeproduksjonen. Alle prĂžvene ble analysert for de zoonotiske sykdomsfremkallende bakteriene Listeria monocytogenes, Campylobacter spp., og Shiga toksin-produserende Escherichia coli (STEC). Kyr kan vĂŠre friske smittebĂŠrere av disse bakteriene, som dermed kan etablere et reservoar pĂ„ gĂ„rdene. Bakteriene kan overfĂžres fra gĂ„rdsmiljĂžet til melkekjeden og dermed utfordre mattryggheten. Disse bakteriene har forĂ„rsaket melkebĂ„rne sykdomsutbrudd over hele verden, ogsĂ„ i Norge. Campylobacter spp. og STEC har lav infeksiĂžs dose, som vil si at man kan bli syk selv om man bare inntar et lavt antall bakterieceller. L. monocytogenes kan gi sykdommen listeriose, en av de mest alvorlige matbĂ„rne zoonotiske sykdommene vi har i den vestlige verden. Resultater fra denne oppgaven viser en hĂžy forekomst av de tre patogenene i gĂ„rdsmiljĂžet. I tillegg var 7% av melkefiltrene vi testet positive for STEC, 13% positive for L. monocytogenes og 4% positive for Campylobacter spp.. Fire av STEC isolatene bar genet for Intimin, eae, som er ansett som en viktig virulensfaktor som Ăžker sjansen for alvorlig sykdom. Ett av de eae-positive isolatene ble funnet i et melkefilter, noe som indikerer at norsk rĂ„ melk kan inneholde patogene STEC. For Ă„ videre vurdere risikoen for Ă„ bli syk av STEC fra rĂ„ melk undersĂžkte vi hvordan de fire eae-positive isolatene vokste i rĂ„ melk lagret ved forskjellige temperaturer. For alle isolatene Ăžkte antall bakterier etter lagring ved 8°C, og for et isolat var veksten signifikant. Etter lagring ved 6°C ble antallet bakterier redusert de fĂžrste 24 timene, deretter stoppet reduksjonen i antall bakterier. Disse resultatene viser hvor viktig det er Ă„ ha stabil lav lagringstemperatur for rĂ„ melk, helst < 4°C. L. monocytogenes isolatene som ble samlet inn fra melkegĂ„rdene viste genetiske likheter med isolater samlet inn fra urbane og rurale miljĂžer rundt omkring i Norge. Derimot var kloner som dominerte i landbruksmiljĂžet forskjellige fra kliniske isolater og isolater fra matproduksjonslokaler. Videre sĂ„ man at en klone kan persistere pĂ„ en gĂ„rd over tid og at melk kan kontamineres av L. monocytogenes kloner som er til stede i gĂ„rdsmiljĂžet. Til tross for smĂ„ testvolum av tankmelken (25 mL) fant vi bĂ„de STEC og Campylobacter spp. i melkeprĂžvene. 3% av tankmelkprĂžvene og speneprĂžvene var positive for Campylobacter spp. og ett STEC isolat ble funnet i tankmelk. L. monocytogenes ble ikke funnet direkte i melkeprĂžvene. Landbruket i Norge er i stadig utvikling der besetningene blir stĂžrre, men fĂŠrre. Melkebesetningene er midt i en overgang der tradisjonell oppstalling med melking pĂ„ bĂ„s byttes ut med lĂžsdriftssystemer og melkeroboter. Forekomsten av de tre patogenene funnet i denne studien var hĂžyere i besetningene med lĂžsdrift sammenliknet med besetningene som hadde melkekyrne oppstallet pĂ„ bĂ„s. Pasteurisering er et viktig forebyggende tiltak for Ă„ beskytte konsumenter fra mikrobielle patogener, og i de fleste EU-land er kommersielt salg av rĂ„ melk juridisk begrenset. Denne studien viser at oppstallingstype kan pĂ„virke nivĂ„ene av patogene bakterier i gĂ„rdsmiljĂžet og i rĂ„ melk. Inntak av rĂ„ melk kan eksponere forbruker for patogene bakterier som kan gi alvorlig sykdom, spesielt hos barn, eldre og personer med underliggende sykdommer. Resultatene underbygger viktigheten av Ă„ pasteurisere melk for Ă„ sikre mattryggheten, og at det er avgjĂžrende Ă„ lagre rĂ„ melk ved kontinuerlig lave temperaturer for Ă„ forebygge vekst av zoonotiske patogener

    Setting contextual conditions to resolve grand challenges through responsible innovation:A comparative patent analysis in the circular economy

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    Copyright © 2023 The Authors. This article draws on responsible innovation (RI) undertaken by hybrid organizations, institutional rigidity, and national innovation systems (NISs) to assess and contextualize the innovation performance of for-profit firms seeking to resolve grand challenges (GCs). The extant research on RI lacks the theoretical underpinnings to profile the unique characteristics of RI firms and the contextual conditions behind the resolution of GCs through RI. This study aims to fill this important gap by focusing on a specific type of RI firm—a firm seeking to reduce climate change through implementation of a circular economy model. By studying a multi-country sample of 1153 manufacturing firms, we implemented propensity score matching (PSM) and the Heckman selection model to compare the patent productivity of RI and non-RI firms. Our evidence demonstrates that RI firms display lower likelihood of patenting and lower patent productivity than non-RI firms when they do engage in patenting. Furthermore, we found that a stronger national R&D environment can be conducive to aligning public interests and private incentives by enabling RI firms to enhance their patent productivity. Additionally, RI firms in industries with lower levels of technological complexity capture more value from improvements in R&D environments than RI firms in industries with higher levels of technological complexity. Our argument as a whole contributes to the GC and RI literature streams by considering both the innovation barriers faced by RI-oriented firms and the macro/industry boundary conditions that enable such organizations to overcome them.Governments of Spain and Andalusia (Research Project A-SEJ-196-UGR20); Schoeller Foundation; Taishan Scholar Program of Shandong Province

    Transfer learning for operator selection: A reinforcement learning approach

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    In the past two decades, metaheuristic optimisation algorithms (MOAs) have been increasingly popular, particularly in logistic, science, and engineering problems. The fundamental characteristics of such algorithms are that they are dependent on a parameter or a strategy. Some online and offline strategies are employed in order to obtain optimal configurations of the algorithms. Adaptive operator selection is one of them, and it determines whether or not to update a strategy from the strategy pool during the search process. In the field of machine learning, Reinforcement Learning (RL) refers to goal-oriented algorithms, which learn from the environment how to achieve a goal. On MOAs, reinforcement learning has been utilised to control the operator selection process. However, existing research fails to show that learned information may be transferred from one problem-solving procedure to another. The primary goal of the proposed research is to determine the impact of transfer learning on RL and MOAs. As a test problem, a set union knapsack problem with 30 separate benchmark problem instances is used. The results are statistically compared in depth. The learning process, according to the findings, improved the convergence speed while significantly reducing the CPU time

    Strategies for Early Learners

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    Welcome to learning about how to effectively plan curriculum for young children. This textbook will address: ‱ Developing curriculum through the planning cycle ‱ Theories that inform what we know about how children learn and the best ways for teachers to support learning ‱ The three components of developmentally appropriate practice ‱ Importance and value of play and intentional teaching ‱ Different models of curriculum ‱ Process of lesson planning (documenting planned experiences for children) ‱ Physical, temporal, and social environments that set the stage for children’s learning ‱ Appropriate guidance techniques to support children’s behaviors as the self-regulation abilities mature. ‱ Planning for preschool-aged children in specific domains including o Physical development o Language and literacy o Math o Science o Creative (the visual and performing arts) o Diversity (social science and history) o Health and safety ‱ Making children’s learning visible through documentation and assessmenthttps://scholar.utc.edu/open-textbooks/1001/thumbnail.jp

    Learning disentangled speech representations

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    A variety of informational factors are contained within the speech signal and a single short recording of speech reveals much more than the spoken words. The best method to extract and represent informational factors from the speech signal ultimately depends on which informational factors are desired and how they will be used. In addition, sometimes methods will capture more than one informational factor at the same time such as speaker identity, spoken content, and speaker prosody. The goal of this dissertation is to explore different ways to deconstruct the speech signal into abstract representations that can be learned and later reused in various speech technology tasks. This task of deconstructing, also known as disentanglement, is a form of distributed representation learning. As a general approach to disentanglement, there are some guiding principles that elaborate what a learned representation should contain as well as how it should function. In particular, learned representations should contain all of the requisite information in a more compact manner, be interpretable, remove nuisance factors of irrelevant information, be useful in downstream tasks, and independent of the task at hand. The learned representations should also be able to answer counter-factual questions. In some cases, learned speech representations can be re-assembled in different ways according to the requirements of downstream applications. For example, in a voice conversion task, the speech content is retained while the speaker identity is changed. And in a content-privacy task, some targeted content may be concealed without affecting how surrounding words sound. While there is no single-best method to disentangle all types of factors, some end-to-end approaches demonstrate a promising degree of generalization to diverse speech tasks. This thesis explores a variety of use-cases for disentangled representations including phone recognition, speaker diarization, linguistic code-switching, voice conversion, and content-based privacy masking. Speech representations can also be utilised for automatically assessing the quality and authenticity of speech, such as automatic MOS ratings or detecting deep fakes. The meaning of the term "disentanglement" is not well defined in previous work, and it has acquired several meanings depending on the domain (e.g. image vs. speech). Sometimes the term "disentanglement" is used interchangeably with the term "factorization". This thesis proposes that disentanglement of speech is distinct, and offers a viewpoint of disentanglement that can be considered both theoretically and practically

    The determinants of value addition: a crtitical analysis of global software engineering industry in Sri Lanka

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    It was evident through the literature that the perceived value delivery of the global software engineering industry is low due to various facts. Therefore, this research concerns global software product companies in Sri Lanka to explore the software engineering methods and practices in increasing the value addition. The overall aim of the study is to identify the key determinants for value addition in the global software engineering industry and critically evaluate the impact of them for the software product companies to help maximise the value addition to ultimately assure the sustainability of the industry. An exploratory research approach was used initially since findings would emerge while the study unfolds. Mixed method was employed as the literature itself was inadequate to investigate the problem effectively to formulate the research framework. Twenty-three face-to-face online interviews were conducted with the subject matter experts covering all the disciplines from the targeted organisations which was combined with the literature findings as well as the outcomes of the market research outcomes conducted by both government and nongovernment institutes. Data from the interviews were analysed using NVivo 12. The findings of the existing literature were verified through the exploratory study and the outcomes were used to formulate the questionnaire for the public survey. 371 responses were considered after cleansing the total responses received for the data analysis through SPSS 21 with alpha level 0.05. Internal consistency test was done before the descriptive analysis. After assuring the reliability of the dataset, the correlation test, multiple regression test and analysis of variance (ANOVA) test were carried out to fulfil the requirements of meeting the research objectives. Five determinants for value addition were identified along with the key themes for each area. They are staffing, delivery process, use of tools, governance, and technology infrastructure. The cross-functional and self-organised teams built around the value streams, employing a properly interconnected software delivery process with the right governance in the delivery pipelines, selection of tools and providing the right infrastructure increases the value delivery. Moreover, the constraints for value addition are poor interconnection in the internal processes, rigid functional hierarchies, inaccurate selections and uses of tools, inflexible team arrangements and inadequate focus for the technology infrastructure. The findings add to the existing body of knowledge on increasing the value addition by employing effective processes, practices and tools and the impacts of inaccurate applications the same in the global software engineering industry

    Evolution of ligand specificity of protein kinase A isoforms in the phylum Euglenozoa

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    Brain simulation as a cloud service: The Virtual Brain on EBRAINS

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    open access articleThe Virtual Brain (TVB) is now available as open-source services on the cloud research platform EBRAINS (ebrains.eu). It offers software for constructing, simulating and analysing brain network models including the TVB simulator; magnetic resonance imaging (MRI) processing pipelines to extract structural and functional brain networks; combined simulation of large-scale brain networks with small-scale spiking networks; automatic con- version of user-specified model equations into fast simulation code; simulation-ready brain models of patients and healthy volunteers; Bayesian parameter optimization in epilepsy patient models; data and software for mouse brain simulation; and extensive educational material. TVB cloud services facilitate reproducible online collabo- ration and discovery of data assets, models, and software embedded in scalable and secure workflows, a precondition for research on large cohort data sets, better generalizability, and clinical translation
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