12,705 research outputs found

    Knowledge Graph Building Blocks: An easy-to-use Framework for developing FAIREr Knowledge Graphs

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    Knowledge graphs and ontologies provide promising technical solutions for implementing the FAIR Principles for Findable, Accessible, Interoperable, and Reusable data and metadata. However, they also come with their own challenges. Nine such challenges are discussed and associated with the criterion of cognitive interoperability and specific FAIREr principles (FAIR + Explorability raised) that they fail to meet. We introduce an easy-to-use, open source knowledge graph framework that is based on knowledge graph building blocks (KGBBs). KGBBs are small information modules for knowledge-processing, each based on a specific type of semantic unit. By interrelating several KGBBs, one can specify a KGBB-driven FAIREr knowledge graph. Besides implementing semantic units, the KGBB Framework clearly distinguishes and decouples an internal in-memory data model from data storage, data display, and data access/export models. We argue that this decoupling is essential for solving many problems of knowledge management systems. We discuss the architecture of the KGBB Framework as we envision it, comprising (i) an openly accessible KGBB-Repository for different types of KGBBs, (ii) a KGBB-Engine for managing and operating FAIREr knowledge graphs (including automatic provenance tracking, editing changelog, and versioning of semantic units); (iii) a repository for KGBB-Functions; (iv) a low-code KGBB-Editor with which domain experts can create new KGBBs and specify their own FAIREr knowledge graph without having to think about semantic modelling. We conclude with discussing the nine challenges and how the KGBB Framework provides solutions for the issues they raise. While most of what we discuss here is entirely conceptual, we can point to two prototypes that demonstrate the principle feasibility of using semantic units and KGBBs to manage and structure knowledge graphs

    Simulation-based learning in teacher education: Using Maslow’s Hierarchy of needs to conceptualize instructors’ needs

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    IntroductionSimulation-based learning (SBL) has become an effective tool in the education field, and instructors play a significant role in leading it. Although much is known about participants’ needs, SBL instructors’ needs have yet to be addressed. The study’s goal was to explore SBL instructors’ needs while guiding an SBL workshop using the psychological framework of Maslow’s Hierarchy of Needs.MethodsWe employed a qualitative case-study design, consisting of 68 four-hour-long workshops, held at a teacher-education simulation center by the center’s professional instructors. Data collection comprised 211 statements derived from instructors’ open-ended reflections, the transcripts of two focus groups held with the instructors, and 98 interpersonal communication documents.ResultsData were analyzed using both deductive and inductive thematic analysis, which rendered 11 themes spanning Maslow’s five levels, and revealing two possible simulation-based learning paths: a complete process, in which all needs are met and an incomplete process, in which needs remain unmet.DiscussionTheoretical insights and practical implications are provided for attending to instructors’ needs (i.e., basic needs, security, belonging, self-esteem, self-actualization) to ensure optimal learning in teacher education when using SBL

    One Small Step for Generative AI, One Giant Leap for AGI: A Complete Survey on ChatGPT in AIGC Era

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    OpenAI has recently released GPT-4 (a.k.a. ChatGPT plus), which is demonstrated to be one small step for generative AI (GAI), but one giant leap for artificial general intelligence (AGI). Since its official release in November 2022, ChatGPT has quickly attracted numerous users with extensive media coverage. Such unprecedented attention has also motivated numerous researchers to investigate ChatGPT from various aspects. According to Google scholar, there are more than 500 articles with ChatGPT in their titles or mentioning it in their abstracts. Considering this, a review is urgently needed, and our work fills this gap. Overall, this work is the first to survey ChatGPT with a comprehensive review of its underlying technology, applications, and challenges. Moreover, we present an outlook on how ChatGPT might evolve to realize general-purpose AIGC (a.k.a. AI-generated content), which will be a significant milestone for the development of AGI.Comment: A Survey on ChatGPT and GPT-4, 29 pages. Feedback is appreciated ([email protected]

    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

    Deep Transfer Learning Applications in Intrusion Detection Systems: A Comprehensive Review

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    Globally, the external Internet is increasingly being connected to the contemporary industrial control system. As a result, there is an immediate need to protect the network from several threats. The key infrastructure of industrial activity may be protected from harm by using an intrusion detection system (IDS), a preventive measure mechanism, to recognize new kinds of dangerous threats and hostile activities. The most recent artificial intelligence (AI) techniques used to create IDS in many kinds of industrial control networks are examined in this study, with a particular emphasis on IDS-based deep transfer learning (DTL). This latter can be seen as a type of information fusion that merge, and/or adapt knowledge from multiple domains to enhance the performance of the target task, particularly when the labeled data in the target domain is scarce. Publications issued after 2015 were taken into account. These selected publications were divided into three categories: DTL-only and IDS-only are involved in the introduction and background, and DTL-based IDS papers are involved in the core papers of this review. Researchers will be able to have a better grasp of the current state of DTL approaches used in IDS in many different types of networks by reading this review paper. Other useful information, such as the datasets used, the sort of DTL employed, the pre-trained network, IDS techniques, the evaluation metrics including accuracy/F-score and false alarm rate (FAR), and the improvement gained, were also covered. The algorithms, and methods used in several studies, or illustrate deeply and clearly the principle in any DTL-based IDS subcategory are presented to the reader

    Evaluating the Code Quality of AI-Assisted Code Generation Tools: An Empirical Study on GitHub Copilot, Amazon CodeWhisperer, and ChatGPT

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    Context: AI-assisted code generation tools have become increasingly prevalent in software engineering, offering the ability to generate code from natural language prompts or partial code inputs. Notable examples of these tools include GitHub Copilot, Amazon CodeWhisperer, and OpenAI's ChatGPT. Objective: This study aims to compare the performance of these prominent code generation tools in terms of code quality metrics, such as Code Validity, Code Correctness, Code Security, Code Reliability, and Code Maintainability, to identify their strengths and shortcomings. Method: We assess the code generation capabilities of GitHub Copilot, Amazon CodeWhisperer, and ChatGPT using the benchmark HumanEval Dataset. The generated code is then evaluated based on the proposed code quality metrics. Results: Our analysis reveals that the latest versions of ChatGPT, GitHub Copilot, and Amazon CodeWhisperer generate correct code 65.2%, 46.3%, and 31.1% of the time, respectively. In comparison, the newer versions of GitHub CoPilot and Amazon CodeWhisperer showed improvement rates of 18% for GitHub Copilot and 7% for Amazon CodeWhisperer. The average technical debt, considering code smells, was found to be 8.9 minutes for ChatGPT, 9.1 minutes for GitHub Copilot, and 5.6 minutes for Amazon CodeWhisperer. Conclusions: This study highlights the strengths and weaknesses of some of the most popular code generation tools, providing valuable insights for practitioners. By comparing these generators, our results may assist practitioners in selecting the optimal tool for specific tasks, enhancing their decision-making process

    Message Journal, Issue 5: COVID-19 SPECIAL ISSUE Capturing visual insights, thoughts and reflections on 2020/21 and beyond...

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    If there is a theme running through the Message Covid-19 special issue, it is one of caring. Of our own and others’ resilience and wellbeing, of friendship and community, of students, practitioners and their futures, of social justice, equality and of doing the right thing. The veins of designing with care run through the edition, wide and deep. It captures, not designers as heroes, but those with humble views, exposing the need to understand a diversity of perspectives when trying to comprehend the complexity that Covid-19 continues to generate. As graphic designers, illustrators and visual communicators, contributors have created, documented, written, visualised, reflected, shared, connected and co-created, designed for good causes and re-defined what it is to be a student, an academic and a designer during the pandemic. This poignant period in time has driven us, through isolation, towards new rules of living, and new ways of working; to see and map the world in a different light. A light that is uncertain, disjointed, and constantly being redefined. This Message issue captures responses from the graphic communication design community in their raw state, to allow contributors to communicate their experiences through both their written and visual voice. Thus, the reader can discern as much from the words as the design and visualisations. Through this issue a substantial number of contributions have focused on personal reflection, isolation, fear, anxiety and wellbeing, as well as reaching out to community, making connections and collaborating. This was not surprising in a world in which connection with others has often been remote, and where ‘normal’ social structures of support and care have been broken down. We also gain insight into those who are using graphic communication design to inspire and capture new ways of teaching and learning, developing themselves as designers, educators, and activists, responding to social justice and to do good; gaining greater insight into society, government actions and conspiracy. Introduction: Victoria Squire - Coping with Covid: Community, connection and collaboration: James Alexander & Carole Evans, Meg Davies, Matthew Frame, Chae Ho Lee, Alma Hoffmann, Holly K. Kaufman-Hill, Joshua Korenblat, Warren Lehrer, Christine Lhowe, Sara Nesteruk, Cat Normoyle & Jessica Teague, Kyuha Shim. - Coping with Covid: Isolation, wellbeing and hope: Sadia Abdisalam, Tom Ayling, Jessica Barness, Megan Culliford, Stephanie Cunningham, Sofija Gvozdeva, Hedzlynn Kamaruzzaman, Merle Karp, Erica V. P. Lewis, Kelly Salchow Macarthur, Steven McCarthy, Shelly Mayers, Elizabeth Shefrin, Angelica Sibrian, David Smart, Ane Thon Knutsen, Isobel Thomas, Darryl Westley. - Coping with Covid: Pedagogy, teaching and learning: Bernard J Canniffe, Subir Dey, Aaron Ganci, Elizabeth Herrmann, John Kilburn, Paul Nini, Emily Osborne, Gianni Sinni & Irene Sgarro, Dave Wood, Helena Gregory, Colin Raeburn & Jackie Malcolm. - Coping with Covid: Social justice, activism and doing good: Class Action Collective, Xinyi Li, Matt Soar, Junie Tang, Lisa Winstanley. - Coping with Covid: Society, control and conspiracy: Diana BĂźrhală, Maria Borțoi, Patti Capaldi, TĂąnia A. Cardoso, Peter Gibbons, Bianca Milea, Rebecca Tegtmeyer, Danne Wo

    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

    Psychographic And Behavioral Segmentation Of Food Delivery Application Customers To Increase Intention To Use

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    Dissertation presented as the partial requirement for obtaining a Master's degree in Information Management, specialization in Knowledge Management and Business IntelligenceThis study presents a framework for segmenting Food Delivery Application (FDA) customers based on psychographic and behavioral variables as an alternative to existing segmentation. Customer segments are proposed by applying clustering methods to primary data from an electronic survey. Psychographic and behavioral constructs are formulated as hypotheses based on existing literature, and then evaluated as segmentation variables regarding their discriminatory power for customer segmentation. Detected relevant variables are used in the application of clustering techniques to find adequate boundaries within customer groupings for segmentation purposes. Characterization of customer segments is performed and enriched with implications of findings in FDA marketing strategies. This paper contributes to theory by providing new findings on segmentation that are relevant for an online context. In addition, it contributes to practice by detailing implications of customer segments in an online sales strategy, allowing marketing managers and FDA businesses to capitalize knowledge in their conversion funnel designs
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