218 research outputs found

    A Novel Patent Similarity Measurement Methodology: Semantic Distance and Technological Distance

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    Measuring similarity between patents is an essential step to ensure novelty of innovation. However, a large number of methods of measuring the similarity between patents still rely on manual classification of patents by experts. Another body of research has proposed automated methods; nevertheless, most of it solely focuses on the semantic similarity of patents. In order to tackle these limitations, we propose a hybrid method for automatically measuring the similarity between patents, considering both semantic and technological similarities. We measure the semantic similarity based on patent texts using BERT, calculate the technological similarity with IPC codes using Jaccard similarity, and perform hybridization by assigning weights to the two similarity methods. Our evaluation result demonstrates that the proposed method outperforms the baseline that considers the semantic similarity only

    Heaths, Commons, and Wastes:An investigation into the character, management, and perceptions of heathland landscapes in the medieval and post-medieval periods, with particular reference to the counties of Norfolk, Suffolk, Essex, and Hertfordshire

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    Lowland heathland is a priority habitat for conservation in the United Kingdom but is also valued as a historical cultural landscape.1 Many rare or endangered species of both flora and fauna, unable to thrive in modern agricultural or urban landscapes, inhabit heathland environments. These have long been recognised as the products of past management systems which have been in decline since at least the 18th century, and have now been largely discontinued. For the purposes of conservation, the practices which created and sustained them, based on historical examples, must be maintained or reintroduced in order to perpetuate conditions favourable to those species. This research details both the landscape character of historic heathland within the study area, and the various management practices which influenced and changed that character. As well as making an original contribution to a subject of historical importance, and modern interest, this research will inform the future management of heathland landscapes by showing, clearly and with evidence, how they were managed in the past. Where management practices were referred to directly in historical documents, or recorded in full, this work presents them in detail and each technique is analysed in terms of its probable environmental impacts. Where heaths appear in the documentary record, but direct references to management were not found, landscape character was reconstructed using place-name and other linguistic evidence, and by examining what flora and fauna were mentioned in association with them – many of which lived only in certain kinds of habitats. The results of this work detail a highly variable landscape. Heaths were sometimes open and characterised by low shrubs, but also sometimes wooded – either sparsely or densely – or even largely devoid of flora in some parts. The fauna present on heaths also varied widely between regions and periods; including sheep, pigs, cattle, horses, deer, goats, rabbits, geese, and the Brown Bear. Heaths historically were found on a broad range of soil types, not all of them sandy in nature, and contained a variety of both wet and dry habitats. As the term ‘heath’ was applied to all of these landscapes historically, cultural perceptions of what constituted heathland were also highly variable

    Data journeys in the sciences

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    This is the final version. Available from Springer via the DOI in this record. This groundbreaking, open access volume analyses and compares data practices across several fields through the analysis of specific cases of data journeys. It brings together leading scholars in the philosophy, history and social studies of science to achieve two goals: tracking the travel of data across different spaces, times and domains of research practice; and documenting how such journeys affect the use of data as evidence and the knowledge being produced. The volume captures the opportunities, challenges and concerns involved in making data move from the sites in which they are originally produced to sites where they can be integrated with other data, analysed and re-used for a variety of purposes. The in-depth study of data journeys provides the necessary ground to examine disciplinary, geographical and historical differences and similarities in data management, processing and interpretation, thus identifying the key conditions of possibility for the widespread data sharing associated with Big and Open Data. The chapters are ordered in sections that broadly correspond to different stages of the journeys of data, from their generation to the legitimisation of their use for specific purposes. Additionally, the preface to the volume provides a variety of alternative “roadmaps” aimed to serve the different interests and entry points of readers; and the introduction provides a substantive overview of what data journeys can teach about the methods and epistemology of research.European CommissionAustralian Research CouncilAlan Turing Institut

    The EU Cohesion policy and healthy national development: Management and Promotion in Ukraine

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    Монографія присвячена дослідженню сутності принципів реалізації політики згуртованості Європейського Союзу. Авторами проведено аналіз економічних, екологічних та соціальних аспектів інтеграції досвіду ЄС у державну політику України. У монографії узагальнено підходи до відновлення країни та здорового розвитку. Окрему увагу приділено питанням управління системою охорони здоров’я, тенденціям та перспективам досягнення стану стійкості системи медико-соціального забезпечення населення в умовах впливу COVID-19 на національну економіку. Узагальнено досвід використання маркетингових та інноваційних технологій у контексті здорового національного розвитку.Монография посвящена исследованию сущности принципов реализации политики сплоченности Европейского Союза. Авторами проведен анализ экономических, экологических и социальных аспектов интеграции опыта ЕС в государственную политику Украины. В монографии обобщены подходы к восстановлению и здоровому развитию. Отдельное внимание уделено вопросам управления здравоохранением, тенденциям и перспективам достижения состояния устойчивости системы медико-социального обеспечения населения в условиях влияния COVID-19 на национальную экономику. Обобщен опыт использования маркетинговых и инновационных технологий в контексте здорового национального развития.The monograph focused on the specifics of the principles of the EU Cohesion Policy implementation. The authors conducted an analysis of the economic, ecological and social aspects of the integration of the EU experience into the state policy of Ukraine. The monograph summarizes approaches to the restoration of the country and healthy development. Particular attention is paid to the issues of health care system management, the trends and prospects of achieving the state of resilience of the medical and social provision system of the population in the context of the impact of COVID-19 on the national economy. The experience of using marketing and innovative technologies in the context of healthy national development is summarized. The monograph is generally intended for government officials, entrepreneurs, researchers, graduate students, students of economic, medical, and other specialties

    IDENTIFICATION OF STUDENTS AT RISK OF LOW PERFORMANCE BY COMBINING RULE-BASED MODELS, ENHANCED MACHINE LEARNING, AND KNOWLEDGE GRAPH TECHNIQUES

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    Technologies and online learning platforms have changed the contemporary educational paradigm, giving institutions more alternatives in a complex and competitive environment. Online learning platforms, learning-based analytics, and data mining tools are increasingly complementing and replacing traditional education techniques. However, academic underachievement, graduation delays, and student dropouts remain common problems in educational institutions. One potential method of preventing these issues is by predicting student performance through the use of institution data and advanced technologies. However, to date, scholars have yet to develop a module that can accurately predict students’ academic achievement and commitment. This dissertation attempts to bridge that gap by presenting a framework that allows instructors to achieve four goals: (1) track and monitor the performance of each student on their course, (2) identify at-risk students during the earliest stages of the course progression (3), enhance the accuracy with which at-risk student performance is predicted, and (4) improve the accuracy of student ranking and development of personalized learning interventions. These goals are achieved via four objectives. Objective One proposes a rule-based strategy and risk factor flag to warn instructors about at-risk students. Objective Two classifies at-risk students using an explainable ML-based model and rule-based approach. It also offers remedial strategies for at-risk students at each checkpoint to address their weaknesses. Objective Three uses ML-based models, GCNs, and knowledge graphs to enhance the prediction results. Objective Four predicts students’ ranking using ML-based models and clustering-based KGEs with the aim of developing personalized learning interventions. It is anticipated that the solution presented in this dissertation will help educational institutions identify and analyze at-risk students on a course-by-course basis and, thereby, minimize course failure rates

    WiFi-Based Human Activity Recognition Using Attention-Based BiLSTM

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    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

    Guide for the assessment of cacao quality and flavour

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    The Guide includes detailed protocols and procedures for evaluating cacao in various forms, such as unroasted cacao bean coarse powder, cacao mass, and chocolate. These methodologies have been developed over several years by a diverse group of experts, enabling objective assessments of cacao quality and flavour. It provides a universal language for describing cacao attributes, for a shared understanding among cacao professionals worldwide. This Guide serves as a comprehensive resource for individuals, associations and organisations interested in internationally aligned capacity building, with the objective of setting up cacao quality and flavour assessment facilities and sensory evaluation panels. The development of this Guide has been a collective endeavour spanning several years, drawing upon the expertise of stakeholders across the cacao sector. It began in September 2015 with the formation of an informal working group, coordinated by Cacao of Excellence to explore the establishment of international standards for assessing cacao quality and flavour. The group conducted a comprehensive review of existing standards in cacao, coffee, olive oil and wine. In 2016, a first proposal for a harmonised standard for cocoa quality and flavour assessment was developed, led by Dr Darin Sukha of the Cocoa Research Centre at the University of the West Indies in Trinidad and Tobago (CRC). In 2017 and 2018, individual protocols were developed based on this proposal and reviewed extensively by members of the working group and diverse stakeholders from the cacao sector. Between 2018 to 2022, a meticulous external review and refinement process involved more than 100 people from over 30 countries, resulting in this Guide. By 30 June 2023, more than 1,500 people from 105 countries had downloaded the protocols

    Metasemantics and fuzzy mathematics

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    The present thesis is an inquiry into the metasemantics of natural languages, with a particular focus on the philosophical motivations for countenancing degreed formal frameworks for both psychosemantics and truth-conditional semantics. Chapter 1 sets out to offer a bird's eye view of our overall research project and the key questions that we set out to address. Chapter 2 provides a self-contained overview of the main empirical findings in the cognitive science of concepts and categorisation. This scientific background is offered in light of the fact that most variants of psychologically-informed semantics see our network of concepts as providing the raw materials on which lexical and sentential meanings supervene. Consequently, the metaphysical study of internalistically-construed meanings and the empirical study of our mental categories are overlapping research projects. Chapter 3 closely investigates a selection of species of conceptual semantics, together with reasons for adopting or disavowing them. We note that our ultimate aim is not to defend these perspectives on the study of meaning, but to argue that the project of making them formally precise naturally invites the adoption of degreed mathematical frameworks (e.g. probabilistic or fuzzy). In Chapter 4, we switch to the orthodox framework of truth-conditional semantics, and we present the limitations of a philosophical position that we call "classicism about vagueness". In the process, we come up with an empirical hypothesis for the psychological pull of the inductive soritical premiss and we make an original objection against the epistemicist position, based on computability theory. Chapter 5 makes a different case for the adoption of degreed semantic frameworks, based on their (quasi-)superior treatments of the paradoxes of vagueness. Hence, the adoption of tools that allow for graded membership are well-motivated under both semantic internalism and semantic externalism. At the end of this chapter, we defend an unexplored view of vagueness that we call "practical fuzzicism". Chapter 6, viz. the final chapter, is a metamathematical enquiry into both the fuzzy model-theoretic semantics and the fuzzy Davidsonian semantics for formal languages of type-free truth in which precise truth-predications can be expressed

    COVID-2019 Impacts on Education Systems and Future of Higher Education

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    The rapid outbreak of the COVID-19 has presented unprecedented challenges on education systems. Closing schools and universities and cancelling face-to-face activities have become a COVID-19 inevitable reality in most parts of the world. To be business-as-usual, many higher education providers have taken steps toward digital transformation, and implementing a range of remote teaching, learning and assessment approaches. This book provides timely research on COVID-19 impacts on education systems and seeks to bring together scholars, educators, policymakers and practitioners to collectively and critically identify, investigate and share best practices that lead to rethinking and reframing the way we deliver education in future
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