184,867 research outputs found

    Renovations of a university library: the potential for place attachment among Gen Z students during a pandemic

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    University libraries are adapting their spaces to help support the needs of Gen Z students by adding collaborative spaces and encouraging social interactions. This qualitative case study explores the person-place interactions between Gen Z students and a Research 1 (R1) state university library during a full-scale renovation and worldwide pandemic. A tripartite framework of place attachment was used as a guide to examine the findings. Twenty-two undergraduate students in the library were interviewed, in addition to seven librarians, one facilities director, and one architect who oversaw the library's renovation. Observations and photo documentation were also used as supplemental data to support the information gained from the interviews. The analysis of the data revealed that place dependence was the strongest form of place attachment found in the data. Additionally, there were multiple connections found between place attachment constructs. Features of the library such as the spatial layout, technology, and access to information connected both physically based place attachment and place dependence. A collaborative atmosphere and peer motivation intertwined with socially based place attachment and place dependence. Also, relaxation, comfort, and safety were features that linked socially based place attachment and place affect. The library's major renovation that was underway during data collection, combined with the COVID-19 pandemic had a significant influence on the information gathered in this study. Implications and suggested interior design guidelines are provided.Includes bibliographical references

    Research report : Collaborative Peer 2 Peer Edition: Avoiding Conflicts is Better than Solving Conflicts

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    Collaborative edition is achieved by distinct sites that work independently on (a copy of) a shared document. Conflicts may arise during this process and must be solved by the collaborative editor. In pure Peer to Peer collaborative editing, no centralization nor locks nor time-stamps are used which make conflict resolution difficult. We propose an algorithm which relies on the notion or semantics dependence and avoids the need of any integration transformation to solve conflicts. Furthermore, it doesn't use any history file recording operations performed since starting the edition process. We show how to define editing operations for semi-structured documents i.e. XML-like trees, that are enriched with informations derived for free from the editing process. Then we define the semantics dependence relation required by the algorithm and we present preliminary results obtained by a prototype implementation.Comment: 12 page

    Development of OCIPSE Learning Model to Increase Students' Scientific Creativity in Natural Science Learning

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    This Research & Development (R & D) has the main goal to develop and produce OCIPSE learning model. The main product of this research is the OCIPSE learning model with five phases, they are 1) Orient and organize the students for study; 2) Collaborative Investigation; 3) Presentation and discussion; 4) Strengthening of scientific creativity; and 5) Evaluate and provide recognition. The OCIPSE learning model' quality data is obtained through an expert validation process by using the OCIPSE learning model Qualification Assessment Instrument. The OCIPSE learning model quality analysis used an average validity score, single measures ICC, and Cronbach's coefficient alpha. The result of the research shows OCIPSE learning model with average content validity (3.69), construct validity (3.69), with the validity of each aspect statistically in (rα = .92) and reliability in (α = .87).  The results of this study indicate that the developed OCIPSE learning model was declared qualified by experts. The research implication is that a qualified OCIPSE learning model can be used to enhance the scientific creativity of junior high school students in natural science learning.&nbsp

    Policy forums: Why do they exist and what are they used for?

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    Policy forums are issue-based intermediary organizations where diverse types of political and societal actors repeatedly interact. Policy forums are important elements of modern governance systems as they allow actors to learn, negotiate, or build trust. They can vary in composition, size, membership logic, and other distinct features. This article lays the foundation of a theory of policy forums based on three interrelated elements: First, it discusses conditions for the formation of a forum and describes the logic of these organizations as one of an asymmetric multipartite exchange. Second, it enumerates the potential set of goals and motivations of participating actors that are fed into this exchange. Third, it proposes eight different dimensions on which policy forums differ and which affect the exchange mechanisms among actors. We claim that empirical work on policy forums should systematically take these elements into account and propose elements of a research agenda

    Pathways to Coastal Resiliency: the Adaptive Gradients Framework

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    Current and future climate-related coastal impacts such as catastrophic and repetitive flooding, hurricane intensity, and sea level rise necessitate a new approach to developing and managing coastal infrastructure. Traditional “hard” or “grey” engineering solutions are proving both expensive and inflexible in the face of a rapidly changing coastal environment. Hybrid solutions that incorporate natural, nature-based, structural, and non-structural features may better achieve a broad set of goals such as ecological enhancement, long-term adaptation, and social benefits, but broad consideration and uptake of these approaches has been slow. One barrier to the widespread implementation of hybrid solutions is the lack of a relatively quick but holistic evaluation framework that places these broader environmental and societal goals on equal footing with the more traditional goal of exposure reduction. To respond to this need, the Adaptive Gradients Framework was developed and pilot-tested as a qualitative, flexible, and collaborative process guide for organizations to understand, evaluate, and potentially select more diverse kinds of infrastructural responses. These responses would ideally include natural, nature-based, and regulatory/cultural approaches, as well as hybrid designs combining multiple approaches. It enables rapid expert review of project designs based on eight metrics called “gradients”, which include exposure reduction, cost efficiency, institutional capacity, ecological enhancement, adaptation over time, greenhouse gas reduction, participatory process, and social benefits. The framework was conceptualized and developed in three phases: relevant factors and barriers were collected from practitioners and experts by survey; these factors were ranked by importance and used to develop the initial framework; several case studies were iteratively evaluated using this technique; and the framework was finalized for implementation. The article presents the framework and a pilot test of its application, along with resources that would enable wider application of the framework by practitioners and theorists

    A Generic Conceptual Model for Risk Analysis in a Multi-agent Based Collaborative Design Environment

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    Organised by: Cranfield UniversityThis paper presents a generic conceptual model of risk evaluation in order to manage the risk through related constraints and variables under a multi-agent collaborative design environment. Initially, a hierarchy constraint network is developed to mapping constraints and variables. Then, an effective approximation technique named Risk Assessment Matrix is adopted to evaluate risk level and rank priority after probability quantification and consequence validation. Additionally, an Intelligent Data based Reasoning Methodology is expanded to deal with risk mitigation by combining inductive learning methods and reasoning consistency algorithms with feasible solution strategies. Finally, two empirical studies were conducted to validate the effectiveness and feasibility of the conceptual model.Mori Seiki – The Machine Tool Compan

    A Deep Embedding Model for Co-occurrence Learning

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    Co-occurrence Data is a common and important information source in many areas, such as the word co-occurrence in the sentences, friends co-occurrence in social networks and products co-occurrence in commercial transaction data, etc, which contains rich correlation and clustering information about the items. In this paper, we study co-occurrence data using a general energy-based probabilistic model, and we analyze three different categories of energy-based model, namely, the L1L_1, L2L_2 and LkL_k models, which are able to capture different levels of dependency in the co-occurrence data. We also discuss how several typical existing models are related to these three types of energy models, including the Fully Visible Boltzmann Machine (FVBM) (L2L_2), Matrix Factorization (L2L_2), Log-BiLinear (LBL) models (L2L_2), and the Restricted Boltzmann Machine (RBM) model (LkL_k). Then, we propose a Deep Embedding Model (DEM) (an LkL_k model) from the energy model in a \emph{principled} manner. Furthermore, motivated by the observation that the partition function in the energy model is intractable and the fact that the major objective of modeling the co-occurrence data is to predict using the conditional probability, we apply the \emph{maximum pseudo-likelihood} method to learn DEM. In consequence, the developed model and its learning method naturally avoid the above difficulties and can be easily used to compute the conditional probability in prediction. Interestingly, our method is equivalent to learning a special structured deep neural network using back-propagation and a special sampling strategy, which makes it scalable on large-scale datasets. Finally, in the experiments, we show that the DEM can achieve comparable or better results than state-of-the-art methods on datasets across several application domains

    Choosing an organisational form: the case of collaborative procurement initiatives

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    This paper deals with different organisational forms of collaborative procurement and provides insight into when to use which form. Different forms from the literature are compared with empirical examples to give an overview of forms, which are then described in terms of strategy, skills and organisation. Whilst acknowledging variations, the paper distinguishes between two main forms: virtual networks and third-party organisations. Using empirical data and four theoretical perspectives (transaction cost economics, resource-based view, contingency theory, agency theory), the paper reflects on when which form can be used and presents an overall framework to help choose an organisational for
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