Tind Technologies (Norway)
Hes-so: ArODES Open Archive (University of Applied Sciences and Arts Western Switzerland / Haute école spécialisée de Suisse occidentale / FH Westschweiz)Not a member yet
15764 research outputs found
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Enhancing knowledge transmission ::the perspective of gamification user profiles
No full textIn the realm of knowledge transmission, organizations face the challenge of finding effective strategies to engage individuals and facilitate knowledge transfer. Traditional methods often fall short, failing to capture individuals’ attention and ignite their motivation to actively participate in the knowledge transmission process. This article introduces Colearnis, a novel knowledge transmission platform, which allows peers to transfer knowledge in a gamified manner by using videos and quizzes which are directly created by the employees. This article also presents a long-term field study investigating the use of Colearnis with 130 employees in a worldwide metallurgy and tooling company. A multi-dimensional evaluation approach makes use of user surveys and behavior-tracking data to explore prospective avenues which might benefit knowledge transmission. Users have been profiled under demographical and managerial aspects, however also under their gamification user types according to the Hexad framework for gamification design. This study explores the connections between user profiles and engagement behaviors within Colearnis. The findings suggest that factors such as; age influence the achiever and philanthropist user types, however also that individuals with greater managerial duties are more likely to be classified as socializer, free-spirit, or philanthropist user types. Additionally, this study suggests that socializer or disruptor user types are more likely to consume or react to peers’ self-created knowledge. On the other hand, achiever user profiles are less likely to react or start quizzes. These findings equip organizations with valuable insights to further design and implement engaging ad-hoc knowledge transmission systems. These systems could be further tailored to align with individuals’ managerial profiles and gamification user types, optimizing engagement and increasing the likelihood of successful knowledge transmission
Foreign direct investment motivation and spillovers from southern MNCs in Switzerland ::the role of FDI motivation and cultural dimension
No full textAn increasing number of studies analysed spillovers from northern economies to southern/northern economies, whilst little attention has been paid by scholars to study these effects from southern to northern economies. This study tests FDI spillovers from southern MNCs in Switzerland. It explores the intra- and inter-industry levels and focuses on the potential role of FDI motivation and cultural dimension in determining the size and the extent of intra- and inter-industry spillovers. Using firms-level data from Switzerland, we found that FDI intra- and inter-industry spillovers differ according to FDI motivation. Cultural dimension seems to be a significant element when assessing spillovers
Factors explaining age-related prospective memory performance differences ::a meta-analysis
No full textObjectives : The age-prospective memory paradox states that younger adults perform better than older adults in laboratory tasks, while the opposite has been observed for naturalistic tasks. These terms insufficiently characterise tasks and task settings. We therefore revisited the age-prospective memory paradox using a newly developed taxonomy to better understand how tasks characteristics or task settings contribute to age-related differences in performance. Methods : We conducted a meta-analysis of 138 studies, classifying prospective memory tasks according to our newly developed taxonomy. The taxonomy included 9 categories that considered how close any task or task setting was to daily life. Results : When categorizing relevant studies with this taxonomy, we found that older adults did better than younger adults in ‘close to real-life’ tasks done at home and, particularly, in to-do lists and diary tasks. However, they did worse in ‘far from real-life’ tasks done in naturalistic environments or in simulations of real-life tasks in a laboratory. Discussion : Results of this meta-analysis suggest that the level of abstraction of a task and familiarity of the environment in which the task is taken can explain some of the differences between performances of younger and older people. This is relevant for the choice of task settings and task properties to experimentally address any prospective memory research questions that are being asked
The quality of life and well-being of nursing home residents and their relatives during the COVID-19 pandemic ::a quantitative approach
No full textReconstruction of the lightning return-stroke current from the radiated magnetic field
No full textThis paper presents a new method to solve the inverse problem of reconstructing the lightning return-stroke current from measurements of the radiated magnetic field. Although the lightning channel is still assumed to be straight, vertical and at a known distance from the sensors measuring the fields, no model or channel-base measurement of the current is required, so that, unlike previous approaches to this kind of inverse problem, several assumptions on the current propagation along the channel can be dropped. The method is formulated in the frequency domain and is based on a double Fourier series representation of the unknown current as a function of two variables, i.e., the vertical coordinate and the frequency. The theoretical investigation results in an inversion algorithm, which is tested against simulated data in order to obtain some examples of current reconstruction
In Their Own Words ::Disseminating Feminist Self-Art Histories in Sound Archives
No full textIn 2009, artist Marysia Lewandowska began digitizing and sharing the Women Audio Archive (WAA) online. Begun in 1983 and conducted until the early 1990s, the WAA is a sound archive containing around 120 hours of public and private conversations recorded by the artist between London, the United States, and Canada with a Sony Walkman WM-F1 cassette player. The WAA embodies the trajectory of feminist interview and oral history practices of the 1970s in an exemplary way, deliberately exploiting the potential of analog recording technology to capture traditionally marginalized voices of art and social history. Considering the obsolescence of recording technologies and dissemination channels, this paper interrogates the historical forms of accessibility to feminist art practices of self-historicization and calls for reflection on the shift that the digitization of these sound documents entails. Particular attention will be given to the historical negotiations of intellectual co-ownership and the contemporary contexts in which private analogue sound archives can become public and open source following their digitization
Graphical insight ::revolutionizing seizure detection with EEG representation
No full textEpilepsy is characterized by recurring seizures that result from abnormal electrical activity in the brain. These seizures manifest as various symptoms including muscle contractions and loss of consciousness. The challenging task of detecting epileptic seizures involves classifying electroencephalography (EEG) signals into ictal (seizure) and interictal (non-seizure) classes. This classification is crucial because it distinguishes between the states of seizure and seizure-free periods in patients with epilepsy. Our study presents an innovative approach for detecting seizures and neurological diseases using EEG signals by leveraging graph neural networks. This method effectively addresses EEG data processing challenges. We construct a graph representation of EEG signals by extracting features such as frequency-based, statistical-based, and Daubechies wavelet transform features. This graph representation allows for potential differentiation between seizure and non-seizure signals through visual inspection of the extracted features. To enhance seizure detection accuracy, we employ two models: one combining a graph convolutional network (GCN) with long short-term memory (LSTM) and the other combining a GCN with balanced random forest (BRF). Our experimental results reveal that both models significantly improve seizure detection accuracy, surpassing previous methods. Despite simplifying our approach by reducing channels, our research reveals a consistent performance, showing a significant advancement in neurodegenerative disease detection. Our models accurately identify seizures in EEG signals, underscoring the potential of graph neural networks. The streamlined method not only maintains effectiveness with fewer channels but also offers a visually distinguishable approach for discerning seizure classes. This research opens avenues for EEG analysis, emphasizing the impact of graph representations in advancing our understanding of neurodegenerative diseases
Global taxonomy of stablecoins
No full textAs stablecoins address the challenges of price stability in the cryptocurrency market, this paper provides a comprehensive taxonomy of stablecoins, categorizing them based on governance, value, and design dimensions. Our study aims to enrich the ongoing discourse in digital currency and provide insights into the future trajectory of stablecoins in decentralized finance
Usage of text embedding for cross-lingual plagiarism detection
No full textThis article introduces an automated method for cross-lingual similarity assessment for plagiarism detection. This method is applied to help for automated plagiarism detection, comparing a suspicious text to an indexed corpus. The approach is based on the usage of a multilingual sentence encoder, to embed the semantic of sentences extracted from the suspicious document. We then retrieve the most similar sentence from the reference corpus. To address the scalability issue of the nearest neighbor search in high-dimensional vector search, we use Faiss, a heuristic search engine based on Voronoi cells of cluster’s centroids. Finally, a classifier is trained using the highest cosine similarity between the sentence and the reference corpus items, the sentence embeddings, and a few other features to classify the duplicated content. This method is evaluated on 328 documents of our real media partner database with different metrics. Top approach achieves a F1 score of 89% which would be confirmed with a larger and more representative dataset