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Reusing test cases across apps that share similar functionalities reduces both the effort required to produce useful test cases and the time to offer reliable apps to the market. The main approaches to reuse test cases across apps combine different semantic matching and test generation algorithms to migrate test cases across Android apps. In this paper we define a general framework to evaluate the impact and effectiveness of different choices of semantic matching with Test Reuse approaches on migrating test cases across Android apps. We offer a thorough comparative evaluation of the many possible choices for the components of test migration processes. We propose an approach that combines the most effective choices for each component of the test migration process to obtain an effective approach. We report the results of an experimental evaluation on 8,099 GUI events from 337 test configurations. The results attest the prominent impact of semantic matching on test reuse. They indicate that sentence level perform better than word level embedding techniques. They surprisingly suggest a negligible impact of the corpus of documents used for building the word embedding model for the Semantic Matching Algorithm. They provide evidence that semantic matching of events of selected types perform better than semantic matching of events of all types. They show that the effectiveness of overall Test Reuse approach depends on the characteristics of the test suites and apps.

Background: Patients are hospitalized for extended periods, particularly in intensive care units (ICUs). As a result, the saturation probe (pulse oximeter) remains attached for an extended period and microorganisms can grow in the wet environment. If the pulse oximeters are not reprocessed, cross-infection may occur. The literature contains several studies in which gloves were used for the measurement while various SpO2 (peripheral arterial oxygen saturation) measurements were compared with each other. However, such comparisons have yet to be made with the results of arterial blood gas SpO2 measurements by pulse oximeter, considered as the gold standard. The present study aimed to compare arterial blood gas values with the fingertip saturation measurement performed by having adult patients wear gloves of different colors, one after the other, on their fingers and determining the effect of the differently colored gloves (transparent, white, black, light blue) on saturation values.Methods: The study was conducted on 54 patients in an ICU. Intra-arterial blood gas SpO2 results were measured. Oxygen saturation was measured while the patient 1. did not wear gloves and 2. sequentially wore a series of gloves of different colors. Paired t-test, correlation analysis, and Bland Altman charts were used to evaluate the results.Results: The mean SpO2% value of the participants' intra-arterial blood gas measurements was 97.76±2.04. The mean SpO2% value obtained from the measurements of the fingers with a transparent glove was 0.43 points lower than the mean SpO2% value of the intra-arterial blood gas measurements (t=0.986, p=0.61). The mean SpO2% value obtained from the measurements of the fingers with a white glove was 0.93 points lower than the mean SpO2% value of the intra-arterial blood gas measurements (t=1.157, p=0.093).Conclusion: Of the measurements performed with a glove, the mean SpO2% value obtained from the measurements of the fingers with a transparent glove was mor, Hintergrund: Patienten werden über längere Zeiträume stationär behandelt, insbesondere auf Intensivstation und Mikroorganismen können sich in der feuchten Kammer vermehren. Werden die Sättigungssonden nicht aufbereitet, kann es zu Kreuzinfektionen kommen. In der Literatur wurden mehrere Studien durchgeführt, in denen Handschuhe zur Messung verwendet wurden, wobei verschiedene SpO2-Messungen miteinander verglichen wurden. Solche Vergleiche mit den Ergebnissen arterieller Blutgas-SpO2-Messungen, die als Goldstandard gelten, stehen jedoch aus. Ziel der vorliegenden Studie war es, arterielle Blutgaswerte mit der Sättigungsmessung an den Fingerspitzen bei der erwachsene Patienten zu vergleichen, die transparente Handschuhe unterschiedlicher Farbe an den Fingern trugen, um die Auswirkung von Handschuhen auf die Sättigungswerte zu bestimmen.Methode: Die Studie wurde an 54 Patienten auf einer Intensivstation durchgeführt. Die intraarteriellen Blutgas-SpO2-Ergebnisse der Patienten wurden gemessen. Die Sauerstoffsättigung wurde gemessen, wenn der Patient keine Handschuhe bzw. einen andersfarbigen Handschuh trug. Bei der Analyse der Studie wurden der gepaarte T-Test, die Korrelationsanalyse und Bland-Altman-Diagramme verwendet.Ergebnisse: Der mittlere SpO2%-Wert der intraarteriellen Blutgasmessungen betrug 97,76±2,04. Der mittlere SpO2%-Wert aus den Messungen der Finger mit einem transparenten Handschuh war 0,43 Punkte niedriger als der mittlere SpO2%-Wert der intraarteriellen Blutgasmessungen (t=0,986, p=0,61). Der mittlere SpO2%-Wert aus den Messungen der Finger mit einem weißen Handschuh war 0,93 Punkte niedriger als der mittlere SpO2%-Wert der intraarteriellen Blutgasmessungen (t=1,157, p=0,093).Schlussfolgerung: Bei den mit Handschuhen durchgeführten Messungen stimmte der mittlere SpO2%-Wert, der aus den Messungen an den Fingern mit einem transparenten Handschuh erhalten wurde, besser mit dem mittleren SpO2%-Wert der intraarteriellen Blutgasmessungen überein als bei Messu

In the banking world trades of securities are finalized every day, on behalf of the banks themselves or of their clients. When the trades have been booked by the front office the confirmations sent by the counterparty have to be checked and connected to the correct trade by hand, posing the question whether this process could not be automated using machine learning techniques. There is no straightforward solution to this problem since the confirmations differ between counterparties, and can contain different enriched information or even be in different formats. This thesis addresses the problem of matching trades with their corresponding confirmations via deep learning methods. A model is trained using contrastive learning methods on generated pairs of trades and confirmations, with the goal of matching the pairs in the latent space by using nearest neighbor classification. Accuracy is measured by dividing the correctly classified samples by the total number of samples in a testing batch. The model achieves an accuracy as high as 97.8% over 100 trade-confirmation samples with a 30-dimensional latent space, and it is shown that similar contrastive methods can indeed be used in order to solve this problem., Banker handlar varje dag med värdpapper av olika slag, antingen för sin egen vinning eller för sina kunders. När en affär har blivit beslutad mellan två parter så bokförs denna i bägge parternas interna system. En konfirmation kommer sedan skickas från den andra parten som manuellt måste paras ihop med affären vilket väcker frågan om huruvida detta inte kan automatiseras med hjälp av maskininlärning. Det finns inte en uppenbar lösning på detta problemet då konfirmationsmeddelandena kan skiljer sig åt mellan olika parter och kan innehålla olika tillagd information eller till och med vara i olika format. En model tränas genom att använda kontrast-inlärning på genererade par av affärer och konfirmationer av affärer för att kunna para ihop paren i det latenta rummet genom att se vilka grannar som ligger närmast. Nogrannheten mäts genom att dela antalet korrekt klassificerade exempel med det totala antalet par i en grupp test-par. Modellen uppnår en noggrannhet så hög som 97.8% på 100 affärs-konfirmationspar med ett 30-dimensionellt latent rum, och det visas att kontrast-inlärning kan användas för att lösa problemet. Det är dock svårt att säga mycket om hur väl modellen kan generalisera de inlärda kunskaperna eftersom träningsdatan behövde genereras och därför saknar en del av komplexiteten av ett äkte data set.

In this thesis, a novel approach to classifying personal data is tested. Previous personal data classification models read the personal data before classifying it. However, this thesis instead investigates an approach to classify personal data by looking at contextual information frequently available in data sets. The thesis compares the well-researched word embedding methods Word2Vec, Global representations of Vectors (GloVe) and Bidirectional Encoder Representations from Transformers (BERT) used in conjunction with the different types of classification methods Bag Of Word representation (BOW), Convolutional Neural Networks (CNN), and Long Short-term Memory (LSTM) when solving a personal data classification task. The comparisons are made by extrinsically evaluating the different embeddings' and models' performance in a personal data classification task on a sizable collection of well-labeled datasets belonging to Spotify. The results suggest that the embedded representations of the contextual data capture enough information to be able to classify personal data both when classifying non-personal data against personal data, and also when classifying different types of personal data from each other., I denna uppsats undersöks ett nytt tillvägagångssätt att klassificera personlig data. Tidigare dataklassificerings modeller läser data innan den klassificerar den. I denna uppsats undersöks istället ett tillvägagångssätt där den kontextuella informationen används. Uppsatsen jämför flera väletablerade metoder för 'word embedding' så som Word2Vec, Global representations of Vectors (GloVe) och Bidirectional Encoder Representations from Transformers (BERT) i kombination med klassificeringsmodellerna Bag Of Word representation (BOW), Convolutional Neural Networks (CNN) och Long Short-term Memory (LSTM). Modellerna jämförs genom att evaluera deras förmåga att klassificera olika typer av personlig data baserad på namngivning och beskrivning av dataset. Resultaten pekar på att representationerna samt modellerna fångar tillräckligt med information för att kunna klassificera personlig data baserat på den kontextuell information som gavs. Utöver detta antyder resultaten att modellerna även klarar av att urskilja olika typer av personlig data från varandra.

In the banking world trades of securities are finalized every day, on behalf of the banks themselves or of their clients. When the trades have been booked by the front office the confirmations sent by the counterparty have to be checked and connected to the correct trade by hand, posing the question whether this process could not be automated using machine learning techniques. There is no straightforward solution to this problem since the confirmations differ between counterparties, and can contain different enriched information or even be in different formats. This thesis addresses the problem of matching trades with their corresponding confirmations via deep learning methods. A model is trained using contrastive learning methods on generated pairs of trades and confirmations, with the goal of matching the pairs in the latent space by using nearest neighbor classification. Accuracy is measured by dividing the correctly classified samples by the total number of samples in a testing batch. The model achieves an accuracy as high as 97.8% over 100 trade-confirmation samples with a 30-dimensional latent space, and it is shown that similar contrastive methods can indeed be used in order to solve this problem., Banker handlar varje dag med värdpapper av olika slag, antingen för sin egen vinning eller för sina kunders. När en affär har blivit beslutad mellan två parter så bokförs denna i bägge parternas interna system. En konfirmation kommer sedan skickas från den andra parten som manuellt måste paras ihop med affären vilket väcker frågan om huruvida detta inte kan automatiseras med hjälp av maskininlärning. Det finns inte en uppenbar lösning på detta problemet då konfirmationsmeddelandena kan skiljer sig åt mellan olika parter och kan innehålla olika tillagd information eller till och med vara i olika format. En model tränas genom att använda kontrast-inlärning på genererade par av affärer och konfirmationer av affärer för att kunna para ihop paren i det latenta rummet genom att se vilka grannar som ligger närmast. Nogrannheten mäts genom att dela antalet korrekt klassificerade exempel med det totala antalet par i en grupp test-par. Modellen uppnår en noggrannhet så hög som 97.8% på 100 affärs-konfirmationspar med ett 30-dimensionellt latent rum, och det visas att kontrast-inlärning kan användas för att lösa problemet. Det är dock svårt att säga mycket om hur väl modellen kan generalisera de inlärda kunskaperna eftersom träningsdatan behövde genereras och därför saknar en del av komplexiteten av ett äkte data set.

In this thesis, a novel approach to classifying personal data is tested. Previous personal data classification models read the personal data before classifying it. However, this thesis instead investigates an approach to classify personal data by looking at contextual information frequently available in data sets. The thesis compares the well-researched word embedding methods Word2Vec, Global representations of Vectors (GloVe) and Bidirectional Encoder Representations from Transformers (BERT) used in conjunction with the different types of classification methods Bag Of Word representation (BOW), Convolutional Neural Networks (CNN), and Long Short-term Memory (LSTM) when solving a personal data classification task. The comparisons are made by extrinsically evaluating the different embeddings' and models' performance in a personal data classification task on a sizable collection of well-labeled datasets belonging to Spotify. The results suggest that the embedded representations of the contextual data capture enough information to be able to classify personal data both when classifying non-personal data against personal data, and also when classifying different types of personal data from each other., I denna uppsats undersöks ett nytt tillvägagångssätt att klassificera personlig data. Tidigare dataklassificerings modeller läser data innan den klassificerar den. I denna uppsats undersöks istället ett tillvägagångssätt där den kontextuella informationen används. Uppsatsen jämför flera väletablerade metoder för 'word embedding' så som Word2Vec, Global representations of Vectors (GloVe) och Bidirectional Encoder Representations from Transformers (BERT) i kombination med klassificeringsmodellerna Bag Of Word representation (BOW), Convolutional Neural Networks (CNN) och Long Short-term Memory (LSTM). Modellerna jämförs genom att evaluera deras förmåga att klassificera olika typer av personlig data baserad på namngivning och beskrivning av dataset. Resultaten pekar på att representationerna samt modellerna fångar tillräckligt med information för att kunna klassificera personlig data baserat på den kontextuell information som gavs. Utöver detta antyder resultaten att modellerna även klarar av att urskilja olika typer av personlig data från varandra.

In recent years, the availability of parliamentary transcriptions has motivated the use of Natural Language Processing (NLP) methods for investigating these datasets quantitatively. One area of study for political scientists has been the expression of emotion by parliamentary speakers and the factors that influence it. However, there is a lack of research on non-anglophone legislatures and insufficient validation of existing sentiment analysis methods. In this study, a technique for creating domain-specific sentiment lexica with word embeddings is applied to datasets of parliamentary speech from Bulgaria and Denmark in order to investigate the effects of party status and proceeding type. By embedding each corpus with Global Vectors (GloVe), manually produced seed lists of positive and negative words can be expanded using measures of vector similarity. The resulting lexica, called ParLex DK/BG, are used to score and compare the two corpora. The sentiment analysis indicates that for both legislatures, government/coalition status is associated with more positive emotion relative to opposition or other status, though this is much more pronounced in Denmark. With regard to proceeding type, there is no consistent cross-national pattern, but proceeding type does interact with party status. In both countries, sentiment gaps between coalition and opposition are largest during ministerial questionings, and in the Bulgarian parliament, the effect of party status is only clearly apparent during questionings and draft decisions. These differences may reflect the contrast between a more established (Denmark) and more politically turbulent (Bulgaria) legislature. Confidence in these results is also moderated by evaluation with a hand-annotated gold standard of speeches. Correlation between ParLex and manual annotation is 0.40 for Bulgarian and 0.48 for Danish. ParLex DK is also outperformed by a common general-use lexicon, indicating that domain-specificity does not offer

In recent years, the availability of parliamentary transcriptions has motivated the use of Natural Language Processing (NLP) methods for investigating these datasets quantitatively. One area of study for political scientists has been the expression of emotion by parliamentary speakers and the factors that influence it. However, there is a lack of research on non-anglophone legislatures and insufficient validation of existing sentiment analysis methods. In this study, a technique for creating domain-specific sentiment lexica with word embeddings is applied to datasets of parliamentary speech from Bulgaria and Denmark in order to investigate the effects of party status and proceeding type. By embedding each corpus with Global Vectors (GloVe), manually produced seed lists of positive and negative words can be expanded using measures of vector similarity. The resulting lexica, called ParLex DK/BG, are used to score and compare the two corpora. The sentiment analysis indicates that for both legislatures, government/coalition status is associated with more positive emotion relative to opposition or other status, though this is much more pronounced in Denmark. With regard to proceeding type, there is no consistent cross-national pattern, but proceeding type does interact with party status. In both countries, sentiment gaps between coalition and opposition are largest during ministerial questionings, and in the Bulgarian parliament, the effect of party status is only clearly apparent during questionings and draft decisions. These differences may reflect the contrast between a more established (Denmark) and more politically turbulent (Bulgaria) legislature. Confidence in these results is also moderated by evaluation with a hand-annotated gold standard of speeches. Correlation between ParLex and manual annotation is 0.40 for Bulgarian and 0.48 for Danish. ParLex DK is also outperformed by a common general-use lexicon, indicating that domain-specificity does not offer

The modern musician faces a new challenge: how can technology be used to enhance a performance? This thesis documents the development of a Bluetooth remote controller that will aid today’s performing musicians by interacting with a digital display (e.g., an iPad) to flip musical score pages remotely. At its core, while mimicking a Bluetooth pedal (the current industry standard), this device attaches to the musician’s hand. In its pilot stages, the device has been referred to “MBC” (Music Bluetooth Controller).

Hand-worn haptic systems must be able to produce high-quality haptics while also being lightweight and energy-efficient. In order to meet market expectations, research is being done into novel drivetrains that may be implemented in hand worn devices. This is being pushed forward by the growing demand in the virtual reality sector, which is placing pressure on the development of new wearable force feedback technology. In order to validate a proof of concept, this thesis proposes a novel force feedback drivetrain with a dual actuator setup-a motor and a brake—that is integrated into a tabletop prototype. Using both a motor and a brake will reduce weight and improve the haptic rendering quality relative to each component when considered separately. To evaluate the presumptive advantages, a theoretical analysis into the suggested hybrid actuation solution is conducted. The analysis comprises of numerous simulations using a model of the hybrid drivetrain's working principle. Additionally, the analysis is employed to investigate and spot any early-stage defects or undesirable behavior. Consequently, a 3D model was created in order to 3D print a functioning prototype in order to apply the theory in a physical version. The prototype is initially used to validate the simulation model and enforce the findings of the theoretical analysis. Force data is measured when using the prototype and in turn is fed into the simulation model to assess whether the output behaviour is consistent with the prototype. Both the model's competence and the prototype's predictability are assessed using the outcomes. Finally, an experiment is conducted to both asses the mechanical performance and predictability as well as the participant's perception; 2 virtual environments and 3 actuation modes (motor, brake, and hybrid) were cross-examined and each repeated 6 times, for a total of 36 trials. This experiment ultimately assesses the prototypes validity and determines whether the t, Mechanical Engineering

This study was conducted to explore budget DIY VR-gloves with haptics, and its use cases within Virtual Reality (VR). The VR-gloves were built according to an open-source project, called LucidGloves. A user test with 19 users was later conducted, where the VR-gloves were compared to Vive-controllers regarding the user experience in a VR-environment. The result for the entire test group showed no significant difference between the two units. A significant difference was found for the males, where the virtual hands were perceived more as their own (virtual body ownership) when using the VR-gloves. For the experienced VR-users, there was a significant difference regarding the object interaction, where the Vive-controllers appeared more realistic. The conclusions made is that if VR-gloves increase virtual body ownership for males, there is a potential to increase performance in VR-training simulators with VR-gloves. It is also crucial that the VR-gloves perform faultless to keep the user’s presence in VR. This is at the same time is difficult to do with one pair of gloves that should suit multiply hand sizes. The suggestions for improvement that were identified was to develop the responsivity and interaction for the VR-gloves. Further areas of improvement were to increase the robustness of the gloves, where suggestions were developed regarding a different component layout, battery placement and cord attachment., Denna studie utfördes för att utforska egenbyggda billiga VR-handskar med haptik och dess användningsmöjligheter inom Virtual Reality (VR). VR-handskarna byggdes utifrån ett open source-projekt kallat LucidGloves. Ett användartest med 19 deltagare jämförde sedan VR-handskarna med Vive-kontroller i avseende på användarupplevelse i en VR-miljö. För hela testgruppen fanns ingen signifikant skillnad mellan de två styrsystemen. För männen upplevdes de virtuella händerna mer som ens egna händer (virtuellt kroppsägande) när VR-handskar användes. För enbart erfarna VR-användare fanns dessutom en signifikant skillnad gällande objektinteraktion, där det upplevdes mer realistiskt med Vive-kontrollerna. Slutsatser som dragits är att handskarna med ökat virtuellt kroppsägande för män visar potential i att förbättra träningssimulatorer i VR. Det är även viktigt att handskarna fungerar felfritt för att behålla användarens närvaro i VR (presence), men att detta är svårt att åstadkomma med ett par handskar som ska passa för olika handstorlekar. Förbättringsförslag som identifierades var framför allt att utveckla responsiviteten och interaktionen för handskarna. Ytterligare förbättringsförslag var att förbättra robustheten på handskarna, där förslag om förbättrad komponentlayout, batteriplacering och sladdfäste togs fram.

Historically author profiling has been used in forensic linguistics. However, it is not until the last decades that the analysis method has worked into computer science and machine learning. In comparison, determining author profiling characteristics in machine learning is nothing new. This paper investigates the possibility to improve upon previous results with modern frameworks using data sets that have seen limited usage. The purpose of this master thesis was to use pre-trained transformers or embeddings together with transfer learning. In addition, to examine if general author profiling characteristics of anonymous users on internet forums or conversations on social media could be determined. The data sets used to investigate the questions above were PAN15 and PANDORA, which contains various properties in text data based on authors paired with ground truth labels such as gender, age, and Big Five/OCEAN. In addition, transfer learning of BERT and GloVe was used as a starting point to decrease the learning time of a new task. PAN15, a Twitter data set, did not contain enough data when training a model and was augmented using PANDORA, a Reddit-based data set. Ultimately, BERT obtained the best performance using a stacked approach, achieving 86 − 91% accuracy for each label on unseen data.

The purpose of this study is to design and implement an electronic glove to improve productivity and safety in the industrial workshop of the INEM Educational Institution in the city of Monteria, Cordoba. This research was guided by the following stages, first, the application of surveys before and after the implementation of the electronic device, with the purpose of determining the impact of this in relation to the productivity of the tasks and the well-being of the operators of the industrial workshop. Next, the development of a web application that stores the data collected by the electronic glove to allow a better management of the information. The research yielded optimal results that demonstrate the relevant intervention that this type of technology has within the optimization of industrial tasks, in terms of time management, inventory management and ease in the handling of the different tools of the workshop; along with the efficient management of information, this because it caused a better manageability of processes and items, as well as offering a new innovative and creative tool for the industry., El presente estudio tiene como propósito diseñar e implementar un guante electrónico, para favorecer la productividad y seguridad en las tareas del taller industrial de la Institución Educativa INEM de la Ciudad de Montería, Córdoba, en Colombia. Esta investigación es de tipo tecnológico-descriptivo y estuvo guiada por una etapa de encuestas, antes y después de la implementación del dispositivo electrónico, con el propósito de determinar su impacto en relación con la productividad de las tareas y el bienestar de los operarios del taller industrial, y seguidamente, el desarrollo de una aplicación web que almacena los datos recogidos por el guante electrónico, para permitir una mejor administración de la información. La investigación arrojó resultados alentadores que demuestran la intervención relevante que tiene este tipo de tecnología dentro de la optimización de las labores industriales, en cuanto al manejo del tiempo, la gestión de inventarios, facilidad en la manipulación de las distintas herramientas del taller, junto con la gestión eficiente de la información, debido a que provocó un mejor manejo de los procesos y de los artículos, así como el ofrecimiento de una herramienta innovadora y creativa para la industria.

Text classification is an essential task in natural language processing. While graph neural networks (GNNs) have successfully been applied to this problem both through graph classification and node classification approaches, their typical applications suffer from several issues. In the graph classification case, common graph construction techniques tend to leave out syntactic information. In the node classification case, most widespread datasets and applications tend to suffer from encoding relatively little information in the chosen node features. Finally, there are great benefits to be gained from combining the two GNN approaches. To tackle these concerns, we propose DepNet, a two-stage framework for text classification using GNN models. In the first stage we replace current graph construction methods by utilizing syntactic dependency parsing in order to include as much syntactic information in the GNN input as possible. In the second stage we combine both graph classification and node classification methods by utilizing the former to produce node embeddings for the latter, maximizing the potential of GNNs for text classification. We find that this technique significantly improves the performance of both graph classification and node classification approaches to text classification.

This study was conducted to explore budget DIY VR-gloves with haptics, and its use cases within Virtual Reality (VR). The VR-gloves were built according to an open-source project, called LucidGloves. A user test with 19 users was later conducted, where the VR-gloves were compared to Vive-controllers regarding the user experience in a VR-environment. The result for the entire test group showed no significant difference between the two units. A significant difference was found for the males, where the virtual hands were perceived more as their own (virtual body ownership) when using the VR-gloves. For the experienced VR-users, there was a significant difference regarding the object interaction, where the Vive-controllers appeared more realistic. The conclusions made is that if VR-gloves increase virtual body ownership for males, there is a potential to increase performance in VR-training simulators with VR-gloves. It is also crucial that the VR-gloves perform faultless to keep the user’s presence in VR. This is at the same time is difficult to do with one pair of gloves that should suit multiply hand sizes. The suggestions for improvement that were identified was to develop the responsivity and interaction for the VR-gloves. Further areas of improvement were to increase the robustness of the gloves, where suggestions were developed regarding a different component layout, battery placement and cord attachment., Denna studie utfördes för att utforska egenbyggda billiga VR-handskar med haptik och dess användningsmöjligheter inom Virtual Reality (VR). VR-handskarna byggdes utifrån ett open source-projekt kallat LucidGloves. Ett användartest med 19 deltagare jämförde sedan VR-handskarna med Vive-kontroller i avseende på användarupplevelse i en VR-miljö. För hela testgruppen fanns ingen signifikant skillnad mellan de två styrsystemen. För männen upplevdes de virtuella händerna mer som ens egna händer (virtuellt kroppsägande) när VR-handskar användes. För enbart erfarna VR-användare fanns dessutom en signifikant skillnad gällande objektinteraktion, där det upplevdes mer realistiskt med Vive-kontrollerna. Slutsatser som dragits är att handskarna med ökat virtuellt kroppsägande för män visar potential i att förbättra träningssimulatorer i VR. Det är även viktigt att handskarna fungerar felfritt för att behålla användarens närvaro i VR (presence), men att detta är svårt att åstadkomma med ett par handskar som ska passa för olika handstorlekar. Förbättringsförslag som identifierades var framför allt att utveckla responsiviteten och interaktionen för handskarna. Ytterligare förbättringsförslag var att förbättra robustheten på handskarna, där förslag om förbättrad komponentlayout, batteriplacering och sladdfäste togs fram.

The modern musician faces a new challenge: how can technology be used to enhance a performance? This thesis documents the development of a Bluetooth remote controller that will aid today’s performing musicians by interacting with a digital display (e.g., an iPad) to flip musical score pages remotely. At its core, while mimicking a Bluetooth pedal (the current industry standard), this device attaches to the musician’s hand. In its pilot stages, the device has been referred to “MBC” (Music Bluetooth Controller).

Hand-worn haptic systems must be able to produce high-quality haptics while also being lightweight and energy-efficient. In order to meet market expectations, research is being done into novel drivetrains that may be implemented in hand worn devices. This is being pushed forward by the growing demand in the virtual reality sector, which is placing pressure on the development of new wearable force feedback technology. In order to validate a proof of concept, this thesis proposes a novel force feedback drivetrain with a dual actuator setup-a motor and a brake—that is integrated into a tabletop prototype. Using both a motor and a brake will reduce weight and improve the haptic rendering quality relative to each component when considered separately. To evaluate the presumptive advantages, a theoretical analysis into the suggested hybrid actuation solution is conducted. The analysis comprises of numerous simulations using a model of the hybrid drivetrain's working principle. Additionally, the analysis is employed to investigate and spot any early-stage defects or undesirable behavior. Consequently, a 3D model was created in order to 3D print a functioning prototype in order to apply the theory in a physical version. The prototype is initially used to validate the simulation model and enforce the findings of the theoretical analysis. Force data is measured when using the prototype and in turn is fed into the simulation model to assess whether the output behaviour is consistent with the prototype. Both the model's competence and the prototype's predictability are assessed using the outcomes. Finally, an experiment is conducted to both asses the mechanical performance and predictability as well as the participant's perception; 2 virtual environments and 3 actuation modes (motor, brake, and hybrid) were cross-examined and each repeated 6 times, for a total of 36 trials. This experiment ultimately assesses the prototypes validity and determines whether the t, Mechanical Engineering

The purpose of this study is to design and implement an electronic glove to improve productivity and safety in the industrial workshop of the INEM Educational Institution in the city of Monteria, Cordoba. This research was guided by the following stages, first, the application of surveys before and after the implementation of the electronic device, with the purpose of determining the impact of this in relation to the productivity of the tasks and the well-being of the operators of the industrial workshop. Next, the development of a web application that stores the data collected by the electronic glove to allow a better management of the information. The research yielded optimal results that demonstrate the relevant intervention that this type of technology has within the optimization of industrial tasks, in terms of time management, inventory management and ease in the handling of the different tools of the workshop; along with the efficient management of information, this because it caused a better manageability of processes and items, as well as offering a new innovative and creative tool for the industry., El presente estudio tiene como propósito diseñar e implementar un guante electrónico, para favorecer la productividad y seguridad en las tareas del taller industrial de la Institución Educativa INEM de la Ciudad de Montería, Córdoba, en Colombia. Esta investigación es de tipo tecnológico-descriptivo y estuvo guiada por una etapa de encuestas, antes y después de la implementación del dispositivo electrónico, con el propósito de determinar su impacto en relación con la productividad de las tareas y el bienestar de los operarios del taller industrial, y seguidamente, el desarrollo de una aplicación web que almacena los datos recogidos por el guante electrónico, para permitir una mejor administración de la información. La investigación arrojó resultados alentadores que demuestran la intervención relevante que tiene este tipo de tecnología dentro de la optimización de las labores industriales, en cuanto al manejo del tiempo, la gestión de inventarios, facilidad en la manipulación de las distintas herramientas del taller, junto con la gestión eficiente de la información, debido a que provocó un mejor manejo de los procesos y de los artículos, así como el ofrecimiento de una herramienta innovadora y creativa para la industria.

Historically author profiling has been used in forensic linguistics. However, it is not until the last decades that the analysis method has worked into computer science and machine learning. In comparison, determining author profiling characteristics in machine learning is nothing new. This paper investigates the possibility to improve upon previous results with modern frameworks using data sets that have seen limited usage. The purpose of this master thesis was to use pre-trained transformers or embeddings together with transfer learning. In addition, to examine if general author profiling characteristics of anonymous users on internet forums or conversations on social media could be determined. The data sets used to investigate the questions above were PAN15 and PANDORA, which contains various properties in text data based on authors paired with ground truth labels such as gender, age, and Big Five/OCEAN. In addition, transfer learning of BERT and GloVe was used as a starting point to decrease the learning time of a new task. PAN15, a Twitter data set, did not contain enough data when training a model and was augmented using PANDORA, a Reddit-based data set. Ultimately, BERT obtained the best performance using a stacked approach, achieving 86 − 91% accuracy for each label on unseen data.

It is quite well known how important our sense of vision is on the course of our daily lives. And as for people who are visually impaired must resort to some kind of counter measures such as a cane or a walking stick to cope with their daily activities. But such solutions are not accurate let alone be perfect. In this paper there are various presentations which are sophisticated yet simple contraption which exactly meets the above-mentioned needs, which is accuracy, using an ultrasonic sensor latched up on a glove and functioning with the help of a microcontroller. Upon receiving input from the microcontroller, the vibrator and buzzer notify the person wearing the glove if an obstacle has been detected with the help of the glove.

A (randomized controlled) hand hygiene study was conducted in 80 nursing homes across the Netherlands. Compliance

The difficulties that exist to establish a dialogue with deaf people are many due to the fact that a large number of people do not know dactylology or sign language. In Ecuador, people with this disability are indifferent from certain technology, which reduces their communication possibilities. Due to this, the use of a kit that helps in the learning of sign language is proposed. Through preliminary interviews and literature review, guidelines were obtained on how the kit should be designed. Thus, the proposed kit consists of a glove linked by Bluetooth to a mobile application. The prototype built initially allows the learning of the alphabet and the formation of basic words of the Ecuadorian sign language. With this prototype an evaluation was carried out with adults, to get an opinion of the didactic kit. The results obtained were mostly positive, which allows speculating that such a kit could help in the learning of sign language., Las dificultades que existen para entablar un diálogo con personas sordas son muchas debido a que una gran cantidad de personas no conocen la dactilología o lenguaje de señas. En Ecuador, las personas con esta discapacidad están apartadas de ciertas tecnologías lo que disminuye sus posibilidades de comunicación. Debido a esto, se propone la utilización de un kit que ayude en el aprendizaje del lenguaje de señas. Mediante entrevistas preliminares y revisión bibliográfica se obtuvieron lineamientos sobre cómo se debería diseñar el kit. Así, el kit propuesto está compuesto de un guante vinculado por Bluetooth a una aplicación móvil. El prototipo construido permite inicialmente el aprendizaje del abecedario y la formación de palabras básicas del lenguaje de señas ecuatoriano. Con este prototipo se realizó una evaluación con personas adultas, para llegar a obtener una opinión del kit didáctico. Los resultados obtenidos fueron en su mayoría positivos, lo cual permite especular que un kit de este tipo podría ayudar en el aprendizaje de lenguaje de señas.

It is quite well known how important our sense of vision is on the course of our daily lives. And as for people who are visually impaired must resort to some kind of counter measures such as a cane or a walking stick to cope with their daily activities. But such solutions are not accurate let alone be perfect. In this paper there are various presentations which are sophisticated yet simple contraption which exactly meets the above-mentioned needs, which is accuracy, using an ultrasonic sensor latched up on a glove and functioning with the help of a microcontroller. Upon receiving input from the microcontroller, the vibrator and buzzer notify the person wearing the glove if an obstacle has been detected with the help of the glove.

The difficulties that exist to establish a dialogue with deaf people are many due to the fact that a large number of people do not know dactylology or sign language. In Ecuador, people with this disability are indifferent from certain technology, which reduces their communication possibilities. Due to this, the use of a kit that helps in the learning of sign language is proposed. Through preliminary interviews and literature review, guidelines were obtained on how the kit should be designed. Thus, the proposed kit consists of a glove linked by Bluetooth to a mobile application. The prototype built initially allows the learning of the alphabet and the formation of basic words of the Ecuadorian sign language. With this prototype an evaluation was carried out with adults, to get an opinion of the didactic kit. The results obtained were mostly positive, which allows speculating that such a kit could help in the learning of sign language., Las dificultades que existen para entablar un diálogo con personas sordas son muchas debido a que una gran cantidad de personas no conocen la dactilología o lenguaje de señas. En Ecuador, las personas con esta discapacidad están apartadas de ciertas tecnologías lo que disminuye sus posibilidades de comunicación. Debido a esto, se propone la utilización de un kit que ayude en el aprendizaje del lenguaje de señas. Mediante entrevistas preliminares y revisión bibliográfica se obtuvieron lineamientos sobre cómo se debería diseñar el kit. Así, el kit propuesto está compuesto de un guante vinculado por Bluetooth a una aplicación móvil. El prototipo construido permite inicialmente el aprendizaje del abecedario y la formación de palabras básicas del lenguaje de señas ecuatoriano. Con este prototipo se realizó una evaluación con personas adultas, para llegar a obtener una opinión del kit didáctico. Los resultados obtenidos fueron en su mayoría positivos, lo cual permite especular que un kit de este tipo podría ayudar en el aprendizaje de lenguaje de señas.

It is quite well known how important our sense of vision is on the course of our daily lives. And as for people who are visually impaired must resort to some kind of counter measures such as a cane or a walking stick to cope with their daily activities. But such solutions are not accurate let alone be perfect. In this paper there are various presentations which are sophisticated yet simple contraption which exactly meets the above-mentioned needs, which is accuracy, using an ultrasonic sensor latched up on a glove and functioning with the help of a microcontroller. Upon receiving input from the microcontroller, the vibrator and buzzer notify the person wearing the glove if an obstacle has been detected with the help of the glove.

The difficulties that exist to establish a dialogue with deaf people are many due to the fact that a large number of people do not know dactylology or sign language. In Ecuador, people with this disability are indifferent from certain technology, which reduces their communication possibilities. Due to this, the use of a kit that helps in the learning of sign language is proposed. Through preliminary interviews and literature review, guidelines were obtained on how the kit should be designed. Thus, the proposed kit consists of a glove linked by Bluetooth to a mobile application. The prototype built initially allows the learning of the alphabet and the formation of basic words of the Ecuadorian sign language. With this prototype an evaluation was carried out with adults, to get an opinion of the didactic kit. The results obtained were mostly positive, which allows speculating that such a kit could help in the learning of sign language., Las dificultades que existen para entablar un diálogo con personas sordas son muchas debido a que una gran cantidad de personas no conocen la dactilología o lenguaje de señas. En Ecuador, las personas con esta discapacidad están apartadas de ciertas tecnologías lo que disminuye sus posibilidades de comunicación. Debido a esto, se propone la utilización de un kit que ayude en el aprendizaje del lenguaje de señas. Mediante entrevistas preliminares y revisión bibliográfica se obtuvieron lineamientos sobre cómo se debería diseñar el kit. Así, el kit propuesto está compuesto de un guante vinculado por Bluetooth a una aplicación móvil. El prototipo construido permite inicialmente el aprendizaje del abecedario y la formación de palabras básicas del lenguaje de señas ecuatoriano. Con este prototipo se realizó una evaluación con personas adultas, para llegar a obtener una opinión del kit didáctico. Los resultados obtenidos fueron en su mayoría positivos, lo cual permite especular que un kit de este tipo podría ayudar en el aprendizaje de lenguaje de señas.

It has been more than a year since the coronavirus (COVID-19) engulfed the whole world, disturbing the daily routine, bringing down the economies, and killing two million people across the globe at the time of writing. The pandemic brought the world together to a joint effort to find a cure and work toward developing a vaccine. Much to the anticipation, the first batch of vaccines started rolling out by the end of 2020, and many countries began the vaccination drive early on while others still waiting in anticipation for a successful trial. Social media, meanwhile, was bombarded with all sorts of both positive and negative stories of the development and the evolving coronavirus situation. Many people were looking forward to the vaccines, while others were cautious about the side-effects and the conspiracy theories resulting in mixed emotions. This study explores users's tweets concerning the COVID-19 vaccine and the sentiments expressed on Twitter. It tries to evaluate the polarity trend and a shift since the start of the coronavirus to the vaccination drive across six countries. The findings suggest that people of neighboring countries have shown quite a similar attitude regarding the vaccination in contrast to their different reactions to the coronavirus outbreak.

The introduction of artificial intelligence techniques in the retail market is making a revolution in shopping experience. It allows shoppers to walk into a store, grab what they want and simply walk out without scanning barcodes or having to stand in long queues. That is what we call cashierless stores. In this project, it aims to provide an efficient solution to the automatic retail product identification. This solution presents an artifact one can use to build an end-to-end smart system for cashierless stores. Henceforth, a solution based on text classification is proposed to recognize and identify the products. For that, deep learning techniques are used such as RNN and LSTM to build the classifier. The performance of this classifier is evaluated using various metrics and it shows its efficiency with an accuracy exceeding 86%.

It has been more than a year since the coronavirus (COVID-19) engulfed the whole world, disturbing the daily routine, bringing down the economies, and killing two million people across the globe at the time of writing. The pandemic brought the world together to a joint effort to find a cure and work toward developing a vaccine. Much to the anticipation, the first batch of vaccines started rolling out by the end of 2020, and many countries began the vaccination drive early on while others still waiting in anticipation for a successful trial. Social media, meanwhile, was bombarded with all sorts of both positive and negative stories of the development and the evolving coronavirus situation. Many people were looking forward to the vaccines, while others were cautious about the side-effects and the conspiracy theories resulting in mixed emotions. This study explores users's tweets concerning the COVID-19 vaccine and the sentiments expressed on Twitter. It tries to evaluate the polarity trend and a shift since the start of the coronavirus to the vaccination drive across six countries. The findings suggest that people of neighboring countries have shown quite a similar attitude regarding the vaccination in contrast to their different reactions to the coronavirus outbreak.

It is quite well known how important our sense of vision is on the course of our daily lives. And as for people who are visually impaired must resort to some kind of counter measures such as a cane or a walking stick to cope with their daily activities. But such solutions are not accurate let alone be perfect. In this paper there are various presentations which are sophisticated yet simple contraption which exactly meets the above-mentioned needs, which is accuracy, using an ultrasonic sensor latched up on a glove and functioning with the help of a microcontroller. Upon receiving input from the microcontroller, the vibrator and buzzer notify the person wearing the glove if an obstacle has been detected with the help of the glove.

The introduction of artificial intelligence techniques in the retail market is making a revolution in shopping experience. It allows shoppers to walk into a store, grab what they want and simply walk out without scanning barcodes or having to stand in long queues. That is what we call cashierless stores. In this project, it aims to provide an efficient solution to the automatic retail product identification. This solution presents an artifact one can use to build an end-to-end smart system for cashierless stores. Henceforth, a solution based on text classification is proposed to recognize and identify the products. For that, deep learning techniques are used such as RNN and LSTM to build the classifier. The performance of this classifier is evaluated using various metrics and it shows its efficiency with an accuracy exceeding 86%.

It has been more than a year since the coronavirus (COVID-19) engulfed the whole world, disturbing the daily routine, bringing down the economies, and killing two million people across the globe at the time of writing. The pandemic brought the world together to a joint effort to find a cure and work toward developing a vaccine. Much to the anticipation, the first batch of vaccines started rolling out by the end of 2020, and many countries began the vaccination drive early on while others still waiting in anticipation for a successful trial. Social media, meanwhile, was bombarded with all sorts of both positive and negative stories of the development and the evolving coronavirus situation. Many people were looking forward to the vaccines, while others were cautious about the side-effects and the conspiracy theories resulting in mixed emotions. This study explores users's tweets concerning the COVID-19 vaccine and the sentiments expressed on Twitter. It tries to evaluate the polarity trend and a shift since the start of the coronavirus to the vaccination drive across six countries. The findings suggest that people of neighboring countries have shown quite a similar attitude regarding the vaccination in contrast to their different reactions to the coronavirus outbreak.

The difficulties that exist to establish a dialogue with deaf people are many due to the fact that a large number of people do not know dactylology or sign language. In Ecuador, people with this disability are indifferent from certain technology, which reduces their communication possibilities. Due to this, the use of a kit that helps in the learning of sign language is proposed. Through preliminary interviews and literature review, guidelines were obtained on how the kit should be designed. Thus, the proposed kit consists of a glove linked by Bluetooth to a mobile application. The prototype built initially allows the learning of the alphabet and the formation of basic words of the Ecuadorian sign language. With this prototype an evaluation was carried out with adults, to get an opinion of the didactic kit. The results obtained were mostly positive, which allows speculating that such a kit could help in the learning of sign language., Las dificultades que existen para entablar un diálogo con personas sordas son muchas debido a que una gran cantidad de personas no conocen la dactilología o lenguaje de señas. En Ecuador, las personas con esta discapacidad están apartadas de ciertas tecnologías lo que disminuye sus posibilidades de comunicación. Debido a esto, se propone la utilización de un kit que ayude en el aprendizaje del lenguaje de señas. Mediante entrevistas preliminares y revisión bibliográfica se obtuvieron lineamientos sobre cómo se debería diseñar el kit. Así, el kit propuesto está compuesto de un guante vinculado por Bluetooth a una aplicación móvil. El prototipo construido permite inicialmente el aprendizaje del abecedario y la formación de palabras básicas del lenguaje de señas ecuatoriano. Con este prototipo se realizó una evaluación con personas adultas, para llegar a obtener una opinión del kit didáctico. Los resultados obtenidos fueron en su mayoría positivos, lo cual permite especular que un kit de este tipo podría ayudar en el aprendizaje de lenguaje de señas.

It has been more than a year since the coronavirus (COVID-19) engulfed the whole world, disturbing the daily routine, bringing down the economies, and killing two million people across the globe at the time of writing. The pandemic brought the world together to a joint effort to find a cure and work toward developing a vaccine. Much to the anticipation, the first batch of vaccines started rolling out by the end of 2020, and many countries began the vaccination drive early on while others still waiting in anticipation for a successful trial. Social media, meanwhile, was bombarded with all sorts of both positive and negative stories of the development and the evolving coronavirus situation. Many people were looking forward to the vaccines, while others were cautious about the side-effects and the conspiracy theories resulting in mixed emotions. This study explores users's tweets concerning the COVID-19 vaccine and the sentiments expressed on Twitter. It tries to evaluate the polarity trend and a shift since the start of the coronavirus to the vaccination drive across six countries. The findings suggest that people of neighboring countries have shown quite a similar attitude regarding the vaccination in contrast to their different reactions to the coronavirus outbreak.

It has been more than a year since the coronavirus (COVID-19) engulfed the whole world, disturbing the daily routine, bringing down the economies, and killing two million people across the globe at the time of writing. The pandemic brought the world together to a joint effort to find a cure and work toward developing a vaccine. Much to the anticipation, the first batch of vaccines started rolling out by the end of 2020, and many countries began the vaccination drive early on while others still waiting in anticipation for a successful trial. Social media, meanwhile, was bombarded with all sorts of both positive and negative stories of the development and the evolving coronavirus situation. Many people were looking forward to the vaccines, while others were cautious about the side-effects and the conspiracy theories resulting in mixed emotions. This study explores users's tweets concerning the COVID-19 vaccine and the sentiments expressed on Twitter. It tries to evaluate the polarity trend and a shift since the start of the coronavirus to the vaccination drive across six countries. The findings suggest that people of neighboring countries have shown quite a similar attitude regarding the vaccination in contrast to their different reactions to the coronavirus outbreak.

It is quite well known how important our sense of vision is on the course of our daily lives. And as for people who are visually impaired must resort to some kind of counter measures such as a cane or a walking stick to cope with their daily activities. But such solutions are not accurate let alone be perfect. In this paper there are various presentations which are sophisticated yet simple contraption which exactly meets the above-mentioned needs, which is accuracy, using an ultrasonic sensor latched up on a glove and functioning with the help of a microcontroller. Upon receiving input from the microcontroller, the vibrator and buzzer notify the person wearing the glove if an obstacle has been detected with the help of the glove.

The human brain integrates tactile sensory information from the fingertips to efficiently manipulate objects. Sensory impairments due to neurological disorders, e.g. stroke, largely reduce hand dexterity and the ability to perform daily living activities. Several feedback augmentation techniques have been investigated for rehabilitative purposes with promising outcomes. However, they often require the use of unpractical, expensive, or complex devices. In this work we propose the delivery of vibrotactile feedback based on the Discrete Event-driven Sensory feedback Control (DESC)to promote motor learning in post stroke rehabilitation. For this purpose, we prototyped a novel wearable device, namely the DESC glove. It consisted of a soft glove instrumented with PolyVinylidene Fluoride (PVDF) sensors at the fingertips and eccentric-mass vibration actuators to be worn on the forearm. We proceeded with the characterization of the device, which resulted in promising outcomes. The DESC glove was tested with ten healthy participants subsequently in a pick and lift timed task. The effects of augmented vibrotactile feedback were assessed comparing it to a baseline, consisting of wearing the device unpowered. The results of this pilot study showed a decrease in the time necessary to perform the task, a reduction in the time delay from load force to grip force activation and a diminishing of the grip force applied on the object, which led to a lower breakage rate in the intervention condition. These promising outcomes encourage further experiments with stroke survivors to validate the effectiveness of the device to improve hand dexterity and promote stroke rehabilitation., DESC glove, Biomedical Engineering

This thesis investigates how to remove personal data from logs using machine learning when rule-based scripts are not enough and manual scanning is too extensive. Three types of machine learning models were created and compared. One word model using logistic regression, another word model using LSTM and a sentence model also using LSTM. Data logs were cleaned and annotated using rule-based scripts, datasets from various countries and dictionaries from various languages. The created dataset for the sentence based model was imbalanced, and a lite version of data augmentation was applied. A hyperparameter optimization library was used to find the best hyperparameter combination. The models learned the training and the validation set well but did perform worse on the test set consisting of log data from a different server logging other types of data., Detta examensarbete undersöker om det är möjligt att skapa ett program som automatiskt identifierar och tar bort persondata från dataloggar med hjälp av maskinlärning. Att förstå innebörden av vissa ord kräver också kontext: Banan kan syfta på en banan som man kan äta eller en bana som man kan springa på. Kan en maskinlärningsmodell ta nytta av föregående och efterkommande ord i en sekvens av ord för att få en bättre noggrannhet på om ordet är känsligt eller ej. Typen av data som förekommer i loggarna kan vara bland annat namn, personnummer, användarnamn och epostadress. För att modellen ska kunna lära sig att känna igen datan krävs det att det finns data som är färdigannoterad med facit i hand. Telefonnummer, personnummer och epostadress kan bara se ut på ett visst sätt och behöver nödvändigtvis ingen maskininlärning för att kunna pekas ut. Kan man skapa en generell modell som fungerar på flera typer av dataloggar utan att använda regelbaserade algoritmer. Resultaten visar att den annoterade datan som användes för träning kan ha skiljt allt för mycket från de loggar som har testats på (osedd data), vilket betyder att modellen inte är bra på att generalisera.

In 2011, the world watched in amazement how IBM’s AI named Watson won at Jeopardy!. Right afterwards, IBM decided to use this power to revolutionize the healthcare system. AI doctors would change everyone’s lives. Sadly, Watson did not revolutionize healthcare. It did not prove to be as useful in reality as was anticipated. How could this happen? In short, IBM started with a very specific use case, then invented a super high-tech solution for it, and then started wondering how it could actually be useful. This example actually illustrates the problem that CrossGuard has. Luckily, CrossGuard’s problem is multiple orders of magnitude smaller than it was for IBM. CrossGuard is a company that has developed a protective glove for so-called Historical European Martial Arts (HEMA), or medieval sword fighting. The glove is called the ProGauntlet. It has been designed to withstand high-impact blows from steel swords repeatedly, to protect the users’ hands from virtually any type of impact during HEMA. Not only do they protect very well, they also let the user move their hands naturally, without restricting the freedom of movement. It is the ultimate HEMA glove, but as the HEMA market is relatively small, CrossGuard wants to make the ProGauntlet useful for other purposes, too. Therefore the aim of this project has been to find the next market for the ProGauntlet. This is where IBM’s example comes in. Just like Watson, the ProGauntlet is a technological solution that is looking for a problem to solve. The initial aim of this project was precisely this: finding another market for the ProGauntlet. The research method consisted of a product analysis, literature research and user research, mainly in the form of interviews. The most promising markets were researched in-depth: ice hockey, field hockey, lacrosse, kendo, Filipino Martial Arts (FMA) and motorcycle riding. Of these, the only people that would benefit from the ProGauntlet (besides HEMA) is a certain niche of the FMA., Strategic Product Design

The human brain integrates tactile sensory information from the fingertips to efficiently manipulate objects. Sensory impairments due to neurological disorders, e.g. stroke, largely reduce hand dexterity and the ability to perform daily living activities. Several feedback augmentation techniques have been investigated for rehabilitative purposes with promising outcomes. However, they often require the use of unpractical, expensive, or complex devices. In this work we propose the delivery of vibrotactile feedback based on the Discrete Event-driven Sensory feedback Control (DESC)to promote motor learning in post stroke rehabilitation. For this purpose, we prototyped a novel wearable device, namely the DESC glove. It consisted of a soft glove instrumented with PolyVinylidene Fluoride (PVDF) sensors at the fingertips and eccentric-mass vibration actuators to be worn on the forearm. We proceeded with the characterization of the device, which resulted in promising outcomes. The DESC glove was tested with ten healthy participants subsequently in a pick and lift timed task. The effects of augmented vibrotactile feedback were assessed comparing it to a baseline, consisting of wearing the device unpowered. The results of this pilot study showed a decrease in the time necessary to perform the task, a reduction in the time delay from load force to grip force activation and a diminishing of the grip force applied on the object, which led to a lower breakage rate in the intervention condition. These promising outcomes encourage further experiments with stroke survivors to validate the effectiveness of the device to improve hand dexterity and promote stroke rehabilitation., DESC glove, Biomedical Engineering

In 2011, the world watched in amazement how IBM’s AI named Watson won at Jeopardy!. Right afterwards, IBM decided to use this power to revolutionize the healthcare system. AI doctors would change everyone’s lives. Sadly, Watson did not revolutionize healthcare. It did not prove to be as useful in reality as was anticipated. How could this happen? In short, IBM started with a very specific use case, then invented a super high-tech solution for it, and then started wondering how it could actually be useful. This example actually illustrates the problem that CrossGuard has. Luckily, CrossGuard’s problem is multiple orders of magnitude smaller than it was for IBM. CrossGuard is a company that has developed a protective glove for so-called Historical European Martial Arts (HEMA), or medieval sword fighting. The glove is called the ProGauntlet. It has been designed to withstand high-impact blows from steel swords repeatedly, to protect the users’ hands from virtually any type of impact during HEMA. Not only do they protect very well, they also let the user move their hands naturally, without restricting the freedom of movement. It is the ultimate HEMA glove, but as the HEMA market is relatively small, CrossGuard wants to make the ProGauntlet useful for other purposes, too. Therefore the aim of this project has been to find the next market for the ProGauntlet. This is where IBM’s example comes in. Just like Watson, the ProGauntlet is a technological solution that is looking for a problem to solve. The initial aim of this project was precisely this: finding another market for the ProGauntlet. The research method consisted of a product analysis, literature research and user research, mainly in the form of interviews. The most promising markets were researched in-depth: ice hockey, field hockey, lacrosse, kendo, Filipino Martial Arts (FMA) and motorcycle riding. Of these, the only people that would benefit from the ProGauntlet (besides HEMA) is a certain niche of the FMA., Strategic Product Design

This thesis investigates how to remove personal data from logs using machine learning when rule-based scripts are not enough and manual scanning is too extensive. Three types of machine learning models were created and compared. One word model using logistic regression, another word model using LSTM and a sentence model also using LSTM. Data logs were cleaned and annotated using rule-based scripts, datasets from various countries and dictionaries from various languages. The created dataset for the sentence based model was imbalanced, and a lite version of data augmentation was applied. A hyperparameter optimization library was used to find the best hyperparameter combination. The models learned the training and the validation set well but did perform worse on the test set consisting of log data from a different server logging other types of data., Detta examensarbete undersöker om det är möjligt att skapa ett program som automatiskt identifierar och tar bort persondata från dataloggar med hjälp av maskinlärning. Att förstå innebörden av vissa ord kräver också kontext: Banan kan syfta på en banan som man kan äta eller en bana som man kan springa på. Kan en maskinlärningsmodell ta nytta av föregående och efterkommande ord i en sekvens av ord för att få en bättre noggrannhet på om ordet är känsligt eller ej. Typen av data som förekommer i loggarna kan vara bland annat namn, personnummer, användarnamn och epostadress. För att modellen ska kunna lära sig att känna igen datan krävs det att det finns data som är färdigannoterad med facit i hand. Telefonnummer, personnummer och epostadress kan bara se ut på ett visst sätt och behöver nödvändigtvis ingen maskininlärning för att kunna pekas ut. Kan man skapa en generell modell som fungerar på flera typer av dataloggar utan att använda regelbaserade algoritmer. Resultaten visar att den annoterade datan som användes för träning kan ha skiljt allt för mycket från de loggar som har testats på (osedd data), vilket betyder att modellen inte är bra på att generalisera.

In this work-in-progress paper we describe our method of combining expert knowledge and RDF graph embeddings to solve for specific downstream tasks such as entity resolution. We show that efficiency gains can be made by choosing the correct gradient descent algorithm and that expert input can lead to the desired results.

[ES] En este trabajo final de grado se ha abordado el estudio y desarrollo de una interfaz de Realidad Aumentada presentada sobre un Head-Up Display, dentro de un sistema para proporcionar a los agentes de bomberos la visualización de imágenes térmicas a través de una cámara infrarroja, controlado mediante gestos de los dedos. Se recopila el proceso realizado desde la búsqueda de información acerca de la tecnología a utilizar hasta los detalles del desarrollo de la interfaz. Se marcan las pautas principales de investigación de cara a una mejora del programa capaz de gestionar el sistema al completo. Además, también se realiza un estudio de alternativas de ordenadores de placa reducida compatible con el uso de dicha interfaz, dado que este tipo de hardware será el núcleo principal del sistema.

Yagmur Koc, Zusammenfassung in deutscher Sprache, Universität Innsbruck, Masterarbeit, 2019, (VLID)4539106

The Sign Language Translator is a glove that translates sign language to text and speech in real time. The glove is outfitted with an Arduino Lilypad, an Accelerometer, Flex Sensors and Contact Sensors. Values from these sensors are sent via bluetooth to an iPhone application which predicts and displays the translated gesture. Through the application, users are able to calibrate the glove and view the translation.Team Advisor: Professor Pooria M. YaghiniDepartment of Electrical Engineering and Computer ScienceWebsite: http://projects.eng.uci.edu/projects/asl-communications-device

[ES] En este trabajo final de grado se ha abordado el estudio y desarrollo de una interfaz de Realidad Aumentada presentada sobre un Head-Up Display, dentro de un sistema para proporcionar a los agentes de bomberos la visualización de imágenes térmicas a través de una cámara infrarroja, controlado mediante gestos de los dedos. Se recopila el proceso realizado desde la búsqueda de información acerca de la tecnología a utilizar hasta los detalles del desarrollo de la interfaz. Se marcan las pautas principales de investigación de cara a una mejora del programa capaz de gestionar el sistema al completo. Además, también se realiza un estudio de alternativas de ordenadores de placa reducida compatible con el uso de dicha interfaz, dado que este tipo de hardware será el núcleo principal del sistema.

Background Unilateral cerebral palsy (CP) is a condition that affects muscle control and function on one side of the body. Children with unilateral CP experience difficulties using their hands together secondary to disturbances that occur in the developing fetal or infant brain. Often, the more affected limb is disregarded. Constraint-induced movement therapy (CIMT) aims to increase use of the more affected upper limb and improve bimanual performance. CIMT is based on two principles: restraining the use of the less affected limb (for example, using a splint, mitt or sling) and intensive therapeutic practice of the more affected limb. Objectives To evaluate the effect of constraint-induced movement therapy (CIMT) in the treatment of the more affected upper limb in children with unilateral CP. Search methods In March 2018 we searched CENTRAL, MEDLINE, Embase, CINAHL, PEDro, OT seeker, five other databases and three trials registers.We also ran citation searches, checked reference lists, contacted experts, handsearched key journals and searched using Google Scholar. Selection criteria Randomised controlled trials (RCTs), cluster-RCTs or clinically controlled trials implemented with children with unilateral CP, aged between 0 and 19 years, where CIMT was compared with a different form of CIMT, or a low dose, high-dose or dose-matched alternative form of upper-limb intervention such as bimanual intervention. Primarily, outcomes were bimanual performance, unimanual capacity and manual ability. Secondary outcomes included measures of self-care, body function, participation and quality of life. Data collection and analysis Two review authors independently screened titles and abstracts to eliminate ineligible studies. Five review authors were paired to extract data and assess risk of bias in each included study. GRADE assessments were undertaken by two review authors. Main results We included 36 trials (1264 participants), published between 2004 and 2018. Sample sizes ranged

Background: In 2011, the Australasian Society for Infectious Diseases (ASID) and the Australian Infection Control Association (AICA), now known as the Australasian College of Infection Prevention and Control (ACIPC), produced a position statement on infection control requirements for preventing and controlling Clostridium difficile infection (CDI) in healthcare settings. Method(s): The statement updated in 2017 to reflect new literature available.The authors reviewed the 2011 position statement and critically appraised new literature published between 2011 and 2017 and relevant current infection control guidelines to identify where new evidence had become available or best practice had changed. Result(s): The position statement was updated incorporating the new findings. A draft version of the updated position statement was circulated for consultation to members of ASID and ACIPC. The authors responded to all comments received and updated the position statement. Conclusion(s): This updated position statement emphasizes the importance of health service organizations having evidence-based infection prevention and control programs and comprehensive antimicrobial stewardship programs, to ensure the risk of C. difficile acquisition, transmission and infection is minimised.Copyright © 2018 Australasian College for Infection Prevention and Control