Auflistung nach Autor:in "Filipe, Joaquim"

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    Publikation
    Adaptable GDPR assessment tool for micro and small enterprises
    (SciTePress, 2022) Löffler, Emanuel; Schneider, Bettina; Goerre, Andreas; Asprion, Petra; Filipe, Joaquim; Smialek, Michal; Brodsky, Alexander; Hammoudi, Slimane [in: Proceedings of the 24th International Conference on Enterprise Information Systems]
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    Publikation
    Augmented feedback system to support physical therapy of non-specific low back pain
    (Springer, 2010) Brodbeck, Dominique; Degen, Markus; Stanimirov, Michael; Kool, Jan; Scheermesser, Mandy; Oesch, Peter; Neuhaus, Cornelia; Fred, Ana; Filipe, Joaquim; Gamboa, Hugo [in: Biomedical Engineering Systems and Technologies]
    Low back pain is an important problem in industrialized countries. Two key factors limit the effectiveness of physiotherapy: low compliance of patients with repetitive movement exercises, and inadequate awareness of patients of their own posture. The Backtrainer system addresses these problems by real-time monitoring of the spine position, by providing a framework for most common physiotherapy exercises for the low back, and by providing feedback to patients in a motivating way. A minimal sensor configuration was identified as two inertial sensors that measure the orientation of the lower back at two points with three degrees of freedom. The software was designed as a flexible platform to experiment with different hardware, and with various feedback modalities. Basic exercises for two types of movements are provided: mobilizing and stabilizing. We developed visual feedback - abstract as well as in the form of a virtual reality game - and complemented the on-screen graphics with an ambient feedback device. The system was evaluated during five weeks in a rehabilitation clinic with 26 patients and 15 physiotherapists. Subjective satisfaction of subjects was good, and we interpret the results as encouraging indication for the adoption of such a therapy support system by both patients and therapists.
    04B - Beitrag Konferenzschrift
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    Publikation
    Case model for the RoboInnoCase recommender system for cases of digital business transformation: structuring information for a case of digital change
    (SciTePress, 2019) Witschel, Hans Friedrich; Peter, Marco; Seiler, Laura; Parlar, Soyhan; Gatziu Grivas, Stella; Bernardino, Jorge; Salgado, Ana; Filipe, Joaquim [in: ICEIS 2019. 21st International Conference on Enterprise Information Systems. Proceedings]
    In this work, we develop a case model to structure cases of past digital transformations which act as input data for a recommender system. The purpose of that recommender is to act as an inspiration and support for new cases of digital transformation. To define the case model, case analyses, where 40 cases of past digital transformations are analysed and coded to determine relevant attributes and values, literature research and the particularities of the case for digital change, are used as a basis. The case model is evaluated by means of an experiment where two different scenarios are fed into a prototypical case-based recommender system and then matched, based on an entropically derived weighting system, with the case base that contains cases structured according to the case model. The results not only suggest that the case model’s functionality can be guaranteed, but that a good quality of the given recommendations is achieved by applying a case-based recommender system using the proposed case model. The results not only suggest that the case model’s functionality can be guaranteed, but that a good quality of the given recommendations is achieved by applying a case-based recommender system using the proposed case model.
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    Publikation
    Cybersecurity by design for smart home environments
    (2019) Siddhanti, Pragati; Asprion, Petra; Schneider, Bettina; Filipe, Joaquim; Smialek, Michal; Brodsky, Alexander; Hammoudi, Slimane [in: ICEIS 2019. 21st International Conference on Enterprise Information Systems. Proceedings]
    The Internet of Things (IoT) is being increasingly adopted by businesses to improve operations, processes, and products. While it opens endless opportunities, it also presents tremendous challenges especially in the area of cyber risks and related security controls. With billions of interconnected devices worldwide, how do we ensure that they are sufficiently secure and resilient? As a reasonable solution, ‘Cybersecurity by Design’ seems a promising approach. In this research, ‘Smart Homes’ - as IoT containing products – are selected as unit of analysis because they are exposed to numerous cyber threats with corresponding adverse consequences for the life, safety and health of residents. By aiming to secure Smart Home Environments (SHEs) from cyber threats, we adopted ‘design science’ as methodology and developed a holistic approach, highlighting ‘good practices’, which can be applied in every phase of the SHEs product lifecycle. In addition to these good practices, a ‘Cyber Security Maturity Assessment’ tool for SHEs has been developed. Both artefacts have already been validated and incrementally improved, and are now awaiting their future application and further enhancements.
    04B - Beitrag Konferenzschrift
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    Publikation
    Enhance classroom preparation for flipped classroom using AI and analytics
    (SciTePress, 2018) Diwanji, Prajakta; Hinkelmann, Knut; Witschel, Hans Friedrich; Hammoudi, Slimane; Smialek, Michal; Camp, Olivier; Filipe, Joaquim [in: ICEIS 2018. 20th International Conference on Enterprise Information Systems. Proceedings]
    In a flipped classroom setting, it is important for students to come prepared for the classroom. Being prepared in advance helps students to grasp the concepts taught during classroom sessions. A recent student survey at Fachhochschule Nordwestschweiz (FHNW), Business School, Switzerland, revealed that only 27.7% students often prepared before a class and only 7% always prepared before a class. The main reason for not preparing for classes was lack of time and workload. A literature review study revealed that there is a growth of the use of Artificial Intelligence (AI), for example, chatbots and teaching assistants, which support both teachers and students for classroom preparation. There is also a rise in the use of data analytics to support tutor decision making in real time. However, many of these tools are based on external motivation factors like grading and assessment. Intrinsic motivation among students is more rewarding in the long term. This paper proposes an application based on AI and data analysis that focuses on intrinsically motivating and preparing students in a flipped classroom approach.
    04B - Beitrag Konferenzschrift
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    Publikation
    Enterprise maps: zooming in and out of enterprise models
    (SciTePress, 2022) Spahic, Maja; Hinkelmann, Knut; Filipe, Joaquim; Smialek, Michal; Brodsky, Alexander; Hammoudi, Slimane [in: Proceedings of the 24th International Conference on Enterprise Information Systems]
    A company’s architecture can be represented by domain-specific models, which are defined by domain-specific modeling language. Since not all stakeholders are interested in the same models, dedicated views can be created to support navigation through the enterprise models. These views offer a snippet of the entire company and cover stakeholder-specific concerns. The relationships between the different views and models remain hidden and can be unveiled with much effort. The developed concept of the zoomability principle offers the ability to change the degree of detail using zoom in and out of the enterprise model. The different models and modeling languages used to express an enterprise are considered, and a form of navigation is established similar to an online map. The concept is based on two pillars,”Zoom Within” and”Zoom into Complements”. For this purpose, a metamodel was developed, which formalizes the elements used in the concept and their relationships. Developing the artifact, rules were defined that contribute to a generic approach allowing an application to another case. Furthermore, a prototype was developed, representing the zoomability principle and offering the possibility to perform zooming behavior. The artifact was evaluated through a demonstration. An additional prototype was created to demonstrate that the developed concept can be applied to a predefined set of situations.
    04B - Beitrag Konferenzschrift
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    Publikation
    Human-centered artificial intelligence: a multidimensional approach towards real world evidence
    (2019) Schneider, Bettina; Asprion, Petra; Grimberg, Frank; Filipe, Joaquim; Smialek, Michal; Brodsky, Alexander; Hammoudi, Slimane [in: ICEIS 2019. 21st International Conference on Enterprise Information Systems. Proceedings]
    This study indicates the significance of a human-centered perspective in the analysis and interpretation of Real World Data. As an exemplary use-case, the construct of perceived ‘Health-related Quality of Life’ is chosen to show, firstly, the significance of Real World Data and, secondly, the associated ‘Real World Evidence’. We settled on an iterative methodology and used hermeneutics for a detailed literature analysis to outline the relevance and the need for a forward-thinking approach to deal with Real World Evidence in the life science and health care industry. The novelty of the study is its focus on a human-centered artificial intelligence, which can be achieved by using ‘System Dynamics’ modelling techniques. The outcome – a human-centered ‘Indicator Set’ can be combined with results from data-driven, AI-based analytics. With this multidimensional approach, human intelligence and artificial intelligence can be intertwined towards an enriched Real World Evidence. The developed approach considers three perspectives – the elementary, the algorithmic and – as novelty – the human-centered evidence. As conclusion, we claim that Real World Data are more valuable and applicable to achieve patient-centricity and personalization if the human-centered perspective is considered ‘by design’.
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    Natural language-based user guidance for knowledge graph exploration: a user study
    (SciTePress, 2021) Witschel, Hans Friedrich; Riesen, Kaspar; Grether, Loris; Cucchiara, Rita; Fred, Ana; Filipe, Joaquim [in: Proceedings of the 13th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management]
    Large knowledge graphs hold the promise of helping knowledge workers in their tasks by answering simple and complex questions in specialised domains. However, searching and exploring knowledge graphs in current practice still requires knowledge of certain query languages such as SPARQL or Cypher, which many untrained end users do not possess. Approaches for more user-friendly exploration have been proposed and range from natural language querying over visual cues up to query-by-example mechanisms, often enhanced with recommendation mechanisms offering guidance. We observe, however, a lack of user studies indicating which of these approaches lead to a better user experience and optimal exploration outcomes. In this work, we make a step towards closing this gap by conducting a qualitative user study with a system that relies on formulating queries in natural language and providing answers in the form of subgraph visualisations. Our system is able to offer guidance via query recommendations based on a current context. The user study evaluates the impact of this guidance in terms of both efficiency and effectiveness (recall) of user sessions. We find that both aspects are improved, especially since query recommendations provide inspiration, leading to a larger number of insights discovered in roughly the same time.
    04B - Beitrag Konferenzschrift
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    Publikation
    Random walks on human knowledge: incorporating human knowledge into data-driven recommenders
    (2018) Witschel, Hans Friedrich; Martin, Andreas; Bernardino, Jorge; Salgado, Ana; Filipe, Joaquim [in: IC3K 2018. 10th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management. Proceedings]
    We explore the use of recommender systems in business scenarios such as consultancy. In these situations, apart from personal preferences of users, knowledge about objective business-driven criteria plays a role. We investigate strategies for representing and incorporating such knowledge into data-driven recommenders. As a baseline, we choose a robust and flexible paradigm that is based on a simple graph-based representation of past customer cases and choices, in combination with biased random walks. On a real data set from a business intelligence consultancy firm, we study how the incorporation of two important types of explicit human knowledge – namely taxonomic and associative knowledge – impacts the effectiveness of a data-driven recommender. Our results show no consistent improvement for taxonomic knowledge, but quite substantial and significant gains when using associative knowledge.
    04B - Beitrag Konferenzschrift