In een van de laatste decennia van de vijftiende eeuw vond aan de voet van de toen nog Moorse stad Granada een interessant conflict plaats tussen een van de belangrijkste edellieden van het land, een oom van de koning met de naam Enrique Enríquez, en chroniqueur Hernando de Ribera.
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We present a novel architecture for an AI system that allows a priori knowledge to combine with deep learning. In traditional neural networks, all available data is pooled at the input layer. Our alternative neural network is constructed so that partial representations (invariants) are learned in the intermediate layers, which can then be combined with a priori knowledge or with other predictive analyses of the same data. This leads to smaller training datasets due to more efficient learning. In addition, because this architecture allows inclusion of a priori knowledge and interpretable predictive models, the interpretability of the entire system increases while the data can still be used in a black box neural network. Our system makes use of networks of neurons rather than single neurons to enable the representation of approximations (invariants) of the output.
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Het borgen van het eindniveau is in het hbo een actueel en interessant vraagstuk. Wanneer opleidingen kunnen aantonen hoe studenten dit eindniveau binnen hun opleiding behalen, geeft dit het hbo-diploma waarde en biedt dit diploma de student een goede start van een mooie loopbaan. Er is echter ook veel vraag naar helderheid wat afstuderen precies betekent, welke rol onderzoek daarin speelt en wat de eisen zijn die aan een goed afstudeerprogramma worden gesteld. Naar aanleiding van het rapport Vreemde ogen dwingen van de Commissie Externe Validering Examenkwaliteit (2012), heeft de Vereniging Hogescholen een expertgroep samengesteld onder voorzitterschap van Daan Andriessen om een protocol te ontwikkelen dat opleidingen helpt een verantwoord afstudeerprogramma te ontwerpen. Dit artikel presenteert de belangrijkste boodschappen uit het protocol en biedt tevens enkele richtlijnen voor het construeren van beoordelingsformulieren voor afstudeerwerkstukken. We hopen met deze bijdrage opleidingen enkele handvatten te bieden voor het (her)ontwerpen van het afstudeerprogramma en daarmee het borgen van het eindniveau
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This paper introduces a novel distributed algorithm designed to optimize the deployment of access points within Mobile Ad Hoc Networks (MANETs) for better service quality in infrastructure less environments. The algorithm operates based on local, independent execution by each network node, thus ensuring a high degree of scalability and adaptability to changing network conditions. The primary focus is to match the spatial distribution of access points with the distribution of client devices while maintaining strong connectivity to the network root. Using autonomous decision-making and choreographed path-planning, this algorithm bridges the gap between demand-responsive network service provision and the maintenance of crucial network connectivity links. The assessment of the performance of this approach is motivated by using numerical results generated by simulations.
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Introduction The Integrated Recovery Scales (IRS) was developed by the Dutch National Expertise board for routine outcome monitoring with severe mental illnesses. This board aimed to develop a multidimensional recovery measure directed at 1. clinical recovery, 2. physical health, 3. social recovery (work, social contacts, independent living) and 4. existential, personal recovery. The measure had to be short, suited for routine outcome monitoring and present the perspective of both mental health professionals and service users with severe mental illnesses. All aspects are assessed over a period of the pas 6 months. Objectives The objective of this research is validation of the Integral Recovery Scales and to test the revelance for clinical practice and police evaluation. Methods The instrument was tested with 500 individuals with severe mental illnesses (80% individuals with a psychotic disorder), of whom 200 were followed up for 1 year. For the questions concerning clinical recovery, physical health and social recovery mental health care workers conducted semi structured interviews with people living with serious illnesses. The questions concerning personal health were self-rated. We analyzed interrater reliability, convergent and divergent validity and sensitivity to change. Results The instrument has a good validity and is easy to complete for service users and mental health care workers and appropriate for clinical and policy evaluation goals. Conclusions The Integrated Recovery Scales can be a useful instrument for a simple and meaningful routine outcome monitoring. Page: 121
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Introduction F-ACT is a flexible version of Assertive Community Treatment to deliver care in a changing intensity depending on needs of individuals with severe mental illnesses (Van Veldhuizen, 2007). In 2016 a number of the FACT-teams in the Dutch region of Utrecht moved to locations in neighborhoods and started to work as one network team together with neighborhood based facilities in primary care (GP’s) and in the social domain (supported living, social district teams, etc.). This should create better chances on clinical, social and personal recovery of service users. Objectives This study describes the implementation, obstacles and outcomes for service users. The main question is whether this Collaborative Mental Health Care in the Community produces better outcome than regular FACT. Measures include (met/unmet) needs for care, quality of life, clinical, functional and personal recovery, and hospital admission days. Methods Data on care utilization regarding the innovation are compared to regular FACT. Qualitative interviews are conducted to gain insight in the experiences of service users, their family members and mental health care workers. Changes in outcome measures of service users in pilot areas (N=400) were compared to outcomes of users (matched on gender and level of functioning) in regular FACT teams in the period 2015-2018 (total N=800). Results Data-analyses will take place from January to March 2019. Initial analyses point at a greater feeling of holding and safety for service users in the pilot areas and less hospital admission days. Conclusions Preliminary results support the development from FACT to a community based collaborative care service.
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In the aftermath of the systemic financial crises of 2007-9, several scholars argued that the problem of systemic financial crises is not well understood. At the same time, the introduction of digital technologies led to new threats and opportunities for the design of the monetary and financial system. For example, thousands of private cryptocurrencies have been implemented and hundreds of research papers on the (possible) introduction of public digital currencies have been published. It is often not explained why these new forms of digital money are needed and which (systemic) problems they (can) solve. In addition, the literature does not provide requirements nor guidelines to shape the development of the monetary and financial system in the digital age. This thesis applies design science to the monetary and financial system as a whole. The application of this novel methodology offers new possibilities to examine this complex system. The contribution of this thesis is threefold. First, different theories on money, banking and systemic financial crises have been researched through an extensive literature review and balance sheets. Second, those theories have been used to develop design requirements and guidelines. Finally, the consensus and pivotal dissensions about the systemic problem(s) of the current monetary and financial system, requirements and guidelines among experts have been identified through semistructured interviews. This research process results in widely supported requirements that demarcate the design space and widely supported guidelines that aim to give direction within the design space, that is, to the future development of the monetary and financial system.
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From the article: Abstract—By using agent technology, a versatile and modular monitoring system can be built. In this paper, such a multiagentbased monitoring system will be described. The system can be trained to detect several conditions in combination and react accordingly. Because of the distributed nature of the system, the concept can be used in many situations, especially when combinations of different sensor inputs are used. Another advantage of the approach presented in this paper is the fact that every monitoring system can be adapted to specific situations. As a case-study, a health monitoring system will be presented.
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Conference proceedings International Symposium on Intelligent Manufacturing Environments
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Social media platforms such as Facebook, YouTube, and Twitter have millions of users logging in every day, using these platforms for commu nication, entertainment, and news consumption. These platforms adopt rules that determine how users communicate and thereby limit and shape public discourse.2 Platforms need to deal with large amounts of data generated every day. For example, as of October 2021, 4.55 billion social media users were ac tive on an average number of 6.7 platforms used each month per internet user.3 As a result, platforms were compelled to develop governance models and content moderation systems to deal with harmful and undesirable content, including disinformation. In this study: • ‘Content governance’ is defined as a set of processes, procedures, and systems that determine how a given platform plans, publishes, moder ates, and curates content. • ‘Content moderation’ is the organised practice of a social media plat form of pre-screening, removing, or labelling undesirable content to reduce the damage that inappropriate content can cause.
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