7,385 research outputs found

    Undergraduate Catalog of Studies, 2023-2024

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    Design and implementation of an automatic nursing assessment system based on CDSS technology

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    BACKGROUND: Various quantitative and quality assessment tools are currently used in nursing to evaluate a patient's physiological, psychological, and socioeconomic status. The results play important roles in evaluating the efficiency of healthcare, improving the treatment plans, and lowing relevant clinical risks. However, the manual process of the assessment imposes a substantial burden and can lead to errors in digitalization. To fill these gaps, we proposed an automatic nursing assessment system based on clinical decision support system (CDSS). The framework underlying the CDSS included experts, evaluation criteria, and voting roles for selecting electronic assessment sheets over paper ones.METHODS: We developed the framework based on an expert voting flow to choose electronic assessment sheets. The CDSS was constructed based on a nursing process workflow model. A multilayer architecture with independent modules was used. The performance of the proposed system was evaluated by comparing the adverse events' incidence and the average time for regular daily assessment before and after the implementation.RESULTS: After implementation of the system, the adverse nursing events' incidence decreased significantly from 0.43 % to 0.37 % in the first year and further to 0.27 % in the second year (p-value: 0.04). Meanwhile, the median time for regular daily assessments further decreased from 63 s to 51 s.CONCLUSIONS: The automatic assessment system helps to reduce nurses' workload and the incidence of adverse nursing events.</p

    Developing A Road Freight Transport Performance Measurement System To Drive Sustainability:An Empirical Study Of Egyptian Road Freight Transport Companies

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    While several road freight performance measurement systems have been developed, only a limited number of quantified performance measurement frameworks encompassing diverse sets of performance metrics from multiple sustainable perspectives are available on a technological platform. These sets of metrics could be integrated as crucial performance indicators for assessing the operational performance of various road freight transport companies. These indicators include fuel efficiency, trip duration, vehicle loading, and cargo capacity. The objective of this research is to construct a conceptual road freight performance measurement framework that comprehensively incorporates performance elements from sustainable viewpoints (economic, environmental, and social), leveraging technology to measure the performance of road freight transport companies. This proposed framework aims to aid these companies in gauging their performance using technology, thus enhancing their operations towards sustainability.Within the road freight transport sector, several challenges exist, with congestion, road infrastructure maintenance, and driver training and qualifications being particularly pressing issues. The developed performance measurement framework offers the means for companies to evaluate the effects of technology integration on vehicles and overall performance. This allows companies to measure their performance from an operational standpoint rather than solely a strategic one, thereby identifying areas requiring improvement. Egypt was chosen as the empirical study location due to its relatively low level of technological integration within its road freight sector.This thesis employs an explanatory mixed methods approach, encompassing four distinct phases. The first phase entails a review to formulate the proposed theoretical performance measurement framework. Subsequently, the second phase involves conducting semi-structured interviews using a Delphi method to both develop a conceptual performance measurement framework and explore the present state of Egypt's road freight transport sector. Following this, the third phase encompasses surveys based on the results derived from Delphi analysis, involving diverse participants from the road freight transport industry. The aim is to validate the developed performance measurement framework through an empirical study conducted in Egypt. Lastly, the fourth phase centres around organizing focus groups involving stakeholders within road freight transport companies. The goal here is to propose a roadmap for implementing the developed road freight transport performance measurement framework within the Egyptian context.The primary theoretical contribution of this research is the development of a road freight transport performance measurement framework that integrates the three sustainability dimensions with technology. Additionally, this study offers practical guidance for the application of the developed framework in various countries and contexts. From a practical standpoint, this research aids road freight transport managers in evaluating their operational performance, thereby identifying challenges, devising action plans, and making informed decisions to mitigate these issues and enhance sustainability-oriented performance. Ultimately, the developed road freight transport performance measurement framework is poised to promote performance measurement aligned with technology, fostering progress towards achieving the sustainable development goals by 2030

    Graduate Catalog of Studies, 2023-2024

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    A Trust Management Framework for Vehicular Ad Hoc Networks

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    The inception of Vehicular Ad Hoc Networks (VANETs) provides an opportunity for road users and public infrastructure to share information that improves the operation of roads and the driver experience. However, such systems can be vulnerable to malicious external entities and legitimate users. Trust management is used to address attacks from legitimate users in accordance with a user’s trust score. Trust models evaluate messages to assign rewards or punishments. This can be used to influence a driver’s future behaviour or, in extremis, block the driver. With receiver-side schemes, various methods are used to evaluate trust including, reputation computation, neighbour recommendations, and storing historical information. However, they incur overhead and add a delay when deciding whether to accept or reject messages. In this thesis, we propose a novel Tamper-Proof Device (TPD) based trust framework for managing trust of multiple drivers at the sender side vehicle that updates trust, stores, and protects information from malicious tampering. The TPD also regulates, rewards, and punishes each specific driver, as required. Furthermore, the trust score determines the classes of message that a driver can access. Dissemination of feedback is only required when there is an attack (conflicting information). A Road-Side Unit (RSU) rules on a dispute, using either the sum of products of trust and feedback or official vehicle data if available. These “untrue attacks” are resolved by an RSU using collaboration, and then providing a fixed amount of reward and punishment, as appropriate. Repeated attacks are addressed by incremental punishments and potentially driver access-blocking when conditions are met. The lack of sophistication in this fixed RSU assessment scheme is then addressed by a novel fuzzy logic-based RSU approach. This determines a fairer level of reward and punishment based on the severity of incident, driver past behaviour, and RSU confidence. The fuzzy RSU controller assesses judgements in such a way as to encourage drivers to improve their behaviour. Although any driver can lie in any situation, we believe that trustworthy drivers are more likely to remain so, and vice versa. We capture this behaviour in a Markov chain model for the sender and reporter driver behaviours where a driver’s truthfulness is influenced by their trust score and trust state. For each trust state, the driver’s likelihood of lying or honesty is set by a probability distribution which is different for each state. This framework is analysed in Veins using various classes of vehicles under different traffic conditions. Results confirm that the framework operates effectively in the presence of untrue and inconsistent attacks. The correct functioning is confirmed with the system appropriately classifying incidents when clarifier vehicles send truthful feedback. The framework is also evaluated against a centralized reputation scheme and the results demonstrate that it outperforms the reputation approach in terms of reduced communication overhead and shorter response time. Next, we perform a set of experiments to evaluate the performance of the fuzzy assessment in Veins. The fuzzy and fixed RSU assessment schemes are compared, and the results show that the fuzzy scheme provides better overall driver behaviour. The Markov chain driver behaviour model is also examined when changing the initial trust score of all drivers

    Graduate Catalog of Studies, 2023-2024

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    Multidisciplinary perspectives on Artificial Intelligence and the law

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    This open access book presents an interdisciplinary, multi-authored, edited collection of chapters on Artificial Intelligence (‘AI’) and the Law. AI technology has come to play a central role in the modern data economy. Through a combination of increased computing power, the growing availability of data and the advancement of algorithms, AI has now become an umbrella term for some of the most transformational technological breakthroughs of this age. The importance of AI stems from both the opportunities that it offers and the challenges that it entails. While AI applications hold the promise of economic growth and efficiency gains, they also create significant risks and uncertainty. The potential and perils of AI have thus come to dominate modern discussions of technology and ethics – and although AI was initially allowed to largely develop without guidelines or rules, few would deny that the law is set to play a fundamental role in shaping the future of AI. As the debate over AI is far from over, the need for rigorous analysis has never been greater. This book thus brings together contributors from different fields and backgrounds to explore how the law might provide answers to some of the most pressing questions raised by AI. An outcome of the Católica Research Centre for the Future of Law and its interdisciplinary working group on Law and Artificial Intelligence, it includes contributions by leading scholars in the fields of technology, ethics and the law.info:eu-repo/semantics/publishedVersio

    From abuse to trust and back again

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