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Large Language Models for Democratizing Business Process Modeling: BPMN Model Generation and Style Guide Adherence 5th

Large Language Models for Democratizing Business Process Mod...

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5th Southern African Conference for Artificial Intelligence Research

作者： Wenger, Seline Spahic-Bogdanovic, Maja Martin, Andreas FHNW Univ Appl Sci & Arts Northwestern Switzerlan Sch Business Riggenbachstrasse 16 CH-4600 Olten Switzerland Univ Camerino Via Madonna Carceri 9 I-62032 Camerino MC Italy

ISBN: (纸本)9783031782541;9783031782558

Business Process Management (BPM) is important for organizations, with process modeling being a key component. However, creating accurate and consistent models is challenging and time-consuming. As large language models (LLMs) offer potential solutions, this article explores using LLMs to generate business process models that follow company internal style guides. Interviews with process engineers at a company provided insights into current practices and challenges. A prototype using OpenAI's GPT-4 API was developed based on these insights. This tool enables non-experts to generate business process models in BPMN 2.0 notation through a user-friendly interface. Evaluation using the PET dataset demonstrated that the LLM-generated models are comparable to those created by human experts regarding recall and precision.

关键词： Large Language Models Business Process Modeling Business Process Model and Notation Modeling Style Guides Model Generation Business Process Management

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Deep Learning Based Non-invasive Meningitis Screening Using High-Resolution Ultrasound in Neonates and Infants from Mozambique, Spain and Morocco 1st

Deep Learning Based Non-invasive Meningitis Screening Using ...

引用

1st MICCAI Meets Africa Workshop

作者： Jobst, Beatrice M. Carandell, Francesc Ajanovic, Sara Sial, Hassan Jimenez, Javier Quesada, Rita Santos, Fabiao Lopez-Azorin, Manuela Valverde, Eva Ybarra, Marta Bravo, M. Carmen Munoz, David Agut, Thais Salas, Barbara Carreras, Nuria Alarcon, Ana Iriondo, Martin Luaces, Carles Sidat, Muhammad Zandamela, Mastalina Rodrigues, Paula Martins, Luzidina Cassia, Uneisse Bramugy, Justina Cossa, Anelsio Mucasse, Campos Buck, W. Chris Arias, Sara El Abbass, Chaymae Tligui, Houssain Barkat, Amina Amalik, Najat Zizi, Imane Ibanez, Alberto Parrilla, Montserrat Elvira, Luis Calvo, Cristina Pellicer, Adelina Cabanas, Fernando Bassat, Quique Petrone, Paula Kriba Barcelona Sci Pk Barcelona 08028 Spain Univ Barcelona Hosp Clin Barcelona Inst Global Hlth ISGlobal Barcelona 08036 Spain Barcelona Inst Global Hlth ISGlobal Biomed Data Sci Team Barcelona 08003 Spain Quironsalud Madrid Univ Hosp Dept Pediat & Neonatol Madrid 28223 Spain Hosp La Paz Inst Hlth Res La Paz Univ Hosp IdiPaz Dept Neonatol Madrid 28046 Spain Univ Barcelona Emergency Dept St Joan Deu Hosp Inst Recerca St Joan Deu Barcelona 08950 Spain Univ Barcelona Dept Neonatol St Joan Deu Hosp Inst Recerca St Joan Deu Barcelona 08950 Spain Univ Eduardo Mondlane Fac Med Maputo 257 Mozambique CISM Manhica 1929 Mozambique Maputo Cent Hosp Maputo 1100 Maputo Mozambique Hosp Geral Mavalane Maputo 1100 Mozambique Univ Calif Los Angeles David Geffen Sch Med Los Angeles CA 90095 USA Ctr Hosp Univ Ibn Sina Hop Enfants Ctr Natl Reference Neonatol & Nutr Rabat 6527 Morocco Univ Mohammed V Rabat Equipe Rech Sante & Nutr Couple Mere Enfant Fac Med & Pharm Rabat 6203 Morocco Inst Tecnol Fis & Informac CSIC Madrid 28006 Spain La Paz Univ Hosp Fdn IdiPaz Pediat & Infect Dis Dept Madrid 28046 Spain Carlos III Hlth Inst Biomed Res Network Ctr Infect Dis CIBERINFEC Madrid 28029 Spain Translat Res Network Pediat Infect Dis RITIP Madrid 28046 Spain Univ Autonoma Madrid Madrid 28049 Spain La Paz Univ Hosp IDIPAZ Biomed Res Fdn Madrid 28046 Spain ICREA Barcelona 08010 Spain Univ Barcelona Dept Pediat Hosp St Joan Deu Barcelona 08950 Spain Carlos III Hlth Inst CIBER Epidemiol & Publ Hlth Madrid 28029 Spain

ISBN: (纸本)9783031791024;9783031791031

Meningitis is a life-threatening disease, resulting in severe neurological damage or death if not treated in time. The standard diagnostic method is an invasive lumbar puncture (LP), not exempt of complications and not always feasible, especially in resource-poor settings. To overcome these challenges, we developed Neosonics (R), a novel non-invasive high-resolution ultrasound (HRUS) technology that detects backscatter signals from white blood cells (WBCs) in cerebrospinal fluid (CSF) below the infant fontanel. Using deep learning (DL) for image analysis, this technology classifies patients based on WBC levels, providing a rapid, non-invasive screening method for infant meningitis and with this, limiting indications for LPs for positive cases only, if not contraindicated. A convolutional neural network was trained and validated using CSF HRUS patient data gathered from cohorts from three different countries, Mozambique, Spain and Morocco. Then, a soft voting ensemble-learning technique was applied to give a classification on a patient-level. The DL model showed on a single-image level a sensitivity (SE) and specificity (SP) of 71.1% and 87.0% for the Mozambican cohort, SE= 73.3% and SP = 75.5% for the Spanish cohort, and SE = 72.0% and SP = 88.7% for the Moroccan cohort. On a patient-level, the overall SE and SP was 94.4% and 94.8%, respectively. We demonstrate in this study the significance of combining HRUS and DL for the non-invasive detection of infant meningitis, offering an efficient, cost-effective solution suitable also for limited resource settings and remote areas.

关键词： Neonatal and Infant Meningitis High-Resolution Ultrasound Deep Learning

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A Multi-objective Genetic Algorithm Approach for Multi-component Products Recovery and Remanufacturing Planning 5th

A Multi-objective Genetic Algorithm Approach for Multi-compo...

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5th International Conference on Innovative Intelligent Industrial Production and Logistics

作者： Belhocine, Latifa Dahane, Mohammed Yagouni, Mohammed Univ Lorraine LGIPM F-57000 Metz France USTHB LaROMAD Algiers Algeria

ISBN: (纸本)9783031807596;9783031807602

The remanufacturing process has gained recognition primarily for its effectiveness in addressing environmental concerns related to End-Of-Life (EOL) and End-Of-Use (EOU) products. Consequently, a growing number of companies specialise in remanufacturing various product types. This practice not only prolongs product lifespan but also reduces manufacturing costs. This paper examines the challenges encompassing all stages of the remanufacturing process: product recovery, transportation, and remanufacturing operations for customers with similar product types over a finite horizon. The problem involves planning the recovery of used products for remanufacturing and grade enhancement. The main decisions include selecting customers for product recovery and replacement, optimising transportation for used product retrieval, and making decisions for the post-remanufacturing grade. The objective is to minimise both economic and environmental costs. To address this, we propose an NSGA-II (Non-dominated Sorting Genetic Algorithm) based multi-objective solution approach to tackle this problem.

关键词： Remanufacturing Electronic products reconditioning Multi-components products Product performance Multi-objective NSGA-II

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Turkish Legal Single-Document Summarizing 2nd

Turkish Legal Single-Document Summarizing

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2nd International Conference on information Technologies and Their Applications

作者： Albayati, Maha Ahmed Abdullah Findik, Oguz Karabuk Univ TR-78000 Karabuk Turkiye

ISBN: (纸本)9783031734199;9783031734205

Text summarization is the compression of source text into a condensed version while preserving the information content and overall meaning. Due to the large amount of information research, articles, documents, books, etc., and the development of Internet technologies, text summarization has become an important tool by extracting the most important parts and clarifying the basic purpose of the text. It is very necessary for lawyers and ordinary citizens to conduct thorough research related to their case before answering questions in court. For some time, they had to read very long rulings and try to pick out useful information from them or hire legal editors to create summaries. Due to the lack of research related to summarizing Turkish legal texts, we propose an automated text summarization system by using two novel hybrid pretrained approach models. Our new dataset is collected from official government sites that included Supreme Court, high court and district court cases. We achieved satisfactory results according to the legal professionals (lawyers) evaluation and rouge evaluation metrics, our summary text is Readable and understandable even by non-specialized people. In the future, we aim to obtain better summaries and build an application available to everyone, and open the way for further research using the dataset used in our study.

关键词： Turkish legal text summarize pretrained model hyper approach text summarization

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An ISR Asset Planning Application 8th

An ISR Asset Planning Application

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2024 World Congress in computer science, computer Engineering and Applied Computing-CSCE

作者： Mueller, Wilmuth Reinert, Frank Pfirrmann, Uwe Sander, Jennifer Fraunhofer IOSB Fraunhoferstr 1 D-76131 Karlsruhe Germany

ISBN: (纸本)9783031856273;9783031856280

In many reconnaissance and surveillance tasks, the challenge is to deploy a considerable set of assets in the best manner for satisfying a set of given information requirements. The paper at hand presents an approach for an optimal planning of ISR asset deployment in order to satisfy the information needs of a commander. Based on the processes of information requirements management (IRM) and collection management (CM), a two-step approach has been developed. In the first step, an operator assigns to each target on which reconnaissance or surveillance has to be performed a set of suitable assets. The operator may assign the suitable assets to a target either directly, based on his experience and knowledge, or supported by an intelligent multi-agent system, which generates automatically an asset assignment proposal. The multi-agent system consists of three types of intelligent agents, a target agent representing the targets on which reconnaissance or surveillance has to be performed, the asset agents representing the assets available to the operator, and an interface agent responsible for the communication with the other components of the application. In the second step an automatic planning component may be used for computing an optimal asset assignment and execution order. Mathematically, the second step corresponds to an optimization problem under a considerable set of constraints. More precisely, the problem at hand possesses distinctive similarities to certain problem classes considered in the Operations Research domain, in particular to routing problems like Vehicle Routing Problems (VRPs). Thereby, customers in a VRP correspond to information requirements and vehicles in a VRP correspond to assets, here. Using these similarities, we worked out a mathematical formalization for the problem underlying the second step of our approach.

关键词： ISR asset planning intelligent agents multi-agent system optimization problem

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Towards the Automation of the Product Definition Process for Design-to-Order Manufacturing Systems 5th

Towards the Automation of the Product Definition Process for...

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5th International Conference on Innovative Intelligent Industrial Production and Logistics

作者： Beauchemin, Maude Gaudreault, Jonathan Zwingmann, Xavier Lehoux, Nadia Univ Laval Quebec City PQ Canada

ISBN: (纸本)9783031807749;9783031807756

In the last decade, the focus of automation in the manufacturing industry has been on the physical and logical aspects of the production system, supposing the product definition is well known. The steps required to create this product definition (in terms of design, engineering, and industrialization) are still mostly achieved by humans, although making use of the computer-aided tools that compose the CAx chain. This is efficient when the same product is afterward produced thousands of times, making the extensive human labor profitable. However, for design-to-order manufacturing systems, such a methodology suffers from long lead times and exorbitant costs directly transferred to the client. Industrial visits and discussions with design-to-order manufacturers followed by a detailed modelization of their current manufacturing processes led us to target the need for automation of the product definition process. We propose a new approach focusing on product families defined by data and algorithms which encapsulate product family semantics. This approach allows clients to generate their own personalized product definitions from this family in a few clicks. Our approach is currently implemented in SMEs from different industries, ranging from the construction industry to the medical implant sector, as well as our own research factory producing personalized micro-trailers.

关键词： Design-to-order Industrialization CAD/CAM Process automation

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Learning and Embodied Decisions in Active Inference 5th

Learning and Embodied Decisions in Active Inference

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5th International Workshop on Active Inference

作者： Priorelli, Matteo Stoianov, Ivilin Peev Pezzulo, Giovanni Natl Res Council Italy Inst Cognit Sci & Technol Rome Italy Natl Res Council Italy Inst Cognit Sci & Technol Padua Italy

ISBN: (纸本)9783031771378;9783031771385

Biological organisms constantly face the necessity to act timely in dynamic environments and balance choice accuracy against the risk of missing valid opportunities. As formalized by embodied decision models, this might require brain architectures wherein decision-making and motor control interact reciprocally, in stark contrast to traditional models that view them as serial processes. Previous studies have assessed that embodied decision dynamics emerge naturally under active inference - a computational paradigm that considers action and perception as subject to the same imperative of free energy minimization. In particular, agents can infer their targets by using their own movements (and not only external sensations) as evidence, i.e., via self-evidencing. Such models have shown that under appropriate conditions, action-generated feedback can stabilize and improve decision processes. However, how adaptation of internal models to environmental contingencies influences embodied decisions is yet to be addressed. To shed light on this challenge, in this study we systematically investigate the learning dynamics of an embodied model of decision-making during a two-alternative forced choice task, using a hybrid (discrete and continuous) active inference framework. Our results show that active inference agents can adapt to embodied contexts by learning various statistical regularities of the task - namely, prior preferences for the correct target, cue validity, and response strategies that prioritize faster or slower (but more accurate) decisions. Crucially, these results illustrate the efficacy of learning discrete preferences and strategies using sensorimotor feedback from continuous dynamics.

关键词： active inference hybrid models embodied decisions motor inference motor learning

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Fine-Tuning and Efficacy Assessment of BERT-Based Models in Detecting Early Signs of Depression 4th

Fine-Tuning and Efficacy Assessment of BERT-Based Models in ...

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4th International Conference on Advanced Network Technologies and Intelligent Computing-ANTIC-Annual

作者： Kumar, Vaibhav Singh, Vibhav Prakash MNNIT Allahabad Dept Comp Sci Prayagraj India

ISBN: (纸本)9783031837920;9783031837937

This study investigates utilizing Bidirectional Encoder Representations from Transformers(BERT) models for detecting depression indicators through text classification. BERT has demonstrated impressive performance in natural language processing tasks like classification and sentiment analysis. The research emphasizes fine-tuning pre-trained BERT models, optimizing hyperparameters, modifying layer architectures, and employing ensemble techniques to enhance text classification accuracy for depression detection. The findings explore BERT's potential to revolutionize text analysis for addressing mental health challenges.

关键词： Natural Language Processing Fine Tuning Transformers BERT RoBERTa Depression

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Apple and Its Management of Innovation Approach - To Be or Not to Be Obsolete? 4th

Apple and Its Management of Innovation Approach - To Be or N...

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4th International Conference on Advanced Research in Technologies information Innovation and Sustainability-ARTIIS-Annual

作者： Ribeiro, Jorge Gaibor, Leonardo Torrinha, Madalena Grilo, Rafael Au-Yong-Oliveira, Manuel Univ Aveiro Dept Econ Management Ind Engn & Tourism P-3810193 Aveiro Portugal INESC TEC Porto Portugal Res Unit Governance Competitiveness & Publ Polici P-3810193 Aveiro Portugal

ISBN: (纸本)9783031840777;9783031840784

Apple is one of the most valuable companies regarding market capitalization. A massive part of this success has come from radically innovating, and introducing products such as the iPod, iPhone, iPad, Airpods and many others that have changed our perception of mobile devices. Yet nowadays, innovation seems to have slowed down at the company and pivoted mainly to incremental innovation, and the companies' lawsuits for practices of planned obsolescence keep piling up. The purpose of this paper is to discover if consumers agree with the perception that Apple is becoming less innovative. Therefore, we created an exploratory survey (n = 58), and our results show that 62% of our respondents have the perception that Apple has become less innovative. However, this does not reflect their whole perception as Apple and non-Apple customers see incremental innovation in completely different ways. Chi-square tests were performed, and two statistically significant associations were found. Non-Apple customers are more aware that Apple has been taken to court for planned obsolescence. On the other hand, awareness of planned obsolescence and Apple making devices difficult to repair are apparently associated. We outlie a recommendation for Apple, as our finding regarding durability being a key motive in the purchasing process is contrary to the literature. This finding, coupled with the fact that some Apple devices have limited durability, could mean that if laws force Apple to explicitly state the durability of their devices, they could start treading on dangerous ground. We consequently recommend Apple to cautiously consider improving the durability of their devices or else their sales could suffer.

关键词： Innovation Apple Planned Obsolescence Commercial Strategy

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Advancing the Reliability of Ultra-Low Field MRI Brain Volume Analysis Using CycleGAN 1st

Advancing the Reliability of Ultra-Low Field MRI Brain Volum...

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1st MICCAI Meets Africa Workshop

作者： Hsu, Peter Marchetto, Elisa Sodickson, Daniel Johnson, Patricia Veraart, Jelle NYU Dept Radiol Bernard & Irene Schwartz Ctr Biomed Imaging Grossman Sch Med New York NY USA NYU Vilcek Inst Grad Biomed Sci Grossman Sch Med New York NY USA NYU Dept Radiol Ctr Adv Imaging Innovat & Res CAI2R Grossman Sch Med New York NY USA

ISBN: (纸本)9783031791024;9783031791031

The increasing prevalence of neurodegenerative diseases poses a significant threat to the well-being of the growing elderly population, with biological age being a major risk factor. This has increased the demand for cost-effective and informative neuroimaging modalities and analysis tools. Specifically, measuring brain volume is of critical importance as abnormal atrophy patterns are strong indicators of disease onset. Ultra-low field (ULF) MRI provides an innovative pathway to more accessible neuroimaging by mitigating various logistical, financial, and safety considerations associated with clinical MRI. However, the image quality of ULF-MRI impacts the reliability of brain volume analysis. Advancements in deep learning (DL) have proven capable of enhancing the image quality and analysis of medical images. Yet, these tools have not been fully realized for ULF-MRI, largely due to data scarcity as the technology is still relatively new. As a result, existing DL techniques for ULF image enhancement are trained with synthetically generated images, leading to potential "domain shift" issues when applied to real images. Here, we introduce a CycleGAN framework that learns with real ULF and high-field (HF) MRIs to improve the image enhancement process compared to existing methods. We demonstrate that this approach increases the accuracy of brain volume measurements based on improved correlations with paired clinical data and higher test-retest reliability across repeat measurements. Ultimately, our proposal has the potential to enhance clinical and research workflows through the increased accessibility and reliability of ULF-MRI.

关键词： Ultra-Low Field MRI CycleGAN Vision Transformers Brain Volume Analysis Transfer Learning

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