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检索条件"丛书名=Lecture Notes in Business Information Processing 252"

共 8647 条记录，以下是451-460 订阅

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Incorporating Behavioral Recommendations Mined from Event Logs into AI Planning 1

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36th International Conference on Advanced information Systems Engineering (CAiSE)

作者： Park, Gyunam Rafiei, Majid Helal, Hayyan Lakemeyer, Gerhard van der Aalst, Wil M. P. Rhein Westfal TH Aachen Proc & Data Sci Grp Aachen Germany Rhein Westfal TH Aachen Knowledge Based Syst Grp Aachen Germany

ISBN: (数字)9783031610004

ISBN: (纸本)9783031609992;9783031610004

AI planning plays a crucial role in the design and optimization of business processes, providing optimal plans, i.e., sequence of activities, based on manually crafted or formally documented rules. When these plans are executed in business processes, the supporting information systems record a wealth of event data. Analyzing such event data facilitates understanding implicit patterns and recommendations that have the potential to refine planning strategies significantly. In this paper, we introduce a systematic approach to mining these recommendations from event data and integrating them into AI planning, thus creating plans that are informed by both the regulatory hard rules and the flexibility of soft recommendations.

关键词： AI Planning Automated Planning Process Mining Behavioral Recommendations

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A Survey to Evaluate the Completeness and Correctness of a Morphological Box for AI Solutions 1

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36th International Conference on Advanced information Systems Engineering (CAiSE)

作者： Rittelmeyer, Jack Daniel Sandkuhl, Kurt Univ Rostock Inst Comp Sci Albert Einstein Str 22 D-18057 Rostock Germany Jonkoping Univ Sch Engn Jonkoping Sweden

ISBN: (数字)9783031610035

ISBN: (纸本)9783031610028;9783031610035

Artificial Intelligence (AI) is a key technology driving digital transformation in enterprises worldwide. However, the implementation of AI projects often faces hurdles, primarily due to misconceptions about AI's capabilities and suitable applications. This research represents a step in a broader research process aimed at creating an artifact to help companies, particularly those outside the IT sector, navigate these challenges. We present an evaluation of a morphological box that outlines critical factors for successful AI integration. The evaluation was carried out by conducting and analyzing a survey in which participants rated the individual features and values, as well as their structure. We also conducted the Kaiser-Meyer-Olkin and Bartlett tests and created a correlation matrix as statistical measures to identify overlap between the elements of the box. After analyzing the data, we found some further room for improvement but that the box seems to include the generally most important aspects. Overall, the participants' ratings for the individual elements were also satisfactory.

关键词： Artificial Intelligence Morphological Box Survey AI Solution Development

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Reviewing the Role of Secret Sharing Schemes in Electronic Payment Protocols 20th

Reviewing the Role of Secret Sharing Schemes in Electronic P...

引用

20th European, Mediterranean, and Middle Eastern Conference (EMCIS)

作者： Kalai, Rym Neji, Wafa Ben Rajeb, Narjes Univ Tunis El Manar LIPSIC Lab Fac Sci Tunis Tunis Tunisia Higher Inst Technol Studies Beja Gen Directorate Technol Studies LIPSIC Lab Tunis Tunisia Univ Carthage Natl Inst Appl Sci & Technol LIPSIC Lab Carthage Tunisia

ISBN: (纸本)9783031564772;9783031564789

Since e-Cash and electronic transactions consist of digital data, there are risks that this data can be easily falsified, compromising the security and efficiency of the entire electronic payment protocol. To ensure the security of the protocol, these data must be protected. This is why researchers have focused on several cryptographic studies including secret sharing. Secret sharing techniques are used to divide a secret into multiple shares and to distribute them among a group of participants. Only when a sufficient number of shares are combined together, the original secret can be reconstructed. Moreover, no information about the secret can be deducted from the shares by a smaller group. In this paper, we investigate the different phases of an electronic payment protocol where secret sharing can be used and more particularly distributed key generation and distributed multikey generation protocols. This paper also highlights the importance of using secret sharing in enhancing the security and confidentiality of electronic payment systems, as well as the ability to prevent unauthorized access to sensitive information. The trust is shared among multiple parties.

关键词： Secret Sharing (SS) Distributed Key Generation (DKG) Distributed Multi-Key Generation (DMKG) electronic payment protocols

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Using Computational Knowledge Extraction Approach to Assess Three Decades of Health Management information Systems for Informed Actions 20th

Using Computational Knowledge Extraction Approach to Assess ...

引用

20th European, Mediterranean, and Middle Eastern Conference (EMCIS)

作者： Watat, Josue Kuika Agbozo, Ebenezer Univ Oslo HISP Ctr Gaustadalleen 30 N-0373 Oslo Norway Ural Fed Univ Ul Mira 32 Ekaterinburg 620002 Russia

ISBN: (纸本)9783031564772;9783031564789

This research explores the role of the District Health information System (DHIS2) in global health decision-making. Although DHIS2 is widely used in healthcare systems around the world, there is a significant shortage of in-depth scholarly research assessing its effectiveness and scope. This gap is critical, as understanding DHIS2's full potential is central in today's global health context, where data-driven decision-making is fundamental to both managing public health crises and improving healthcare delivery. To address this, our research employs the Latent Dirichlet Allocation (LDA) methodology to analyze a corpus of DHIS2-centric research. By doing so, we aim to uncover the main themes and applications of DHIS2 for informed action, thereby providing a more structured view of its impact in the health data management field. In addition, the study yielded a word cloud which depicted a variety of diseases connected to DHIS2 research, outlining its fundamental value in disease surveillance and management. The results emphasize DHIS2's enabling role within the broader HMIS ecosystem in developing a data-centric approach for effective public health interventions and management of health emergencies. This study develops a blueprint for exploiting HMIS to its maximum potential for informed public health activities by gaining sophisticated knowledge of DHIS2 through the LDA analysis. It guides researchers in understanding DHIS2's applications, facilitating further exploration in areas like disease trend analysis. Practitioners can use these insights to improve health surveillance, for instance, by tracking and managing outbreaks, thereby making more informed decisions in public health scenarios.

关键词： Topic Modelling Machine Learning Evidence-based decision-making DHIS2 BERTopic Informed Actions

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Comparing Stability and Sustainability in Agile Systems 25th

Comparing Stability and Sustainability in Agile Systems

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25th International Conference on Agile Software Development (XP)

作者： Healy, Robert Conboy, Kieran Dey, Tapajit Lewzey, Edwin Fitzgerald, Brian Univ Limerick Limerick Ireland Univ Galway Sch Business & Econ Galway Ireland Carnegie Mellon Univ Software Engn Inst Pittsburgh PA USA Intive 4th Floor New Penderel House283-288 High Holborn London England Univ Limerick Lero SFI Res Ctr Software Limerick Ireland

ISBN: (纸本)9783031611537;9783031611544

The World Health Organization (WHO) highlights the significant threat that unsustainably long working hours pose to our mental and physical well-being. Aligning with this concern, an Agile principle emphasizes that "Agile processes promote sustainable development." However, previous work in 2023 debunked this notion of inherent stability in Agile systems, such as the Scrum and Kanban frameworks. In this study, we aim to analyse the relationship between system stability and the tendency of teams to work outside reasonable office hours. We inspect 295 historic Agile projects completed in intive, a software development company. We assess the percentage of late-night, early-morning, or weekend hours where a Product Backlog Item (PBI) was created or resolved and compare this percentage of Unsustainable Hours metric to the Stability Metric and the number of Inventory Days remaining. The analysis showed that almost no correlation exists between the Unsustainable Hours worked and either the system stability or outstanding inventory. These findings indicate that, while working unconventional and potentially excessive hours is a concern, it does not appear to be linked to the stability of Agile systems. This highlights the need for a deeper understanding of individual and team motivations to foster long-term sustainable work practices.

关键词： Agile Sustainability Overwork Stability

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Classifying Healthcare and Social Organizations in Cybersecurity Profiles 1

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18th International Conference on Research Challenges in information Sciences (RCIS)

作者： Ahouanmenou, Steve Van Looy, Amy Poels, Geert Andries, Petra Standaert, Thomas Univ Ghent Fac Econ & Business Adm Dept Business Informat & Operat Management Ghent Belgium Univ Ghent Dept Mkt Innovat & Org Fac Econ & Business Adm Ghent Belgium UGent CVAMO Core Lab Flanders Make Ghent Belgium

ISBN: (数字)9783031594656

ISBN: (纸本)9783031594649;9783031594656

While cybersecurity is of high relevance for all organizations, special care is needed in the healthcare and social realm when coping with sensitive patient data. This study contributes to this under-investigated yet relevant field by examining how cybersecurity measures have been implemented within healthcare and social organizations. We rely on a combination of clustering analysis, discriminant analysis, and Tukey HSD testing to analyze survey data on 265 organizations in Flanders, Belgium. The resulting five clusters unveil five distinct approaches or organizational profiles and three major differentiators. The data suggests that the extent to which training, regular software updates, and data backup are implemented best describes the underlying cybersecurity profiles. Our findings reveal that a significant majority of surveyed organizations are situated in the lower echelons of the cybersecurity implementation differentiators, while only a minority of organizations demonstrate commendable levels of implementation. By enriching cybersecurity insights within the healthcare and social domain, our findings and their implications could resonate deeply, urging researchers to expand their research to bolster cyber resilience in specific sectors.

关键词： Cybersecurity Healthcare Social

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An Accurate Random Forest-Based Action Recognition Technique Using only Velocity and Landmarks' Distances 6th

An Accurate Random Forest-Based Action Recognition Technique...

引用

6th International Conference on information and Knowledge Systems (ICIKS)

作者： Maaoui, Hajer Elaoud, Amani Barhoumi, Walid Univ Carthage Inst Super Sci Appliquees & Technol Mateur Mateur 7030 Tunisia Univ Tunis El Manar Inst Super Informat LR16ES06 Lab Rech Informat Modelisat & Traitement Res Team Intelligent Syst Imaging & Artificial Vi 2 Rue Bayrouni Ariana 2080 Tunisia Univ Carthage Ecole Natl Ingn Carthage ENICarthage 45 Rue Entrepreneurs Tunis 2035 Tunisia

ISBN: (纸本)9783031516634;9783031516641

Human action recognition has gained significant attention recently as it can be adopted for various potential applications, notably for smart activity monitoring for surveillance and assisted living purposes. However, recognizing human activities is a challenging task because of the variety of human actions in daily life. In this work, we propose to extract skeletons from RGB images using deep learning architectures while adopting hand-crafted features for action recognition. The main idea is to extract few features from the skeleton data in order to ensure low feature dimensionality while leading to fast and accurate action recognition. In fact, our objective is to define hand-crafted features that are clearly explainable and related to the kinematics. Each joint is modeled by a single feature vector that encodes only the most essential kinematic information to characterize an action: the relative locations of the joints as well as the velocity of these joints. We have validated the proposed technique on the challenging UTD-MHAD multimodal action dataset and the preliminary obtained results are very encouraging.

关键词： Human action recognition Deep learning Velocity Skeleton Landmarks

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Ontology-Based Multi-perspective Process Mining in Laboratories: A Case Study 5th

Ontology-Based Multi-perspective Process Mining in Laborator...

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5th International Conference on Process Mining (ICPM)

作者： Mayrhuber, Elisabeth Helm, Emmanuel Ehrlinger, Lisa Univ Appl Sci Upper Austria Hagenberg Im Muhlkreis Austria Software Competence Ctr Hagenberg GmbH Hagenberg Im Muhlkreis Austria

ISBN: (纸本)9783031561061;9783031561078

In real-world process mining scenarios, event logs are extracted from relational databases. The de-facto standard for event log exchange, XES (eXtensible Event Stream), has the limitation that it is restricted to a single case notion and hence viewpoint. Although recent trends towards object-centric process mining propose new standards, they are not yet widely adopted by the tool industry. In this paper, we show how to enable multi-perspective process mining based on the established XES standard by means of a case study from the laboratory domain. Inspired by an existing approach, we use semantic technology to enable the mapping between a domain ontology and a relational database. This allows to dynamically switch the perspective with every new query. In addition, we employ the semantic extension of XES to enrich the resulting event log with semantic information from the domain ontology. Our prototype has been evaluated on real-world data from a German laboratory and therefore specifically addresses the challenge on how to process protected health information.

关键词： Process Mining Ontologies Semantic Header Laboratory

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Enhancing Our Understanding of business Process Model Comprehension Using Biometric Data 1

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25th International Working Conference on business Process Modeling, Development, and Support (BPMDS) / 29th International Working Conference on Exploring Modeling Methods for Systems Analysis and Development (EMMSAD)

作者： Krogstie, John Sharma, Kshitij Norwegian Univ Sci & Technol NTNU Trondheim Norway

ISBN: (数字)9783031610073

ISBN: (纸本)9783031610066;9783031610073

Much research has been done on the comprehension and development of conceptual models. In related areas such as linguistics and software engineering one has taken techniques from neuroscience into use, to study the biological and neurological processes when working with textual knowledge representations in tasks such as program code debugging. The use of such techniques has only to a limited degree been used to improve our understanding of visual conceptual models so far. We will in this paper present ongoing research on the use of techniques collecting biometric data to investigate how we work with visual conceptual models. The approach, which are based on techniques used in multi-modal learning analytics (MMLA), investigates how performance on modeling tasks is correlated with biometric data, collecting data in parallel from EEG, eye-tracking, wristbands, and facial expression (through cameras). We find that good understanding of performance of modeling tasks can be achieved by using biometric data in a natural usage situation. We have just scratched the surface of this topic, and we present the start of a larger research program in this area in the concluding remarks.

关键词： business Process Modeling BPMN Multi-modal biometric data Neuro-conceptualization

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CDMiA: Revealing Impacts of Data Migrations on Schemas in Multi-model Systems 1

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36th International Conference on Advanced information Systems Engineering (CAiSE)

作者： Gillet, Annabelle Leclercq, Eric Univ Burgundy Lab Informat Bourgogne EA 7534 Dijon France

ISBN: (数字)9783031610004

ISBN: (纸本)9783031609992;9783031610004

To produce quality results from artificial intelligence (AI) pipelines, data consistency and structure must be finely controlled. This control must take into consideration the heterogeneity of data, and more specifically the heterogeneity of their models. Indeed, multi-model data are at the core of current systems, such as data lakes or polystores, that supply data for AI pipelines. To benefit the most of multi-model systems, data migrations are used to ingest data with a more suitable model than the original model, to apply operators available only for a specific model or to optimize queries, by sending data into a system capable of processing data faster than the original system, even when the migration time is included. However, data migrations are complex in a multi-model environment, in particular because the models do not support the same types of constraints. Thus, such constraints can be preserved, weakened, created or dropped during the migration process. Furthermore, the impact of a migration on a schema is contextual. Indeed, if a schema does not apply a constraint of its source model, it is not important that it is not supported in the destination model. Thus, it is essential to control data migrations, and to assess the impact of a migration on a schema. To do so, we propose the Categorical Data Migration Assessor tool (CDMiA), that relies on category theory to automatically detect the required creations and losses of constraints when migrating a schema from a model to another.

关键词： Multi-model data Data migration Category theory

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