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15th International Conference on Knowledge Management and Information Systems, KMIS 2023 as part of the 15th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management, IC3K 2023

作者： Doering, Claudia Timinger, Holger Wolff, Christian Institute of Data and Process Science University of Applied Sciences Landshut Germany Faculty for Informatics and Data Science Media Informatics Group University of Regensburg Germany

ISBN: (纸本)9789897586712

The paper presents a platform for knowledge and technology transfer processes and relevant information for higher educational institutions (HEIs). Nowadays knowledge transfer or third-mission activities are daily business for universities. Nevertheless, they often lack internal standardized processes and procedures. Every HEI tends to establish their own way of efficiently handling transfer activities, without sharing their knowledge with other HEIs. The presented platform outlines standardized processes with knowledge from several HEIs, presented in digitized form. The processes and the platform were evaluated with use cases and a standardized user experience questionnaire (UEQ). The results presented in this contribution indicate a high need for and positive perception of the processes and the platform. Copyright © 2023 by SCITEPRESS - science and Technology Publications, Lda.

关键词： Knowledge management

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Study of the shear-rate dependence of granular friction based on community detection

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science China(Physics,Mechanics & Astronomy) 2019年第4期62卷 38-44页

作者： YongWen Zhang GaoKe Hu XiaoSong Chen Wei Chen WenQi Liu Data Science Research Center Faculty of Science Kunming University of Science and Technology CAS Key Laboratory of Theoretical Physics Institute of Theoretical Physics Chinese Academy of Sciences School of Physical Sciences University of Chinese Academy of Sciences State Key Laboratory of Multiphase Complex System Institute of Process Engineering Chinese Academy of Sciences

In this study, computer simulations are performed on three-dimensional granular systems under shear conditions. The system comprises granular particles that are confined between two rigid plates. The top plate is subjected to a normal force and driven by a shearing velocity. A positive shear-rate dependence of granular friction, known as velocity-strengthening, exists between the granular and shearing plate. To understand the origin of the dependence of frictional sliding, we treat the granular system as a complex network, where granular particles are nodes and normal contact forces are weighted edges used to obtain insight into the interiors of granular matter. Community structures within granular property networks are detected under different shearing velocities in the steady state. Community parameters, such as the size of the largest cluster and average size of clusters, show significant monotonous trends in shearing velocity associated with the shear-rate dependence of granular friction. Then, we apply an instantaneous change in shearing velocity. A dramatic increase in friction is observed with a change in shearing velocity in the non-steady state. The community structures in the non-steady state are different from those in the steady state. Results indicate that the largest cluster is a key factor affecting the friction between the granular and shearing plate.

关键词： granular shear-rate friction community detection

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MQTT-4EST: RulE-basEd WEb Editor for Semantic-aware Topic Naming in MQTT 19

MQTT-4EST: RulE-basEd WEb Editor for Semantic-aware Topic Na...

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19th IEEE Annual Consumer Communications and Networking Conference, CCNC 2022

作者： Piller, Tobias Christian Merz, David Maria Khelil, Abdelmajid Institute for Data and Process Science Landshut University of Applied Sciences Am Lurzenhof 1 Landshut84036 Germany

ISBN: (纸本)9781665431620

Message Queuing Telemetry Transport (MQTT) is an established data transmission protocol in virtually all Smart-∗ domains. The protocol is based on the publish/subscribe pattern. Messages are published to so-called topics, to which subscribers subscribe, in order to receive the content of interest. As the name of the topic can be chosen freely by the publishing entity without relying on a shared semantic model, the subscribers can insufficiently reason on the semantic of the topic name. However, this can be desirable when topic trees closely resemble structures found in the real world. One approach to formulate semantics in a machine-readable format are ontologies. This paper demonstrates how ontologies allow to couple topic trees with explicit semantics. To this end we present a novel editor that supports users in creating topic trees that follow explicit semantics. © 2022 IEEE.

关键词： Ontology

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Universality class of machine learning for critical phenomena

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science China(Physics,Mechanics & Astronomy) 2023年第12期66卷 63-70页

作者： Gaoke Hu Yu Sun Teng Liu Yongwen Zhang Maoxin Liu Jingfang Fan Wei Chen Xiaosong Chen School of Systems Science and Institute of Nonequilibrium Systems Beijing Normal UniversityBeijing 100875China Data Science Research Center Faculty of ScienceKunming University of Science and TechnologyKunming 650500China State Key Laboratory of Multiphase Complex Systems Institute of Process EngineeringChinese Academy of SciencesBeijing 100190China University of Chinese Academy of Sciences Beijing 100049China

Herein,percolation phase transitions on a two-dimensional lattice were studied using machine learning *** reveal that different phase transitions belonging to the same universality class can be identified using the same neural networks(NNs),whereas phase transitions of different universality classes require different *** on this finding,we proposed the universality class of machine learning for critical ***,we investigated and discussed the NNs of different universality *** research contributes to machine learning by relating the NNs with the universality class.

关键词： universality class machine learning percolation

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Extracting Multifaceted Characteristics of Patients With Chronic Disease Comorbidity: Framework Development Using Large Language Models

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JMIR Medical Informatics 2025年 13卷 e70096页

作者： Junyan Zhang Junchen Zhou Liqin Zhou Zhichao Ba Base of the State Key Laboratory of Urban Environmental Process and Digital Modelling Capital Normal University Beijing China School of Medicine and Health Management Huazhong University of Science and Technology Wuhan China Research Institute for Data Management & Innovation Nanjing University Suzhou China

Background Research on chronic multimorbidity has increasingly become a focal point with the aging of the population. Many studies in this area require detailed patient characteristic information. However, the current methods for extracting such information are complex, time-consuming, and prone to errors. The challenge of quickly and accurately extracting patient characteristics has become a common issue in the study of chronic disease comorbidities. Objective Our objective was to establish a comprehensive framework for extracting demographic and disease characteristics of patients with multimorbidity. This framework leverages large language models (LLMs) to extract feature information from unstructured and semistructured electronic health records pertaining to these patients. We investigated the model’s proficiency in extracting feature information across 7 dimensions: basic information, disease details, lifestyle habits, family medical history, symptom history, medication recommendations, and dietary advice. In addition, we demonstrated the strengths and limitations of this framework. Methods We used data sourced from a grassroots community health service center in China. We developed a multifaceted feature extraction framework tailored for patients with multimorbidity, which consists of several integral components: feasibility testing, preprocessing, the determination of feature extraction, prompt modeling based on LLMs, postprocessing, and midterm evaluation. Within this framework, 7 types of feature information were extracted as straightforward features, and three types of features were identified as intricate features. On the basis of the straightforward features, we calculated patients’ age, BMI, and 12 disease risk factors. Rigorous manual verification experiments were conducted 100 times for straightforward features and 200 times for intricate features, followed by comprehensive quantitative and qualitative assessments of the experimental outcomes. Results

关键词： large language model zero-shot prompting information extraction chronic disease multimorbidity natural language processing

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Behavior and mechanism of pre-oxidation improvement on fluidization in the fluidized reduction of titanomagnetite

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International Journal of Minerals,Metallurgy and Materials 2024年第11期31卷 2458-2465页

作者： Haoyan Sun Ajala Adewole Adetoro Zhiqiang Wang Qingshan Zhu State Key Laboratory of Mesoscience and Engineering Institute of Process EngineeringChinese Academy of SciencesBeijing 100190China School of Chemical Engineering University of Chinese Academy of SciencesBeijing 100049China Data Science AI modeling CentreUniversity of HullHull HU67RXUK

The direct reduction process is an important development direction of low-carbon ironmaking and efficient comprehensive utilization of poly-metallic iron ore,such as ***,the defluidization of reduced iron particles with a high metallization degree at a high temperature will seriously affect the operation of fluidized bed *** the pre-oxidation enhancing reduction and the particle surface modification of titanomagnetite,the behavior and mechanism of pre-oxidation improvement on fluidization in the fluidized bed reduction of titanomagnetite are systematically studied in this ***-oxidation treatment of titanomagnetite can significantly lower the critical stable reduction fluidization gas velocity to 0.17 m/s,which is reduced by 56%compared to that of titanomagnetite reduction without pre-oxidation,while achieving a metallization degree of>90%,Corresponding to the different reduction fluidization behaviors,three pre-oxidation operation regions have been divided,taking oxidation degrees of 26%and 86%as the *** on the particle surface morphology evolution in the pre-oxidation-reduction process,the relationship between the surface morphology of pre-oxidized ore and the reduced iron with fluidization properties is *** improving method of pre-oxidation on the reduction fluidization provides a novel approach to prevent defluidization by particle surface modification,especially for the fluidized bed reduction of poly-metallic iron ore.

关键词： fluidization direct reduction pre-oxidation titanomagnetite iron whisker

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process comparison using object-centric process cubes

arXiv

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arXiv 2021年

作者： Ghahfarokhi, Anahita Farhang Berti, Alessandro van der Aalst, Wil M.P. Process and Data Science institute RWTH Aachen University Germany

process mining provides ways to analyze business processes. Common process mining techniques consider the process as a whole. However, in real-life business processes, different behaviors exist that make the overall process too complex to interpret. process comparison is a branch of process mining that isolates different behaviors of the process from each other by using process cubes. process cubes organize event data using different dimensions. Each cell contains a set of events that can be used as an input to apply process mining techniques. Existing work on process cubes assume single case notions. However, in real processes, several case notions (e.g., order, item, package, etc.) are intertwined. Object-centric process mining is a new branch of process mining addressing multiple case notions in a process. To make a bridge between object-centric process mining and process comparison, we propose a process cube framework, which supports process cube operations such as slice and dice on object-centric event logs. To facilitate the comparison, the framework is integrated with several object-centric process discovery approaches. © 2021, CC BY.

关键词： data mining

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Supporting the Development of a Mobile Context-Aware Application by an MDA-based Approach

Supporting the Development of a Mobile Context-Aware Applica...

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Engineering, Technology and Innovation (ICE/ITMC), IEEE International Conference on & Management of Technology (IAMOT) Joint Conference, International Association For

作者： Julian Dörndorfer Markus Schmidtner Institute for Data and Process Science University of Applied Science Landshut Landshut Germany

ISBN: (纸本)9781665488181

Mobile devices and context recognition are the most important drivers of digitization. They help to increase productivity and efficiency by optimizing processes and adapting the situation according to context. For example, sensor data from a smartphone can be used together with vehicle and customer data to better plan routes for delivery drivers and adjust them during delivery. To exploit these possibilities, a mobile context-aware application must be developed. The model-driven architecture (MDA)-based development approach simplifies the development of such applications by designing a domain-specific modeling language (DSML) called SenSoMod. SenSoMod facilitates collaboration between domain experts and developers by discussing problems at a higher, more abstract level of the modeling language. Thus, SenSoMod helps to get a better estimation of the complexity of the application and thus supports the project management. Assisted by a modeling tool, code is generated from the designed model, reducing the implementation time of context-aware applications. Thus, the development time can be shortened and adaptations can be made faster. To test the assumed improvements that can positively impact project management, a proof-of-concept implementation of a mobile emergency corridor application was conducted. (Abstract)

关键词： Context-aware services Productivity Adaptation models Project management Estimation Collaboration Mobile handsets

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Robust extraction of rain-induced attenuation from microwave link observations using local regression 9

Robust extraction of rain-induced attenuation from microwave...

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9th International Workshop on Precipitation in Urban Areas: Urban Challenges in Rainfall Analysis, UrbanRain 2012

作者： Schatzmann, A. Scheidegger, A. Rieckermann, J. Ruckstuhl, A. Institute for Data Analysis and Process Design Zurich University of Applied Sciences Winterthur Switzerland Dept. of Urban Water Management Eawag: Swiss Federal Institute of Aquatic Science and Technology Dübendorf Switzerland

ISBN: (纸本)9783906031217

Recently, the rain-induced attenuation of microwave links (MWL) has been suggested as a novel tool to monitor rainfall in urban areas. However, this requires robust methods to identify and remove baseline attenuation during dry weather, which is not trivial. In this paper, we present a novel statistical method to identify the baseline attenuation based on robust local regression (REBS) offline and in real-time. To test the correct baseline removal, we were able to test the algorithm on an extraordinary dataset of a dense network of rain gauges and disdrometers that provides an unrivalled ground truth reference rain fall and avoids uncertainties due to scaling effect between the path-average MWL measurements and point rain gauge observations. Our results show that the robust regression algorithms predict the path-average rainfall intensities from MWL signal levels that are practically unbiased and match the reference rainfall well. Although the scatter for 1-min rainfall intensities can vary up to 80% of the reference measurements, this it reduced to about 20% for 10min average intensities.

关键词： Rain

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Sensing Quality Driven Positioning and Orientation for LiDAR Sensors

Sensing Quality Driven Positioning and Orientation for LiDAR...

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Artificial Intelligence and Internet of Things (GCAIoT), IEEE Global Conference

作者： Dominic Scholze Abdullah Al-Khatib Abdelmajid Khelil Institute for Data and Process Science Landshut University of Applied Sciences Germany

Beam-based sensors like LiDAR are indispensable for modern infrastructures, machines, and autonomous moving objects. Their placement is crucial for their value and acceptance in the considered applications. However, determining the sensor’s blind areas requires significant time and resources when relying on simulation. We propose a set of analytical indicators that significantly reduce this overhead associated with the placement and installation of beam-based *** on a geometrical model that considers both the sensor and sensing quality, we define novel indicators accordingly and show their effectiveness for intelligent traffic safety infrastructure. The proposed indicators contribute to sensor calibration during the initial sensor setup and represent a vital step toward self-calibration throughout the entire system’s life cycles.

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