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arXiv 2025年

作者： Pieris, Dhammika Department of Information Systems Engineering and Informatics Faculty of Computing University of Sri Jayawardenepura Sri Lanka

The Cognitive Data Model (CDM) is proposed. A novel approach to database design, inspired by the belief that the human brain operates with a logical data model independent of its anatomical structure. The study aims to identify and replicate this CDM to enhance database design, resolving limitations of the existing models in handling complex relationships, scalability, and adaptability. The methodology involves empirical observation, cognitive experiments, iterative modelling and critical thinking. Findings suggest that the information processing in the brain occurs sequentially with forming associations on atomic static data in a pairwise, time-dependent manner. This insight led to the development of a meta-framework for the brain’s information processing to design CDM based on it. The CDM offers improved data modelling and database design, efficient querying, and potential applications in AI, machine learning, and big data analytics. Future research will focus on formalizing the model, implementing it in 3D environments, and developing a query language. Copyright © 2025, The Authors. All rights reserved.

关键词： Structured Query Language

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Identifying and Documenting Best Practices in Digital Transformation 23

Identifying and Documenting Best Practices in Digital Transf...

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Proceedings of the 28th European Conference on Pattern Languages of Programs

作者： Mohammad Yusuf Momand Valentino Vranić Institute of Informatics Information Systems and Software Engineering Faculty of Informatics and Information Technologies Slovak University of Technology in Bratislava Slovakia

ISBN: (纸本)9798400700408

Digital transformation allows organizations to maintain sustainable development and address ongoing challenges. The current digital transformation and advanced technology mega-trend significantly impact society and organizations, making digital technology crucial for public and private organizations, universities, and daily life. Despite the rising demand, there is often a lack of standard policies governing the use of digital technology. Practical experience and literature reveal key challenges in transitioning from traditional to digital systems, including limited public awareness, mindset, ICT skills, government support, and collaboration between organizations and software engineering societies. Governments must establish digital transformation policies and offer software development guidelines for public organizations to digitalize their systems. Additionally, they should provide or support research projects funded by governmental and nongovernmental organizations to identify infrastructure and regulatory issues within Afghanistan’s digital transformation context. This study documents six organizational patterns observed during the transformation of traditional systems into digital systems, illustrating their sequence and explaining the development of a pattern language from these patterns.

关键词： digital transformation organizational patterns patterns software engineering

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Iterative Design of a Decision Support System for Fall Risk Detection in residential care facilities

Iterative Design of a Decision Support System for Fall Risk ...

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作者： Tschorn, Niklas Keuchel, Maren Müller, Inga Milkov, Sarah Potthoff, Christian Windrath, Dioselina Weber, Yvonne Meister, Sven Burmann, Anja Fraunhofer Institute for Software and Systems Engineering ISST Dortmund / Health Care Informatics Faculty of Health School of Medicine Witten/Herdecke University Speicherstraße 6 Witten Germany Fraunhofer Institute for Software and Systems Engineering ISST Dortmund Germany HS Gesundheit Bochum Bochum Germany Diakonie Michaelshoven Cologne Germany Connext Communication GmbH Paderborn Germany Health Care Informatics Faculty of Health School of Medicine Witten/Herdecke University Witten Germany

Nursing care jobs are predominantly described as burdensome. In particular, the workload and the time available to deal with it are in a state of imbalance. Nurses are very often under time pressure and have to make decisions under psychological, emotional and physical stresses. Machine learning methods and in particular, Decision Support systems (DSS) can be used to support nurses with improved information (e.g. visualization of individual health risks) for decisions that are not easy to make. As falls are one of the most common health problems in care facilities, we will present a concept of a DSS for the prevention of falls that was developed in the PFLIP research project. We explain our user-centered design process based on ISO 9241-210-2019. User feedback is obtained at each phase so that nurses can identify problems at an early stage. The result is a conceptual design, visualized as a click dummy, to identify individual fall risks and predict preventive measures to reduce the risk of falling. © 2024 The Author(s), published by De Gruyter.

关键词： Electronic health record

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Cost-Effective HWIL testing methodology for SALS guided missiles

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Materials Today: Proceedings 2022年 62卷 2509-2515页

作者： Todi, Ivana Kuzmanovi, Vladimir University of Belgrade Faculty of Mechanical Engineering Weapon Systems Department Kraljice Marije 16 Belgrade 11120 Serbia University of Belgrade Faculty of Mathematics Department for Computer Science and Informatics Studentski Trg 16 Belgrade 11000 Serbia

Verifying a new missile design requires a series of successful real-life tests on a firing range in various scenarios. Such an approach is extremely expensive and requires complex infrastructure and logistics. The costs of developing a new missile design can be significantly reduced by applying extensive and well thought out laboratory testing prior to any real-life test. Laboratory tests such as Hardware-In-The-Loop (HWIL) simulation enable the missile to be tested in a controlled environment inside a laboratory. HWIL testing methodology enables engineers to test the missile or its components in various simulated scenarios that correspond to real-life flights. Usually, a five-axis motion platform is used to perform HWIL simulation of terminal guidance. Three inner axes of the five-axis motion platform are used for simulation of the missiles body angles, while the two outer axes are used for simulation of the target movement relative to the missile. Such an approach requires spacious laboratories and expensive equipment. In this paper, we present a cost-effective HWIL testing methodology for Semi-Active-Laser-Seeker (SALS) guided missiles. The presented methodology requires only a three-axis motion platform and a fixed laser source. In the paper, we propose a two-stage HWIL testing procedure. In the first stage, the INS algorithm, guidance algorithm and autopilot algorithms are verified. In the second stage of the proposed HWIL testing methodology, the terminal guidance algorithm based on SALS angles is verified. Besides the HWIL testing methodology, we present the guidance law used in the testing procedure as well as the design of intercommunication between all the devices required to perform the tests. Next, the obtained results after each stage of the proposed HWIL testing methodology are presented and analyzed. Finally, a conclusion is drawn and limitations of the proposed testing methodology are explained. © 2020

关键词： Embedded systems

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Semi-analytical finite element method applied for characterizing micropolar fibrous composites

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Applied Mathematics and Mechanics(English Edition) 2024年第12期45卷 2147-2164页

作者： J.A.OTERO Y.ESPINOSA-ALMEYDA R.RODRIGUEZ-RAMOS J.MERODIO School of Engineering and Sciences Monterrey Institute of TechnologyEstado de Mexico 52926Mexico Institute of Engineering and Technology Autonomous University of Ciudad JuarezCiudad JuarezChihuahua 32310Mexico Postgraduate Program in Computational Modeling in Science and Technology Federal Fluminense UniversityRıo de Janeiro 27255-125Brazil Faculty of Mathematics and Computer Science University of HavanaLa Habana 10400Cuba Department of Mathematics Applied to ICT School of Informatics Systems EngineeringTechnical University of MadridMadrid 28031Spain

A semi-analytical finite element method(SAFEM),based on the two-scale asymptotic homogenization method(AHM)and the finite element method(FEM),is implemented to obtain the effective properties of two-phase fiber-reinforced composites(FRCs).The fibers are periodically distributed and unidirectionally aligned in a homogeneous *** framework addresses the static linear elastic micropolar problem through partial differential equations,subject to boundary conditions and perfect interface contact *** mathematical formulation of the local problems and the effective coefficients are presented by the *** local problems obtained from the AHM are solved by the FEM,which is denoted as the *** numerical results are provided,and the accuracy of the solutions is analyzed,indicating that the formulas and results obtained with the SAFEM may serve as the reference points for validating the outcomes of experimental and numerical computations.

关键词： semi-analytical approach fiber-reinforced composite(FRC) effective property finite element method(FEM) asymptotic homogenization method(AHM) micropolar elasticity

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Comparative Analysis of PPG Signal Capturing Using Piezoelectric, Photosensor, and Earlobe Devices

Comparative Analysis of PPG Signal Capturing Using Piezoelec...

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Biomedical engineering Conference (JIBEC), Jordanian International

作者： Amjed Al-Fahoum Ghadeer Al Omari Biomedical Systems and Informatics Engineering Dept Hijjawi Faculty for Engineering Technology Yarmouk University Irbid Jordan

ISBN: (数字)9798331539542

ISBN: (纸本)9798331539559

This paper provides an in-depth analysis of the use of three different photoplethysmography (PPG) sensors; piezoelectric, photosensor, and earlobe device to capture PPG signals from normal subjects. This study uses bispectrum analysis to provide insight into the time characteristics, frequency characteristics, time-frequency distributions, and frequency-frequency distributions at Yarmouk University Labs. The results provide information on how well each type of sensor performs and whether it is appropriate for use in clinical and research settings. While the photosensor and earlobe device offered useful advantages in terms of setup and usability, the piezoelectric sensor impressed with its improved signal quality and analytical clarity.

关键词： Performance evaluation Time-frequency analysis Three-dimensional displays Sensitivity Sensor phenomena and characterization Piezoelectric devices Biosensors Reliability Usability Monitoring

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Patterns for Improving User Contribution 23

Patterns for Improving User Contribution

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Proceedings of the 28th European Conference on Pattern Languages of Programs

作者： Mohammad Daud Haiderzai Valentino Vranić Institute of Informatics Information Systems and Software Engineering Faculty of Informatics and Information Technologies Slovak University of Technology in Bratislava Slovakia

ISBN: (纸本)9798400700408

User contributions is an important part in software development, the pursuit of identifying effective means of user contributions in software development is a crucial area of interest for software companies and their development teams. Determining the most opportune moments, locations, and methods for such contributions presents a significant challenge for organizations, which necessitates the exploration of generic and proven solutions. Applying patterns, established and observed solutions may provide the answers to such challenges and similar ones. This paper offers insights into the practical implementation of seven newly discovered organizational patterns in a real-life environment. The patterns are comprehensively described, accompanied by illustrative examples, and subsequently applied in actual practices.

关键词： organizational patterns software development software engineering

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In-Depth Examination of Student Attrition in Higher Education Through Decision Tree, Random Forest, and XGBoost Algorithms

In-Depth Examination of Student Attrition in Higher Educatio...

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International Conference on Electrical engineering, Computer Science and informatics (EECSI)

作者： Clement Aurelio Johan Setiawan Faculty of Engineering and Informatics Information Systems Study Universitas Multimedia Nusantara Tangerang Indonesia

ISBN: (数字)9798350355314

ISBN: (纸本)9798350355321

Customer Customer churn, a critical metric for businesses reliant on customer loyalty, involves the loss of customers from a company. This study examines churn among college and university students, leading to financial losses, decreased accreditation, and diminished reputations for educational institutions, ultimately reducing their appeal to prospective students. To identify factors contributing to student churn and classify students as likely to churn or not, this research utilizes Decision Tree, Random Forest, and XGBoost algorithms. These classification algorithms, with XGBoost and Random Forest enhancing Decision Trees through boosting and bagging techniques, respectively, are well-suited for the task. The data was sourced from the Academic Information Bureau and processed before model development. The model with the best performance will predict student churn on new, unseen data. Findings indicate varying performance metrics for each model, including accuracy, precision, recall, and F1-score. The XGBoost model excelled, achieving an accuracy of 98%, precision of 99%, recall of 96%, and an F1-score of 97%, significantly improving over the base Decision Tree model across all metrics. Notably, all models showed better performance in predicting the majority class (not churn) compared to the minority class (churn).

关键词： Measurement Accuracy Computational modeling Predictive models Approximation algorithms Prediction algorithms Data models Classification algorithms Decision trees Random forests

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Forecasting the Number of Traffic Accidents in Jakarta Using Artificial Neural Network

Forecasting the Number of Traffic Accidents in Jakarta Using...

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2023 International Conference on Information Technology and Computing, ICITCOM 2023

作者： Yulianti, Henny Pranoto, Gatot Tri Yaddarabullah Krishnasari, Erneza Dewi Marchenko, Michael Informatics Engineering Universitas Siber Asia Jakarta Indonesia Informatics Engineering Pelita Bangsa University Bekasi Indonesia Universitas Trilogi Department of Informatics Jakarta Indonesia Universitas Trilogi Department of Visual Communication Design Jakarta Indonesia Dnipro National University Dnipropetrovsk Faculty of Physics Electronics and Computer Systems Oblast Ukraine

ISBN: (纸本)9798350359633

Traffic accidents are a problem confronted by means of each a around the arena, Indonesia isn't any exception. The Indonesian national Police recorded an increase inside the number of traffic accidents in 2019 in comparison to 2018. based totally on POLRI information, there had been 107,500 traffic accidents in 2019, an increase from 103,672 incidents in 2018. in particular in Jakarta, that is the capital city of the Republic of Indonesia, traffic accidents are a common phenomenon, in conjunction with the unexpectedly developing use of motorized motors on the dual carriageway. for that reason, a examine is wanted to determine the variety of traffic accidents with the intention to occur in the future. The observe will forecast the number of traffic accidents for every month based totally on datasets from 2015 to 2020 from the Jakarta Metro Jaya Police Traffic Directorate. The approach used on this examine makes use of facts mining methods by using comparing the artificial Neural community Backpropagation, Deep getting to know and Linear Regression algorithms to decide which algorithm is right for predicting the range of traffic injuries inside the Jakarta region in each following month. This examine concludes that the synthetic Neural community Backpropagation set of rules is the first-rate set of rules to be applied in predicting the number of visitors accidents within the Jakarta vicinity with a Root suggest square mistakes (RMSE) of 29.477. studies trying out with the aid of applying the synthetic Neural network Backpropagation algorithm version has verified to expose the price of forecasting the number of traffic accidents in Jakarta with a mean monthly accuracy cost of 97.34%. © 2023 IEEE.

关键词： Forecasting

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Integration of K-Means and SVM for Customer Segmentation Based on Customer Behaviour Using LRFM and Product Preference

Integration of K-Means and SVM for Customer Segmentation Bas...

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International Seminar on Research of Information Technology and Intelligent systems (ISRITI)

作者： Valenzia Tanaka Samuel Ady Sanjaya Information Systems Department Faculty of Engineering and Informatics Universitas Multimedia Nusantara Tangerang Indonesia

ISBN: (数字)9798331519643

ISBN: (纸本)9798331519650

In the era of Big Data, utilizing customer transaction data in the retail industry across various sectors has become crucial for understanding customer behavior and optimizing marketing strategies. This study aims to segment customers using the integration of K-Means clustering and Support Vector Machine (SVM) models based on LRFM (Length, Recency, Frequency, Monetary) and product preferences. A total of 365,736 transactions involving 24,950 customers were collected and processed, resulting in 8 customer clusters with distinct characteristics. The 8 clusters were determined based on the elbow method, a silhouette score of 0.323, and decisions made by stakeholders. Following the clustering results, SVM classification was performed, demonstrating an accuracy of 99.52%, which indicates the model's ability to effectively identify customer segments. It can be concluded that the combination of K-Means and SVM proves effective in generating relevant and actionable customer segmentation. This method allows companies to identify groups of customers based on their purchasing behavior and provides deep insights into customer preferences. Furthermore, this approach can be applied periodically, enabling segmentation to be updated in accordance with changes in consumer behavior. With the capability for automation, this process not only reduces manual workload but also enhances operational efficiency. Overall, the combination of K-Means and SVM supports the development of more focused marketing strategies and improves strategic decision-making in loyalty programs.

关键词： Support vector machines Industries Seminars Accuracy Consumer behavior Automation Decision making Companies Stakeholders Resource management

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