1. A genetic algorithm based ESC model to handle the unknown initial conditions of state of charge for lithium ion battery cellKristijan Korez, Dušan Fister, Riko Šafarič, 2025, izvirni znanstveni članek Opis: Classic enhanced self-correcting battery equivalent models require proper model parameters and initial conditions such as the initial state of charge for its unbiased functioning. Obtaining parameters is often conducted by optimization using evolutionary algorithms. Obtaining the initial state of charge is often conducted by measurements, which can be burdensome in practice. Incorrect initial conditions can introduce bias, leading to long-term drift and inaccurate state of charge readings. To address this, we propose two simple and efficient equivalent model frameworks that are optimized by a genetic algorithm and are able to determine the initial conditions autonomously. The first framework applies the feedback loop mechanism that gradually with time corrects the externally given initial condition that is originally a biased arbitrary value within a certain domain. The second framework applies the genetic algorithm to search for an unbiased estimate of the initial condition. Long-term experiments have demonstrated that these frameworks do not deviate from controlled benchmarks with known initial conditions. Additionally, our experiments have shown that all implemented models significantly outperformed the well-known ampere-hour coulomb counter integration method, which is prone to drift over time and the extended Kalman filter, that acted with bias.
Ključne besede: enhanced self-correcting model, state of charge estimation, lithium-ion cell parameter identification
Objavljeno v DKUM: 08.01.2025; Ogledov: 0; Prenosov: 2
 Celotno besedilo (5,96 MB) |
2. Segregation dynamics driven by network leadersWen-Xuan Wang, Yuhao Feng, Siru Chen, Wenzhe Xu, Xinjian Zhuo, Huijia Li, Matjaž Perc, 2022, izvirni znanstveni članek Opis: Network segregation - a critical problem in real-life networks - can reveal the emergence of conflicts or signal an impending collapse of the whole system. However, the strong heterogeneity of such networks and the various definitions for key nodes continue to pose challenges that limit our ability to foresee segregation and to determine the main drivers behind it. In this paper, we show that a multi-agent leader-follower consensus system can be utilized to define a new index, named leadership, to identify key leaders in real-life networks. And then, this paper explores the emergence of network segregation that is driven by these leaders based on the removal or the rewiring of the relations between different nodes in agreement with their contribution distance. We finally show that the observed leaders-driven segregation dynamics reveals the dynamics of heterogeneous attributes that critically influence network structure and its segregation. Thus, this paper provides a theoretical method to study complex social interactions and their roles in network segregation, which ultimately leads to a closed-form explanation for the emergence of imbalanced network structure from an evolutionary perspective.
Ključne besede: complex networks, network segregation, multi-agent leader–follower consensus system, key leaders identification, leader, segregation, social physics
Objavljeno v DKUM: 08.07.2024; Ogledov: 122; Prenosov: 13
Celotno besedilo (3,18 MB)
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3. Motor unit identification in the M waves recorded by high-density electromyMiloš Kalc, Jakob Škarabot, Matjaž Divjak, Filip Urh, Matej Kramberger, Matjaž Vogrin, Aleš Holobar, 2023, izvirni znanstveni članek Ključne besede: M wave, high-density surface EMG, firing identification, motor unit
Objavljeno v DKUM: 13.06.2024; Ogledov: 144; Prenosov: 14
Celotno besedilo (2,30 MB)
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4. Identification of motor unit firings in H-reflex of soleus muscle recorded by high-density surface electromyographyMiloš Kalc, Jakob Škarabot, Matjaž Divjak, Filip Urh, Matej Kramberger, Matjaž Vogrin, Aleš Holobar, 2023, izvirni znanstveni članek Ključne besede: motor units identification, high-density surface EMG, decomposition, H-reflex
Objavljeno v DKUM: 13.06.2024; Ogledov: 133; Prenosov: 11
Celotno besedilo (1,43 MB)
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5. Materials for HybridNeuro webinar titled "Validation of results: statistical models and MU identification accuracy"Aleš Holobar, Nina Murks, 2024, zaključena znanstvena zbirka raziskovalnih podatkov Opis: This dataset contains a collection of teaching materials that were used in the HybridNeuro project webinar titled "Validation of results: statistical models and MU identification accuracy". The webinar was presented by Aleš Holobar and covered the complexities of motor unit (MU) identification accuracy, regression analysis and Bayesian models. The primary aim of the webinar was to spark a robust discussion within the scientific community, particularly focusing on the application and implications of linear mixed models and Bayesian regression in the realm of MU identification. The teaching materials include Matlab and R source code for statistical analysis of the included data, as well as three examples of MU identification results in CSV format (from both synthetic and experimental HDEMG signals). The presentation slides in PDF format are also included. The dataset is approximately 9 MB in size.
Ključne besede: HybridNeuro, webinar, teaching materials, statistical models, regression analysis, motor unit identification, matlab, rstudio, statistics, surface high density electromyogram (HDEMG), tibialis anterior, dataset
Objavljeno v DKUM: 30.05.2024; Ogledov: 221; Prenosov: 20
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6. New suptech tool of the predictive generation for insurance companies : the case of the European marketTimotej Jagrič, Daniel Zdolšek, Robert Horvat, Iztok Kolar, Niko Erker, Jernej Merhar, Vita Jagrič, 2023, izvirni znanstveni članek Opis: Financial innovation, green investments, or climate change are changing insurers’ business ecosystems, impacting their business behaviour and financial vulnerability. Supervisors and other stakeholders are interested in identifying the path toward deterioration in the insurance company’s financial health as early as possible. Suptech tools enable them to discover more and to intervene in a timely manner. We propose an artificial intelligence approach using Kohonen’s self-organizing maps. The dataset used for development and testing included yearly financial statements with 4058 observations for European composite insurance companies from 2012 to 2021. In a novel manner, the model investigates the behaviour of insurers, looking for similarities. The model forms a map. For the obtained groupings of companies from different geographical origins, a common characteristic was discovered regarding their future financial deterioration. A threshold defined using the solvency capital requirement (SCR) ratio being below 130% for the next year is applied to the map. On the test sample, the model correctly identified on average 86% of problematic companies and 79% of unproblematic companies. Changing the SCR ratio level enables differentiation into multiple map sections. The model does not rely on traditional methods, or the use of the SCR ratio as a dependent variable but looks for similarities in the actual insurer’s financial behaviour. The proposed approach offers grounds for a Suptech tool of predictive generation to support early detection of the possible future financial distress of an insurance company.
Ključne besede: European insurance market, suptech, supervision, financial deterioration identification, neural networks
Objavljeno v DKUM: 25.03.2024; Ogledov: 220; Prenosov: 22
Celotno besedilo (2,55 MB)
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7. Implementation of acoustic data link technology in industries : diplomsko deloSimon Srebot, 2023, diplomsko delo Opis: The main topic of this bachelor's thesis is the implementation of Acoustic Data Link (ADL) in the industry, where the aim is to find suitable industrial applications where the implementation of ADL would be feasible and expedient. The thesis is based on a six-month Product Innovation Project hosted by the Institute of Industrial Management at the Graz University of Technology and in cooperation with TDK Corporation, where our international team of students were given the challenge of exploring possible industrial applications of ADL.
The bachelor's thesis includes the description, composition and explained operation of ADL technologies as well as other similar technologies. It also includes the comparison between existing technologies and ADL, idea generation methods for possible applications and research results for each use case of the technology. The thesis concludes with a comparison of possible ADL implementations and their market research.
Ključne besede: Data Transfer, Acoustic Data Link, Piezo Elements, Radio Frequency Identification
Objavljeno v DKUM: 28.02.2024; Ogledov: 281; Prenosov: 22
Celotno besedilo (5,34 MB) |
8. The dose–response relationship of quercetin on the motor unit firing patterns and contractile properties of muscle in men and womenKohei Watanabe, Shun Kunugi, Aleš Holobar, 2023, izvirni znanstveni članek Opis: Quercetin is one type of ergogenic aid and its effects on the neuromuscular system have recently attracted interest, but its dose-effect is not yet fully understood. The aim of this study was to examine the effect of different doses of quercetin ingestion on motor unit firing patterns and muscle contractile properties in humans. Thirteen young males and females conducted neuromuscular performance tests before (PRE) and 60 min after (POST) ingestions of 500 or 200 mg of quercetin glycosides (Qg500/Qg200, respectively) or placebo (PLA) on three different days. At PRE and POST, motor unit firing rates were calculated from high-density surface electromyography of the vastus lateralis muscle during 120-s isometric contraction of knee extension at 10% of maximal voluntary contraction. Electrically elicited forces in knee extensor muscles were also measured. After 60 s of voluntary contraction, motor unit firing rates, normalized by the exerted muscle force at POST, were significantly lower at POST than PRE with Qg500 and Qg200 (p < 0.05), but not with PLA (p > 0.05). Changes in motor unit firing rates normalized by the exerted force from PRE to POST were significantly greater with Qg500 than Qg200 at the end of contraction (p < 0.05). Under all three conditions, the electrically elicited force did not significantly change from PRE to POST (p > 0.05). These results suggest that both 500 and 200-mg quercetin ingestions alter motor unit firing patterns, and that quercetin’s effect is at least partially dose-dependent.
Ključne besede: ergogenic aids, nutritional supplementation, multichannel surface electromyography, motor unit identification, quercetin
Objavljeno v DKUM: 09.02.2024; Ogledov: 273; Prenosov: 20
Celotno besedilo (1,14 MB)
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9. Research on vehicle re-identification algorithm based on fusion attention methodPeng Chen, Shuang Liu, Simon Kolmanič, 2023, izvirni znanstveni članek Opis: The specific task of vehicle re-identification is how to quickly and correctly match the same vehicle in different scenarios. In order to solve the problem of inter-class similarity and environmental interference in vehicle images in complex scenes, one fusion attention method is put forward based on the idea of obtaining the distinguishing features of details-the mechanism for the vehicle re-identification method. First, the vehicle image is preprocessed to restore the image's attributes better. Then, the processed image is sent to ResNet50 to extract the features of the second and third layers, respectively. Then, the feature fusion is carried out through the two-layer attention mechanism for a network model. This model can better focus on local detail features, and global features are constructed and named SDLAU-Reid. In the training process, a data augmentation strategy of random erasure is adopted to improve the robustness. The experimental results show that the mAP and rank-k indicators of the model on VeRi-776 and the VehicleID are better than the results of the existing vehicle re-identification algorithms, which verifies the algorithm's effectiveness.
Ključne besede: vehicle re-identification, attention mechanism, key-point, local feature, feature fusion
Objavljeno v DKUM: 06.02.2024; Ogledov: 348; Prenosov: 25
Celotno besedilo (5,28 MB)
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10. NARX Deep Convolutional Fuzzy System for Modelling Nonlinear Dynamic ProcessesMarjan Golob, 2023, izvirni znanstveni članek Opis: This paper presents a new approach for modelling nonlinear dynamic processes (NDP). It is based on a nonlinear autoregressive with exogenous (NARX) inputs model structure and a deep convolutional fuzzy system (DCFS). The DCFS is a hierarchical fuzzy structure, which can overcome the deficiency of general fuzzy systems when facing high dimensional data. For relieving the curse of dimensionality, as well as improving approximation performance of fuzzy models, we propose combining the NARX with the DCFS to provide a good approximation of the complex nonlinear dynamic behavior and a fast-training algorithm with ensured convergence. There are three NARX DCFS structures proposed, and the appropriate training algorithm is adapted. Evaluations were performed on a popular benchmark—Box and Jenkin’s gas furnace data set and the four nonlinear dynamic test systems. The experiments show that the proposed NARX DCFS method can be successfully used to identify nonlinear dynamic systems based on external dynamics structures and nonlinear static approximators.
Ključne besede: process identification, input-output modelling, NARX model, decomposed fuzzy system, hierarchical fuzzy system, deep convolutional fuzzy system
Objavljeno v DKUM: 30.11.2023; Ogledov: 422; Prenosov: 12
Celotno besedilo (5,86 MB)
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