AGH (Akademia Górniczo-Hutnicza) University of Science and Technology: Journals
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RECONSTRUCTION OF MUON BUNDLES IN KM3NET DETECTORS USING MACHINE LEARNING METHODS: on behalf of the KM3NeT collaboration
No full textThe KM3NeT Collaboration is installing the ARCA and ORCA neutrino detectorsat the bottom of the Mediterranean Sea. The focus of ARCA is neutrinoastronomy, while ORCA is optimised for neutrino oscillation studies. Bothdetectors are already operational in their intermediate states and collect valuabledata, including the measurements of the muons produced by cosmic rayinteractions in the atmosphere. This work explores the potential of machinelearning models for the reconstruction of muon bundles, which are multi-muonevents. For this, data collected with intermediate detector configurations ofARCA and ORCA was used in addition to simulated data from the envisagedfinal configurations of those detectors. Prediction of the total number of muonsin a bundle as well as their total energy and even the energy of the primarycosmic ray is presented.
The combination of soil magnetometry with portable XRF spectroscopy as an effective tool for the assessment of sources of trace elements in topsoil
Full text linkThe origin of potentially toxic elements (PTEs) may influence their persistence, mobility and determine the extent to which they pose a threat to the soil environment. Therefore, the research objective of this study was to obtain information on the origin of nine PTEs present in the soil at two Natura 2000 protected areas. The second objective was to test the usability of three popular soil indices in assessing soil pollution in the study area. The research was carried out in two forested areas belonging to the Natura 2000 network of European protected areas, located in the Cieszyn region (southern Poland) on the Polish-Czech border. The research involved the analysis of the distribution of elements in topsoil cores (to 30 cm depth), based on high-resolution measurements obtained from a combination of soil magnetometry and portable XRF spectrometer (pXRF). Measurement of the vertical distribution of volume magnetic susceptibility (κ) along the core was performed using a Bartington MS2C sensor and the analysis of PTE contents using an Explorer 7000 XRF spectrometer. Based on the obtained results, three popular geochemical indices of soil contamination with metals and metalloids were calculated: geo-accumulation index (Igeo), single pollution index (PI), and enrichment index (EF).Research has shown that the use of a pXRF spectrometer allows for the assessment of the distribution of PTEs in the soil profile with high accuracy, as well as a precise determination of the source of these elements and tracking the migration of pollutants deep into the soil profile. The peak of magnetic susceptibility values in the upper part of the profile strongly correlated with the contents of Pb, As and Zn, which confirmed the anthropogenic origin of these PTEs in the soil in both study areas. The distribution pattern of most of the remaining studied elements (Ti, V, Cr, Co, and Ni) in the soil profile and the analysis of geochemical indicators (Igeo , PI and EF) indicated their lithogenic and/or pedogenic origin.The use of a pXRF spectrometer allows the assessment of the distribution of PTEs in the soil profile with high measurement resolution and enables precise determination of the source of elements, tracking the migration of pollutants down the soil profile. The combination of soil magnetometry and pXRF, supported by the analysis of geochemical indicators, has proven to be a very effective tool in examining soil contamination and environmental site assessment
Eye Disease Segmentation using Hybrid Neural Encoder Decoder based Unet Hybrid Inception
Full text linkDiabetic retinopathy (DR) is one of the major causes of vision problems worldwide. With proper treatment, early diagnosis of DR can prevent the progression of the disease. In this paper, we present a combinative method using U-Net with a modified Inception architecture for the diagnosis of both the diseases. The proposed method is based on deep neural architecture formalising encoder decoder modelling with convolutional architectures namely Inception and Residual Connection. The performance of the proposed model was validated on the IDRid 2019 contest dataset. Experiments demonstrate that the modified Inception deep feature extractor improves DR classification with a classification accuracy of 99.34% in IDRid across classes with comparison to Resnet. The paper Benchmark tests the dataset with proposed model of Hybrid Dense-ED-UHI: Encoder Decoder based U-Net Hybrid Inception model with 15 fold cross validation. The paper in details discusses the various metrics of the proposed model with various visualisation and multifield validations
Mitigating Central Tendency And Acquiescence Biases in Survey Design: A Methodological Exploration With Empirical Evidence
Full text linkThis paper presents a survey design methodology aimed at mitigating central tendency and acquiescence biases, which are commonly encountered in traditional Likert-scale surveys. The proposed approach employs a forced ranking method, using a case study involving 220 engineering students at the University of Zagreb as a source of data to assess whether respondents exhibit patterns of systematically avoiding honest answers for any reason. Statistical analysis demonstrates the effectiveness of the design in reducing these biases. The results provide strong evidence that the method developed in this article can minimize response distortions without sacrificing data richness. While the primary focus is on the methodological aspects, the case study illustrates the potential of this approach for ethical and attitudinal research. The study concludes with recommendations for refining survey techniques and exploring their broader applicability in different populations and contexts.This paper presents a survey design methodology aimed at mitigating central tendency and acquiescence biases, which are commonly encountered in traditional Likert-scale surveys. The proposed approach employs a forced ranking method, using a case study involving 220 engineering students at the University of Zagreb as a source of data to assess whether respondents exhibit patterns of systematically avoiding honest answers for any reason. Statistical analysis demonstrates the effectiveness of the design in reducing these biases. The results provide strong evidence that the method developed in this article can minimize response distortions without sacrificing data richness. While the primary focus is on the methodological aspects, the case study illustrates the potential of this approach for ethical and attitudinal research. The study concludes with recommendations for refining survey techniques and exploring their broader applicability in different populations and contexts
Strategies for trading in money markets
Full text linkMoney market trading is a part of Investment Banking and highly business relevant to the Swiss Banking sector. It is astonishing, therefore, that there are very few scientific studies or papers available on this subject. The goal of this article is to clarify and analyse the relevance, chances, and risks of money market trading within the Swiss banking sector and provides comprehensive information not only to professionals such as employees of banks but also for other clients interested in this specific topic. Various aspects of the money market were analysed, taking in a mix of interviews with experienced banking professionals as well as literary analysis. These aspects include products of and participants in the money market and combine it with the politics of the Swiss National Bank over the last few years. Furthermore, the implications of Basel III on cash trading were explored and explained by way of an example. From the interviews with banking experts, some basic requirements for the job profile of money market traders were defined, 5 strategies for money trading designed and related risks identified
CHARACTERISTIC SKY BACKGROUND FEATURES AROUND GALAXY MERGERS
Full text linkIn the context of finding galaxy merger in large-scale surveys, we applied MachineLearning algorithms that, instead of using the images as it is the currentstandard, made used of flux measurements. Training multiple NNs using aclass-balanced dataset of mergers and non-mergers Sloan Digital Sky Survey,we found that the sky background error parameters could provide a validation92.64 ± 0.15 % accuracy of and a training accuracy of 92.36 ± 0.21 %.Moreover, analysing the NN identifications led us to find that a simple decisiondiagram using the sky error for two flux filters is enough to get a 91.59 % accuracy.By understanding how the galaxies vary along the diagram, and trying toparametrize the methodology in the deeper images of the Hyper Suprime-Cam,we are currently trying to define and generalize this sky error-based methodology
Tożsamość narracyjna. Strategie konstytuowania siebie w relacji z miejscem poprzez opowieść – na przykładzie Nowohuckiej telenoweli Renaty Radłowskiej
Full text linkAnaliza narracyjna 19 reportaży składających się na zbiór Nowohucka telenowela Renaty Radłowskiej pokazuje, jak budowniczowie i pierwsi mieszkańcy Nowej Huty używają opowieści do konstruowania własnej tożsamości w relacji z miejscem. Podstawą teoretyczną przedstawionych badań jest narratologia Mieke Bal, która zakłada trójdzielność tekstów narracyjnych (tekst, opowieść i fabuła). Spisane przez reporterkę historie zawierają tę samą (lub podobną) opowieść, każda stanowi jednak odrębny tekst narracyjny. Analizowanie ich swoistości prowadzi do wniosków na temat intencji i statusu bohaterów. Dla świadków i uczestników budowy Nowej Huty opowiadanie staje się gestem emancypacji wobec „tożsamości mniemanych” – wizerunków projektowanych przez PRL-owskich ideologów czy funkcjonujących społecznie stereotypów. Efekty badań mogą stanowić uzupełnienie dla faktografii dotyczącej początków Nowej Huty.
The impact of Ukrainian immigration on inter-voivodship migration in Poland – an attempt to estimate the regional “displacement” effect using the input-output method
Full text linkThe aim of the article is to estimate the strength of the “displacement” effect of the residents of Polish voivodeships to other regions of the country and determine the regional differentiation caused by the mass inflow of immigrants from Ukraine to Poland in 2022. The study used a modified input-output method, which allows for capturing and balancing both internal and external migration. The first stage of the study consisted in constructing inter-voivodeship migration tables, taking into account the inflow of immigrants from Ukraine. In the second stage of the study, the “displacement” effect was measured using the input-output method, which showed its strong spatial differentiation – the strongest effect was observed in voivodeships with a relatively higher level of the unemployment rate and lower wages (i.e. Warmińsko-Mazurskie and Świętokrzyskie), while the weakest – in voivodeships with large urban centres and capacious labour markets (i.e. Mazowieckie, Małopolskie, Dolnośląskie). The study also revealed a paradox, namely that the eastern provinces closest to Ukraine (i.e. Podkarpackie, Lubelskie) showed a relatively weak capacity to absorb Ukrainian immigrants, whose admission could cause greater disruptions in the local labour markets in these regions than in more distant provinces. The construction of the migration input-output tables was mainly based on data from the Bank Danych Lokalnych Głównego Urzędu Statystycznego (Local Data Bank of Central Statistical Office of Poland) and the Office for Foreigners for the years 2022 and 2015
ANALYSIS OF TRANSIENT STATES IN THE POWER SUPPLY SYSTEM FOR SELECTED INDUSTRIAL ROBOT
Full text linkIndustrial robots are controlled by dedicated controllers, which are powered by single-phase or three-phase power supply system. The main power parameters characterizing the power supply system of these robots are: nominal supply voltage (1-phase: 100-120 V, 200-240 V or 3-phase 200-575 V AC), frequency of the supply voltage (50 or 60 Hz), nominal power consumed by industrial robot. The dynamics of power consumption in the power supply system of controlled robot can be studied by recording instantaneous values of voltages and currents in each phase of the power grid. In this article are presented results for measurements of mentioned instantaneous values for chosen single-phase powered robot, taken by specialized recorder. Obtained measurements from recorder allows to calculate numerically various energetic values in the power supply system of robot: peak-peak values, RMS values, coefficients of deformation and values of harmonic amplitudes (FFT), values of active, reactive and apparent power and the power coefficient (tgϕ). The analysis of waveforms of instantaneous values of voltage and current allows to determine the occurrence of transient states during work of robot axes and characterizing its duration and the range of value changes). Carried out analyses can be using to properly design protection systems of the power supply system, at eventual selection of filters for higher harmonics and to determine effective power consumption of studied robot. The analyses of transient states which occurred during work of studied robot in this publication significantly expand the knowledge about the dynamics of power consumption and its possible impact on the quality of electricity in the power supply grid