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1

Wzorcowanie mierników jakości energii klasy A

Pniewski Michał

Wiadomości Elektrotechniczne

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2025

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R. 93, nr 2

3--7

PL

Niniejszy artykuł jest próbą odpowiedzi na najczęściej stawiane pytania dotyczące wzorcowania analizatorów jakości energii elektrycznej (AJEE). W artykule przedstawiono wybrane zagadnienia dotyczące wzorcowania mierników jakości klasy A określonej w normie PN-EN 61000-4-30 [7]. Omówiono zasady zachowania spójności pomiarowej oraz dotyczące zasady wzorcowania przyrządów pomiarowych w zakresie metrologii prawnej i w zakresie działalności akredytowanych laboratoriów wzorcujących. Szczegółowo pokazano zakres wzorcowania AJEE w akredytowanym laboratorium wzorcującym. Przedstawiono zagadnienie zmiany oprogramowania układowego i jego wpływu na ważność świadectwa wzorcowania AJEE

EN

This article is an attempt to answer the most common questions concerning the calibration of power quality analysers (AJEE). This article presents selected issues related to the calibration of class A quality meters specified in PN-EN 61000-4-30 [7]. The principles of maintaining measurement traceability were discussed. The principles concerning the calibration of measuring instruments in the scope of legal metrology and the scope of activity of accredited calibration laboratories were presented. The scope of AJEE calibration in an accredited calibration laboratory was discussed in detail. The issue of changing the firmware and its impact on the validity of the AJEE calibration certificate was discussed.

2

Grouping rice varieties in Morocco based on key agronomic traits : A PCA and HCA approach

Elwahab Fathalah, Sedki Mohamed, Karidioula Lagnigui C., Boukita Hassan, Brhadda Najiba, Ziri Rabea

Journal of Water and Land Development

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2025

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no. 65

230--237

EN

The identification and classification of rice varieties based on key agronomic traits are essential for enhancing productivity and adaptability in diverse growing environments. This study focused on 18 rice varieties cultivated in Morocco, comprising 14 Korea-Africa Food and Agriculture Cooperation Initiative (KAFACI) lines, three National Institute of Agricultural Research (Fr.: Institut national de la recherche agronomique - INRA) Morocco varieties, and a control cultivar, ‘Lagostino’, widely used by Moroccan farmers. The experiment was conducted at the Sidi Allah Tazi Experimental Domain (Fr.: Domaine Expérimental de Sidi Allal Tazi) using a randomised complete block design (RCBD) with three replications. Hierarchical cluster analysis (HCA) and principal component analysis (PCA) were utilised to group varieties based on significant agronomic traits. The analysis revealed four distinct clusters. Cluster 1, including ‘KF190066’, showed high values for plant height, 1000-seed weight, and panicle length. Cluster 2, represented by the control cultivar ‘Lagostino’, was characterised by an earlier heading and fewer panicles per plant. Cluster 3, including ‘KF190064’ and ‘KF190065’, displayed the highest straw and seed yields despite shorter panicles. Cluster 4, comprising ‘Ka WS 9294292’, ‘Nachat’ (INRA Morocco), ‘CB MS11’, and ‘Hayat’ (INRA Morocco), exhibited extended heading and maturity durations, alongside higher tiller and panicle counts per plant. These findings highlight the agronomic diversity potential of rice varieties in Morocco, providing critical insights for breeding programs. The identification of superior varieties, such as ‘KF190064’, ‘Hayat’, and ‘KF190066’, reinforces their potential for boosting rice production and sustainability under Morocco’s agro-climatic conditions.

3

The correlation between microplastics characteristics and sediment grain size to microplastics accumulation in coral reef sediment in Gede Island, Rembang, Indonesia

Widiaratih Rikha, Sulhana Baiq Lista Azkia, Putranto Ari Bawono, Maslukah Lilik, Ismanto Aris, Ayuningrum Diah, Hadibarata Tony, Satya Eridhani Dharma

Journal of Ecological Engineering

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2025

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Vol. 26, nr 3

200--212

EN

In general, microplastics (MPs) have been identified at higher concentrations in marine sediments than in seawater. This is attributed to the trapping effect of sediments on MPs. MPs in the ocean undergo a sinking process, ultimately accumulating in marine sediments. MPs have been identified as a significant threat to marine biodiversity, particularly in coral reef habitats, due to their potential carcinogenic effects. This study examines the correlation between MPs characteristics – specifically, size and shape – and sediment grain size with MPs abundance in adjacent coral reef sediments in Rembang Regency, Central Java, Indonesia. To achieve this, Pearson’s correlation and principal component analysis (PCA) methods were employed. The findings indicate that most MPs are concentrated in nearshore regions near anthropogenic sources. Moreover, the correlation based on Pearsons was found to be particularly significant for MPs size, shape, and grain size, with values of 0.84, 0.754, and 0.431, respectively. The PCA result demonstrates that the greater the abundance of MPs in the sediment, particularly those that are MPs smaller in size and compact shape, such as fragments and pellets, the greater the likelihood of their sinking and infiltration into the sediment. This finding highlights the crucial role of MPs size and shape in tight relationship to their density in determining the rate of sinking and infiltration of MPs into the sediment

4

On explainability of cluster prototypes with rough sets: A case study in the FMCG market

Grzegorowski Marek, Janusz Andrzej, Marcinowski Łukasz, Skowron Andrzej, Ślęzak Dominik, Śliwa Grzegorz

International Journal of Applied Mathematics and Computer Science

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2025

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Vol. 35, no. 1

19--31

EN

Despite the growing popularity of machine learning (ML), such solutions are often incomprehensible to employees and difficult to control. Addressing this issue, we discuss some essential problems of explainable ML applications in the fast-moving consumer goods (FMCG) market. This research puts forward a new approach to effective supply management by utilizing rough sets (RST), distance-based clustering, and dimensionality reduction techniques. In the presented case study, we aim to reduce the work done by experts by applying a single delivery plan to many similar points of sale (PoS). We achieve this objective by clustering vending machines based on historical sales patterns. To verify the feasibility of such an approach, we performed a series of experiments related to demand prediction on two data representations with various clustering techniques. The conducted experiments confirmed that, without losing quality in terms of MAE and RMSE, we could operate on PoS in an aggregate manner, thus reducing the workload of preparing delivery plans.

5

Zastosowanie analizy głównych składowych i maszyn wektorów nośnych do klasyfikacji obiektów powietrznych

Wajszczyk Bronisław, Banaś Wiktoria, Błaszczyk Agnieszka, Kapski Adrian, Słowak Paweł

Elektronika : konstrukcje, technologie, zastosowania

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2025

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Vol. 66, Nr 10

2--5

PL

W artykule przedstawiono badania dotyczące zastosowania analizy głównych składowych (PCA) w połączeniu z maszynami wektorów nośnych (SVM) do klasyfikacji obiektów powietrznych na podstawie parametrów kinematycznych. Wygenerowano syntetyczne zbiory danych reprezentujące różne typy obiektów, takie jak samoloty, drony, ptaki i balony, opisane cechami lotu, m.in. średnią wysokością, prędkością, przyspieszeniem i długością trajektorii. Analiza PCA została wykorzystana do redukcji wymiarowości i wizualizacji separowalności danych, a klasyfikator SVM - do nadzorowanej klasyfikacji w przestrzeni zredukowanych cech. Wyniki wskazują, że połączenie PCA i SVM umożliwia skuteczną klasyfikację nawet w przypadku częściowego nakładania się klas. Metoda ma potencjał zastosowania w praktycznych systemach rozpoznawania obiektów powietrznych opartych na danych radarowych lub fuzji czujników.

EN

This paper presents a study on the use of Principal Component Analysis (PCA) combined with Support Vector Machines (SVM) for the classification of airborne objects based on kinematic parameters. Synthetic datasets representing different aerial objects, such as airplanes, drones, birds, and balloons, were generated using statistical distributions of flight features, including average height, velocity, acceleration, and trajectory length. PCA was applied to reduce dimensionality and visualize data separability, while SVM was employed as a supervised learning classifier in the reduced feature space. The results show that the PCA-SVM combination enables effective classification even when class distributions partially overlap. The method demonstrates potential for practical implementation in radar-based or sensor fusion systems for aerial object identification.

6

Application of the D5 discipline from the G8D method in solving quality management problems for NOK parts

Cyganiuk Joanna, Kuryło Piotr, Al-Zubiedy Ali, Mazur Magdalena

Budownictwo o Zoptymalizowanym Potencjale Energetycznym

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2025

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Vol. 14

55--65

EN

The article discusses what is the G8D method, focusing on the fifth discipline of this method, D5, which involves the selection and verification of permanent corrective actions for root causes and escape points. The rationale for applying the G8D method and using the D5 discipline of this method was analyzed for the case of a NOK part, specifically a part with an undrilled hole. The algorithm that must be applied to correctly go through all the steps of the D5 discipline has been presented, in order to obtain verified corrective actions both for the point in the process where NOK parts are produced and for the control point where NOK was not detected. The practical application of this discipline for selected initial conditions (the transition through disciplines D0-D4), as well as the solution for the problem of producing defective products that protect the production system from further manufacturing of such parts has been presented. In construction literature, a similar approach is applied in the quality management of industrial prefabricates, where systematic defect analysis leads to the optimization of production processes. The applicability of the D5 discipline and the Poka Yoke method for securing the production station against the possibility of producing a NOK part was presented.

7

Learning a s part of knowledge exchange processes in the context of online work, based on the example of generation z employees

Albrychiewicz-Słocińska Anna, Nejman Żaneta, Varga Erika

Zeszyty Naukowe. Organizacja i Zarządzanie / Politechnika Śląska

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2024

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z. 191

9--26

EN

Purpose: The objective of the argument in this paper is to attempt at answering the question whether learning and knowledge exchange are the key factors determining online work preferences for Generation Z employees. Design/methodology/approach: The essence of knowledge management is that all knowledge, both explicit and tacit, accumulated by an organization becomes easily accessible to each of its members. This is important for decision-making processes and allows the organization to become more agile. Knowledge management is most often associated with modern information technologies. Thanks to them, streams of various data can be processed and analyzed in many different ways. However, in the literature there is an increasingly common attitude that more attention should be paid not only to the technological but also to the human aspect of knowledge management. The processes of knowledge exchange among employees have been subject to extensive research and studies, yet the recent years have added another thread to the discussion about the matter, i.e. a significant proportion of employees switching to the online work model. Based on the findings of the studies conducted on a group of employees representing Generation Z, the Principal Component Analysis (PCA) technique was applied to organize the factors with the highest relevance for the respondents in online work. Findings: PCA demonstrated that the components recognized as most important were those relating to knowledge transfer and their impact on employee efficiency, and on the other hand employee relations as a factor that supports the learning processes. Research limitations/implications: In order to dwell upon the underlying causes of this situation, it should be recommended to proceed with further in-depth qualitative research. Practical implications: What the research communicates to the organization is that although Generation Z members are aware of the significance of the knowledge transfer and learning processes and they understand the role of peer relations in these processes, they are unable to overcome the social barriers created by the online working system due to lack of appropriate skills. Originality/value: The paper reveals new aspects that play crucial role in shaping Generation Z attitude to online work from one side. On the other hand it also helps to design synthetic tool researching this area in the future.

8

Analiza porównawcza wydajności architektury głębokiego uczenia się w klasyfikacji obrazów podwodnych

Mehrunnisa, Juszka Dawid, Zhang Yi, Leszczuk Mikołaj

Przegląd Telekomunikacyjny + Wiadomości Telekomunikacyjne

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2024

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nr 4

187--190

PL

W tym badaniu oceniamy wydajność modeli VGG-16, EfficientNetB0 i SimCLR w klasyfikacji 5000 podwodnych zdjęć. Zbiór danych podzielono na 75 procent do celów szkoleniowych i 25 procent do testów, przy czym ręczne etykietowanie zapewniało dokładne odwzorowanie podstaw. Zastosowaliśmy grupowanie K-średnich do segmentacji zbioru danych na podstawie podobieństwa oraz PCA w celu zmniejszenia wymiarowości przy jednoczesnym zachowaniu struktury semantycznej. Zróżnicowany zbiór danych zwiększa zdolność modeli do uogólniania w różnych warunkach. Oceniliśmy grupowanie i klasyfikacje za pomocą wyniku sylwetki, wskaźnika Daviesa-Bouldina i wskaźnika Calinskiego-Harabasza. Wyniki ujawniają mocne i słabe strony każdego modelu, dostarczając informacji na temat przyszłych ulepszeń w analizie obrazów podwodnych.

EN

In this study, we assess the performance of the VGG-16, EfficientNetB0, and SimCLR models in classifying 5,000 underwater images. The dataset was split into 75 perceent for training and 25 percent for testing, with manual labeling ensuring accurate ground truth. We used K-means clustering to segment the dataset based on similarity, and PCA to reduce dimensionality while maintaining the semantic structure. The diverse dataset boosts the models’ ability to generalize across various conditions. We evaluated clustering and classification using the silhouette score, Davies-Bouldin index, and Calinski-Harabasz index. The results reveal each model’s strengths and weaknesses, providing insights for future improvments in underwater image analysis.

9

Czynniki wpływające na rozwój polskich winnic na przykładzie województwa wielkopolskiego

Elwira BRODNICKA

Problemy Jakości

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2024

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R. 56, nr 6

17--27

PL

Cel: Celem głównym artykułu jest określenie ważności czynników wewnętrznych i zewnętrznych wpływających na rozwój polskich winnic na przykładzie województwa wielkopolskiego. Celem pomocniczym jest dokonanie charakterystyki właścicieli tych winnic i ustalenie czynników determinujących decyzję o założeniu winnicy przez inwestora. Projekt badania/metodyka badawcza/koncepcja: Do realizacji celu wykorzystano autorski kwestionariusz ankietowy oraz dane udostępnione przez KOWR. Badanie przeprowadzono metodą CAWI z wykorzystaniem formularza Google Forms. Uzyskane wyniki opracowano za pomocą analizy PCA oraz analizy CA. Przeprowadzono także analizę branży winiarskiej w latach gospodarczych 2011/2012 – 2021/2022. Wyniki/wnioski: W badaniu wzięło udział 11 (52%) właścicieli wielkopolskich winnic. W wyniku przeprowadzonych badań stwierdzono, że najczęściej osobą zakładającą winnicę jest mężczyzna po 50. roku życia. Najbardziej kluczowe predyspozycje mające wpływ na podjęcie decyzji o założeniu winnicy przez inwestora to hobby – czynniki o charakterze biznesowym, zaś o charakterze personalnym – kompetencje menadżerskie. Czynnikami wewnętrznymi ułatwiającymi zakładanie i funkcjonowanie winnic w województwie wielkopolskim są aspekty finansowe i społeczne, zaś czynnikami utrudniającymi – aspekty organizacyjno-zarządcze. Natomiast czynnikami zewnętrznymi ułatwiającymi zakładanie i funkcjonowanie winnic na badanym obszarze są czynniki inicjujące i środowiskowe, zaś czynnikami utrudniającymi są głównie aspekty koniunkturalne. Ograniczenia: Do ograniczeń prowadzonych badań można zaliczyć problem z identyfikacją winnic w województwie wielkopolskim wynikającą z braku ich jednolitego spisu. Zastosowanie praktyczne: Uzyskane wnioski z przeprowadzonych badań mogą stanowić drogowskaz dla potencjalnych inwestorów, wskazując na czynniki ograniczające i sprzyjając powstawaniu i funkcjonowaniu winnic. Oryginalność/wartość poznawcza: Dotychczas w literaturze przedmiotu nie prowadzono badań dotyczących wpływu czynników wewnętrznych i zewnętrznych na rozwój polskich winnic oraz czynników wpływających na podjęcie decyzji przez inwestora o założeniu winnicy.

EN

Purpose: The primary objective is to determine the importance of internal and external factors influencing the development of Polish vineyards, using the Wielkopolska Voivodeship as a case study. The secondary objective is to characterize vineyard owners and identify the factors determining an investor’s decision to establish a vineyard. Design/methodology/approach: The goal was achieved using an original survey questionnaire and data from the National Support Center for Agriculture (KOWR). The study was conducted using the CAWI method via Google Forms. The results were analyzed using the PCA and CA methods. The wine industry in the marketing years 2011/2012 – 2021/2022 was also analyzed. Findings/conclusions: The study involved 11 (52%) vineyard owners in Wielkopolska. The founders of vineyards are most often men over 50. The key predispositions influencing the investment decision are, on the business side, the hobby aspect, and on the personal side, managerial competences. Internal factors supporting the development of winemaking are financial and social aspects, while organizational and management aspects create challenges. External factors supporting development are initiation and environmental factors, while economic factors hinder it. Research limitations: The limitations of the conducted research include the problem of identifying vineyards in the Wielkopolska province resulting from the lack of a uniform list. Practical implications: The results can serve as a guide for potential investors by indicating factors that hinder or facilitate the development of vineyards. Originality/value: The literature on the subject lacks research on the importance of environmental impact on the development of Polish vineyards and investment decisions.

10

Influence of the type of fuel used on the content of gamma radionuclides in the soot from the smoke ducts of the home furnaces

Stobiński Marcin

Nukleonika

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2024

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Vol. 69, No. 2

93--97

EN

This paper presents the results of the measurements of gamma radioactive isotopes in soot samples from 15 different chimneys of household furnaces fired with various types of solid fuel. Soot samples were collected by the chimney sweep during the mandatory periodic cleaning of the chimneys. The γ-spectrometry technique using the high-purity germanium (HPGe) detector was employed for radiometry of the above-mentioned soot. It was found that the determined activity of gamma isotopes in soot is at a level similar to that in fly ash from power plants around the world. Artificial 137Cs was detected only in the soot from the combustion of biofuel or mixed fuel. The results obtained were chemometrically analyzed to find the relationship between the fuel used and the gamma isotope content in the soot. The analysis of 137Cs, 40K, 228Th, and 226Ra is sufficient to differentiate between the soot obtained and tested, and it varied with the fuel type burned (fossil fuels/biofuels).

11

Assessment of heavy metal pollution in groundwater using a multivariate analysis approach

Sbai Khalid, Tahri Latifa, Hafiane Fatima Zahra, Halima Oumaima Iben, Fekhaoui Mohammed

Journal of Water and Land Development

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2024

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no. 61

175--182

EN

The current study aims to assess underground water pollution using an integrated approach that combines statistical methods such as principal component analysis (PCA) and water quality diagrams (Piper diagram, Schoeller-Berkalov diagram). A total of twenty water samples were collected from the Tiflet region in the Sebou basin and analysed for various physicochemical parameters, including temperature, pH, and heavy metal concentrations (Cu2+, Zn2+, Fe2+ and Pb2+). The average concentrations of Pb2+, Zn2+, Cu2+, and Fe2+ in the water samples were found to be 41.9, 14.8, 20.1, and 8.1 mg∙dm-3, respectively. These concentrations indicate a significant presence of heavy metals in the groundwater samples. Therefore, it can be concluded that the groundwater in this area is heavily polluted with heavy metals and other pollutants. This finding raises concerns regarding the use of this water for irrigation and agricultural activities in the region. This suggests that these four components play a crucial role in determining the overall water quality. The distribution patterns of the metals Pb2+, Zn2+, Cu2+, and Fe2+ in the well water within the study area are of particular environmental concern. It is recommended to establish a monitoring network to ensure the sustainable management of water resources in order to address this issue effectively.

12

Field Measurements and Machine Learning Algorithms to Monitor Water Quality in Lakes Located in Landscape Parks – A Case Study

Walczak Natalia, Walczak Zbigniew, Laks Ireneusz

Journal of Ecological Engineering

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2024

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Vol. 25, nr 1

49--64

EN

One of the greatest threats to many lakes is their accelerated eutrophication resulting from anthropogenic pressure, agricultural intensification, and climate change. A very important element of surface water protection in environmentally conserved areas is the proper monitoring of water quality and detection of potential threats by examining the physicochemical properties of water and performing statistical analyses that enable possible exposure of unfavourable trends. The article presents the analyses of the results of measurements made in three lakes located in the Sierakowski Landscape Park. As part of the measurements, water quality indicators i.e., phosphorus, nitrogen, BOD5 and COD, were determined monthly for a year at the inflows and outflows of the studied lakes. The test results of selected water quality indicators were analysed using machine learning algorithms i.e., PCA and k-means. The conducted tests enabled statistical estimation of changes in water quality indicators in the reservoirs and evaluation of their correlation.

13

The Use of Machine Learning Methods to Determine Risk Zones for Construction Disasters Caused by Wind - A Case Study in Poland

Laks Ireneusz

Inżynieria Mineralna

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2024

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Vol. 2, no. 2

art. no. 62

EN

The increasing availability and use of artificial intelligence (AI) methods and algorithms have led to their widespread use in analyses aimed at identifying the decisive factors that influence the course of a studied phenomenon or process. AI algorithms include a wide range of methods. They can be used together or separately. The article describes the use of two Machine Learning (ML) methods, PCA and k-means, to identify parameters that may increase or decrease the risk of construction disasters caused by strong winds in Poland. The analysis was conducted using a unique dataset on construction disasters in Europe, sourced from the General Office of Construction Supervision in Poland for the period 1995-2019. The occurrence of disasters was categorised by voivodeship and cause, with information provided on the number of people injured. ML analyses were conducted to determine whether land development, population density, and weather factors, such as wind, have an impact on the number of recorded disasters.

PL

Zwiększająca się dostępność i wykorzystanie metod oraz algorytmów sztucznej inteligencji prowadzą do ich szerokiego zastosowania w analizach mających na celu identyfikację czynników decydujących o przebiegu badanego zjawiska lub procesu.

14

Impact of agriculture on soil and water quality in the north-east of Algeria: Boumaiza Plain

Majour Habiba, Sedrati Nassima, Halimi Fahima, Attoui Badra

Geomatics, Landmanagement and Landscape

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2024

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no. 4

7--21

EN

The Boumaiza Plain is situated in the northeast of Algeria and encompasses a vast area of the ElKebir West watershed, which has a significant water potential. The intensification of agricultural activities in this region has led to a notable increase in the use of phytosanitary products, which may impact the physico-chemical quality of groundwater and soil. A sampling campaign was conducted in 2022 to assess the impact of agriculture. To achieve this aim, we analysed 12 points, comprising 7 wells and 5 boreholes, as well as the grain size and physicochemical characteristics of 12 soil samples. The methodology employed for processing the analysis results is based on multivariate statistical methods. The results of the analyses revealed pollution of agricultural origin. This is substantiated by the observation of relatively high levels of nutrients, including NO2, NO3, as well as potassium which exceed 5 mg/l in water and 40.76 mg/l for soil analyses. Principal component analysis (PCA) was also applied, while the opposition of physicochemical elements to nitrites, nitrites, chlorides, sulfates, ammonium, and potassium variables highlights another mechanism involved in water mineralization, which is governed by the inputs of surface water fromagricultural areas and the intrusion of rich in organic matter waste from domesticated animals.

PL

Równina Boumaiza znajduje się w północno-wschodniej Algierii i obejmuje rozległy obszar zlewni El-Kebir West, który ma znaczny potencjał wodny. Intensyfikacja działalności rolniczej w tym regionie doprowadziła do znacznego wzrostu stosowania produktów fitosanitarnych, co może mieć wpływ na jakość fizykochemiczną wód gruntowych i gleby. W 2022 r. przeprowadzono kampanię pobierania próbek w celu oceny wpływu rolnictwa. Aby osiągnąć ten cel, przeanalizowaliśmy 12 punktów, obejmujących 7 studni i 5 otworów wiertniczych, a także wielkość ziarna i właściwości fizykochemiczne 12 próbek gleby. Metodologia zastosowana do przetwarzania wyników analizy opiera się na wielowymiarowych metodach statystycznych. Wyniki analiz ujawniły zanieczyszczenie pochodzenia rolniczego. Potwierdza to obserwacja stosunkowo wysokich poziomów składników odżywczych, w tym NO 2 , NO 3 , a także potasu, które przekraczają 5 mg/l w wodzie i 40,76 mg/l w analizach gleby. Zastosowano również analizę głównych składowych (PCA), natomiast kontrast pierwiastków fizykochemicznych ze zmiennymi azotynami, azotynami, chlorkami, siarczanami, amoniakiem i potasem wskazuje na inny mechanizm zaangażowany w mineralizację wody, który jest regulowany przez dopływ wód powierzchniowych z obszarów rolniczych i wnikanie bogatych w materię organiczną odpadów pochodzących od zwierząt domowych.

15

Structural and mineralogical mapping using multispectral satellite data (Aster, Landsat 8 OLI, and Sentinel 2B) combined with field work in the Western High Atlas, Morocco

Elbakhouch Nouhaila, Ibouh Hassan, Touil Ahmed, Chafiki Driss

Geologos

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2024

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Vol. 30, No. 2

119--136

EN

The Tighardine area in the Western High Atlas Massif is composed of rocks ranging in age from Neoproterozoic to Cenozoic. The area is intensely deformed with a multidirectional diversity of faults and also hosts a polymetallic ore deposit (Tighardine mine) and prospects of significant economic value, some of which are related to fault structures. In order to identify favourable areas of mineral deposition, structural and mineralogical mapping using satellite images was conducted in this region. For this purpose, various remote sensing approaches were employed on images from Landsat 8 OLI, Sentinel 2 and ASTER sensors. The process started with lineament extraction methods so as to identify faults manually from satellite images. Principal component analysis (PCA) and the optimal indexing factor (OIF) were used to achieve good discrimination of lithological units. Additionally, several band ratios were applied to ASTER, Landsat 8 OLI and Sentinel 2, in order to derive multiple maps corresponding to hydrothermal alteration zones. Analysis of the results from the obtained maps and their overlay with field data has allowed us to: (i) identify three main structural orientations. The most frequent and longest is the NE–SW direction, which coincides with the principal mineralised horizon of the Tighardine deposit. Results suggest an extension of this horizon towards the south-west at the Ait Zitoune and towards the west in the Ait Hsayn region. Two new fault set has been identified by remote sensing: NW-SE fracture, generally of Mesozoic-Cenozoic age, and an E-W fractures trend, particularly developed in the Neoproterozoic basement and considered of Ediacaran age; (ii) highlighting two potential mineralisation zones: in the Ediacaran basement, revealing alterations of silica, dolomite, clay minerals, iron oxide and alunite-kaolinite-pyrophyllite, hosting the main mineralisation axis (Tighardine mine); in the northern part corresponding to the overthrust zones of Cambrian onto Cenozoic formations.

16

Zastosowanie techniki FTIR i metod chemometrycznych do oceny procesu biologicznego oczyszczania ścieków komunalnych osadem czynnym

Piaskowski Krzysztof, Walendzik Bartosz

Gaz, Woda i Technika Sanitarna

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2024

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Nr 1

32--39

PL

Biologiczny proces osadu czynnego jest najpopularniejszą metodą stosowaną w licznych oczyszczalniach ścieków, która z reguły pozwala na uzyskanie wymaganego efektu ekologicznego. Jednakże charakteryzuje się ona również pewną niestabilnością uzyskiwanych efektów zależną od warunków i parametrów, na które częściowo eksploatator nie ma wpływu. Dlatego też poszukuje się szybkich technik analitycznych do kontroli i oceny osadu czynnego, które w przypadku pojawienia się nieprawidłowości w komorach biologicznych pozwolą na podjęcie decyzji operacyjnych korygujących proces, jak również jego optymalizację. W niniejszym artykule zaprezentowano możliwości wykorzystania analizy FTIR-DRIFT zawiesiny osadu czynnego połączonej z analizą chemometryczną wybranych parametrów osadu i ścieków do oceny procesu oczyszczania na poszczególnych etapach pracy reaktora biologicznego. Uzyskane wyniki wskazują, że zastosowanie techniki FTIR do szybkiej oceny procesu biologicznego jest możliwe, a w połączeniu z modelowaniem PLS i po odpowiednim skalibrowaniu z wartościami parametrów fizyczno-chemicznych może stanowić element kontrolny w eksploatacji oczyszczalni ścieków.

EN

The activated sludge process is the most popular method used in many sewage treatment plants, which usually allows to achieve the required ecological effect. However, it is also characterized by a certain instability of the obtained effects, depending on conditions and parameters which are partly beyond the operator's influence. Therefore, rapid analytical techniques are being sought for the control and assessment of activated sludge, which, in the event of irregularities occurring in biological tanks, will allow operational decisions to be made to correct the process as well as its optimization. This article presents the possibilities of using FTIR-DRIFT analysis of activated sludge suspension combined with chemometric analysis of selected sludge and sewage parameters to assess the course of the purification process at various stages of operation of the biological reactor. The obtained results indicate that the use of the FTIR technique for rapid assessment of a biological process is possible, and in combination with PLS modeling and after appropriate calibration with physical and chemical parameters, it can constitute a control element in the operation of sewage treatment plants.

17

Milling cutter fault diagnosis using unsupervised learning on small data: A robust and autonomous framework

Patange Abhishek, Soman Rohan, Pardeshi Sujit, Kuntoglu Mustafa, Ostachowicz Wieslaw

Eksploatacja i Niezawodność

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2024

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Vol. 26, no. 1

art. no. 178274

EN

Tool condition affects the tolerances and the energy consumption and hence needs to be monitored. Artificial intelligence (AI) based data-driven techniques for tool condition determination are proposed. Unfortunately, the data-driven techniques are data-hungry. This paper proposes a methodology for classification based on unsupervised learning using limited unlabeled training data. The work presents a multi-class classification problem for the tool condition monitoring. The principal component analysis (PCA) is employed for dimensionality reduction and the principal components (PCs) are used as input for classification using k-means clustering. New collected data is then projected on the PC space, and classified using the clusters from the training. The methodology has been appliedforclassification of tool faults in 6 classes in a vertical milling center. The use of limited input parameters from the user makes the method ideal for monitoring a large number of machines with minimal human intervention. Furthermore, due to the small amount of data needed for the training, the method has the potential to be transferable.

18

Statistical Study of Groundwater Salinity at Lake Dayet Erroumi, Morocco

El Qryefy Mohamed, Abdelhadi Hichar, El Qryefy Mouhcine, El Hammoumi Tarik, El Kharrim Khadija

Ecological Engineering & Environmental Technology

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2024

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Vol. 25, iss. 8

27--36

EN

In the present study, descriptive and multivariate statistical techniques (principal component analysis) were used to investigate groundwater salinity in the area adjacent to Lake Dayet Erroumi. Nine groundwater samples were collected during September 2019 and analyzed for the following physicochemical variables: pH, EC, DO, Ca2+, Mg2+, Na+ , K+ , HCO3 - , Cl- , SO4 2- and NO3 - . On the basis of on concentration averages, cation abundance is Na+ >Ca2+ > Mg2+ > K+ and anion abundance is Cl- > HCO3 - > SO4 2- > NO3 - . Two principal components were selected on the basis of eigenvalue, which explains 71.39% of the total variance. The first principal component (F1) accounts for 52.37% of total variance and indicates water salinization, which depends on abiotic factors. The second principal component (F2) explains 19.01% of the information and indicates parameters dependent on biotic factors (DO and pH). Projection of the observations revealed two groups of wells: the first group comprises the wells characterized by very high salinity, and the second group comprises the wells with lower salinity. These results show that the wells on the southern shore of the lake are more highly mineralized than other wells. The high mineralization of the groundwater is of natural origin, due to the leaching of Triassic evaporitic rocks.

19

Monitoring a metabolic profile of wheat by using FTIR spectroscopy and chemometric methods — concept studies

Borek-Dorosz Aleksandra, Kurczab Rafał

Science, Technology and Innovation

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2023

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Vol. 17, no. 1-2

41--75

EN

Changes in plants under the influence of a variety of chemical and physical factors are reflected in metabolomic changes. To date, there are very few methods that would allow studying metabolic changes occurring in single cells. Spectroscopic methods especially combined with the chemometrics methods are a very good tool to investigate such changes in metabolomics. Tracking changes in plants is of particular importance in industry, especially when studying how the use of fertilizers affects plants. In this paper, we present preliminary research as concept of proof to examine whether the use of FTIR (Fourier Transform Infrared Spectroscopy) helps to monitor the changes in the metabolomic profile of the plants. For preliminary research, four species of cereals and cuckooflower were used. In this step, it was possible to verify the differences in metabolites that are produced by plants belonging to different families. Then one species of grain was selected and subjected to eleven different physical and chemical factors. Next, the research was expanded to determine the optimal concentration of hydrogen peroxide. FTIR spectra of leaves and extracts of the plants were obtained for all experimental groups and then analyzed with the use of chemometric methods: HCA (Hierarchical Component Analysis) and PCA (Principal Component Analysis). Those methods were used to help in the interpretation of metabolic changes resulting in the plant in response to external factors.

20

Relationships between Wellbeing and Sustainable Development in a Group of Selected Developed Countries

Drastichová Magdaléna, Filzmoser Peter, Gajanin Rastko

Problemy Ekorozwoju

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2023

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Vol. 18, nr 2

49--77

EN

This work evaluates the crucial aspects of sustainable development (SD) related to wellbeing and quality of life, which were measured by twenty-two relevant indicators (indices) in a sample of 31 countries over the period 2010 – 2019. All the pillars of SD are reflected, while the indicators applied either reflect one of these dimensions, i.e. the economic, social or environmental pillar of SD, or two/all of them. Several of these indicators also measure specific aspects encompassed by the particular pillars, which are of great importance for SD and have to be included. These include especially health and inequality, which belong to the social pillar of SD, and are reflected in several indicators used. Furthermore, the indicator of subjective happiness is included as well. Principal component analysis (PCA) and parallel factor analysis (PARAFAC) are the main methods used to analyse relationships between twenty-two indicators (composite indices) reflecting crucial aspects of SD, wellbeing, and quality of life in the sample. Three stages of both analyses were carried out. For both of them similar results were identified. Principal component 1 (for PCA)/component 1 (for PARAFAC) divided the sample into the less and the more developed countries, since the positive contribution was predominantly determined by the socioeconomic, wellbeing and the more complex environmental or SD indicators, which are predominantly the highest (high) in the more developed countries. On the contrary, the negative contribution was determined by the pollution damage indicators, which are the highest in the less developed countries. Principal component 2 (for PCA)/component 2 (for PARAFAC) divided the sample according to a crucial aspect of the social pillar of SD, i.e. quality of health, particularly reflected in Healthy life years at birth (HLY), which has also poor results in the many developed countries. At the third stage this component is determined by the environmental indicators reflecting resource depletion/consumption and also pollution damages in monetary values, being crucial for SD, since a number of them had the highest values in the developed countries.

PL

Niniejsza praca ocenia kluczowe aspekty zrównoważonego rozwoju (SD) związane z dobrostanem i jakością życia, które zostały zmierzone za pomocą dwudziestu dwóch odpowiednich wskaźników (wskaźników) w próbie 31 krajów w latach 2010-2019. Uwzględniono wszystkie filary zrównoważonego rozwoju, natomiast zastosowane wskaźniki odzwierciedlają albo jeden z tych wymiarów, tj. filar ekonomiczny, społeczny lub środowiskowy ZR, albo dwa/wszystkie z nich. Niektóre z tych wskaźników mierzą również konkretne aspekty objęte poszczególnymi filarami, które mają ogromne znaczenie dla zrównoważonego rozwoju i muszą zostać uwzględnione. Wśród nich wyróżnić należy zwłaszcza zdrowie i nierówności, które należą do społecznego filaru zrównoważonego rozwoju i znajdują odzwierciedlenie w przyjętych wskaźnikach. Ponadto uwzględniono również wskaźnik subiektywnego szczęścia. Analiza głównych składowych (PCA) i równoległa analiza czynnikowa (PARAFAC) to główne metody stosowane do analizy relacji między dwudziestoma dwoma wskaźnikami (wskaźnikami złożonymi) odzwierciedlającymi kluczowe aspekty SD, dobrostanu i jakości życia. Przeprowadzono trzy etapy obu analiz. Zidentyfikowano podobne wyniki. Komponent główny 1 (w przypadku PCA)/komponent 1 (w przypadku PARAFAC) podzielił próbę na kraje słabiej i bardziej rozwinięte, ponieważ pozytywny wkład był determinowany głównie przez wskaźniki społeczno-ekonomiczne, dobrobyt i bardziej złożone wskaźniki środowiskowe lub zrównoważonego rozwoju, które są przeważnie najwyższe (wysokie) w krajach bardziej rozwiniętych. O ujemnym wkładzie zadecydowały wskaźniki szkód powodowanych przez zanieczyszczenia, które są najwyższe w krajach słabiej rozwiniętych. Komponent główny 2 (dla PCA)/komponent 2 (dla PARAFAC) podzielił próbę według kluczowego aspektu społecznego filaru SD, jakim jest zdrowie, w szczególności Healthy life years at birth (HLY), który wypadł słabo także w wielu krajach rozwiniętych. W trzecim etapie składnik ten jest określany przez wskaźniki środowiskowe odzwierciedlające wyczerpywanie się/konsumpcję zasobów, a także szkody spowodowane zanieczyszczeniami w wartościach pieniężnych, które są kluczowe dla zrównoważonego rozwoju, gdyż wiele z nich miało najwyższe wartości w krajach rozwiniętych.