Browsing by Subject "PCA"

Now showing 1 - 11 of 11

Access status: Open Access ,
A SPC strategy for decision making in manufacturing processes
(AGH University of Science and Technology Press, 2019) Gil Del Val, Alain; Sawik, Bartosz; Alba, Maria Agustín Martin; Faulin, Javier; Diéguez-Elizondo, Pedro María
Tapping is an extensively employed manufacturing process by which a multi-teeth tool, known as a tap, cuts a mating thread when driven into a hole. When taps are new or slightly worn, the process is under control and the geometry of the resulting threads on the workpiece is correct. But as the tap wear increases, the thread geometry deviates progressively from the correct one and eventually the screw threads become unacceptable. The aim of this paper is to outline the development of a statistical process control strategy for decision making based on data coming from the current signal of the tap spindle for assessing thread quality. It could operate on line, and indicates when the tap wear is so critical that, if the process were continued, it would result in unacceptable screw threads. The system would be very cost-effective since the tapping process could be run without any operator intervention.
Access status: Open Access ,
Novel approach for big data classification based on hybrid parallel dimensionality reduction using spark cluster
(Wydawnictwa AGH, 2019) Ali, Ahmed Hussein; Abdullah, Mahmood Zaki
The big data concept has elicited studies on how to accurately and efficiently extract valuable information from such huge dataset. The major problem during big data mining is data dimensionality due to a large number of dimensions in such datasets. This major consequence of high data dimensionality is that it affects the accuracy of machine learning (ML) classifiers, it also results in time wastage due to the presence of several redundant features in the dataset. This problem can be possibly solved using a fast feature reduction method. Hence, this study presents a fast HP-PL which is a new hybrid parallel feature reduction framework that utilizes spark to facilitate feature reduction on shared/distributed-memory clusters. The evaluation of the proposed HP-PL on KDD99 dataset showed the algorithm to be significantly faster than the conventional feature reduction techniques. The proposed technique required >1 minute to select 4 dataset features from over 79 features and 3,000,000 samples on a 3-node cluster (total of 21 cores). For the comparative algorithm, more than 2 hours was required to achieve the same feat. In the proposed system, Hadoop’s distributed file system (HDFS) was used to achieve distributed storage while Apache Spark was used as the computing engine. The model development was based on a parallel model with full consideration of the high performance and throughput of distributed computing. Conclusively, the proposed HP-PL method can achieve good accuracy with less memory and time compared to the conventional methods of feature reduction. This tool can be publicly accessed at https://github.com/ahmed/Fast-HP-PL.
Access status: Open Access ,
Optimizing built-up area extraction in semi-arid regions using Sentinel-2A imagery: a comparative analysis of spectral indices and PCA-based classification in Batna, Algeria
(Wydawnictwa AGH, 2026) Wahiba, Touati; Kalla, Mahdi; Kacha, Lemya
Accurate detection of built-up areas in semi-arid regions is vital for urban planning and environmental monitoring. However, built-up surfaces and bare soils often produce very similar spectral responses. As a result, this similarity causes confusion in satellite image classification. Additionally, spectral overlap among urban materials, bare soil, and sparse vegetation further complicates detection. This study evaluates several spectral indices, including DBSI, NDTI, NDVI, BRBA, and BSI, combined with Principal Component Analysis (PCA) to enhance built-up area extraction from Sentinel-2A imagery. Images captured during the driest season were selected to maximize spectral contrast. Three classification schemes based on Support Vector Machine (SVM) were tested. The first scheme used DBSI, NDTI, and NDVI. The second used BRBA, NDTI, and NDVI. The third relied on PCA-derived components. The results indicate that the PCA-based approach achieved the highest classification accuracy at 95%. In comparison, the DBSI/NDTI/NDVI combination reached 93%, while the BRBA/NDTI/NDVI scheme achieved 92%. Therefore, PCA helps reduce spectral confusion and enhances the identification of built-up areas in semi-arid environments. Overall, combining multiple spectral indices with dimensionality reduction offers a reliable method for urban analysis using Sentinel-2 imagery.
Access status: Restricted ,
Przewidywanie wyników biopsji raka piersi z wykorzystaniem metod uczenia maszynowego
(Data obrony: 2018-01-24) Tomczyk, Marta
Wydział Elektrotechniki, Automatyki, Informatyki i Inżynierii Biomedycznej
Access status: Restricted ,
Rozpoznawanie niebezpiecznych narzędzi z wykorzystaniem obliczeń miękkich
(Data obrony: 2012-07-13) Sieradzki, Radosław
Wydział Elektrotechniki, Automatyki, Informatyki i Elektroniki
Access status: Open Access ,
Satellite data based abundance mapping of mafic and ultramafic rocks in Mettupalayam, Tamil Nadu, India
(Wydawnictwa AGH, 2021) Libeesh, Nharakkat Kalarikkal; Arivazhagan, Sundaram
The mafic and ultramafic rocks of Mettupalayam belong to the southern granulite terrain of India, which is concomitant with vital economic resources. The advantage of Advanced Spaceborne Thermal Emission and Reflectance Radiometer (ASTER) data for mapping the litho units are exploited well here for differentiating the rock units with the aid of band combination (1, 3, 6), principal component analysis (5, 1, 6) and band ratioed band combination (2/3, 3/2, 1/5 and (9–8)/1, (8–6)/2, and (9–6)/3). As part of the field study, the collection of samples and ground control points were carried out and in addition to that, the generation of laboratory reflectance spectra for samples was achieved. The Spectral Angle Mapper (SAM) and Support Vector Machine (SVM) were performed using ASTER data with the aid of spectra obtained from the laboratory conditions to demarcate the abundance of mafic and ultramafic rocks of the area. The XRF method was used to retrieve the major oxides of the field-collected samples and the spectral absorption characters are validated with it. The results show a vibrant interpretation of the litho units.
Access status: Open Access ,
Screen scraping i jego zastosowania na przykładzie Coffee Research Institute oraz Allegro.pl
(Data obrony: 2020-10-22) Wis, Krzysztof
Wydział Zarządzania
Access status: Restricted ,
Selected methods of optimization predictors in well logging measurements
(Data obrony: 2019-12-10) Pyśniak, Kacper
Wydział Geologii, Geofizyki i Ochrony Środowiska
Access status: Open Access ,
The acoustic emission (AE) controlling method of the electric sheet blanking process - a comparative study of selected data mining methods
(Wydawnictwa AGH, 2022) Kochański, Andrzej Witold; Czyżewski, Piotr; Moszczyński, Leszek
The article presents an experimental stand to assess the state of punch in the process of sheet blanking. Blanking trials were carried out on an eccentric press. During all the trials, there were recorded signals of acoustic emission (AE) that accompanied the process of blanking. For the recorded AE signals, the methodology of data preparation and analysis was presented. On that basis, the results of the assessment of the state of the punch were presented, and they employed five methods of visualization: Andrews curves, Principal Components Analysis, Linear Discriminant Analysis, a modified method of Stochastic Neighbor Embedding and Sammon Mapping. The aim of the work was to assess the possibility of using visualization methods to predict the condition of the tool on the basis of acoustic emission signals in processes carried out in extremely short times.
Access status: Restricted ,
The mechanisms of neuroprotective action of the ketogenic diet in the pilocarpine model of seizures. Biochemical changes of hippocampal formation analyzed using FTIR microspectroscopy
(Data obrony: 2019-10-10) Owczarek, Dorota
Wydział Fizyki i Informatyki Stosowanej
Access status: Restricted ,
Wykorzystanie Pythona do analizy widm fluorescencyjnych technikami PCA
(Data obrony: 2020-10-07) Kula, Joanna
Wydział Elektrotechniki, Automatyki, Informatyki i Inżynierii Biomedycznej