TY - JOUR AU - Mohamed, Ahmed AU - Alarifi, Saad S. AU - Al-Kahtany, Khaled AU - Mohammed, Musaab Adam Abbakar TI - Application of gravity and remote sensing data to groundwater storage variation in Wadi Al Dawasir, Saudi Arabia JF - JOURNAL OF KING SAUD UNIVERSITY - SCIENCE J2 - J KING SAUD UNIV SCI VL - 36 PY - 2024 IS - 5 SN - 1018-3647 DO - 10.1016/j.jksus.2024.103172 UR - https://m2.mtmt.hu/api/publication/34828936 ID - 34828936 LA - English DB - MTMT ER - TY - JOUR AU - Abbadi, Alaa AU - Rácz, Ádám AU - Bokányi, Ljudmilla TI - Exploring the comminution process of waste printed circuit boards in recycling: a review JF - JOURNAL OF MATERIAL CYCLES AND WASTE MANAGEMENT J2 - J MATER CYCLES WASTE PY - 2024 SN - 1438-4957 DO - 10.1007/s10163-024-01945-3 UR - https://m2.mtmt.hu/api/publication/34767864 ID - 34767864 AB - The increasing amount of electronic waste (e-waste) has placed significant burdens on society and the environment, particularly with regards to waste printed circuit boards (WPCBs), which are essential in electronics manufacturing. As natural resources become scarce, it is crucial to effectively recycle and reclaim WPCBs due to their high value and large output. Comminuting printed circuit boards is a crucial step in enabling the recovery of valuable materials, and this review provides an in-depth analysis of WPCB comminution. It explores the structure, types, and composition of the WPCBs, including their mechanical properties. The review thoroughly surveys conventional mechanical comminution machinery and also discusses emerging technologies such as innovative pretreatment approaches, electrodynamic disintegration, high voltage electrical pulses, and abrasive waterjet cutting. The literature has been critically examined to identify research gaps and inconsistencies, and future directions for increased efficiency and sustainability are proposed. LA - English DB - MTMT ER - TY - JOUR AU - Mohammed, Musaab Adam Abbakar AU - Szabó, Norbert Péter AU - Szűcs, Péter TI - Multi-step modeling of well logging data combining unsupervised and deep learning algorithms for enhanced characterization of the Quaternary aquifer system in Debrecen area, Hungary JF - MODELING EARTH SYSTEMS AND ENVIRONMENT J2 - MESE PY - 2024 PG - 17 SN - 2363-6203 DO - 10.1007/s40808-024-01986-5 UR - https://m2.mtmt.hu/api/publication/34753099 ID - 34753099 AB - In this research, a multi-step modeling approach is followed using unsupervised and deep learning algorithms to interpret the geophysical well-logging data for improved characterization of the Quaternary aquifer system in the Debrecen area, Hungary. The Most Frequent Value-Assisted Cluster Analysis (MFV-CA) is used to map lithological variations within the aquifer system. Additionally, the Csókás method is used to discern both vertical and horizontal fluctuations in hydraulic conductivity. MFV-CA is introduced to cope with the limitation of the conventional Euclidean distance-based k-means clustering known for its low resistance to outlying values, resulting in deformed cluster formation. However, the computational time and demands of MFV-CA are evident, making them costly and time-consuming. As a result, Deep Learning (DL) methods are suggested to provide fast characterization of the groundwater aquifers. These methods include Multi-Layer Perceptron Neural Networks (MLPNN), Convolutional Neural Networks (CNN), Recurrent Neural Networks (RNN), and Long Short-Term Memory (LSTM), which are implemented for classification and regression. The classification categorized the inputs into three distinct lithologies trained initially by the results of MFV-CA. At the same time, the regression model offered a continuous estimations of hydraulic conductivity trained by the results of the Csókás model. The results demonstrated significant compatibility between the outcomes derived from the clustering and Csókás approaches and DL algorithms. Accordingly, the lithofacies and hydraulic conductivity variations across the main hydrostratigraphical units are mapped. This integration enhanced the understanding of the groundwater system, offering promising inputs for groundwater and development and management. LA - English DB - MTMT ER - TY - GEN AU - Szegedi, Kristóf István AU - Lengyel, György AU - Marton, Tibor TI - Looking for the Final Palaeolithic and Mesolithic Carpathian Basin: opportunities and limits of recent researches in Hungary PY - 2024 UR - https://m2.mtmt.hu/api/publication/34728485 ID - 34728485 N1 - 32. Jahrestagung der Arbeitsgemeinschaft Mesolithikum 07.-09. März 2024 SZEGEDI, Kristóf István / LENGYEL, György / MARTON, Tibor Looking for the Final Palaeolithic and Mesolithic Carpathian Basin: opportunities and limits of recent researches in Hungary LA - English DB - MTMT ER - TY - GEN AU - Szegedi, Kristóf István TI - Final Palaeolithic and Early Mesolithic in the Carpathian Basin: current research and issues PY - 2024 UR - https://m2.mtmt.hu/api/publication/34718010 ID - 34718010 LA - English DB - MTMT ER - TY - JOUR AU - Mohammed, Musaab Adam Abbakar AU - Szabó, Norbert Péter AU - Alao, Joseph O. AU - Szűcs, Péter TI - Geophysical characterization of groundwater aquifers in the Western Debrecen area, Hungary: insights from gravity, magnetotelluric, and electrical resistivity tomography JF - SUSTAINABLE WATER RESOURCES MANAGEMENT J2 - SUST WATER RES MANAG VL - 10 PY - 2024 IS - 2 PG - 15 SN - 2363-5037 DO - 10.1007/s40899-024-01062-x UR - https://m2.mtmt.hu/api/publication/34717098 ID - 34717098 AB - The recent study followed a multi-methodological approach integrating gravity, magnetotelluric (MT), and electrical resistivity tomography (ERT) to investigate the geometry and hydrological characteristics of the main hydrostratigraphical units in the Western Debrecen area, Eastern Hungary. The integration of these methods aims to delineate potential zones for groundwater development and guide effective extraction strategies. In the gravity investigation, the Bouguer anomaly map undergoes spectral analysis for the separation of shallow and deep features, offering a preliminary indication of basement rock depth. Subsequently, gravity data inversion is employed to map variations in basement rock topography, revealing a basin structure, with sediment thicknesses extending up to 2 km. On the other hand, the MT data are modeled using the 1D Occam inversion algorithm to validate the results of the gravity data analysis. This inversion, constrained with lithological logs is further utilized to delineate the main hydrostratigraphical units in the study area. Accordingly, four units are identified, including the Nagyalföld Aquifer, Algyő and Endrődi Aquitards, the Badenian Aquifer, and the Pre-Neogene Aquitard. Consequently, Dar Zarrouk parameters based transmissivity and the hydraulic conductivity of the aquifer units are measured. The Nagyalföld aquifer showed a hydraulic conductivity that ranged between 7.9 and 11.9 m/day, while the Badenian aquifer showed an average hydraulic conductivity of 13.1 m/day. The ERT data are employed to map the spatial distribution of the depth to the water table. The shallow water table is observed in regions characterized by an elevated thickness of sedimentary rocks, attributed to their high specific capacity. Integrating these hydrogeophysical methods provided a comprehensive understanding of the subsurface hydrology and enabled better-informed decision-making for groundwater development. LA - English DB - MTMT ER - TY - JOUR AU - Mohammed, Musaab Adam Abbakar AU - Szabó, Norbert Péter AU - Szűcs, Péter TI - Joint interpretation and modeling of potential field data for mapping groundwater potential zones around Debrecen area, Eastern Hungary JF - ACTA GEODAETICA ET GEOPHYSICA J2 - ACTA GEOD GEOPHYS VL - 59 PY - 2024 SN - 2213-5812 DO - 10.1007/s40328-023-00433-8 UR - https://m2.mtmt.hu/api/publication/34570001 ID - 34570001 AB - The Debrecen area, as part of the Great Hungarian Plain (GHP), is associated with a multi-aquifer system that is overly exploited to fulfill the development plans. This research aims to jointly interpret and model gravity and magnetic data to map the subsurface geology and structures that govern groundwater occurrence. Various potential field techniques, including spectral analysis, anomaly derivatives, analytical signal, and Euler deconvolution were employed to map the distribution and depth of the buried geological structures. The combination of the potential field techniques enabled the construction of a detailed lineament map, providing valuable insights into the distribution of the subsurface structural features. It was indicated that the main structural trend is NW–SE and NE–SW, that coincides with the main structural trends in Hungary. Subsequently, a lineament density map is derived, indicating that the eastern, central, and northwestern parts of the area form the most promising zones for groundwater prospection. The joint inversion of gravity and magnetic data has further enhanced the understanding of subsurface geology. The depth to the basement rock varied between 1.18 and 2.2 km. The highest depth to the basement meets with thick sedimentary sequences bounded by normal faults forming graben and horst structures. Moreover, the distribution of these sediments is investigated using lithological logs indicating the thickness of the main hydrostratigraphic units in the Debrecen area. These units include Nagyalföld Aquifer, Algyő Aquitard, Endrőd Aquitard, and Miocene Badenian Aquifer units, which mainly consist of sand, silt, marl, and gravel. The recent study demonstrated the effectiveness of the joint interpretation in enhancing the knowledge of lithology and geological structures. However, a detailed geophysical survey is recommended to characterize the hydrostratigraphic units in the Debrecen area. LA - English DB - MTMT ER - TY - JOUR AU - FADOUL MOHAMMED IBRAHIM, JAMAL ELDIN AU - Basyooni-M. Kabatas, Mohamed A. AU - Móricz, Ferenc AU - Kocserha, István TI - Transforming Zeolite Tuff and Cigarette Waste into Eco-Friendly Ceramic Bricks for Sustainable Construction JF - BUILDINGS J2 - BUILDINGS-BASEL VL - 14 PY - 2024 IS - 1 PG - 21 SN - 2075-5309 DO - 10.3390/buildings14010144 UR - https://m2.mtmt.hu/api/publication/34545433 ID - 34545433 AB - The use of waste materials has gained attention as a sustainable approach in various industries. Cigarette waste, which is typically discarded as a non-recyclable material, poses a significant environmental challenge due to its toxicity and slow decomposition rate. However, by incorporating this waste into ceramic bricks, new approaches for waste management and resource utilization are explored. This research work provides a detailed evaluation of the possibility of utilizing natural zeolite tuff incorporated with cigarette waste to produce sustainable ceramic bricks. Uniform powders are produced by milling various combinations of zeolitic tuff and cigarette waste using a planetary ball mill. The substitution ratios ranged from 0% to 12% by weight of the zeolitic tuff, with increments of 2%. Ceramic discs were formed by dry pressing and then subjected to sintering at different heat treatment temperatures (950–1250 °C). The impact of the inclusion of cigarette waste on the microstructural and technical features of zeolite tuff-based ceramic bricks has been thoroughly investigated. The results of the experiments demonstrate that incorporating cigarette waste into the development of ceramic bricks leads to improved thermal insulation properties, with thermal conductivity ranging from 0.33 to 0.93 W/m·K. Additionally, these bricks exhibit a lighter weight in a range of 1.45 to 1.96 g/cm3. Although the inclusion of cigarette waste slightly reduces the compressive strength, with values ranging from 6.96 to 58.6 MPa, it still falls within the acceptable range specified by standards. The inclusion of cigarette waste into zeolite tuff is an innovative approach and sustainable practice for reducing energy consumption in buildings while simultaneously addressing the issue of waste disposal and pollution mitigation. LA - English DB - MTMT ER - TY - JOUR AU - Abdelrahman, Moataz AU - Szabó, Norbert Péter TI - A case study of petrophysical prediction using machine learning integrated with interval inversion in a tight sand reservoir in Egypt JF - IOP CONFERENCE SERIES: EARTH AND ENVIRONMENTAL SCIENCE J2 - IOP CONF SER EARTH AND ENVIRON SCI VL - 1295 PY - 2024 IS - 1 PG - 9 SN - 1755-1307 DO - 10.1088/1755-1315/1295/1/012008 UR - https://m2.mtmt.hu/api/publication/34544315 ID - 34544315 AB - This study presents a new algorithm for reservoir characterization using borehole logging data, which integrates unsupervised machine learning techniques and interval inversion to automatically determine layers’ boundaries and petrophysical parameters. The research aims to reduce the time and manual input required for borehole inversion to estimate petrophysical parameters. The algorithm was used to predict different layer boundaries of sand-shale intercalations for both synthetic and field wireline log data. Field well logging measurements were obtained from an oil and gas field in Egypt, specifically the Jurassic reservoir. The reservoir is composed of a dense sandstone layer with significant heterogeneity due to diagenesis, which converts kaolinite into illite. The algorithm was used to predict petrophysical parameters, resulting in a decrease in porosity and permeability. The field data from the well reveals that the reservoir is made up of varying-quality sandstone, impacting storage capacity and hydrocarbon saturation. The algorithm demonstrates consistent convergence of the data at 7.5%. Overall, the integration of the new cluster technique and interval inversion can improve the time-intensive and laborious process of borehole data inversion to estimate petrophysical parameters. LA - English DB - MTMT ER - TY - THES AU - Al Marashly, Omar TI - Inversion-based Fourier transformation algorithm used in processing geophysical data PY - 2024 DO - 10.14750/ME.2024.002 UR - https://m2.mtmt.hu/api/publication/34531215 ID - 34531215 LA - English DB - MTMT ER -