Search Everything

Tip: Search using "First Name + Last Name", e.g.
János Kiss instead of Kiss János.

Publications - 6374

Effects of Various Herbicide Types and Doses, Tillage Systems, and Nitrogen Rates on CO2 Emissions from Agricultural Land: A Literature Review

Viktoria Vona István Mihály Kulmány Ali Adnan Hassouni Laszló Bede Sándor Zsebő Dávid Stencinger Zainulabdeen Khalaf Hashim Bálint Horváth Agampodi Gihan Shyamal Dharmendra De Silva Zainulabdeen Khalaf Hashim

Publication Name: Agriculture Switzerland

Publication Date: 2024-10-01

Volume: 14

Issue: 10

Page Range: Unknown

Description:

Although herbicides are essential for global agriculture and controlling weeds, they impact soil microbial communities and CO2 emissions. However, the effects of herbicides, tillage systems, and nitrogen fertilisation on CO2 emissions under different environmental conditions are poorly understood. This review explores how various agricultural practices and inputs affect CO2 emissions and addresses the impact of pest-management strategies, tillage systems, and nitrogen fertiliser usage on CO2 emissions using multiple databases. Key findings indicate that both increased and decreased tendencies in greenhouse gas (GHG) emissions were observed, depending on the herbicide type, dose, soil properties, and application methods. Several studies reported a positive correlation between CO2 emissions and increased agricultural production. Combining herbicides with other methods effectively controls emissions with minimal chemical inputs. Conservation practices like no-tillage were more effective than conventional tillage in mitigating carbon emissions. Integrated pest management, conservation tillage, and nitrogen fertiliser rate optimisation were shown to reduce herbicide use and soil greenhouse gas emissions. Fertilisers are similarly important; depending on the dosage, they may support yield or harm the soil. Fertiliser benefits are contingent on appropriate management practices for specific soil and field conditions. This review highlights the significance of adaptable management strategies that consider local environmental conditions and can guide future studies and inform policies to promote sustainable agriculture practices worldwide.

Open Access: Yes

DOI: 10.3390/agriculture14101800

Novel Insights in Soil Mechanics: Integrating Experimental Investigation with Machine Learning for Unconfined Compression Parameter Prediction of Expansive Soil

Chuangxin Lyu Haidar Hosamo Hosamo Ammar N. Alnmr Mounzer Omran Alzawi R. P. Ray

Publication Name: Applied Sciences Switzerland

Publication Date: 2024-06-01

Volume: 14

Issue: 11

Page Range: Unknown

Description:

This paper presents a novel application of machine learning models to clarify the intricate behaviors of expansive soils, focusing on the impact of sand content, saturation level, and dry density. Departing from conventional methods, this research utilizes a data-centric approach, employing a suite of sophisticated machine learning models to predict soil properties with remarkable precision. The inclusion of a 30% sand mixture is identified as a critical threshold for optimizing soil strength and stiffness, a finding that underscores the transformative potential of sand amendment in soil engineering. In a significant advancement, the study benchmarks the predictive power of several models including extreme gradient boosting (XGBoost), gradient boosting regression (GBR), random forest regression (RFR), decision tree regression (DTR), support vector regression (SVR), symbolic regression (SR), and artificial neural networks (ANNs and proposed ANN-GMDH). Symbolic regression equations have been developed to predict the elasticity modulus and unconfined compressive strength of the investigated expansive soil. Despite the complex behaviors of expansive soil, the trained models allow for optimally predicting the values of unconfined compressive parameters. As a result, this paper provides for the first time a reliable and simply applicable approach for estimating the unconfined compressive parameters of expansive soils. The proposed ANN-GMDH model emerges as the pre-eminent model, demonstrating exceptional accuracy with the best metrics. These results not only highlight the ANN’s superior performance but also mark this study as a groundbreaking endeavor in the application of machine learning to soil behavior prediction, setting a new benchmark in the field.

Open Access: Yes

DOI: 10.3390/app14114819

Metallographic and magnetic analysis of direct laser sintered soft magnetic composites

Imre Fekete L. K. Varga B. Kocsis

Publication Name: Journal of Magnetism and Magnetic Materials

Publication Date: 2020-05-01

Volume: 501

Issue: Unknown

Page Range: Unknown

Description:

In this present study, soft magnetic composite samples were made from iron-silicon alloys. For the purpose of optimizing 3D printing parameters, preliminary experiments were performed. Metallographic and computed tomography investigations were used to determine the appropriate sintering settings. Besides the microscopic and CT analysis, considering the permeability spectra have been compared to the samples.

Open Access: Yes

DOI: 10.1016/j.jmmm.2020.166425

Examination of the Resistance Components of an Energy-Efficient Electric Vehicle

Péter Korös Zoltan Pusztai Ferenc Szauter

Publication Name: Journal of Physics Conference Series

Publication Date: 2024-01-01

Volume: 2848

Issue: 1

Page Range: Unknown

Description:

The paper presents a comprehensive examination of measurement-based modelling regarding resistance forces. This work offers a detailed explanation of the experimental techniques employed to measure the resistance forces experienced by a lightweight vehicle. The modelling approach is particularly beneficial for characterizing vehicle with low resistance values. Our investigation encompasses key vehicle motion states, including cornering and straight-line motion, making it greatly useful for optimization purposes. The measurements were conducted in a proving ground and laboratory environment. The road load coefficients can be breakdown into components from total resistance force measurement. Based on breakdown, future vehicle development goals can be addressed with a focus on reducing resistance forces.

Open Access: Yes

DOI: 10.1088/1742-6596/2848/1/012011

Linear fuzzy rule base interpolation using fuzzy geometry

Suman Das Laszlo T. Koczy Debjani Chakraborty

Publication Name: International Journal of Approximate Reasoning

Publication Date: 2019-09-01

Volume: 112

Issue: Unknown

Page Range: 105-118

Description:

Fuzzy Rule Interpolation (FRI) provides an interpretable decision in sparse fuzzy rule based system. The objective of this work is to establish a mathematical demonstration of the pattern of existing fuzzy rule base using fuzzy geometry. Though several authors contributed on fuzzy rule base interpolation but there is a need to generate closed mathematical form of interpolating pattern. The present work is an initiative to demonstrate the same. First part of this paper presents some spatial geometrical transformation of a fuzzy point. In the second part of this paper, a new FRI scheme is suggested using fuzzy geometry with above mentioned transformation. The proposed method operates in two different steps. In the first step, all the fuzzy rules are converted into fuzzy sets or mostly fuzzy points in higher dimension by using mathematical operator on the individual of antecedent and consequent parts. All rules or fuzzy points are then joined with a class of fuzzy line segments (FLS). Second step considers the identification of mathematical pattern of the interpolated piecewise linear fuzzy polynomial which is able to compute the desired conclusion of a given observation. The presented method not only associates the FRI technique to classical interpolation technique, but also promises to provide the geometrical visualization of the behaviour of fuzzy sets during the interpolation process.

Open Access: Yes

DOI: 10.1016/j.ijar.2019.05.004

Sparse fuzzy systems generation and fuzzy rule interpolation: A practical approach

Szilveszter Kovacs Tamás D. Gedeon Laszlo T. Koczy None Chong

Publication Name: IEEE International Conference on Fuzzy Systems

Publication Date: 2003-07-11

Volume: 1

Issue: Unknown

Page Range: 494-499

Description:

In this paper, we explore the use of a sparse fuzzy system generation technique in conjunction with simple projection-based fuzzy rule interpolation, to generate sparse fuzzy systems with relatively few rules whilst still achieving reasonable system accuracy. Through setting a parameter value, the user is able to control, to some extent, the number of rules generated by the rule extraction technique. The rule interpolation approach enables the sparse fuzzy system to maintain a reasonable accuracy. The effectiveness of this approach is validated experimentally.

Open Access: Yes

DOI: DOI not available

Evaluation of Advances in Battery Health Prediction for Electric Vehicles from Traditional Linear Filters to Latest Machine Learning Approaches

Adrienn Dineva

Publication Name: Batteries

Publication Date: 2024-10-01

Volume: 10

Issue: 10

Page Range: Unknown

Description:

In recent years, there has been growing interest in Li-ion battery State-of-Health (SOH) estimation due to its critical role in ensuring the safe and reliable operation of Electric Vehicles (EVs). Effective energy management and accurate SOH prediction are essential for the reliability and sustainability of EVs. This paper presents an in-depth review of SOH estimation techniques, starting with an overview of seminal methods that lay the theoretical groundwork for battery modeling and SOH prediction. The review then evaluates recent advancements in Machine Learning (ML) and Artificial Intelligence (AI) techniques, emphasizing their contributions to improving SOH estimation. Through a rigorous screening process, the paper systematically assesses the evolution of these advanced methods, addressing specific research questions to evaluate their effectiveness and practical implications. Key findings highlight the potential of hybrid models that integrate Equivalent Circuit Models (ECMs) with Deep Learning approaches, offering enhanced accuracy and real-time performance. Additionally, the paper discusses limitations of current methods, such as challenges in translating laboratory-based models to real-world conditions and the computational complexity of some prospective methods. In conclusion, this paper identifies promising future research directions aimed at optimizing hybrid models and overcoming existing constraints to advance SOH estimation and battery management in Electric Vehicles.

Open Access: Yes

DOI: 10.3390/batteries10100356

Age-dependent aerobic capacity among young and middle-aged males

No authors available

Publication Name: Gazzetta Medica Italiana Archivio per le Scienze Mediche

Publication Date: 2016-03-01

Volume: 175

Issue: 3

Page Range: 68-75

Description:

BACKGROUND: Good aerobic capacity is one of the attributes of good cardiovascular function. Physical activity that is performed in steady state and the lower third zone of submaximal intensity seems appropriate for physiological adaptation in advancing age. There is a need to evaluate the effect of age on physiological variables contributing to aerobic capacity using submaximal intensities. The purpose of this study is to analyze the differences m oxygen uptake, oxygen pulse, and minute ventilation during exercise at steady state, ventilatory threshold, and maximal intensity zones among men of different ages. METHODS: Three hundred and twelve senior managers m three age groups (20-30, 30-40, and 40-50) completed an exercise protocol in six stages. RESULTS: Hie result demonstrated a series of differences among the age groups: height, weight, oxygen uptake, oxygen pulse and relative minute ventilation. Accordmg to these results the morphological physiological variables decline with age. CONCLUSIONS: These findings demonstrate the specificities of the morphological, ventilatory, metabolic, and cardiovascular changes throughout aging. When designing a physical activity program, it seems that similar principles can be followed in different age groups; however, maximal intensity maintenance is limited by physiological barriers m older adults. (Cite this article as: Ihasz F, Boros P, Szabo P. Olah A, Fueedi B. Bognar J. Age-dependent aerobic capacity among young and middle-aged males. Gazz Med Ital - Arch Sci Med 2016;175:68-75).

Open Access: No

DOI: DOI not available

Numerical Study of the Ultimate Bearing Capacity of Two Adjacent Rough Strip Footings on Granular Soil: Effects of Rotational and Horizontal Constraints of Footings

Mojtaba Lezgy-Nazargah Majid Movahedi Rad Vahid Shafaie Mahdi Salari

Publication Name: Buildings

Publication Date: 2024-06-01

Volume: 14

Issue: 6

Page Range: Unknown

Description:

In this paper, the numerical study of the ultimate bearing capacity (UBC) of two closely spaced strip footings on granular soil is investigated using the finite element method (FEM) and upper bound limit analysis (UBLA). Although the UBC of two adjacent footings has previously been studied in other experimental and numerical research, in all the previously reported studies, the footings were not allowed to rotate and move horizontally freely. Due to the deformation of the soil medium, two closely spaced footings are subjected to horizontal movements and tilting, even under central vertical loads. When the two adjacent footings are not permitted to rotate and move in the horizontal directions, the unwanted bending moment and horizontal force act on the footings. Indeed, the UBC of two closely spaced rough footings is evaluated under incorrect constraints in earlier research. In the present research, the UBC of two adjacent rough footings is evaluated with and without these incorrect constraints. The key finding of this study is that constraining the horizontal and rotational movement of the foundation artificially increases the UBC, which does not reflect field conditions. When foundations are permitted to rotate and move horizontally, there is no increase in UBC; however, there is an increased risk of differential settlement and structural instability.

Open Access: Yes

DOI: 10.3390/buildings14061653