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Found 6334 publications

Innovative Cone Clustering and Path Planning for Autonomous Formula Student Race Cars Using Cameras †

Gergo Igneczi Balázs Szőnyi

Publication Name: Engineering Proceedings

Publication Date: 2024-01-01

Volume: 79

Issue: 1

Page Range: Unknown

Description:

In this research, we present a novel approach for cone clustering, path planning, and path visualization in autonomous Formula Student race cars, utilizing the YOLOv8 model and a ZED 2 camera, executed on a Jetson Orin computer. Our system first identifies and then deprojects the positions of cones in space, employing an advanced clustering mechanism to generate midpoints and draw connecting lines. In previous clustering algorithms, cones were stored separately by color and connected based on relevance to create the lane edges. However, our proposed solution adopts a fundamentally different approach. Cones on the left and right sides within a dynamically changing maximum and minimum distance are connected by a central line, and the midpoint of this line is marked distinctly. Cones connected in this manner are then linked by their positions to form the edges of the track. The midpoints on these central lines are displayed as markers, facilitating the visualization of the optimal path. In our research, we also cover the analysis of the clustering algorithm on global maps. The implementation utilizes the ROS 2 framework for real-time data handling and visualization. Our results demonstrate the system’s efficiency in dynamic environments, highlighting potential advancements in the field of autonomous racing. The limitation of our approach is the dependency on precise cone detection and classification, which may be affected by environmental factors such as lighting and cone positioning.

Open Access: Yes

DOI: 10.3390/engproc2024079096

Land subsidence modeling and mapping in Darab region, Iran

Mahrooz Rezaei Narges Kariminejad Vahid Shafaie Monireh Mina Mohammad Reza Loveimi Michel J.P.M. Riksen

Publication Name: Advanced Tools for Studying Soil Erosion Processes Erosion Modelling Soil Redistribution Rates Advanced Analysis and Artificial Intelligence

Publication Date: 2024-01-01

Volume: Unknown

Issue: Unknown

Page Range: 275-294

Description:

Land subsidence refers to the collapse of Earth's surface. This study aimed to model land subsidence using machine learning methods in the Darab region of Fars Province, which is recognized as one of the most critical provinces suffering from land subsidence in the country. Nineteen factors affecting the occurrence of land subsidence were selected as independent variables for the modeling process: slope degree, aspect, distance to rivers, stream density, elevation, land use, normalized difference vegetation index (NDVI), plan curvature, profile curvature, topographic wetness index, pH, electrical conductivity, mean annual rainfall, mean weight diameter (MWD), clay, silt, calcium carbonate equivalent (CCE), sodium content, and organic matter. Modeling was conducted using: artificial neural network (ANN), maximum entropy (MaxEnt), and support vector machine (SVM). The performance of algorithms was compared both individually and in combination. Validation results using the receiver operating characteristic (ROC) curve to identify landslide prone areas showed that land subsidence susceptibility maps produced by single MaxEnt model had highest accuracy, with area under the curve (AUC) of 0.92. According to the prioritization of effective factors, elevation and land use were determined to be the most crucial factors for land subsidence. The results of this spatial modeling of land subsidence susceptibility can greatly aid land allocation planning and water resource management in the study area.

Open Access: Yes

DOI: 10.1016/B978-0-443-22262-7.00011-4

Efficiency Analysis of Kolmogorov-Arnold Networks for Visual Data Processing †

János Hollósi

Publication Name: Engineering Proceedings

Publication Date: 2024-01-01

Volume: 79

Issue: 1

Page Range: Unknown

Description:

In the field of artificial neural networks, the use of multilayer perceptrons (MLPs) has long been a well-established methodology. Recently, the theory of Kolmogorov–Arnold Networks (KANs) has emerged as a potential alternative to multilayer perceptrons, inspired by the Kolmogorov–Arnold representation theorem. It has been demonstrated that solutions based on the Kolmogorov–Arnold Network (KAN) can achieve better efficiency than those based on the multilayer perceptron (MLP) for certain problems. In this work, we investigate how the new theory can be applied to a special image classification task when some adversarial attack method is applied. The aim of the research is to explore the potential of the theory to answer the question of its applicability to complex tasks of practical importance.

Open Access: Yes

DOI: 10.3390/engproc2024079068

Numerical Study of the Geogrid Reinforced Soil Wall Incorporating Strain-Softening Constitutive Soil Model

Seyed Ali Emamian Majid Movahedi Rad Vahid Shafaie Géza Herczeg Mahdi Salari

Publication Name: Advances in Transdisciplinary Engineering

Publication Date: 2024-01-01

Volume: 59

Issue: Unknown

Page Range: 327-333

Description:

This study embarks on a numerical exploration of Geogrid Reinforced Soil Walls (GRSW), employing finite difference analysis to compare two soil constitutive models, highlighting the efficacy of a refined strain-softening model. This innovative approach markedly improves the prediction of GRSW performance, particularly aligning the safety factor more closely with real-world observations. Notably, the strain-softening model demonstrates a superior ability over the perfectly plastic model by significantly reducing the mean overall error in predicting maximum geogrid strain overall from 51% to 30%, reflecting a significant 41% improvement in precision, thereby presenting a significant tool for enhancing geotechnical design practices. The research underlines the potential of this model to elevate the safety and reliability of GRSW constructions, contributing to elevated design standards within the field of geotechnical engineering.

Open Access: Yes

DOI: 10.3233/ATDE240563

Developing sustainable logistic strategies in the context of cognitive biases

Peter Foldesi Eszter Sós

Publication Name: Infocommunications Journal

Publication Date: 2024-01-01

Volume: Unknown

Issue: Unknown

Page Range: 110-118

Description:

Cognitive biases often occur even in the decision-making process of highly qualified company managers due to the drive for efficiency and time pressure in operations. At the same time, there are also long-term strategic decisions where time pressure is no longer a factor, and yet cognitive bias appears, which has to be considered properly. In strategic issues, decision- makers tend to see their wishes and desires rather than the objective reality. The proposed system of fuzzy indicators based on technical and objective data supports decision-making between logistics strategies by mitigating cognitive biases, which is extremely important in the logistics field, where the decisions have to be made partly based on subjective, vague, or uncertain parameters.

Open Access: Yes

DOI: 10.36244/ICJ.2024.5.13

Overview Study of the Applications of Unmanned Aerial Vehicles in the Transportation Sector †

Miklós Kuczmann Áron Ballagi Barnabás Kiss

Publication Name: Engineering Proceedings

Publication Date: 2024-01-01

Volume: 79

Issue: 1

Page Range: Unknown

Description:

This study examines the use of Unmanned Aerial Vehicles (UAVs) in transportation, focusing on traffic monitoring and accident prevention. UAVs provide a cost-effective means for traffic surveillance, route planning, and accident analysis, enhancing data accuracy and timeliness. The paper discusses autonomous and human-intervention-supported drone systems for traffic surveillance, addressing technological and operational challenges and the balance needed for practical implementation. It also presents recent advancements, including a forerunner drone model, and references research on UAVs for maritime navigation safety, underscoring the need for their safe and efficient integration into transportation systems.

Open Access: Yes

DOI: 10.3390/engproc2024079011

Parameter-Driven Campbell Diagram Variations in Turbocharger Rotors: A Rotordynamic Simulation Study Using ROSS †

Cs Tóth-Nagy Márk Pesthy Máté Boros

Publication Name: Engineering Proceedings

Publication Date: 2024-01-01

Volume: 79

Issue: 1

Page Range: Unknown

Description:

This study investigates the influence of rotor design parameters on the Campbell diagrams of automotive turbocharger rotors using rotordynamic simulations. A finite element model of the rotor is developed within the Python-based ROSS package, incorporating key parameters such as disk mass, lubricant viscosity, and bearing positioning. Employing this model, simulations are conducted to generate Campbell diagrams across a range of operational speeds. The analysis focuses on how variations in these parameters affect the critical speeds and corresponding vibration modes identified in the Campbell diagrams. The results provide valuable insights into the rotordynamic behavior of automotive turbochargers and their sensitivity to design choices. This information can be utilized to optimize rotor design for improved stability, reduced noise generation, and enhanced overall performance.

Open Access: Yes

DOI: 10.3390/engproc2024079058

New and little-known Diapheridae of Cambodia and Thailand (Gastropoda: Stylommatophora: Streptaxoidea)

Chirasak Sutcharit Barna Páll-Gergely András Hunyadi

Publication Name: Raffles Bulletin of Zoology

Publication Date: 2024-01-01

Volume: 72

Issue: Unknown

Page Range: 203-213

Description:

To date, the genus Diaphera Albers, 1850 was represented by a single species (D. prima Panha, 2010) in Thailand, and another (D. saurini Benthem Jutting, 1962) was known from Cambodia. Here we report D. prima for the first time from Cambodia, and describe two new species (D. pongrati, new species, D. parini, new species) from Eastern Thailand. Both new species live sympatrically with D. prima, which is reported here from Chachoengsao, Chon Buri, Rayong, and Sa Kaeo Provinces.

Open Access: Yes

DOI: 10.26107/RBZ-2024-0017

Wave Propagation in Composite Metal Foams Investigated by Finite Element Methods in Two Dimensional Case

Balázs Pere Márió Kovács

Publication Name: Advances in Transdisciplinary Engineering

Publication Date: 2024-01-01

Volume: 59

Issue: Unknown

Page Range: 224-230

Description:

The presented work is based on the wave propagation properties of composite metal foams in a two-dimensional model with a focus on the energy absorption. The energy flux method was used for the study and it was shown that composite metal foams have a significant energy absorption capacity. Hence, they can be used with high efficiency, for example, as a sound insulation layer. A pair of materials commonly used in syntactic metal foams, iron shell and aluminium matrix material, was used in the finite element model. Damping is included in the calculations to avoid oscillations.

Open Access: Yes

DOI: 10.3233/ATDE240549