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Found 6334 publications

Sentinels of Sustainability: Practices of Agricultural Farms Clustered in Hungary’s Farmers’ Markets

Károly Kacz Koltai Judit Petra Szabolcs Troján Tamás Vinkóczi Anita Miklósné Varga

Publication Name: Chemical Engineering Transactions

Publication Date: 2024-01-01

Volume: 114

Issue: Unknown

Page Range: 973-978

Description:

The analysis of local farmers' markets (FMs) is an important part of sustainability issues, as the products they offer can guarantee both the proper functioning of local farms and healthy nutrition for inhabitants. The aim of this research is to identify the most important characteristics of FMs small-scale businesses related to agricultural activities based on a convenience sample in Hungary. The database obtained by the questionnaire survey was compiled based on the answers of a total of 220 farm owners/managers. The results were subjected to analysis using a K-means clustering method, which identified four distinct groups of farms with the highest weighting of turnover from agricultural activity. The clustering distinguished beekeeping, arable crop production, animal husbandry, and vegetable and fruit production, which were treated as a separate cluster. The observed differences between the groups indicate that farms primarily engaged in beekeeping and livestock farming have the highest turnover. These findings may be manifested by the group’s member farms in terms of higher professional representation and high-quality products. A noteworthy distribution-related finding is that livestock products exhibit the greatest average distance from the point of origin to the FM, which can be attributed to the sparse geographical location of the production sites. The results could have a considerable consequence for policymakers in informing them about the design of support opportunities and the identification of beneficiary groups.

Open Access: Yes

DOI: 10.3303/CET24114163

THREE NEW SPECIES OF ORIBATID MITES OF THE SUPERFAMILY ORIPODOIDEA (ACARI, ORIBATIDA) FROM VIETNAM

Sergey G. Ermilov Jenő Kontschán V. M. Salavatulin

Publication Name: Zoologicheskii Zhurnal

Publication Date: 2024-01-01

Volume: 103

Issue: 2

Page Range: 3-13

Description:

Three new species of oribatid mites (Oribatida) of the superfamily Oripodoidea – Phauloppia differens sp. n. (Oribatulidae), Oripoda operta sp. n. (Oripodidae) and Pirnodus concavus sp. n. (Oripodidae) – are described, based on adults collected from the bark and tree branches of Dipterocarpus alatus and Haldina cordifolia in southern Vietnam.

Open Access: Yes

DOI: 10.31857/S0044513424020011

Assessing the Performance of Machine Learning Algorithms in Predicting Buckling Moments of Corrugated Web Beams

Andreas Müller Nurullah Bektaş G. Hajdú

Publication Name: Advances in Transdisciplinary Engineering

Publication Date: 2024-01-01

Volume: 59

Issue: Unknown

Page Range: 121-127

Description:

I-beams with corrugated webs have higher torsional stiffness than that of flat web beams. Furthermore, the geometrical dimensions of the beam and the web corrugation heavily influence the precision of the currently used traditional pen-andpaper methods for determining the elastic lateral-torsional buckling moment. This study aims to suggest several machine learning models with the intention of predicting the elastic lateral-torsional buckling moment of corrugated web beams. Multiple machine learning models, including Random Forests, Gradient Boosting, Categorical Boosting, and Deep Neural Networks, were deployed to develop and train models to predict the elastic critical lateral-torsional buckling moments of Ibeams with corrugated web. The database used for training the different models was compiled through linear bifurcation analyses conducted on shell finite element models. The study evaluates the precision of the various machine learning models by examining their performance against statistical parameters derived from both predicted and test data. The findings from the parametric evaluation highlight the surprisingly high performance and accuracy of the machine learning models.

Open Access: Yes

DOI: 10.3233/ATDE240535

Metaheuristics in Logistics: Increasing the Efficiency of Algorithms by Defining Appropriate Parameter Settings

Péter Németh Tamara J. Bíró

Publication Name: Chemical Engineering Transactions

Publication Date: 2024-01-01

Volume: 114

Issue: Unknown

Page Range: 1009-1014

Description:

Metaheuristic algorithms are well-researched and popular techniques in the field of optimization, which can solve complex tasks with a large number of instances with acceptable quality. They are extremely problem- and parameter-sensitive methods, so the exact definition of the necessary data and the testing of the appropriate parameters fundamentally determine the efficiency and performance of an algorithm. This is a time-consuming and expensive task. In many cases, when applying a metaheuristic, it works properly with the variables of a given task and there is no specific interval where a given algorithm can still be effective. To increase efficiency and reduce costs, the authors defined a general parameter definition by applying the Ant Colony Optimization algorithm applicable to the simple Traveling Salesman Problem with the number of cities n=50, where for values of 30 ≤ n ≤ 50, the defined parameter setting structure can be properly applied based on the results. The proposed parameter setting structure can work effectively not only for the task presented in the paper, but also for any similar task within the defined interval. In the case of tasks of a similar size, it is not necessary to experiment with the parameters to achieve the appropriate result, thereby reducing the optimization time and improving efficiency. The presentation of the set parameter setting scenarios and the obtained results all contribute to reducing the optimization time in the field of logistics as well. All of this can also help facilitate the practical application of metaheuristics in solving NP-hard tasks.

Open Access: Yes

DOI: 10.3303/CET24114169

Effects of selective laser melting building directions and surface modifications on surface roughness of Ti6Al4V alloy

Tünde Anna Kovács Hassanen Jaber J. Kónya H. Hargitai

Publication Name: Discover Applied Sciences

Publication Date: 2024-01-01

Volume: 6

Issue: 1

Page Range: Unknown

Description:

Abstract: In this paper, the effect of building direction relative to the substrate (0°, 45°, and 90°) on the surface roughness of Ti6Al4V samples produced by selective laser melting (SLM) has been investigated. After SLM, the samples were subjected to different surface modifications, including acid etching (E) with HF, sandblasting (S) with Al2O3 and sandblasting + etching (SE). Surface roughness of the prepared samples were investigated by Alicona Infinite Focus optical microscopy and Scanning Electron Microscopy (SEM). It was found that there is an inverse relationship between surface roughness and building directions. Additionally, the results showed that the acid etching process increases the surface roughness of the samples at 45° and 90°, while the surface roughness decreases at 0°. Furthermore, the results showed that sandblasting and sandblasting followed with acid etching (SE) effectively reduced the surface roughness of the samples at all building directions. In summary, the acid-etched Ti6Al4V surfaces manufactured at 90° showed a superior surface roughness (Ra = 4.25 ± 0.21, Rz = 29.63 ± 2.34 μm) among the specimens, which is encouraged osseointegration of implants.

Open Access: Yes

DOI: 10.1007/s42452-024-05656-0

The Evolution of Digitalization Transformation and Industry 4.0 in Supply Chain Management: A Systematic Literature Review †

László Buics Tran Nguyen Ngoc Quynh

Publication Name: Engineering Proceedings

Publication Date: 2024-01-01

Volume: 79

Issue: 1

Page Range: Unknown

Description:

The digital revolution is rapidly reshaping supply chains, driven by the confluence of Industry 4.0 and digitalization transformations. This research aims to investigate the evolution of the digitalization transformation era by integrating machine learning and big data management into supply chain management (SCM). A systematic literature review and mapping study were conducted, analyzing 223 articles from the Scopus database and 60 from Web of Science, selected through a Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) screening process and the Population, Exposure, and Outcome (PEO) framework. This study provides a narrative summary of the evolution of decision-making and consultation processes, recommendation approaches, and guidelines for enterprises to achieve sustainability in their supply chain management. It also identifies potential areas for future research in navigating the world of digitized supply chains.

Open Access: Yes

DOI: 10.3390/engproc2024079065

Analysing the Environmental Durability and Chrysotile Content of Asbestos Cement Products by FT-IR Spectroscopy

András Torma Gergely Zoltán Macher Dóra Beke

Publication Name: Chemical Engineering Transactions

Publication Date: 2024-01-01

Volume: 114

Issue: Unknown

Page Range: 709-714

Description:

The aim of this paper is to examine the environmental resistance and chrysotile content of different asbestos cement products and to prove the relationship between these two factors by analytical results. The paper includes Fourier-transform infrared (FT-IR) spectroscopic analysis of asbestos cement pipes and asbestos cement products with corrugated and flat characteristics. The methodology of the study is based on FT-IR spectroscopy and general statistical approaches, and the results obtained are compared using correlation analysis. The background to the topic is that asbestos cement products are still widely used today despite their harmful effects on health, contrary to European Union asbestos-free targets. A damaged and eroded asbestos cement product loses several grams of asbestos and cement per year from its matrix structure, which is exacerbated by exposure to various environmental influences. The match rate of the chrysotile spectrum for analysed samples has been over 50 % in each case. In the number of measurements, the chrysotile detection rate was 7.64 % higher for degraded and eroded samples. In addition, in the samples exposed to environmental factors, the percentage variance was approximately 10 % or higher, with the exception of asbestos cement pipes. The results provide a basis for situational awareness options. Analytic practitioners, material science researchers, and analysts can use them.

Open Access: Yes

DOI: 10.3303/CET24114119

Sustainable Cities by Collaborative Last Mile Parcel Delivery - Live Example Insight

Edit Süle Csilla Bartucz

Publication Name: Springer Proceedings in Earth and Environmental Sciences

Publication Date: 2024-01-01

Volume: Part F2516

Issue: Unknown

Page Range: 457-468

Description:

The restrictive measures during the Covid pandemic resulted in an unexpected growth in e-commerce, which growth has continued since the epidemic. The growth of e-commerce also increased the number of last mile parcel delivery transactions. The growth of last mile parcel logistics also resulted in an increasing number of cars, emissions and traffic problems. City governments introduce restrictive measures against increased environmental burdens, which imposes an additional burden on parcel logistics providers. Collaboration among last-mile service providers can assist boost productivity while at the same time lowering harmful environmental effects. However, there is little service provider cooperation in this industry. This study analyses the development of cooperation between service providers based on an examination of a Central-Eastern European Courier, Express, Parcel (CEP) market, which has market characteristics that can be referred to as typical for this area such as: a small number of dominant service providers; a large number of small service providers who are usually subcontractors of the dominant ones; individualistic operation. The market structure of the example country being presented is oligopoly, which is typical of the CEP market of the countries in the region. The analysis of the Hungarian market is supplemented by the creation of a model that simulates cooperation, which shows that the quantity of delivery vehicles, the distance travelled by the trucks, and the degree of environmental impact brought on by all of this can be decreased.

Open Access: Yes

DOI: 10.1007/978-3-031-48532-9_42

Building Diagnostics Options for Existing Buildings – Innovative Methods

Adam Bukovics Kitti Karolyfi Dóra Szalai Zsolt Szűrös Rita Rebeka Ördög

Publication Name: Chemical Engineering Transactions

Publication Date: 2024-01-01

Volume: 114

Issue: Unknown

Page Range: 793-798

Description:

The increasing number of buildings, due to erosion and extraordinary effects, has increasingly made technological advancements focused on innovative methods possible. This has become more prominent alongside traditional practices such as visual inspection and destructive building diagnostic methods. Thanks to the continuous development of tools, technologies and methodologies, the accurate and detailed digital mapping of buildings (including all their aspects) is available. Among these solutions, the laser scanner point cloud is the most popular due to its high level of detail. The newly emerging and now widespread survey procedures based on laser, photogrammetric remote sensing reflect a real-time, current state of the buildings, which maximizes the accuracy of the Building Information Model (BIM) - Historic Building Information Model (HBIM) completed in the later phases and helps detect structural or surface defects. This study presents the analyzing techniques of point clouds to diagnose buildings, assess their condition, identify errors, and develop sustainability strategies. It also explores areas that require further research and development to enhance the effectiveness of these methods. In the first phase of the paper, the currently used point cloud generation technologies (e.g.: laser scanning, photogrammetry, light detection and ranging (LiDAR)) will be presented with their advantages and disadvantages. The research methodology was conducted using the VOSviewer software to visually analyze bibliometric networks from a dataset of scientific publications, focusing on trends in structural health monitoring and highlighting key areas such as damage detection, computer vision, and AI-based techniques. In the second phase of the study, the possibilities of the analysis of point clouds and image processing-based survey options for structural diagnostic purposes will be explained and presented. The evaluation of the three damage detection methodologies (Geometrical features, Color and intensity information, Combined Method) highlights their complexity, technological requirements, cost, practical applicability, and accuracy. During the analysis, the goal is to map and systematize innovative methods supported by digital tools for diagnostic tasks in existing buildings.

Open Access: Yes

DOI: 10.3303/CET24114133