Journal Description
Engineering Proceedings
Engineering Proceedings
is an open access journal dedicated to publishing findings resulting from conferences, workshops, and similar events, in all areas of engineering. The conference organizers and proceedings editors are responsible for managing the peer-review process and selecting papers for conference proceedings.
Latest Articles
Green House Gas Emission Analysis in the Food Processing Industry: A Case Study of MSME in South India
Eng. Proc. 2024, 66(1), 8; https://doi.org/10.3390/engproc2024066008 - 28 Jun 2024
Abstract
►
Show Figures
Rising carbon emissions are worsening global climatic conditions, posing a grave threat to the environment. Analysing and reducing carbon footprints are vital for combating climate change. A carbon footprint analysis categorises emissions into three scopes, aiming to identify re- duction areas and promote
[...] Read more.
Rising carbon emissions are worsening global climatic conditions, posing a grave threat to the environment. Analysing and reducing carbon footprints are vital for combating climate change. A carbon footprint analysis categorises emissions into three scopes, aiming to identify re- duction areas and promote sustainable practices, such as energy efficiency, renewable energy use, and eco-friendly choices in consumption. The current study’s purpose is to track and analyse the carbon emissions in the inbound and outbound logistics of a process industry belonging to Micro Small and Medium Enterprises using life cycle analysis. Ultimately, this study recommends mitigation strategies to bring down the carbon footprint.
Full article
Open AccessProceeding Paper
A Review on Medical Image Analysis Using Deep Learning
by
Raju Egala and M. V. S. Sairam
Eng. Proc. 2024, 66(1), 7; https://doi.org/10.3390/engproc2024066007 - 28 Jun 2024
Abstract
The objective of the medical image analysis is to increase the effectiveness of the diagnosis options. The Coevolution Neural Network (CNN) is the predominant neural network architecture used in Deep Learning (DL) for medical image analysis. Recently, various innovative technics of DL such
[...] Read more.
The objective of the medical image analysis is to increase the effectiveness of the diagnosis options. The Coevolution Neural Network (CNN) is the predominant neural network architecture used in Deep Learning (DL) for medical image analysis. Recently, various innovative technics of DL such as different activation functions, optimization technics, and loss functions have enhanced the performance of CNNs. The Deep Learning CNN (DL-CNN) assists as valuable tool to assist radiologist in diagnosis and improves efficiency and accuracy. Numerous DL-CNN methods have been published to analyze medical images. This paper compiles the performance metrics of DL-CNN, as presented by various authors. This paper reviews the image analysis of six different diseases, viz., lung cancer, colorectal cancer, liver cancer, stomach cancer, breast cancer, and brain tumors.
Full article
Open AccessProceeding Paper
An Investigation into the Design and Analysis of the Front Frame Bumper with Dynamic Load Impact
by
B. Gowthama Rajan, S. Padmanabhan, Devendra Gautam, Feroja Khan, S. Baskar, A. Lalitha Saravanan and Abhishek Sharma
Eng. Proc. 2024, 66(1), 6; https://doi.org/10.3390/engproc2024066006 - 28 Jun 2024
Abstract
►▼
Show Figures
The present study is aimed at upgrading the passenger car’s front inner bumper. The dynamic explicit time-stepping method IMPACT was used to conduct the impact analysis. The programme was first evaluated against experimental findings for beams subjected to impacts at low loads. The
[...] Read more.
The present study is aimed at upgrading the passenger car’s front inner bumper. The dynamic explicit time-stepping method IMPACT was used to conduct the impact analysis. The programme was first evaluated against experimental findings for beams subjected to impacts at low loads. The deviation between the simulated and experimental findings of the deflected beam ranged from 1.6% to 9.5%. The genuine bumper was subjected to two different kinds of impact simulations. The data were used as a standard against which to compare future bumper improvements. Internal energy absorption is much higher in all the conditions. All three designs are able to absorb more energy without changing their overall performance.
Full article
![](https://pub.mdpi-res.com/engproc/engproc-66-00006/article_deploy/html/images/engproc-66-00006-g001-550.jpg?1719561661)
Figure 1
![](https://pub.mdpi-res.com/engproc/engproc-66-00006/article_deploy/html/images/engproc-66-00006-g003-550.jpg?1719561662)
Figure 3
![](https://pub.mdpi-res.com/engproc/engproc-66-00006/article_deploy/html/images/engproc-66-00006-g004-550.jpg?1719561663)
Figure 4
![](https://pub.mdpi-res.com/engproc/engproc-66-00006/article_deploy/html/images/engproc-66-00006-g005-550.jpg?1719561664)
Figure 5
Open AccessProceeding Paper
Optimizing Social Security Contributions for Spanish Self-Employed Workers: Combining Data Preprocessing and Ensemble Models for Accurate Revenue Estimation
by
Luis Palomero, Vicente García and José Salvador Sánchez
Eng. Proc. 2024, 68(1), 5; https://doi.org/10.3390/engproc2024068005 - 28 Jun 2024
Abstract
►▼
Show Figures
The Real Decreto-ley 13/2022 has amended the framework governing the calculation of Social Security contributions for Spanish self-employed workers. This framework obligates taxpayers to the annual revenue projection, under the possibility of lending money for free or paying unexpected taxes at the end
[...] Read more.
The Real Decreto-ley 13/2022 has amended the framework governing the calculation of Social Security contributions for Spanish self-employed workers. This framework obligates taxpayers to the annual revenue projection, under the possibility of lending money for free or paying unexpected taxes at the end of the year in the case of deviations. To address this issue, the Declarando firm has developed an algorithm to recommend the optimal contributions that combines a Simple Moving Average forecasting method with an offset-adjustment technique. This paper examines how this strategy can be improved by cleaning the input data and combining different forecasts using an Ensemble-based approach. After testing experimentally various alternatives, a promising strategy involves employing a median-based Ensemble on preprocessed data. Although this Ensemble-based approach significantly reduces forecasting errors, the improvements are diluted when the predictions are combined with the offset-adjustment process.
Full article
![](https://pub.mdpi-res.com/engproc/engproc-68-00005/article_deploy/html/images/engproc-68-00005-g001-550.jpg?1719565353)
Figure 1
![](https://pub.mdpi-res.com/engproc/engproc-68-00005/article_deploy/html/images/engproc-68-00005-g003-550.jpg?1719565357)
Figure 3
Open AccessProceeding Paper
Deep Learning for Crime Forecasting of Multiple Regions, Considering Spatial–Temporal Correlations between Regions
by
Martín Solís and Luis-Alexander Calvo-Valverde
Eng. Proc. 2024, 68(1), 4; https://doi.org/10.3390/engproc2024068004 - 28 Jun 2024
Abstract
►▼
Show Figures
Crime forecasting has gained popularity in recent years; however, the majority of studies have been conducted in the United States, which may result in a bias towards areas with a substantial population. In this study, we generated different models capable of forecasting the
[...] Read more.
Crime forecasting has gained popularity in recent years; however, the majority of studies have been conducted in the United States, which may result in a bias towards areas with a substantial population. In this study, we generated different models capable of forecasting the number of crimes in 83 regions of Costa Rica. These models include the spatial–temporal correlation between regions. The findings indicate that the architecture based on an LSTM encoder–decoder achieved superior performance. The best model achieved the best performance in regions where crimes occurred more frequently; however, in more secure regions, the performance decayed.
Full article
![](https://pub.mdpi-res.com/engproc/engproc-68-00004/article_deploy/html/images/engproc-68-00004-g001-550.jpg?1719556530)
Figure 1
![](https://pub.mdpi-res.com/engproc/engproc-68-00004/article_deploy/html/images/engproc-68-00004-g003-550.jpg?1719556533)
Figure 3
Open AccessProceeding Paper
Enhancing Strength and Surface Quality of 3D-Printed Metal-Infused Filaments in Fused Deposition Modelling
by
Rama Seshu K. V. Ganga, Ramu Inala, Chandra Sekhar Jowdula, Praveen Matti and Battina N. Malleswararao
Eng. Proc. 2024, 66(1), 5; https://doi.org/10.3390/engproc2024066005 - 27 Jun 2024
Abstract
►▼
Show Figures
Fused deposition modelling (FDM) is a widely used 3D printing technique known for its versatility across industries. However, achieving optimal strength, crucial for applications like the automotive and aerospace industries, remains a challenge. This study demonstrates the efficacy of metal-infused filaments in enhancing
[...] Read more.
Fused deposition modelling (FDM) is a widely used 3D printing technique known for its versatility across industries. However, achieving optimal strength, crucial for applications like the automotive and aerospace industries, remains a challenge. This study demonstrates the efficacy of metal-infused filaments in enhancing FDM’s strength and quality. By incorporating metal particles into polymer matrices, their mechanical properties are notably improved. PLA and metal-infill PLA (copper, silver) are tested, with silver PLA showing notably higher tensile strength and hardness. Considerations such as infill density and pattern are discussed for optimizing object strength. This work underscores the potential of metal-infused FDM printing for advancing manufacturing capabilities, especially for intricate, high-strength metal components.
Full article
![](https://pub.mdpi-res.com/engproc/engproc-66-00005/article_deploy/html/images/engproc-66-00005-g001-550.jpg?1719479938)
Figure 1
![](https://pub.mdpi-res.com/engproc/engproc-66-00005/article_deploy/html/images/engproc-66-00005-g003-550.jpg?1719479940)
Figure 3
![](https://pub.mdpi-res.com/engproc/engproc-66-00005/article_deploy/html/images/engproc-66-00005-g004-550.jpg?1719479940)
Figure 4
Open AccessProceeding Paper
Internet of Things Enabled Adjustable Ramp System for Productivity Enhancement of Micro, Small and Medium Enterprises
by
Akhil Sharma, Balbir Singh and Prabir Sarkar
Eng. Proc. 2024, 66(1), 4; https://doi.org/10.3390/engproc2024066004 - 27 Jun 2024
Abstract
►▼
Show Figures
The industry usually faces a problem during the loading/unloading of finished products and raw materials from one place to another when both places are at different elevations. As trucks are of variable height and industry loading bays are at different elevations, it is
[...] Read more.
The industry usually faces a problem during the loading/unloading of finished products and raw materials from one place to another when both places are at different elevations. As trucks are of variable height and industry loading bays are at different elevations, it is not possible to drive the pallets effectively into freight, which results in decreasing loading/unloading efficiency of small concerns. In this paper, an adjustable height ramp system for increasing production efficiency and improving the industrial working environment was developed using a linear actuator and automation system for the safe loading and unloading of pallets. This adjustable ramp will help to increase the productivity of micro, small and medium enterprises (MSMEs), and it will provide a safe working environment. Using an adjustable ramp will help create a bridge between industry loading bays and freight, and it will also resolve the issue of different heights of both by making a path between them. The Internet of things (IoT)-enabled lifting and downward movement of the ramp is attempted for oil/air filter MSMEs.
Full article
![](https://pub.mdpi-res.com/engproc/engproc-66-00004/article_deploy/html/images/engproc-66-00004-g001-550.jpg?1719479628)
Figure 1
![](https://pub.mdpi-res.com/engproc/engproc-66-00004/article_deploy/html/images/engproc-66-00004-g003-550.jpg?1719479631)
Figure 3
![](https://pub.mdpi-res.com/engproc/engproc-66-00004/article_deploy/html/images/engproc-66-00004-g004-550.jpg?1719479633)
Figure 4
![](https://pub.mdpi-res.com/engproc/engproc-66-00004/article_deploy/html/images/engproc-66-00004-g005-550.jpg?1719479633)
Figure 5
![](https://pub.mdpi-res.com/engproc/engproc-66-00004/article_deploy/html/images/engproc-66-00004-g006-550.jpg?1719479635)
Figure 6
![](https://pub.mdpi-res.com/engproc/engproc-66-00004/article_deploy/html/images/engproc-66-00004-g007-550.jpg?1719479636)
Figure 7
![](https://pub.mdpi-res.com/engproc/engproc-66-00004/article_deploy/html/images/engproc-66-00004-g008-550.jpg?1719479637)
Figure 8
Open AccessProceeding Paper
Forecasting Methods for Road Accidents in the Case of Bucharest City
by
Cristina Oprea, Eugen Rosca, Ionuț Preda, Anamaria Ilie, Mircea Rosca and Florin Rusca
Eng. Proc. 2024, 68(1), 3; https://doi.org/10.3390/engproc2024068003 - 27 Jun 2024
Abstract
►▼
Show Figures
This paper aims to emphasize the necessity for policy reform, improvements in vehicle design and enhanced public awareness through the projection of future trends in road accidents, injuries and fatalities. The statistical methods that are used in this study are the empirical laws
[...] Read more.
This paper aims to emphasize the necessity for policy reform, improvements in vehicle design and enhanced public awareness through the projection of future trends in road accidents, injuries and fatalities. The statistical methods that are used in this study are the empirical laws of Smeed and Andreassen. The main gap that the researchers identify is the lack of a standardized methodology with the help of which the appropriate forecasting method can be chosen in the area of traffic accidents. In the present study, the authors propose such a methodology that can be generalized, being suitable for use for any urban agglomeration at the micro and macro level.
Full article
![](https://pub.mdpi-res.com/engproc/engproc-68-00003/article_deploy/html/images/engproc-68-00003-g001-550.jpg?1719548352)
Figure 1
Open AccessProceeding Paper
Magnetic Assisted Finishing of Internal Surfaces
by
Munish Kumar, Ajay Choudhary and Dilshad Ahmad Khan
Eng. Proc. 2024, 66(1), 3; https://doi.org/10.3390/engproc2024066003 - 27 Jun 2024
Abstract
Surface quality is one of the most important things to think about when using precision equipment. Inadequate surface quality in engineering products can result in a number of issues, such as excessive wear, failures, improper geometry, and more. Traditional finishing techniques are neither
[...] Read more.
Surface quality is one of the most important things to think about when using precision equipment. Inadequate surface quality in engineering products can result in a number of issues, such as excessive wear, failures, improper geometry, and more. Traditional finishing techniques are neither flexible nor economical when it comes to finishing complex geometries. When it comes to finishing with low tolerances and no surface topography degradation, magnetic assisted finishing systems rank among the best. This chapter discusses the types of magnetic assisted finishing techniques, including BERMP, UAMAF, and MAF, and how they are used to finish internal surfaces.
Full article
Open AccessProceeding Paper
Explaining When Deep Learning Models Are Better for Time Series Forecasting
by
Martín Solís and Luis-Alexander Calvo-Valverde
Eng. Proc. 2024, 68(1), 1; https://doi.org/10.3390/engproc2024068001 - 27 Jun 2024
Abstract
►▼
Show Figures
There is a gap of knowledge about the conditions that explain why a method has a better forecasting performance than another. Specifically, this research aims to find the factors that can influence deep learning models to work better with time series. We generated
[...] Read more.
There is a gap of knowledge about the conditions that explain why a method has a better forecasting performance than another. Specifically, this research aims to find the factors that can influence deep learning models to work better with time series. We generated linear regression models to analyze if 11 time series characteristics influence the performance of deep learning models versus statistical models and other machine learning models. For the analyses, 2000 time series of M4 competition were selected. The results show findings that can help explain better why a pretrained deep learning model is better than another kind of model.
Full article
![](https://pub.mdpi-res.com/engproc/engproc-68-00001/article_deploy/html/images/engproc-68-00001-g001-550.jpg?1719481530)
Figure 1
Open AccessProceeding Paper
Exploring the Dynamics of Natural Sodium Bicarbonate (Nahcolite), Sodium Carbonate (Soda Ash), and Black Ash Waste in Spray Dry SO2 Capture
by
Robert Makomere, Lawrence Koech, Hilary Rutto and Alfayo Alugongo
Eng. Proc. 2024, 67(1), 1; https://doi.org/10.3390/engproc2024067001 - 26 Jun 2024
Abstract
►▼
Show Figures
The efficacy of spray dry systems compared to wet flue gas desulphurisation (FGD) units depends on applying a highly reactive scrubbing reagent. This study assessed sodium-based compounds derived from natural sources and waste by-products as potential agents for treating sulphur dioxide (SO2
[...] Read more.
The efficacy of spray dry systems compared to wet flue gas desulphurisation (FGD) units depends on applying a highly reactive scrubbing reagent. This study assessed sodium-based compounds derived from natural sources and waste by-products as potential agents for treating sulphur dioxide (SO2). Sodium carbonate (Na2CO3) and sodium bicarbonate (NaHCO3) were acquired from mineral deposits, whereas the black ash waste (Na2CO3·NaHCO3) was obtained from the pulp and paper sector. The sorbents introduced in slurry form were subject to SO2 absorption conditions in a lab-scale spray dryer, including an inlet gas phase temperature of 120–180 °C, flue gas flow rate of 21–34 m3/h, and sodium to sulphur normalised stoichiometric ratio (Na:S) of 0.25–1. The comparative performance was evaluated using the metric of %SO2 ( ) removal efficiency. The results showed that NaHCO3 had the highest overall result, with a removal efficiency of 62% at saturation. Black ash was the second best-performing reagent, with a 56% removal efficiency, while Na2CO3 had the lowest efficiency (53%). The maximum degree of SO2 reduction achieved using NaHCO3 under specific operating parameters was at an NSR of 0.875 (69%), a reaction temperature of 120 °C (73%), and a gas inlet flow rate of 34 m3/h. In conclusion, the sodium reagents produced significant SO2 neutralisation, exceeding 50% in their unprocessed state, which is within acceptable limits in small- to medium-sized coal-fired power plants considering retrofitting pollution control systems.
Full article
![](https://pub.mdpi-res.com/engproc/engproc-67-00001/article_deploy/html/images/engproc-67-00001-g001-550.jpg?1719467455)
Figure 1
![](https://pub.mdpi-res.com/engproc/engproc-67-00001/article_deploy/html/images/engproc-67-00001-g003-550.jpg?1719467457)
Figure 3
![](https://pub.mdpi-res.com/engproc/engproc-67-00001/article_deploy/html/images/engproc-67-00001-g004-550.jpg?1719467458)
Figure 4