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6 pages, 355 KiB

Open AccessEditorial

Preface: III International Congress: Technology and Innovation in Engineering and Computing

by Luis Olivera-Montenegro

Eng. Proc. 2025, 83(1), 5; https://doi.org/10.3390/engproc2025083005 - 7 Jan 2025

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Abstract

The III International Congress: Technology and Innovation in Engineering and Computing, organized by Faculty of Engineering, St [...] Full article

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10 pages, 7549 KiB

Open AccessProceeding Paper

Effect of the Process Parameters on the Mechanical Properties of 3D-Printed Specimens Fabricated by Material Extrusion 3D Printing

by Andoni Molina and Julio Acosta-Sullcahuamán

Eng. Proc. 2025, 83(1), 1; https://doi.org/10.3390/engproc2025083001 - 6 Jan 2025

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Abstract

This work aims to study the influences of nozzle temperature, layer thickness and raster angles on the mechanical properties of acrylonitrile butadiene styrene (ABS) and polylactic acid (PLA) specimens fabricated by material extrusion 3D printing. Tensile tests were carried out in order to [...] Read more.

This work aims to study the influences of nozzle temperature, layer thickness and raster angles on the mechanical properties of acrylonitrile butadiene styrene (ABS) and polylactic acid (PLA) specimens fabricated by material extrusion 3D printing. Tensile tests were carried out in order to evaluate the mechanical properties of ABS and PLA specimens. The results showed that tensile strength decreased at a higher nozzle temperature for ABS, while an increase followed by a decrease in tensile strength occurred for PLA, with the maximum value obtained at 250 °C. Scanning electronic microscopy was used to analyze the surface fracture after tensile tests of specimens fabricated with different nozzle temperatures. Moreover, the highest tensile strength values for both ABS and PLA were achieved with a raster angle of [0°], the same direction as the applied tensile load. Additionally, a higher tensile strength was obtained for both ABS and PLA at a lower layer thickness. Based on these results, the process parameters used to manufacture a 3D object influence its mechanical properties. Full article

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9 pages, 3011 KiB

Open AccessProceeding Paper

Design, Manufacturing and Mechanical Evaluation of a 3D Printed Customized Wrist-Hand Orthosis for the Treatment of De Quervain Tenosynovitis

by Sofia Franco, Mauricio Ramos, Renzo Cordova, Emilio Ochoa, Gianella Ccama and Andoni Molina

Eng. Proc. 2025, 83(1), 2; https://doi.org/10.3390/engproc2025083002 - 6 Jan 2025

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Abstract

De Quervain’s tenosynovitis is a pathology that affects the tendons of the thumb and generates pain and inflammation, being common in people between 18 and 30 years old who perform repetitive movements. Despite the innovation of 3D printing in orthotics, customization is lacking. [...] Read more.

De Quervain’s tenosynovitis is a pathology that affects the tendons of the thumb and generates pain and inflammation, being common in people between 18 and 30 years old who perform repetitive movements. Despite the innovation of 3D printing in orthotics, customization is lacking. Therefore, this works aims to develop a 3D printed customized wrist-hand orthosis (WHO) for the treatment of De Quervain tenosynovitis. The WHO includes three main parts, which would be two faces that cover the front and back of the hand and the locks to ensure the coupling of both faces. Prior to 3D printing, feedstock filament characterization tests were carried out, and tensile strength, melt flow index, degradation, and melting temperature were obtained. 3D printing of the WHO was achieved in a short time and with an adequate fit. Subsequently, mechanical tests were carried out to evaluate the maximum force of the WHO in different positions. Full article

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Solution concept. Full article ">Figure 2
Area involved in immobilization [<a href="#B12-engproc-83-00002" class="html-bibr">12</a>]. A: Distal metacarpal area, B: Base of the thumb, C: Central Dorsal Area, D: Wrist Area, E: Distal palmar area. Full article ">Figure 3
Autodesk Fusion 360: Selection of side of application of force (blue arrow). Full article ">Figure 4
Manufacturing process of WHO. Full article ">Figure 5
Mechanical test of WHO. Full article ">Figure 6
Wrist movements, modified of [<a href="#B16-engproc-83-00002" class="html-bibr">16</a>]. (A) Flexion, (B) Extension, (C) Ulnar deviation and (D) Radial deviation. Full article ">Figure 7
FTIR results. Full article ">Figure 8
Manufacturing results: (a) Orthosis printed in 90° degrees. (b) Orthosis printed in 45° to the left. (c) Orthosis printed in 75° to the front. Full article ">

9 pages, 2119 KiB

Open AccessProceeding Paper

Additive Manufacturing of Reinforced Thermoplastic Nanoclay Particle Composites by Fused Filament Fabrication

by Andoni R. Molina and Julio Acosta-Sullcahuamán

Eng. Proc. 2025, 83(1), 3; https://doi.org/10.3390/engproc2025083003 - 7 Jan 2025

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Abstract

In this study, reinforced thermoplastic nanoclay particle composites were prepared and used as filaments for additive manufacturing of specimens by using fused filament fabrication (FFF). Acrylonitrile butadiene styrene (ABS) and polylactic acid (PLA) were used as thermoplastic polymer matrices. The particle reinforced composite [...] Read more.

In this study, reinforced thermoplastic nanoclay particle composites were prepared and used as filaments for additive manufacturing of specimens by using fused filament fabrication (FFF). Acrylonitrile butadiene styrene (ABS) and polylactic acid (PLA) were used as thermoplastic polymer matrices. The particle reinforced composite feedstock filaments were fabricated from ABS and PLA pellets with different contents of nanoclay particles in a twin-screw extruder. Tensile and impact tests were carried out to evaluate the mechanical properties of the composite specimens fabricated by FFF. The mechanical test results showed an increase in the tensile strength of ABS matrix composites, but a decrease in the impact strength. For the case of PLA matrix composites, the tensile strength decreased when introducing the nanoclay particles and only with 3% of nanoclay particles was an increase of impact strength observed. Successful additive manufacturing of the particle-reinforced composite was achieved. Full article

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11 pages, 7503 KiB

Open AccessProceeding Paper

Product Design to Improve the Measurement and Projection of Mill Liner Wear

by Francklyn David Castañeda-Quilcaro, Clelia Lucero Cordova-Yavar and Rubén Felipe Vidal Endara

Eng. Proc. 2025, 83(1), 4; https://doi.org/10.3390/engproc2025083004 - 7 Jan 2025

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Abstract

Currently, in the grinding areas of Peruvian mining operations, there are linings made of various materials such as rubber and steel, all of which have a limited lifespan and eventually wear out. Understanding the wear behavior of these linings has a direct impact [...] Read more.

Currently, in the grinding areas of Peruvian mining operations, there are linings made of various materials such as rubber and steel, all of which have a limited lifespan and eventually wear out. Understanding the wear behavior of these linings has a direct impact on mill performance. There are several solutions for measuring wear, making wear projections, and, most importantly, knowing the replacement date so that the mining company can schedule a plant shutdown. However, these solutions are not swift, as traveling to the mine, returning to the company, processing the data in software, and generating reports take 3 to 10 days depending on the workload of each supplier of these linings. Mining companies seek solutions to monitor the condition of their linings and avoid plant shutdowns as they disrupt production. The primary objective of this tool is to quickly and accurately predict the wear and removal of mill linings with user safety as a top priority. The product design and development process followed the methodology proposed by Ulrich and Eppinger, which includes (a) identifying customer needs, (b) planning, (c) developing product concepts, (d) system-level design, (e) detailed design, and (f) testing and refinement. Key metrics for design were defined through 50 surveys. Additionally, two focus groups with mill lining experts and user testing were conducted, allowing for the refinement and validation of the initial concept. The tool prototype was modeled in 3D, sensors and other electrical mechanisms were purchased, and an LED screen was programmed for data reading. Methodologies such as TRIZ, SCAMPER, and Canva were incorporated, facilitating a well-designed product with attention to detail. Finally, the final characteristics of the digital comb, ranging from 10′ to 25′, were defined and tested on mill linings, and with the help of the Weir Projection application, wear history and projections were rapidly generated. When compared with other measurement tools, minimal differences were found within a range of ±2 mm. Therefore, it is concluded that the prototype assists in quickly scheduling mill lining requirements in advance. Full article

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9 pages, 2397 KiB

Open AccessProceeding Paper

The Evaluation of the Seismic Performance of Unsymmetric-Plan Tall Buildings Using Modal Spectral Time History and Multi-Mode Pushover Analysis

by Luis A. Flores and Rick M. Delgadillo

Eng. Proc. 2025, 83(1), 6; https://doi.org/10.3390/engproc2025083006 - 8 Jan 2025

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Abstract

In recent seismic events that occurred worldwide and in Peru, it has been observed that irregular structures in plan present greater structural damage compared to regular structures. Investigations carried out after seismic events indicate that irregular plan structures collapse due to erroneous structural [...] Read more.

In recent seismic events that occurred worldwide and in Peru, it has been observed that irregular structures in plan present greater structural damage compared to regular structures. Investigations carried out after seismic events indicate that irregular plan structures collapse due to erroneous structural conception and poor seismic analysis. Likewise, the Peruvian earthquake-resistant standard does not establish a permissible limit for the degree of irregularity under analysis, instead qualitatively assessing the structural irregularity. The objective of this article was to study the effect of plan irregularities using innovative methodologies on the structural response of tall 10-story reinforced concrete buildings. In this sense, seventeen (17) structural models are proposed that reflect different irregular configurations in plan: 06 structures Type L, 05 structures Type I, 05 structures Type I, and one regular building. These buildings are numerically modeled using ETABS software V.18.0 through modal analysis, Modal Spectral and Linear Time History (MSLTH), and Multi-Mode Pushover (MPA). For the MSLTH, seven (07) pairs of representative Peruvian earthquakes were analyzed. The results of the modal analysis evaluated in the first two vibration modes demonstrated that Type L irregular structures change their behavior from translational to torsional when the structures present an irregularity greater than 57%. Type I and O structures present translational behavior. Furthermore, the results of the Modal Spectral and MSLTH analysis demonstrate that Type L structures present greater displacements and drifts in both directions. The shear force and the overturning moment for Types L, I, and O decrease as the irregularity in plan increases. Finally, the results of the MPA for irregular Type L structures demonstrated that the lateral stiffness of the structures decreases as the irregularity in plan is critical, increasing the possibility of the formation of plastic mechanisms in the structural elements. Full article

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6 pages, 362 KiB

Open AccessProceeding Paper

A Survey of Process Mining for Customer Management

by Javier Dioses and Leyde Cordova

Eng. Proc. 2025, 83(1), 7; https://doi.org/10.3390/engproc2025083007 - 8 Jan 2025

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Abstract

Currently, organizations are experiencing rapid growth in the digitization of their processes, which generates a high availability of data and metadata in information systems generated by the activities of operations and support areas. This is important for business because it allows them to [...] Read more.

Currently, organizations are experiencing rapid growth in the digitization of their processes, which generates a high availability of data and metadata in information systems generated by the activities of operations and support areas. This is important for business because it allows them to analyze and understand the customer journey to provide a better experience to consumers and generate value in organizations. One way to analyze the customer journey is to use process discovery to obtain an optimal process model. There are several process discovery algorithms that allow for analyzing different business process models. In this paper, we focus on the customer experience because we have found that this is a trend in business that has rarely been addressed using process discovery by means of event logs. Thus, in this study, we conduct a literature review of primary articles about the use of process discovery algorithms using event logs from information systems to provide a better understanding on this topic. As a result, we have found that Heuristic Miner, Alpha Miner, and Inductive Miner are the most used algorithms for customer process discovery. Finally, we explain our findings about process discovery in the customer experience and why this is an emerging topic. Full article

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8 pages, 1424 KiB

Open AccessProceeding Paper

A Convolutional Neural Network for Early Supraventricular Arrhythmia Identification

by Emilio J. Ochoa and Luis C. Revilla

Eng. Proc. 2025, 83(1), 8; https://doi.org/10.3390/engproc2025083008 - 8 Jan 2025

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Abstract

Supraventricular arrhythmias (SVAs), including the often-asymptomatic supraventricular extrasystole (SVE), pose significant challenges in early detection and precise diagnosis. These challenges are of paramount importance, as recurrent SVEs may elevate the risk of developing severe SVAs, potentially resulting in cardiac weakening and subsequent heart [...] Read more.

Supraventricular arrhythmias (SVAs), including the often-asymptomatic supraventricular extrasystole (SVE), pose significant challenges in early detection and precise diagnosis. These challenges are of paramount importance, as recurrent SVEs may elevate the risk of developing severe SVAs, potentially resulting in cardiac weakening and subsequent heart failure. In the study conducted, an innovative approach was introduced that combined a convolutional neural network (CNN) architecture to enable the early identification and characterization of SVEs within electrocardiogram (ECG) signals. The analysis leveraged a dataset comprising 78 half-hour recordings from the highly regarded MIT-BIH Arrhythmia Database, which included annotation headers serving as labels for each recording. Signals were down-sampled by a factor of 2 and split into windows of 512 samples, with 12,288 observations for training. Following the methodology, classic signal preprocessing techniques (filtering and data normalization) were used. The proposed model was based on the UNET 1D model. A binary cross-entropy loss function, Adam optimizer, and a batch size of 128 were obtained after a hyperparameter tuning. As a training-validation methodology, a 50-fold cross-validation technique was used. The approach demonstrated a Dice coefficient of 79.01%, a precision of 80.96%, and a recall rate of 86.60% in detecting SVE events. These findings were corroborated through meticulous comparison with the annotations provided by the MIT-BIH database. The results underscore the immense potential of CNN and deep learning techniques in the early detection of supraventricular arrhythmias. This approach not only offers a valuable tool for healthcare professionals engaged in telemonitoring and early intervention strategies but also represents a significant contribution to the field of cardiac health monitoring. By facilitating efficient and precise identification of SVEs, our research sets the stage for improved patient outcomes and the prevention of severe SVAs, marking substantial advancements in this critical domain. Full article

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8 pages, 7391 KiB

Open AccessProceeding Paper

Comparative Analysis of LiDAR Inertial Odometry Algorithms in Blueberry Crops

by Ricardo Huaman, Clayder Gonzalez and Sixto Prado

Eng. Proc. 2025, 83(1), 9; https://doi.org/10.3390/engproc2025083009 - 9 Jan 2025

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Abstract

In recent years, LiDAR Odometry (LO) and LiDAR Inertial Odometry (LIO) algorithms for robot localization have considerably improved, with significant advancements demonstrated in various benchmarks. However, their performance in agricultural environments remains underexplored. This study addresses this gap by evaluating five state-of-the-art LO [...] Read more.

In recent years, LiDAR Odometry (LO) and LiDAR Inertial Odometry (LIO) algorithms for robot localization have considerably improved, with significant advancements demonstrated in various benchmarks. However, their performance in agricultural environments remains underexplored. This study addresses this gap by evaluating five state-of-the-art LO and LIO algorithms—LeGO-LOAM, DLO, DLIO, FAST-LIO2, and Point-LIO—in a blueberry farm setting. Using an Ouster OS1-32 LiDAR mounted on a four-wheeled mobile robot, the algorithms were evaluated using the translational error metric across four distinct sequences. DLIO showed the highest accuracy across all sequences, with a minimal error of 0.126 m over a 230 m path, while FAST-LIO2 achieved its lowest translational error of 0.606 m on a U-shaped path. LeGO-LOAM, however, struggled due to the environment’s lack of linear and planar features. The results underscore the effectiveness and potential limitations of these algorithms in agricultural environments, offering insights into future improvements and adaptations. Full article

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12 pages, 4916 KiB

Open AccessProceeding Paper

Ecological Protection: Cell Phone Stand with Cable Winding Made of Polypropylene

by Deysi Vanessa Canchis Paredes, Jerson Córdova Salas and Ruben Felipe Vidal Endara

Eng. Proc. 2025, 83(1), 10; https://doi.org/10.3390/engproc2025083010 - 13 Jan 2025

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Abstract

In an increasingly digitized environment, the deterioration of cell phone cables has led to a significant environmental impact due to the lack of adequate protection and care. This often results in cell phone charging cables being in poor condition. Cable damage can include [...] Read more.

In an increasingly digitized environment, the deterioration of cell phone cables has led to a significant environmental impact due to the lack of adequate protection and care. This often results in cell phone charging cables being in poor condition. Cable damage can include situations such as dirt accumulation or incorrect bending, leading to breakage. As a result, the objective was determined to design a prototype of a cell phone holder with internal biodegradable cable winding. Ulrich and Eppinger served as the methodological basis for the design, following phases including customer needs identification, setting objective values, product concept generation, concept selection, concept testing, and final specification filtering. A survey of 100 individuals provided valuable data for validating certain metrics. Additionally, two focus groups with 15 users were conducted, two experts were interviewed, and a 72 h usage test was carried out, all supported by the agile Scrum methodology and the Scamper technique, allowing for feedback and validation of the initial concept. The final prototype was modeled in 3D using the Lumion 11 program and physically constructed, ensuring functionality and adaptability of the cell phone and charger. In conclusion, a cell phone holder with a cable winder was designed, facilitating easy transport and prolonging the lifespan of any charger cable. Full article

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9 pages, 1825 KiB

Open AccessProceeding Paper

NevusCheck: A Dysplastic Nevi Detection Model Using Convolutional Neural Networks

by Andreluis Ingaroca-Torres, Lucía Heredia-Moscoso and Alvaro Aures-García

Eng. Proc. 2025, 83(1), 11; https://doi.org/10.3390/engproc2025083011 - 13 Jan 2025

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Abstract

Dysplastic nevi are skin lesions that have distinctive clinical features and are considered risk markers for the development of melanoma, the deadliest type of skin cancer. A specific deep learning technique to identify diseases is convolutional neural networks (CNNs) because of their great [...] Read more.

Dysplastic nevi are skin lesions that have distinctive clinical features and are considered risk markers for the development of melanoma, the deadliest type of skin cancer. A specific deep learning technique to identify diseases is convolutional neural networks (CNNs) because of their great capacity to extract features and classify objects. Therefore, the research aims to develop a model to diagnose dysplastic nevi using a deep learning network whose classification is based on the pre-trained architecture EfficientNet-B7, which was selected for its high classification accuracy and low computational complexity. As for the results obtained, an accuracy of 78.33% was achieved in the classification model. Also, the degree of similarity between the detection by a dermatology expert and the proposed model reached an accuracy of 79.69%. Full article

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8 pages, 6110 KiB

Open AccessProceeding Paper

Remote Control Device for the Detection and Correction of Errors in the FDM 3D Printing Process in Real Time

by Henry Requena, Kelvin Pozuelo, Carlos Díaz and Jean Coll

Eng. Proc. 2025, 83(1), 12; https://doi.org/10.3390/engproc2025083012 - 14 Jan 2025

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Abstract

This project focuses on developing a remote control device for the real-time detection and correction of errors in fused deposition modeling (FDM) 3D printing. It utilizes a Raspberry Pi computer and a webcam to capture images while a neural network trained with a [...] Read more.

This project focuses on developing a remote control device for the real-time detection and correction of errors in fused deposition modeling (FDM) 3D printing. It utilizes a Raspberry Pi computer and a webcam to capture images while a neural network trained with a dataset generated by the research team identifies errors such as warping, stringing, and spaghetti. Information is efficiently transmitted via MQTT, with instant notifications through Telegram and a user interface. The methodology spans from training the neural network to integrated control strategies with the remote device. Evaluation highlights high precision using confusion matrices and IoU, promising substantial improvements in industrial and critical 3D printing environments. Full article

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15 pages, 9561 KiB

Open AccessProceeding Paper

Design and Implementation of an Indoor and Outdoor Air Quality Measurement Device for the Detection and Monitoring of Gases with Hazardous Health Effects

by Johnathan Gabriel Caselles Nuñez, Oscar Alejandro Contreras Negrette, Kelvin de Jesús Beleño Sáenz and Carlos Gabriel Díaz Sáenz

Eng. Proc. 2025, 83(1), 13; https://doi.org/10.3390/engproc2025083013 - 14 Jan 2025

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Abstract

This paper presents a detailed step-by-step design and construction of an indoor and outdoor air quality monitoring device, composed of electronic sensors capable of measuring gases such as Carbon Monoxide (CO), Nitrogen Dioxide (NO₂), Ozone (O₃), in addition to [...] Read more.

This paper presents a detailed step-by-step design and construction of an indoor and outdoor air quality monitoring device, composed of electronic sensors capable of measuring gases such as Carbon Monoxide (CO), Nitrogen Dioxide (NO₂), Ozone (O₃), in addition to measuring temperature and humidity, as well as concentrations of PM2.5 and PM10 particulate matter suspended in the environment. The device features the ESP32 microprocessor board that integrates IoT wireless connectivity via Wi-Fi, which allows for longer processing time and wireless communication. To evaluate the accuracy of the Q-air device, measurements were taken at strategic sites in the city of Barranquilla, which were compared with data from stationary monitoring stations in the city, the results obtained by Q-Air showed a margin of error less than 1.6%, demonstrating accuracy and efficiency. Full article

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10 pages, 3037 KiB

Open AccessProceeding Paper

Comparative Study of Asparagus Production and Quality in Two Coastal Regions of Peru Based on Meteorological Conditions for Crop Productivity Optimization

by Santiago Castillo, Patrick Villamizar, Diego Piñan, Gabriela Huaynate and Antonio Angulo

Eng. Proc. 2025, 83(1), 14; https://doi.org/10.3390/engproc2025083014 - 15 Jan 2025

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Abstract

This study focuses on remote sensing and monitoring of asparagus crops in the provinces of Ica and Trujillo, highlighting their importance in global food security. Using satellite images and temperature data, productivity was compared using the NDWI, NDVI, and EVI indices. The Grad-CAM [...] Read more.

This study focuses on remote sensing and monitoring of asparagus crops in the provinces of Ica and Trujillo, highlighting their importance in global food security. Using satellite images and temperature data, productivity was compared using the NDWI, NDVI, and EVI indices. The Grad-CAM technique was used to analyze the AlexNet Convolutional Neural Network (CNN) model, seeking to improve productivity. Although AlexNet validated the satellite images, it showed some confusion in regions of medium and low productivity. The model, supported by Grad-CAM, will contribute to the monitoring of optimal climatic conditions. Full article

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10 pages, 2410 KiB

Open AccessProceeding Paper

Ultrasonic Image Processing for the Classification of Benign and Malignant Breast Tumors: Comparative Study of Convolutional Neural Network Architectures

by Erick Acuña Chambi, Daniel Gil Alzamora and Antonio Angulo Salas

Eng. Proc. 2025, 83(1), 15; https://doi.org/10.3390/engproc2025083015 - 21 Jan 2025

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Abstract

This study addresses the limitations of conventional breast cancer diagnosis using ultrasound imaging and machine learning. Using KAGGLE data, we applied preprocessing techniques to identify tumour features. VGGNET16 demonstrated 90% accuracy, simplifying tumour classification. Our findings highlight the potential of neural networks to [...] Read more.

This study addresses the limitations of conventional breast cancer diagnosis using ultrasound imaging and machine learning. Using KAGGLE data, we applied preprocessing techniques to identify tumour features. VGGNET16 demonstrated 90% accuracy, simplifying tumour classification. Our findings highlight the potential of neural networks to improve diagnosis. By combining ultrasound imaging and machine learning, we offer an accurate and patient-friendly alternative highlighting the urgency of early tumour detection. This research presents an innovative approach with promising results, advancing diagnostic accuracy and patient comfort. Full article

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Block diagram of the algorithm. Full article ">Figure 2
(a) ultrasound image of benign tumour; (b) ultrasound image of malignant tumour. Full article ">Figure 3
Diagram of the segmentation process. Full article ">Figure 4
(a) Thresholding, dilatation, and filling of a benign tumour; (b) thresholding, dilatation, and filling of a malignant tumour. Full article ">Figure 5
(a) Canny operator edges of benign tumour; (b) canny operator edges of malignant tumour. Full article ">Figure 6
(a) Image revealed by active contours of the benign tumour; (b) image revealed by active contours of the malignant tumour. Full article ">Figure 7
(a) Result of the multiplication of binarised images of the benign tumour; (b) result of the multiplication of binarised images of the malignant tumour. Full article ">Figure 8
(a) Window with the benign tumour belonging to the sector with the largest area; (b) window with the malignant tumour belonging to the sector with the largest area. Full article ">

9 pages, 3188 KiB

Open AccessProceeding Paper

Dynamics of Lemon Crop Production in Tambo Grande, Piura: Implementation of Convolutional Neural Networks and Analysis of Risk Management Associated with Thermal Climatic Phenomena

by Luis Meneses, Mirtha Ortega, Misael Rivas, Piero Fernández and Antonio Angulo

Eng. Proc. 2025, 83(1), 16; https://doi.org/10.3390/engproc2025083016 - 21 Jan 2025

Viewed by 282

Abstract

Lemon production in Piura, Peru faces climatic challenges such as droughts and El Niño. This study uses satellite indices (NDVI and NDWI) and convolutional neural networks (CNNs, specifically AlexNet) to analyze crop dynamics and health during extreme events. The results highlight the impact [...] Read more.

Lemon production in Piura, Peru faces climatic challenges such as droughts and El Niño. This study uses satellite indices (NDVI and NDWI) and convolutional neural networks (CNNs, specifically AlexNet) to analyze crop dynamics and health during extreme events. The results highlight the impact of extreme precipitation and temperatures, with reflectance levels as early indicators of deterioration. In 1998, El Niño reduced yield to 9.2 tons/ha, compared to 14 tons/ha in 2014. These variables provide key information for pruning, irrigation, and fertilization decisions, improving crop productivity. Full article

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Block diagram of the algorithm. Full article ">Figure 2
Study area. Full article ">Figure 3
Stitched NDVI and NDWI image of the study area for the month of October 2019. Retrieved from Landviewer. Full article ">Figure 4
NDVI time series of the year 2019 (a), 2020 (b), 2021 (c), 2022 (d), 2023 (e). Obtained from the Landviewer webside, using the Landsat 8 time series analysis option. Full article ">Figure 5
Illustration of the convolutional neural network. Note: Adapted from illustration of the convolution neural network [<a href="#B15-engproc-83-00016" class="html-bibr">15</a>]. Full article ">Figure 6
Accuracy and resulting loss learning curves of the AlexNet network. Full article ">Figure 7
Training confusion matrix (a) and validation confusion matrix (b). Full article ">Figure 8
Selective results of Grad-CAM: (a) low-risk class, (b) medium-risk class, and (c) high-risk class. Full article ">

16 pages, 2603 KiB

Open AccessProceeding Paper

Case Study: Implementation of Lean Logistics at Inversiones Karmont S.A.C for Enhancing Distribution Productivity

by Deysi Llanos-Solorzano, Yenipher Dayana Barboza-Quispe and Ruben Felipe Vidal Endara

Eng. Proc. 2025, 83(1), 17; https://doi.org/10.3390/engproc2025083017 - 22 Jan 2025

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Abstract

The main objective of this research was the application of Lean Logistics philosophy to increase productivity in the distribution area. The methodological approach of this research was quantitative, applied in nature, with an explanatory level of study and an experimental design with a [...] Read more.

The main objective of this research was the application of Lean Logistics philosophy to increase productivity in the distribution area. The methodological approach of this research was quantitative, applied in nature, with an explanatory level of study and an experimental design with a pre-experiment degree. With a sample of 179 orders for Confy Marco mattresses, the study was conducted as a pre- and post-test analysis. For the first part of this research, documentary review was used as the data collection technique, with the registration form used as the instrument. The second part of the research employed observation technique, with the structured observation form used as the instrument. The hypothesis test was conducted using the Student’s T-test, which yielded a significance of 0.000 (<0.05), leading to the rejection of the null hypothesis and acceptance of the alternative hypothesis. Productivity before implementation was 61%, and after implementation, it increased to 87%, demonstrating that the application of Lean Logistics improved the productivity of the distribution area at Inversiones Karmont. Full article

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11 pages, 1359 KiB

Open AccessProceeding Paper

Design of a Unit Department for the Administration and Execution of Technological and Innovation Projects: A Case Applied to Mechatronic Projects

by Carlos Gabriel Díaz Saenz, Pablo Daniel Bonaveri and Gustavo Rodriguez Albor

Eng. Proc. 2025, 83(1), 18; https://doi.org/10.3390/engproc2025083018 - 22 Jan 2025

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Abstract

Currently, the administration of innovation and technology, and the execution of technological projects (in this case, mechatronic projects) is, for all types of organizations, a challenge that requires the use of the creativity and initiative of its professionals, investing or implementing processes, machines, [...] Read more.

Currently, the administration of innovation and technology, and the execution of technological projects (in this case, mechatronic projects) is, for all types of organizations, a challenge that requires the use of the creativity and initiative of its professionals, investing or implementing processes, machines, products, and services in such a way that inventions, designs, and prototypes provide solutions to environmental problems and facilitate society. Therefore, in innovation projects, it should be considered that it corresponds not only to the application of new technologies, but also to the generation of an outcome that is useful for the objective, quantifiable, and productive segment, as applied to mechatronic projects. Therefore, it is necessary and relevant to carry out a process of orderly development in the following phases: identification of need, ideation, development, construction, and verification of the final solution of these mechatronic projects. The above is turned towards a comprehensive design process around the academy, which for the purposes of this research takes place at the Universidad Autónoma del Caribe, which, according to the indicators of technological development and innovation, is positioned among the top ten positions at a national level (over 350 measured universities) in the DTI-Sapiens ranking, published every two years since 2017 by the consulting firm Sapiens Research and recognized by the international IREG Observatory. The Unit Department for the Administration and Execution of Technological Projects and Innovation: A Case Applied to Mechatronic Projects aims to achieve a balanced technological offer in the universe of R&D&I projects in mechatronics, among economic and social scientific values. In this way, it will be possible to consolidate links with the socioeconomic environment for the transfer of existing knowledge in HEIs, its exploitation by stakeholders, and the increase in the development of R&D&I projects, strengthening capacities in the UEES relationship for the transfer of know-how to companies. Full article

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12 pages, 10206 KiB

Open AccessProceeding Paper

Portable Biomedical System for Acquisition, Display and Analysis of Cardiac Signals (SCG, ECG, ICG and PPG)

by Valery Sofía Zúñiga Gómez, Adonis José Pabuena García, Breiner David Solorzano Ramos, Saúl Antonio Pérez Pérez, Jean Pierre Coll Velásquez, Pablo Daniel Bonaveri and Carlos Gabriel Díaz Sáenz

Eng. Proc. 2025, 83(1), 19; https://doi.org/10.3390/engproc2025083019 - 23 Jan 2025

Viewed by 198

Abstract

This study introduces a mechatronic biomedical device engineered for concurrent acquisition and analysis of four cardiac non-invasive signals: Electrocardiogram (ECG), Phonocardiogram (PCG), Impedance Cardiogram (ICG), and Photoplethysmogram (PPG). The system enables assessment of individual and simultaneous waveforms, allowing for detailed scrutiny of cardiac [...] Read more.

This study introduces a mechatronic biomedical device engineered for concurrent acquisition and analysis of four cardiac non-invasive signals: Electrocardiogram (ECG), Phonocardiogram (PCG), Impedance Cardiogram (ICG), and Photoplethysmogram (PPG). The system enables assessment of individual and simultaneous waveforms, allowing for detailed scrutiny of cardiac electrical and mechanical dynamics, encompassing heart rate variability, systolic time intervals, pre-ejection period (PEP), and aortic valve opening and closing timings (ET) through an application programmed with MATLAB App Designer, which applies derivative filters, smoothing, and FIR digital filters and evaluates the delay of each one, allowing the synchronization of all signals. These metrics are indispensable for deriving critical hemodynamic indices such as Stroke Volume (SV) and Cardiac Output (CO), paramount in the diagnostic armamentarium against cardiovascular pathologies. The device integrates an assembly of components including five electrodes, operational and instrumental amplifiers, infrared opto-couplers, accelerometers, and advanced filtering subsystems, synergistically tailored for precision and fidelity in signal processing. Rigorous validation utilizing a cohort of healthy subjects and benchmarking against established commercial instrumentation substantiates an accuracy threshold below 4.3% and an Interclass Correlation Coefficient (ICC) surpassing 0.9, attesting to the instrument’s exceptional reliability and robustness in quantification. These findings underscore the clinical potency and technical prowess of the developed device, empowering healthcare practitioners with an advanced toolset for refined diagnosis and management of cardiovascular disorders. Full article

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22 pages, 13430 KiB

Open AccessProceeding Paper

Optimization of Rocker–Bogie Suspension System for Robustness Improvement of Autonomous Rover by Numerical Simulations for Irregular Surfaces in Precision Agriculture

by Leandro Llontop and Nain M. Ramos

Eng. Proc. 2025, 83(1), 20; https://doi.org/10.3390/engproc2025083020 - 23 Jan 2025

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Abstract

Mobile robots are capable of moving in various environments and performing complex tasks. They are essential in applications such as planetary exploration, search missions, hazardous waste cleanup, and process automation. Therefore, their study and improvement are relevant today. In this research, we propose [...] Read more.

Mobile robots are capable of moving in various environments and performing complex tasks. They are essential in applications such as planetary exploration, search missions, hazardous waste cleanup, and process automation. Therefore, their study and improvement are relevant today. In this research, we propose optimizing the rocker–bogie suspension system to enhance the robustness of an autonomous rover used in precision agriculture (PA). PA aims to maximize agricultural efficiency and productivity through advanced technologies, and autonomous rovers play a crucial role in enabling real-time data collection and decision-making. This work was developed by implementing numerical simulations to evaluate the performance of the suspension system. The rocker–bogie suspension system is widely used in space exploration as it can avoid obstacles and maintain stability in challenging terrain. Using degrees of freedom and structural analysis, we designed and validated a rocker–bogie-type suspension geometry adapted to the needs of PA. The results of the simulations showed that optimizing the rocker–bogie suspension system significantly improves the rover’s robustness on uneven surfaces. The performance of the system was evaluated in various scenarios and conditions through numerical simulations, which supported its feasibility and effectiveness in PA. In conclusion, optimizing the rocker–bogie suspension system is an effective strategy to enhance the robustness of an autonomous rover in PA, as demonstrated by the results of the static simulations. This finding has significant implications for maximizing efficiency and agricultural productivity in PA. Full article

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13 pages, 6021 KiB

Open AccessProceeding Paper

Articulated Robotic Arm for Minimally Invasive Stereotactic Localization in Operating Rooms

by Deisy L. Acosta-Ticse, Jorge Edinson Poma-Deza, Juan Orlando Salazar-Campos, Deyby Huamanchahua, Ricardo Andre Reaño-Forsyth, Issael Adrian Rocha-Hauyon, Ruben Felipe Vidal Endara and Ivan Ortega-Ampuero

Eng. Proc. 2025, 83(1), 21; https://doi.org/10.3390/engproc2025083021 - 24 Jan 2025

Abstract

The prolonged use of X-rays has led to an increased exposure of medical personnel to radiation, resulting in a more than 40% higher incidence of cancer compared to patients and other groups. Therefore, this article presents an alternative for protecting medical personnel, which [...] Read more.

The prolonged use of X-rays has led to an increased exposure of medical personnel to radiation, resulting in a more than 40% higher incidence of cancer compared to patients and other groups. Therefore, this article presents an alternative for protecting medical personnel, which involves designing and constructing an articulated robotic arm for minimally invasive stereotactic localization in operating rooms. The project’s main objective is for the robotic arm to assist doctors in minimally invasive procedures, including needle insertion into the patient. The methodology was developed in four stages: the first stage involved direct kinematic analysis, where the Denavit–Hartenberg parameters and robot motion equations were determined; the second stage involved the design and modeling of the robot’s links and joints; the third stage involved obtaining the robot’s dynamics using Jacobian matrices with inertial properties extracted from the elements; and the fourth stage involved the implementation of the robot using structural components (actual measurements), axes, transmissions, motors, 3D printing of the design, and an embedded system for control. The results show that the prototype can accurately assist doctors in minimally invasive procedures. Additionally, the robot provides a versatile solution for medical robotics with compact devices that can be adapted to various environments and are easy to operate. Furthermore, the prototype’s performance in real scenarios promises to enhance healthcare professionals’ capabilities and reduce radiation exposure risks. In conclusion, the prototype proves to be a viable option for protecting medical personnel exposed to radiation. Moreover, as a first version, several aspects for improvement were identified, including strengthening communications, improving the appearance, simplifying control, and optimizing needle actions for confined spaces. Full article

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