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Publications - 6674
Evaluation of SLAM Methods for Small-Scale Autonomous Racing Vehicles †
Publication Name: Engineering Proceedings
Publication Date: 2025-01-01
Volume: 113
Issue: 1
Page Range: Unknown
Description:
Simultaneous Localization and Mapping (SLAM) is a critical component of autonomous navigation, enabling mobile robots to construct maps while estimating their location. In this study, we compare the performance of SLAM Toolbox and Cartographer, two widely used 2D SLAM methods, by evaluating their ability to generate accurate maps for autonomous racing applications. The evaluation was conducted using real-world data collected from a RoboRacer vehicle equipped with a 2D laser scanner and capable of providing odometry, operating on a small test track. Both SLAM methods were tested offline. The resulting occupancy grid maps were analyzed using quantitative metrics and visualization tools to assess their quality and consistency. The evaluation was performed against ground truth data derived from an undistorted photograph of the racetrack.
Open Access: Yes
Assessing predictive validity of competency coefficient in automotive project performance
Publication Name: Tasmimgiri Va Tahqiq Dar Amaliyyat
Publication Date: 2025-09-01
Volume: 10
Issue: 3
Page Range: 469-490
Description:
Purpose: This paper aims to evaluate the predictive validity of the Competency Coefficient (K), a behavioral indicator derived from structured assessments of automotive R&D project managers, by examining its correlation with objective project performance outcomes. Methodology: The study performs a statistical analysis of K against five z-standardized Key Performance Indicators (KPIs) to identify the relationship between behavioral competencies and project performance. Predictive validity was evaluated using Pearson/Spearman correlations and Ordinary Least Squares (OLS) regression; robustness in small samples and model adequacy were assessed with 10,000-sample bootstrap intervals, Leave-One-Out Cross-Validation (LOOCV),Prediction Sum of Squares (PRESS) (PRESS/Q2), and tests for quadratic nonlinearity. Findings: Results reveal positive and statistically significant associations between the Competency Coefficient (K) and KPI-based performance indices. The linear model explained roughly 93% of the variance in project results, and cross-validation confirmed consistent out-of-sample performance (Q2 = 0.88). The restricted sample size (n = 7) and singular organizational environment limit generalizability, while contextual factors may also influence the reported outcomes. Originality/Value: The paper provides original empirical evidence that competency-based behavioral indicators can function as dependable, measurable elements of project performance assessment. The findings emphasize methodological feasibility rather than universal applicability. The contribution lies in the measurement and validation technique, which may be duplicated for verification in larger and more diverse samples.
Open Access: Yes
Artificial neural network analysis of chemical reaction and radiation effects on MHD ternary nanofluid flow over an exponentially accelerated inclined plate
Publication Name: South African Journal of Chemical Engineering
Publication Date: 2026-07-01
Volume: 57
Issue: Unknown
Page Range: Unknown
Description:
This investigation explores the magnetohydrodynamic (MHD) free convective heat and mass transfer characteristics of a ternary nanofluid traversing an exponentially accelerated inclined plate within a porous medium. The theoretical framework integrates the complexities of internal heat generation/absorption and fluctuating wall temperatures. Analytical solutions were rigorously derived utilizing the Laplace transform technique, while a sophisticated Artificial Neural Network (ANN) was implemented to forecast and corroborate these mathematical outcomes. Heat Transfer (Nusselt Number) evaluated against the interplay of the Prandtl number, thermal radiation parameters, and temporal progression. Mass Transfer (Sherwood Number) analyzed as a function of magnetic permeability, the Schmidt number, and time. Thermal Enhancement findings indicate that an augmentation in the nanofluid volume fraction significantly bolsters thermal conductivity, thereby elevating the temperature profile. The proposed Levenberg-Marquardt Algorithm-based Backpropagation Artificial Neural Network (LMA BANN) demonstrated exceptional predictive fidelity. The model achieved a precision threshold exceeding 99.9% for the Nusselt number and near-perfect accuracy for the Sherwood number. These results are substantiated by negligible Mean Squared Error (MSE), Root Mean Squared Error (RMSE), and Mean Absolute Error (MAE) values, coupled with correlation coefficients (R) nearing unity, signifying a robust alignment between the analytical and predicted datasets.
Open Access: Yes
Artificial intelligence-driven performance analysis of carbon nanotubes hybrid nanofluid with wastewater treatment applications: an intelligent neuro-computing model
Publication Name: South African Journal of Chemical Engineering
Publication Date: 2026-07-01
Volume: 57
Issue: Unknown
Page Range: Unknown
Description:
The current study examines the properties of heat radiation on the Darcy Forchheimer flow of carbon nanotube/water based hybrid nanofluid across a Riga plate in the occurrence of oxytactic microbes, employing a novel intelligent numerical computing paradigm based on the legacy of neural networks with the intelligent Bayesian regularization (NN-IBR) method. The AI-driven neuro-computing model for improving the thermal behavior of a carbon nanotube (CNT) hybrid nanofluid in wastewater treatment has a wide range of applications. It has the potential to dramatically improve thermal management efficiency in wastewater treatment plants, improve pollutant removal through optimal heat and mass transfer, and minimize energy consumption in treatment operations. This model can also be used in sustainable water recycling, industrial effluent treatment, and smart environmental management systems, where intelligent prediction and control of nanofluid performance is critical for accomplishing environmentally friendly and cost-effective operations. The Homotopy analysis approach is used to classify the obtained equations. The concentration profile increases as the activation energy parameter values upsurge.
Open Access: Yes
The Relationship Between EMF Exposure and MIMO Systems, and the Exposure Advantages of Lowband Massive MIMO System
Publication Name: Telecom
Publication Date: 2025-09-01
Volume: 6
Issue: 3
Page Range: Unknown
Description:
With the advancement of mobile communications, technologies based on high-element-count antenna systems—such as massive Multiple Input Multiple Output (massive MIMO)—are playing an increasingly important role in enhancing network capacity. However, they introduce new challenges in the measurement and evaluation of electromagnetic field (EMF) exposure. This study presents a detailed, laboratory-based methodology for assessing EMF exposure in cellular systems using Single Input Single Output (SISO) and MIMO technologies. To address the limitations of traditional exposure assessment techniques—particularly under the conditions introduced by 5G and active antenna systems—a shielded test environment with directional antennas was developed and applied across lowband and midband frequency ranges (700–2100 MHz). Downlink electromagnetic power density was measured under standardized modulation, coding, and bandwidth settings for both SISO and MIMO configurations. The results show that MIMO technology does not lead to a significant increase in EMF exposure compared to SISO, with average differences remaining below 1 dB. Moreover, in lower-frequency bands, massive MIMO systems can ensure the required user capacity at significantly lower transmission power, resulting in more than 15 dB reductions in EMF exposure. These findings confirm the potential of massive MIMO to enhance network performance while reducing the level of electromagnetic exposure.
Open Access: Yes
Clinical and Financial Validation of the International Study Group for Pancreatic Surgery (ISGPS) Definition of Post-pancreatectomy Acute Pancreatitis (PPAP): International Multicenter Prospective Study
Alice Cattelani
Masafumi Nakamura
Werner Hartwig
Asahi Sato
Attila Oláh
Christopher M. Halloran
Saxon Connor
Roland Andersson
Jakob R. Izbicki
Martin Loos
Marc G. Besselink
Markus W. Büchler
Cristina Ferrone
Thilo Hackert
Roberto Salvia
Daniel Kilburn
Keith D. Lillemoe
Oliver Strobel
Jens Werner
Mustapha Adham
Charles Vollmer
Nicholas J. Zyromski
Gaetano Corvino
Yi Miao
Massimo Falconi
Christos Dervenis
John P. Neoptolemos
Shailesh V. Shrikhande
Elisa Bannone
Nicolò Pecorelli
Stefano Partelli
Fraser Jeffery
Daniel Halloran
Marco Montorsi
Harish Lavu
Alessio Marchetti
Valentina Andreasi
Francesca Fermi
Domenico Tamburrino
Alessandro Esposito
Giuseppe Malleo
Manish Bhandare
Kaival Gundavda
Kuirong Jiang
Zipeng Lu
Savio George Barreto
Luca Gianotti
Alessandro Zerbi
Helmut Friess
Jie Yin
Rosa Klotz
Daniela Merz
Christoph Michalski
Ulla Klaiber
Gennaro Nappo
Christopher L. Wolfgang
Giovanni Marchegiani
Maximillian Bockhorn
Ugo Boggi
Bodil Andersson
Robert Padbury
Ajith K. Siriwardena
Abe Fingerhut
Olivier R.C. Busch
Giuseppe Kito Fusai
Kevin Christopher Conlon
Alberto Manzoni
Dejan Radenkovic
Michael Sarr
Kyoichi Takaori
Naoki Ikenaga
Pasquale Scornamiglio
Mohammad Abu Hilal
Charles J. Yeo
Marc G. Besselink
Publication Name: Annals of Surgery
Publication Date: 2026-07-01
Volume: 284
Issue: 1
Page Range: e12-e21
Description:
Objective: – To validate the International Study Group for Pancreatic Surgery (ISGPS) definition and grading system of post-pancreatectomy acute pancreatitis (PPAP) after pancreatoduodenectomy (PD). Background: – In 2022, the ISGPS defined PPAP and recommended a prospective validation of its diagnostic criteria and grading system. Methods: – This was a prospective, international, multicenter study including patients undergoing PD at 17 referral pancreatic centers across Europe, Asia, Oceania, and the United States. PPAP diagnosis required the following 3 parameters: (1) postoperative serum hyperamylasemia /hyperlipasemia (POH) persisting on postoperative days 1 and 2, (2) radiologic alterations consistent with PPAP, and (3) a clinically relevant deterioration in the patient’s condition. To validate the grading system, clinical and economic parameters were analyzed across all grades. Results: – Among 2902 patients undergoing PD, 7.5% (n=218) developed PPAP (6.3% grade B and 1.2% grade C). POH occurred in 24.1% of patients. Hospital stay was associated with PPAP grades [no POH/PPAP 10 days [interquartile range (IQR): 7–17] days, grade B 22 days (IQR: 15–34) days, and grade C 43 days (IQR: 27–54) days; P<0.001], as well as intensive care unit admission (no POH/PPAP 5.4%, grade B 12.6%, grade C 82.9%; P<0.010), and hospital readmission rates (no POH/PPAP 7.3%, grade B 16.1%, grade C 18.5%; P<0.05). Costs of grade B and C PPAP were 2 and 11 times greater than uncomplicated clinical courses, respectively (P<0.001). Conclusions: – This first prospective, international validation study of the ISGPS definition and grading system for PPAP highlighted the relevant clinical and financial implications of this condition. These results stress the importance of routine screening for PPAP in patients undergoing PD.
Open Access: Yes
An Integrative Framework for Healthcare Recommendation Systems: Leveraging the Linear Discriminant Wolf–Convolutional Neural Network (LDW-CNN) Model
Publication Name: Diagnostics
Publication Date: 2024-11-01
Volume: 14
Issue: 22
Page Range: Unknown
Description:
In the evolving healthcare landscape, recommender systems have gained significant importance due to their role in predicting and anticipating a wide range of health-related data for both patients and healthcare professionals. These systems are crucial for delivering precise information while adhering to high standards of quality, reliability, and authentication. Objectives: The primary objective of this research is to address the challenge of class imbalance in healthcare recommendation systems. This is achieved by improving the prediction and diagnostic capabilities of these systems through a novel approach that integrates linear discriminant wolf (LDW) with convolutional neural networks (CNNs), forming the LDW-CNN model. Methods: The LDW-CNN model incorporates the grey wolf optimizer with linear discriminant analysis to enhance prediction accuracy. The model’s performance is evaluated using multi-disease datasets, covering heart, liver, and kidney diseases. Established error metrics are used to compare the effectiveness of the LDW-CNN model against conventional methods, such as CNNs and multi-level support vector machines (MSVMs). Results: The proposed LDW-CNN system demonstrates remarkable accuracy, achieving a rate of 98.1%, which surpasses existing deep learning approaches. In addition, the model improves specificity to 99.18% and sensitivity to 99.008%, outperforming traditional CNN and MSVM techniques in terms of predictive performance. Conclusions: The LDW-CNN model emerges as a robust solution for multidisciplinary disease prediction and recommendation, offering superior performance in healthcare recommender systems. Its high accuracy, alongside its improved specificity and sensitivity, positions it as a valuable tool for enhancing prediction and diagnosis across multiple disease domains.
Open Access: Yes
Examining Lean Management Principles in SMEs Through Empirical Data Analysis and Systematic Review †
Publication Name: Engineering Proceedings
Publication Date: 2025-01-01
Volume: 113
Issue: 1
Page Range: Unknown
Description:
While Lean methodologies have been widely adopted in large enterprises, their application in small and medium enterprises remains an area requiring further exploration. This study aims at a hybrid approach combining a systematic literature review based on the PEO framework and PRISMA methodology with comprehensive data analysis from 780 respondents to examine the direct relation between Lean and SMEs. Various statistical methods were used to identify different patterns and themes. The findings suggest that while resource constraints pose significant challenges for SMEs in adopting Lean, tailored approaches with a significant reliance on leadership commitment can considerably enhance operational efficiency, resilience, costs, and waste reduction. Insights from the analysis further revealed a preference for operational methods with limited adoption of complex and strategic methods of Lean across SMEs. The paper concludes with practical recommendations for SMEs and lays a foundation for future directions in terms of integration with ESG and sustainability.
Open Access: Yes
Combined benefits of fermented washed rice water and NPK mineral fertilizer on plant growth and soil fertility over three field planting cycles
Publication Name: Heliyon
Publication Date: 2023-09-01
Volume: 9
Issue: 9
Page Range: Unknown
Description:
Washed rice water (WRW) is the leftover water after washing rice grains and is usually discarded. However, WRW contains nutrients leached from rice, making it a potential plant fertilizer. Reusing WRW promotes better water governance, particularly in the face of increased freshwater needs due to population expansion and climate change. Recent experiments in rain shelters have demonstrated the advantages of using WRW as fertilizer. Building on this, our study assessed WRW's efficacy in an open field against NPK fertilizer, both individually and in combination. The treatments were: R3 (3-day fermented WRW), N1 (full recommended NPK rate), N0.5R3 (half NPK rate and R3), and CON (tap water only). These treatments were tested over three consecutive planting cycles of choy sum (Brassica chinensis var. parachinensis) vegetable. At the end of each planting cycle, measurements were taken for the plant's growth, nutrient content and uptake, as well as various soil chemical properties and bacterial population. Plants were watered daily with 5 mm WRW (R3 and N0.5R3) or tap water (N1 and CON). N0.5R3 showed the best results in terms of plant growth, nutrient content, uptake, and soil nutrient levels. N0.5R3 supplied the most nutrients, especially N, P, and K. Increased plant growth also led to increased plant uptake of nutrients, including micronutrients. Macronutrients had a greater impact on plant biomass than micronutrients, as R3 and N1 had similar results. R3 soils had higher bacterial populations but were more acidic than N1 soils. The negative effect of NPK on bacteria was partially offset by combining NPK with WRW as N0.5R3. No carryover effects were observed, likely because of the high nutrient leaching from heavy rains. These findings confirm WRW's is an effective fertilizer in open fields, but measures like surface mulching are crucial to minimize nutrient leaching prior to its use.
Open Access: Yes
