Applied Sciences

28 pages, 4207 KiB

Open AccessArticle

Multi-Objective Optimization of Energy-Efficient Multi-Stage, Multi-Level Assembly Job Shop Scheduling

by Yingqian Dong, Weizhi Liao and Guodong Xu

Appl. Sci. 2024, 14(19), 8712; https://doi.org/10.3390/app14198712 - 26 Sep 2024

The multi-stage, multi-level assembly job shop scheduling problem (MsMlAJSP) is commonly encountered in the manufacturing of complex customized products. Ensuring production efficiency while effectively improving energy utilization is a key focus in the industry. For the energy-efficient MsMlAJSP (EEMsMlAJSP), an improved imperialist competitive [...] Read more.

The multi-stage, multi-level assembly job shop scheduling problem (MsMlAJSP) is commonly encountered in the manufacturing of complex customized products. Ensuring production efficiency while effectively improving energy utilization is a key focus in the industry. For the energy-efficient MsMlAJSP (EEMsMlAJSP), an improved imperialist competitive algorithm based on Q-learning (IICA-QL) is proposed to minimize the maximum completion time and total energy consumption. In IICA-QL, a decoding strategy with energy-efficient triggers based on problem characteristics is designed to ensure solution quality while effectively enhancing search efficiency. Additionally, an assimilation operation with operator parameter self-adaptation based on Q-learning is devised to overcome the challenge of balancing exploration and exploitation with fixed parameters; thus, the convergence and diversity of the algorithmic search are enhanced. Finally, the effectiveness of the energy-efficient strategy decoding trigger mechanism and the operator parameter self-adaptation operation based on Q-learning is demonstrated through experimental results, and the effectiveness of IICA-QL for solving the EEMsMlAJSP is verified by comparing it with other algorithms. Full article

34 pages, 1477 KiB

Open AccessArticle

TheImpact of Prompting Techniques on the Security of the LLMs and the Systems to Which They Belong

by Teodor Ivănușcă and Cosmin-Iulian Irimia

Appl. Sci. 2024, 14(19), 8711; https://doi.org/10.3390/app14198711 - 26 Sep 2024

Abstract

Large language models have demonstrated impressive capabilities. The recent research conducted in the field of prompt engineering showed that their base performance is just a glimpse of their full abilities. Enhanced with auxiliary tools and provided with examples of how to solve the [...] Read more.

Large language models have demonstrated impressive capabilities. The recent research conducted in the field of prompt engineering showed that their base performance is just a glimpse of their full abilities. Enhanced with auxiliary tools and provided with examples of how to solve the tasks, their adoption into our applications seems trivial. In this context, we ask an uncomfortable question. Are the models secure enough to be adopted in our systems, or do they represent Trojan horses? The idea of prompt injection and jailbreak attacks does not seem to bother the adopters too much. Even though there are a lot of studies that look into the benefits of the prompting techniques, none address their possible downside in regard to the security. We want take a step further and investigate the impact of the most popular prompting techniques on this aspect of large language models and implicitly the systems to which they belong. Using three of the most deployed GPT models to date, we conducted a few of the most popular attacks in different setup scenarios and demonstrate that prompting techniques can have a negative impact on the security of the LLMs. More than that, they also expose other system components that otherwise would have been less exposed. In the end, we try to come up with possible solutions and present future research perspectives. Full article

(This article belongs to the Special Issue Advanced Large Language Models and Natural Language Processing Applications)

21 pages, 9472 KiB

Open AccessArticle

M2Former: Multiscale Patch Selection for Fine-Grained Visual Recognition

by Jiyong Moon and Seongsik Park

Appl. Sci. 2024, 14(19), 8710; https://doi.org/10.3390/app14198710 - 26 Sep 2024

Abstract

Recently, Vision Transformers (ViTs) have been actively applied to fine-grained visual recognition (FGVR). ViT can effectively model the interdependencies between patch-divided object regions through an inherent self-attention mechanism. In addition, patch selection is used with ViT to remove redundant patch information and highlight [...] Read more.

Recently, Vision Transformers (ViTs) have been actively applied to fine-grained visual recognition (FGVR). ViT can effectively model the interdependencies between patch-divided object regions through an inherent self-attention mechanism. In addition, patch selection is used with ViT to remove redundant patch information and highlight the most discriminative object patches. However, existing ViT-based FGVR models are limited to single-scale processing, and their fixed receptive fields hinder representational richness and exacerbate vulnerability to scale variability. Therefore, we propose MultiScale Patch Selection (MSPS) to improve the multiscale capabilities of existing ViT-based models. Specifically, MSPS selects salient patches of different scales at different stages of a MultiScale Vision Transformer (MS-ViT). In addition, we introduce Class Token Transfer (CTT) and MultiScale Cross-Attention (MSCA) to model cross-scale interactions between selected multiscale patches and fully reflect them in model decisions. Compared with previous Single-Scale Patch Selection (SSPS), our proposed MSPS encourages richer object representations based on feature hierarchy and consistently improves performance from small-sized to large-sized objects. As a result, we propose M2Former, which outperforms CNN-/ViT-based models on several widely used FGVR benchmarks. Full article

17 pages, 4363 KiB

Open AccessArticle

Impact of Aerodynamic Interactions on Aeroelastic Stability of Wing-Propeller Systems

by Nils Böhnisch, Carsten Braun, Pier Marzocca and Vincenzo Muscarello

Appl. Sci. 2024, 14(19), 8709; https://doi.org/10.3390/app14198709 - 26 Sep 2024

Abstract

This paper presents initial findings from aeroelastic studies conducted on a wing-propeller model, aimed at evaluating the impact of aerodynamic interactions on wing flutter mechanisms and overall aeroelastic performance. The flutter onset is assessed using a frequency-domain method. Mid-fidelity tools based on the [...] Read more.

This paper presents initial findings from aeroelastic studies conducted on a wing-propeller model, aimed at evaluating the impact of aerodynamic interactions on wing flutter mechanisms and overall aeroelastic performance. The flutter onset is assessed using a frequency-domain method. Mid-fidelity tools based on the time-domain approach are then exploited to account for the complex aerodynamic interaction between the propeller and the wing. Specifically, the open-source software DUST and MBDyn are leveraged for this purpose. The investigation covers both windmilling and thrusting conditions. During the trim process, adjustments to the collective pitch of the blades are made to ensure consistency across operational points. Time histories are then analyzed to pinpoint flutter onset, and corresponding frequencies and damping ratios are identified. The results reveal a marginal destabilizing effect of aerodynamic interaction on flutter speed, approximately 5%. Notably, the thrusting condition demonstrates a greater destabilizing influence compared to the windmilling case. These comprehensive findings enhance the understanding of the aerodynamic behavior of such systems and offer valuable insights for early design predictions and the development of streamlined models for future endeavors. Full article

(This article belongs to the Special Issue Advances in Unsteady Aerodynamics and Aeroelasticity)

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12 pages, 714 KiB

Open AccessArticle

Preparation, Characterization, and Application of P(aluminum chloride-co-diallyldimethylammonium chloride) Hybrid Flocculant

by Xinrui Feng and Bei Liu

Appl. Sci. 2024, 14(19), 8708; https://doi.org/10.3390/app14198708 (registering DOI) - 26 Sep 2024

Abstract

The hybrid flocculant P(aluminum chloride-co-diallyldimethylammonium chloride) was synthesized in this study. Diallyldimethylammonium chloride monomers were used and ammonium persulfate served as the initiator. The structure of P(aluminum chloride-co-diallyldimethylammonium chloride) was characterized using Fourier-transform infrared spectroscopy, scanning electron microscopy, an electrical conductivity test, and [...] Read more.

The hybrid flocculant P(aluminum chloride-co-diallyldimethylammonium chloride) was synthesized in this study. Diallyldimethylammonium chloride monomers were used and ammonium persulfate served as the initiator. The structure of P(aluminum chloride-co-diallyldimethylammonium chloride) was characterized using Fourier-transform infrared spectroscopy, scanning electron microscopy, an electrical conductivity test, and thermogravimetric analysis. Single-factor experiments were conducted to optimize the synthetic conditions of the hybrid flocculant. An optimized product with an intrinsic viscosity of 926.36 mL/g and a flocculation decolorization rate of 99% was obtained under the following reaction conditions: the total monomer concentration was 30%, the initiator concentration was 0.7%, the reaction temperature was 60 °C, and the reaction time was 3 h. The results demonstrated that the PAC-PDMDAAC hybrid flocculant exhibited covalent bonding between its organic–inorganic components and displayed enhanced stability properties due to its high intrinsic viscosity and spatial structure. Moreover, this hybrid flocculant showed superior decolorization performance in disperse-violet-H-FRL-dye wastewater. Full article

17 pages, 1345 KiB

Open AccessArticle

Comparative Analysis of Nucleus Segmentation Techniques for Enhanced DNA Quantification in Propidium Iodide-Stained Samples

by Viktor Zoltán Jónás, Róbert Paulik, Béla Molnár and Miklós Kozlovszky

Appl. Sci. 2024, 14(19), 8707; https://doi.org/10.3390/app14198707 (registering DOI) - 26 Sep 2024

Abstract

Digitization in pathology and cytology labs is now widespread, a significant shift from a decade ago when few doctors used image processing tools. Despite unchanged scanning times due to excitation in fluorescent imaging, advancements in computing power and software have enabled more complex [...] Read more.

Digitization in pathology and cytology labs is now widespread, a significant shift from a decade ago when few doctors used image processing tools. Despite unchanged scanning times due to excitation in fluorescent imaging, advancements in computing power and software have enabled more complex algorithms, yielding better-quality results. This study evaluates three nucleus segmentation algorithms for ploidy analysis using propidium iodide-stained digital WSI slides. Our goal was to improve segmentation accuracy to more closely match DNA histograms obtained via flow cytometry, with the ultimate aim of enhancing the calibration method we proposed in a previous study, which seeks to align image cytometry results with those from flow cytometry. We assessed these algorithms based on raw segmentation performance and DNA histogram similarity, using confusion-matrix-based metrics. Results indicate that modern algorithms perform better, with F1 scores exceeding 0.845, compared to our earlier solution’s 0.807, and produce DNA histograms that more closely resemble those from the reference FCM method. Full article

(This article belongs to the Section Computing and Artificial Intelligence)

10 pages, 2741 KiB

Open AccessArticle

Control and Analysis of Layered Soil Structure to Ensure Railway Roadbed Stability

by Artem Bykov, Dmitry Surzhik, Leila Kassenova, Ainagul Abzhanova, Anastasia Svirina and Kulbarchin Imanzhanova

Appl. Sci. 2024, 14(19), 8706; https://doi.org/10.3390/app14198706 (registering DOI) - 26 Sep 2024

Abstract

This article discusses a method for analyzing the layered structure of soil using the phase-metric method of geoelectric monitoring to ensure the reliability of a railway track. The importance of monitoring soil layers for timely detection of changes that may affect the stability [...] Read more.

This article discusses a method for analyzing the layered structure of soil using the phase-metric method of geoelectric monitoring to ensure the reliability of a railway track. The importance of monitoring soil layers for timely detection of changes that may affect the stability and safety of railway tracks is emphasized. The use of geophysical monitoring methods, such as phase monitoring of the geoelectric signals, allows us to optimize measures to strengthen the roadway and increase its durability. The present article describes laboratory experiments in which a specialized setup was created to simulate the process of drilling through various soil layers. Geoelectric methods involving the registration of phase characteristics of the electromagnetic field were used in an experimental setup. The experiments demonstrated the effectiveness of the phase-metric method for determining the characteristics of the layered structure of the soil. The results showed that the change in the phase of the signal recorded at the receiving electrodes can be used to identify different soil layers with different electrical characteristics, such as moisture and density. The method of modeling the physical and geological environment using equivalent circuits of elements in the form of a dielectric made it possible to more accurately analyze the electrical properties of the soil. Based on the obtained data, an automatic monitoring system was developed using recurrent neural networks (RNNs), in particular long short-term memory (LSTM) networks, for automatic detection of bends and transitions in signal time series. Evaluation of the model’s effectiveness showed high accuracy in identifying layers, which contributes to increasing the reliability and efficiency of monitoring the condition of the railway track. Full article

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25 pages, 2400 KiB

Open AccessArticle

Analytical Study on the Impact of Nonlinear Foundation Stiffness on Pavement Dynamic Response under Vehicle Action

by Lijun Ouyang, Zhuoying Xiang, Bin Zhen and Weixin Yuan

Appl. Sci. 2024, 14(19), 8705; https://doi.org/10.3390/app14198705 (registering DOI) - 26 Sep 2024

Abstract

This paper presents an analytical study of the dynamic responses in the vehicle–pavement–foundation system, where the vehicle is simplified to a two-degree-of-freedom system, the pavement is modeled using both Euler–Bernoulli (E-B) beam and Timoshenko beam with consideration of pavement roughness, and the subgrade [...] Read more.

This paper presents an analytical study of the dynamic responses in the vehicle–pavement–foundation system, where the vehicle is simplified to a two-degree-of-freedom system, the pavement is modeled using both Euler–Bernoulli (E-B) beam and Timoshenko beam with consideration of pavement roughness, and the subgrade is simulated with a Winkler foundation model featuring cubic nonlinear stiffness. The focus is on using approximate analytical solutions of pavement response to discuss the impact of nonlinear stiffness under various parameter conditions. In previous analytical studies of vehicle–pavement–foundation systems, vehicles were typically simplified to a constant moving force, leading to the conclusion that when the applied force is small, the impact of nonlinear stiffness on the pavement’s dynamic response is minimal; whereas when the force is large, the pavement response increases with the increase in nonlinear stiffness. In this study, the force exerted by the vehicle on the pavement is harmonic, and the impact of nonlinear stiffness on the pavement response is different and much more complex. The research finds that there is a critical value for nonlinear stiffness under the given vehicle parameter conditions: when the nonlinear stiffness is less than the critical value, it has almost no effect on the pavement response; when it exceeds the critical value, the pavement’s response first decreases and then increases with the increase in nonlinear stiffness. The critical value of nonlinear stiffness is not fixed and increases as the vehicle velocity and foundation damping. Moreover, an increase in nonlinear stiffness also causes an increase in the offset between the wheel position and the position of maximum pavement deformation. Under the same parameter conditions, the offset in the E-B beam is significantly greater than that in the Timoshenko beam. Our study’s results enhance the understanding of the nonlinear dynamics within the vehicle–pavement interaction. Full article

(This article belongs to the Section Acoustics and Vibrations)

21 pages, 8043 KiB

Open AccessArticle

Innovative System for BIM/GIS Integration in the Context of Urban Sustainability

by Vincenzo Barrile, Fabio La Foresta, Salvatore Calcagno and Emanuela Genovese

Appl. Sci. 2024, 14(19), 8704; https://doi.org/10.3390/app14198704 (registering DOI) - 26 Sep 2024

Abstract

In the context of urban sustainability and the development of resilient cities, the use of 4D geospatial data and the integration and association of building information with geographical information are of considerable interest. Achieving this integration is particularly significant in the scientific field [...] Read more.

In the context of urban sustainability and the development of resilient cities, the use of 4D geospatial data and the integration and association of building information with geographical information are of considerable interest. Achieving this integration is particularly significant in the scientific field from a technical standpoint but poses significant challenges due to the incompatibility between the two environments. This research proposes various methodologies for the effective integration of BIM/GIS data by analyzing their pros and cons and highlights the innovative aspects of the integration between these systems. Starting with the use of commercial software that has enabled the integration of a building’s 3D model within a GIS environment (this system is particularly useful for its ease of management and the potential for practical applications), this study progresses to an experimental virtual/augmented/mixed reality app developed by the authors that allows for the virtual integration of a building with its territorial context. It concludes with an innovative methodology that, by using the customizable and extensible libraries of the Cesium platform, facilitates the integration of structural data within a 4D geospatial space. This study demonstrates the feasibility of integrating BIM and GIS data despite inherent incompatibilities. The innovative use of Cesium platform libraries further enhances this integration, providing a comprehensive solution for intelligent and sustainable urban planning. By addressing the challenges of incompatibility, the final solution offers critical insights for a deeper understanding of evolving urban landscapes and for monitoring urban expansion and its environmental impacts. Full article

(This article belongs to the Special Issue AI-Enhanced 4D Geospatial Monitoring for Healthy and Resilient Cities)

18 pages, 1767 KiB

Open AccessArticle

Studying the Process of Enzyme Treatment on Beef Meat-Bone Paste Quality

by Assemgul Baikadamova, Aitbek Kakimov, Zhanibek Yessimbekov, Anuarbek Suychinov, Rasul Turagulov, Duman Orynbekov, Gulmira Zhumadilova and Yerlan Zharykbasov

Appl. Sci. 2024, 14(19), 8703; https://doi.org/10.3390/app14198703 (registering DOI) - 26 Sep 2024

Abstract

Animal bones, particularly from cattle after slaughter, are commonly discarded, posing environmental challenges and highlighting the need for sustainable valorization. This study investigated the effect of enzyme and organic acid treatment on physicochemical properties, particle size, microstructure and safety of meat-bone paste (MBP). [...] Read more.

Animal bones, particularly from cattle after slaughter, are commonly discarded, posing environmental challenges and highlighting the need for sustainable valorization. This study investigated the effect of enzyme and organic acid treatment on physicochemical properties, particle size, microstructure and safety of meat-bone paste (MBP). Two samples were prepared: a control (MBP-C) without enzyme treatment and an experimental sample (MBP-E) treated with pepsin and ascorbic acid. Results showed that the enzyme reaction rate increased from 0.004 mmol/min at 60 min to 0.014 mmol/min at 120–180 min before declining to 0.006 mmol/min at 480 min, suggesting substrate depletion or product inhibition. Temperature greatly influenced reaction rates, peaking at 0.0129 mmol/min at 30 °C, with significant declines at higher temperatures due to enzyme denaturation. The enzyme’s kinetic performance was proportional to the pepsin concentration, demonstrating enhanced catalytic efficiency at higher enzyme concentrations. Particle size analysis revealed that enzyme treatment significantly reduced bone particle size, with 86.33% of particles measuring between 0.05 and 0.2 mm, compared to 86.4% between 0.25 and 0.75 mm in the untreated sample. Microscopy confirmed these findings, showing an average particle size reduction from 0.21 mm to 0.052 mm after enzyme treatment. Physicochemical analysis revealed no significant differences in chemical composition between the two samples. However, enzyme-treated MBP-E exhibited a lower pH (5.9) compared to MBP-C (7.02), attributed to the addition of ascorbic acid. Water-binding capacity significantly increased in MBP-E (82.54% vs. 77.28%), indicating enhanced hydration and collagen loosening during enzymatic action. Enzyme treatment significantly reduced the total viable count and eliminated pathogenic bacteria (E. coli, Listeria, Salmonella), improving MBP safety. These findings highlight the potential of this approach for valorizing animal bones as a valuable food ingredient while promoting sustainable waste management practices. Full article

(This article belongs to the Section Food Science and Technology)

10 pages, 3805 KiB

Open AccessArticle

Evaluation of Biodentine Tricalcium Silicate-Based Cement after Chlorhexidine Irrigation

by Katarzyna Dąbrowska, Aleksandra Palatyńska-Ulatowska and Leszek Klimek

Appl. Sci. 2024, 14(19), 8702; https://doi.org/10.3390/app14198702 - 26 Sep 2024

Abstract

The effectiveness of biocements applied in specialistic endodontic procedures can be influenced by multiple factors, including the postplacement chemical action of the irrigating solution. This in vitro study aimed to assess the impact of 2% chlorhexidine digluconate on the surface structure and chemical [...] Read more.

The effectiveness of biocements applied in specialistic endodontic procedures can be influenced by multiple factors, including the postplacement chemical action of the irrigating solution. This in vitro study aimed to assess the impact of 2% chlorhexidine digluconate on the surface structure and chemical composition of Biodentine as a perforation repair cement. A total of 54 Biodentine specimens were prepared with strict adherence to the manufacturer’s instructions and irrigated with 2% chlorhexidine with or without ultrasonic activation. The material specimens were divided into three setting-time-based groups: group A—rinsed after 12 min of setting, group B—after 45 min, and group C—after 24 h. The control group was not subjected to any irrigation protocol. The evaluation of the microappearance of biocement surface was performed with the aid of a scanning electron microscope (SEM). The chemical composition of Biodentine was analyzed with the energy dispersive spectroscopy (EDS) method. The SEM images of the specimens in group B and C revealed a heterogeneous and layered surface morphology. The EDS results are comparable between pairs of cement specimens in both groups: after 5 min and 20 min CHX irrigation as well as after 5 min and 20 min ultrasonically activated CHX irrigation. To conclude, the 12 min Biodentine setting time is not recommended when used in perforation closure. Irrigation protocol involving 2% chlorhexidine visibly affected the tested material surface. The EDS results did not confirm any significant changes in Biodentine chemical composition. Further research is required to analyze the influence of the observed changes on the outcome of the endodontic treatment. Full article

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23 pages, 3281 KiB

Open AccessArticle

Potential Role of Tarantula Venom Peptides in Targeting Human Death Receptors: A Computational Study

by Janus Isaiah R. Quiambao, Peter Matthew Paul T. Fowler and Lemmuel L. Tayo

Appl. Sci. 2024, 14(19), 8701; https://doi.org/10.3390/app14198701 (registering DOI) - 26 Sep 2024

Abstract

Animal venom has been gaining traction as a potential source of therapeutics for various diseases. Spiders encompass a wide variety of venom-producing species, of which tarantulas of the family Theraphosidae are widely known across the globe. Research towards tarantula venom therapeutics has led [...] Read more.

Animal venom has been gaining traction as a potential source of therapeutics for various diseases. Spiders encompass a wide variety of venom-producing species, of which tarantulas of the family Theraphosidae are widely known across the globe. Research towards tarantula venom therapeutics has led to its potential application as antinociceptives. Death receptors are cellular receptors that induce apoptosis—the body’s natural suicide mechanism—to destroy malfunctioning cells. These are particularly of interest in cancer research, as this mechanism is tampered with, resulting in cancer cell proliferation. In this study, the viability of venom toxins from the Theraphosidae family of spiders to induce apoptosis by binding to human death receptors is investigated by carrying out anti-cancer screening, molecular docking, ADMET evaluation, then molecular dynamics and thermodynamic analysis twice, first to ascertain the best receptor–peptide systems per receptor, and secondly to more comprehensively describe binding stability and thermodynamics. Results point to favorable receptor–peptide interactions due to similarities in equilibrium behavior with the death ligand–death receptor systems, along with favorable end-state binding energies and ADMET analysis results. Further inquiry is recommended to assess the real-life efficacy and viability of theraphotoxins as apoptosis therapeutics and further improve on their ability to induce apoptosis. Full article

12 pages, 4088 KiB

Open AccessArticle

Three-Dimensional Analysis of Maxillary Expansion during Mixed Dentition: Comparison between Leaf Expander and Aligners—A Case-Control Study

by Francesca Silvestrini-Biavati, Sirus Imenpour, Francesca Poli, Elis Kola, Andrea Abate, Valentina Lanteri and Alessandro Ugolini

Appl. Sci. 2024, 14(19), 8700; https://doi.org/10.3390/app14198700 (registering DOI) - 26 Sep 2024

Abstract

The objective of this retrospective study was to compare the dento-alveolar effects of two different expansion protocols, Invisalign First (IF) and Leaf Expander (LE), in patients in mixed dentition with transversal upper maxillary deficiency. Materials and Methods: 30 patients were treated with IF, [...] Read more.

The objective of this retrospective study was to compare the dento-alveolar effects of two different expansion protocols, Invisalign First (IF) and Leaf Expander (LE), in patients in mixed dentition with transversal upper maxillary deficiency. Materials and Methods: 30 patients were treated with IF, whereas 38 patients were treated with LE. For each sample 3D digital cast models were analyzed pre and post expansion and transversal diameter of the upper arch, molar rotation and inclination and arch perimeter were measured. Results: LE resulted in a more significant expansion of the molar width and the arch perimeter, with less effect on the expansion of deciduous canines and deciduous molars. IF allowed a more effective molar derotation, but with a greater buccal tipping movement than LE, which determines a more bodily movement of the molars: the expansion determined by IF seems to be more dental than skeletal. Conclusions: IF is a good alternative to LE in case of limited transversal maxillary contraction, particularly when there is a significant mesio-rotation of the first upper molars. Full article

(This article belongs to the Special Issue Present and Future of Orthodontics - 2nd Edition)

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18 pages, 7730 KiB

Open AccessArticle

Color Brightness Recognition of Extremely Severe Amblyopia Children in an Indoor Environment

by Yuhang Li, Xiaodong Zhu and Yan Gu

Appl. Sci. 2024, 14(19), 8699; https://doi.org/10.3390/app14198699 (registering DOI) - 26 Sep 2024

Abstract

This study aims to investigate how indoor lighting (natural and artificial) and distances (3 m and 5 m) affect color recognition in visually impaired children. Ten participants from a special education school were selected to identify the brightness of five colors at varying [...] Read more.

This study aims to investigate how indoor lighting (natural and artificial) and distances (3 m and 5 m) affect color recognition in visually impaired children. Ten participants from a special education school were selected to identify the brightness of five colors at varying lighting and distance circumstances. Each color was presented at six different brightness levels, classified into the low-brightness, the standard-color, and the high-brightness groups. Participants were directed to assess the top three brightness levels they considered most attractive, and each rating was assigned a weighted score. The findings revealed that: (1) Visually impaired children can recognize color brightness in both natural and artificial lighting situations. In indoor conditions, the low-brightness group exhibited greater recognition ability compared to the high-brightness group. Purple did not exhibit a clear pattern, as colors from the high-brightness, the low-brightness, and the standard-color groups were all preferred. (2) Significant differences were observed in the brightness recognition among visually impaired children at distances of 3 m and 5 m. Recognition for low-brightness colors improved with distance, contrasting high-brightness scores that declined. However, there was no significant variation in the perception of green with distance changes. Full article

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15 pages, 4200 KiB

Open AccessArticle

High-Order Active Disturbance Rejection Controller for High-Precision Photoelectric Pod

by Zongdi Yin, Shenmin Song, Meng Zhu and Hao Dong

Appl. Sci. 2024, 14(19), 8698; https://doi.org/10.3390/app14198698 (registering DOI) - 26 Sep 2024

Abstract

With the rapid development of the information age, the need for high-resolution reconnaissance and surveillance is becoming more and more urgent. It is necessary to develop photoelectric pods with a high-precision stabilization function, which isolate the influence of external disturbance and realize the [...] Read more.

With the rapid development of the information age, the need for high-resolution reconnaissance and surveillance is becoming more and more urgent. It is necessary to develop photoelectric pods with a high-precision stabilization function, which isolate the influence of external disturbance and realize the tracking of maneuvering targets. In this paper, the internal frame stabilization loop control technique is studied. Firstly, the mathematical models of the current loop are established. Secondly, the friction model, parametric model, and mechanical resonance model of the system are identified. Finally, a fourth-order tracking differentiator and a fifth-order extended state observer are designed. Through simulation verification, the stability performance of HO-ADRC, increasing by 145.17%, is better than that of PID. In terms of disturbance suppression and noise removal ability, HO-ADRC is also better than PID. Full article

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17 pages, 1232 KiB

Open AccessArticle

Dual-Layer Reinforcement Learning for Quadruped Robot Locomotion and Speed Control in Complex Environments

by Yilin Zhang, Jiayu Zeng, Huimin Sun, Honglin Sun and Kenji Hashimoto

Appl. Sci. 2024, 14(19), 8697; https://doi.org/10.3390/app14198697 (registering DOI) - 26 Sep 2024

Abstract

Walking robots have been widely applied in complex terrains due to their good terrain adaptability and trafficability. However, in some environments (such as disaster relief, field navigation, etc.), although a single strategy can adapt to various environments, it is unable to strike a [...] Read more.

Walking robots have been widely applied in complex terrains due to their good terrain adaptability and trafficability. However, in some environments (such as disaster relief, field navigation, etc.), although a single strategy can adapt to various environments, it is unable to strike a balance between speed and stability. Existing control schemes like model predictive control (MPC) and traditional incremental control can manage certain environments. However, they often cannot balance speed and stability well. These methods usually rely on a single strategy and lack adaptability for dynamic adjustment to different terrains. To address this limitation, this paper proposes an innovative double-layer reinforcement learning algorithm. This algorithm combines Deep Double Q-Network (DDQN) and Proximal Policy Optimization (PPO), leveraging their complementary strengths to achieve both fast adaptation and high stability in complex terrains. This algorithm utilizes terrain information and the robot’s state as observations, determines the walking speed command of the quadruped robot Unitree Go1 through DDQN, and dynamically adjusts the current walking speed in complex terrains based on the robot action control system of PPO. The speed command serves as a crucial link between the robot’s perception and movement, guiding how fast the robot should walk depending on the environment and its internal state. By using DDQN, the algorithm ensures that the robot can set an appropriate speed based on what it observes, such as changes in terrain or obstacles. PPO then executes this speed, allowing the robot to navigate in real time over difficult or uneven surfaces, ensuring smooth and stable movement. Then, the proposed model is verified in detail in Isaac Gym. Wecompare the distances walked by the robot using six different control methods within 10 s. The experimental results indicate that the method proposed in this paper demonstrates excellent speed adjustment ability in complex terrains. On the designed test route, the quadruped robot Unitree Go1 can not only maintain a high walking speed but also maintain a high degree of stability when switching between different terrains. Ouralgorithm helps the robot walk 25.5 m in 10 s, outperforming other methods. Full article

(This article belongs to the Special Issue Artificial Intelligence and Its Application in Robotics)

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14 pages, 1616 KiB

Open AccessArticle

Impacts of Electrolyzed Water Treatments on Bioactive Compounds and Microbial and Visual Quality of Minimally Processed ‘Granny Smith’ Apples

by Nandi E. Nyamende, Gunnar Sigge, Zinash A. Belay, Buhle Mpahleni and Oluwafemi J. Caleb

Appl. Sci. 2024, 14(19), 8696; https://doi.org/10.3390/app14198696 (registering DOI) - 26 Sep 2024

Abstract

Ready-to-eat fresh-cut apples deteriorate rapidly in visual quality due to browning, leading to consumer rejection and food waste. In addition, minimal processing induces tissue damage and releases organic substrates, which could accelerate microbial growth. The present study evaluated the impacts of alkaline and [...] Read more.

Ready-to-eat fresh-cut apples deteriorate rapidly in visual quality due to browning, leading to consumer rejection and food waste. In addition, minimal processing induces tissue damage and releases organic substrates, which could accelerate microbial growth. The present study evaluated the impacts of alkaline and acidic electrolyzed water (AIEW and AEW) on natural microbial load and bioactive compounds on fresh-cut ‘Granny Smith’ apples. Minimally processed apples were dipped for 10 min in AEW and AIEW solutions (200 mg L⁻¹), packed in PET containers with lids, and stored for 9 days at 2 °C. Overall, fresh-cut ‘Granny Smith’ apples treated with AEW significantly (p < 0.05) maintained higher total phenolics (99.4 ± 4.3 mg GAE L⁻¹) and antioxidant capacity (79.5 ± 6.5 mg VitCE L⁻¹) compared to the non-treated control samples (42.9 ± 5.1 mg GAE L⁻¹, 31.9 ± 8.1 mg GAE L⁻¹, respectively). Similarly, pretreatment with AIEW maintained the highest total flavonol content (55.71 ± 1.5 mg QE L⁻¹) compared to the AEW-treated samples and control (p < 0.05). AEW pretreatment led to a 2 Log and a 1 Log decline in total aerobic mesophilic bacteria and yeasts and moulds, respectively. The best visual quality and highest visual score was maintained by AEW and followed by AIEW. This study further demonstrated the effectiveness of electrolyzed water treatments in minimizing browning and enhancing bioactive compounds in fresh-cut ‘Granny Smith’ apples. Full article

(This article belongs to the Special Issue Novel Approaches for Food Processing and Preservation)

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17 pages, 3339 KiB

Open AccessArticle

Compression Index Regression of Fine-Grained Soils with Machine Learning Algorithms

by Mintae Kim, Muharrem A. Senturk and Liang Li

Appl. Sci. 2024, 14(19), 8695; https://doi.org/10.3390/app14198695 - 26 Sep 2024

Abstract

Soil consolidation, particularly in fine-grained soils like clay, is crucial in predicting settlement and ensuring the stability of structures. Additionally, the compressibility of fine-grained soils is of critical importance not only in civil engineering but also in various other fields of study. The [...] Read more.

Soil consolidation, particularly in fine-grained soils like clay, is crucial in predicting settlement and ensuring the stability of structures. Additionally, the compressibility of fine-grained soils is of critical importance not only in civil engineering but also in various other fields of study. The compression index (C_c), derived from soil properties such as the liquid limit (LL), plastic limit (PL), plasticity index (PI), water content (w), initial void ratio (e₀), and specific gravity (G_s), plays a vital role in understanding soil behavior. This study employs machine learning algorithms—the random forest regressor (RFR), gradient boosting regressor (GBR), and AdaBoost regressor (ABR)—to predict the C_c values based on a dataset comprising 915 samples. The dataset includes LL, PL, W, PI, G_s, and e₀ as the inputs, with C_c as the output parameter. The algorithms are trained and evaluated using metrics such as the coefficient of determination (R²), mean absolute error (MAE), mean squared error (MSE), and root mean squared error (RMSE). Hyperparameter optimization is performed to enhance the model performance. The best-performing model, the GBR model, achieves a training R² of 0.925 and a testing R² of 0.930 with the input combination [w, PL, LL, PI, e₀, G_s]. The RFR model follows closely, with a training R² of 0.970 and a testing R² of 0.926 using the same input combination. The ABR model records a training R² of 0.847 and a testing R² of 0.921 under similar conditions. These results indicate superior predictive accuracy compared to previous studies using traditional statistical and machine learning methods. Machine learning algorithms, specifically the gradient boosting regressor and random forest regressor, demonstrate substantial potential in predicting the C_c value for fine-grained soils based on multiple soil parameters. This study involves leveraging the efficiency and effectiveness of these algorithms in geotechnical engineering applications, offering a promising alternative to traditional oedometer testing methods. Accurately predicting the compression index can significantly aid in the assessment of soil settlement and the design of stable foundations, thereby reducing the time and costs associated with laboratory testing. Full article

(This article belongs to the Special Issue The Application of Machine Learning in Geotechnical Engineering, 2nd Edition)

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30 pages, 9663 KiB

Open AccessArticle

Design of a Human Muscle-Powered Flying Machine

by Igor Piotrowski, Marcin Królikowski and Kamil Urbanowicz

Appl. Sci. 2024, 14(19), 8694; https://doi.org/10.3390/app14198694 - 26 Sep 2024

Abstract

This study explores the design and development of a human-powered aircraft (HPA), leveraging modern engineering techniques, materials science, and advanced CAD/CAM tools. The project addresses key aspects of aircraft design, including the geometry of wings and tail, control and power transmission mechanisms, propeller [...] Read more.

This study explores the design and development of a human-powered aircraft (HPA), leveraging modern engineering techniques, materials science, and advanced CAD/CAM tools. The project addresses key aspects of aircraft design, including the geometry of wings and tail, control and power transmission mechanisms, propeller selection, and material identification to achieve ultra-lightweight construction. The 3DExperience platform facilitated comprehensive model creation, simulation, and production process development, while XFLR5 was employed for aerodynamic profile analysis using the vortex lattice and panel methods. JavaProp aided in evaluating propeller thrust and power requirements. Computational fluid dynamics (CFD) simulations using the SST k-ω turbulence model provided critical insights into flow behavior. The design was found to be theoretically capable of flight, although challenges arose in selecting appropriate software for aerodynamic analysis, leading to the use of XFLR5 for early-stage design and the more advanced 3DExperience platform for final evaluations. Although structural strength analyses were not performed due to the complexity of composite materials, future work in this area could enhance the precision of component selection and aircraft mass estimation. Full article

(This article belongs to the Section Mechanical Engineering)

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