Applied Sciences

21 pages, 3367 KiB

Open AccessArticle

An Audio Watermarking Algorithm Based on Adversarial Perturbation

by Shiqiang Wu, Jie Liu, Ying Huang, Hu Guan and Shuwu Zhang

Appl. Sci. 2024, 14(16), 6897; https://doi.org/10.3390/app14166897 (registering DOI) - 6 Aug 2024

Abstract

Recently, deep learning has been gradually applied to digital watermarking, which avoids the trouble of hand-designing robust transforms in traditional algorithms. However, most of the existing deep watermarking algorithms use encoder–decoder architecture, which is redundant. This paper proposes a novel audio watermarking algorithm [...] Read more.

Recently, deep learning has been gradually applied to digital watermarking, which avoids the trouble of hand-designing robust transforms in traditional algorithms. However, most of the existing deep watermarking algorithms use encoder–decoder architecture, which is redundant. This paper proposes a novel audio watermarking algorithm based on adversarial perturbation, AAW. It adds tiny, imperceptible perturbations to the host audio and extracts the watermark with a pre-trained decoder. Moreover, the AAW algorithm also uses an attack simulation layer and a whitening layer to improve performance. The AAW algorithm contains only a differentiable decoder, so it reduces the redundancy. The experimental results also demonstrate that the proposed algorithm is effective and performs better than existing audio watermarking algorithms. Full article

(This article belongs to the Special Issue Recent Advances in Multimedia Steganography and Watermarking)

20 pages, 4646 KiB

Open AccessArticle

High-Definition Dynamic Voltage Restorer Systems Using Equivalent Time Sampling Techniques and Circular Structural Memory Filters

by Jae-ha Ko

Appl. Sci. 2024, 14(16), 6896; https://doi.org/10.3390/app14166896 (registering DOI) - 6 Aug 2024

Abstract

Due to advances in power electronics technology and the evolution of automation devices, the number of electrical devices that are sensitive to power quality is rapidly increasing, and for this reason, users are increasing their demand for high quality. To meet power quality [...] Read more.

Due to advances in power electronics technology and the evolution of automation devices, the number of electrical devices that are sensitive to power quality is rapidly increasing, and for this reason, users are increasing their demand for high quality. To meet power quality demands, many power conversion devices are used, including dynamic voltage restorers (DVRs). DVRs are recognized as devices that can effectively manage problems such as voltage segments, swells, and harmonics. DVR control requires many samples for harmonic compensation, which has the disadvantage of being complicated to implement due to fast digital signal processing computation and the application of the cyclic discrete Fourier transform. In this paper, a high-precision DVR system configuration is proposed that compensates for harmonics using a periodically equivalent time-interval sampling technique and a novel circular-structured memory filter. The proposed circular-structured multi-pointer memory filter is an effective filter algorithm for high-precision input voltage measurement because it can remove noise and compensate for the delay of the phase angle of the filter in voltage measurement. A simulation and DVR prototype system were built, and the feasibility and effectiveness of the phase angle multi-filter voltage detection method and the compensation method were verified by experiments. Full article

(This article belongs to the Special Issue Advanced Power Electronics Converters: Design, Control and Applications)

9 pages, 754 KiB

Open AccessArticle

Biomechanical Characterization of the CrossFit^® Isabel Workout: A Cross-Sectional Study

by Manoel Rios, Ricardo Cardoso, Pedro Fonseca, João Paulo Vilas-Boas, Victor Machado Reis, Daniel Moreira-Gonçalves and Ricardo J. Fernandes

Appl. Sci. 2024, 14(16), 6895; https://doi.org/10.3390/app14166895 (registering DOI) - 6 Aug 2024

Abstract

A cross-sectional study was conducted to biomechanically characterize Isabel’s workout (30 snatch repetitions with 61 kg fixed weight), focusing on eventual changes in knee, hip and shoulder angles. A three-dimensional markerless motion capture system was used to collect data from 11 highly trained [...] Read more.

A cross-sectional study was conducted to biomechanically characterize Isabel’s workout (30 snatch repetitions with 61 kg fixed weight), focusing on eventual changes in knee, hip and shoulder angles. A three-dimensional markerless motion capture system was used to collect data from 11 highly trained male crossfitters along the Isabel workout performed at maximal effort. The routine was analyzed globally and in initial, middle and final phases (10, 20 and 30 repetitions, respectively). Lift total time increased (1.51 ± 0.18 vs. 1.97 ± 0.20 s) and maximal lift velocity (2.64 ± 0.12 vs. 2.32 ± 0.13 m/s) and maximal lift power (15.58 ± 2.34 vs. 13.80 ± 2.49 W/kg) decreased from the initial to final phases, while the time from lift until the bar crossed the hip and shoulder (34.20 ± 4.00 vs. 27.50 ± 5.10 and 39.70 ± 16.80 vs. 30.90 ± 13.90%) decreased along the Isabel workout. In addition, a decrease in hip flexion was observed during the last two phases when the bar crosses the knee (62.62 ± 24.80 vs. 53.60 ± 19.99°º). Data evidence a decrease in the power profile and a change in hip flexion throughout the Isabel workout, without compromising the other joints. Full article

(This article belongs to the Special Issue Advances in the Biomechanical Analysis of Human Movement)

10 pages, 349 KiB

Open AccessArticle

Rheological and Biochemical Properties of Blood in Runners: A Preliminary Report

by Aneta Teległów, Wacław Mirek, Grzegorz Sudoł, Szymon Podsiadło, Konrad Rembiasz and Bartłomiej Ptaszek

Appl. Sci. 2024, 14(16), 6894; https://doi.org/10.3390/app14166894 (registering DOI) - 6 Aug 2024

Abstract

Purpose: Physical activity induces numerous modifications in the morphological, rheological, and biochemical properties of blood. The purpose of this study was to evaluate changes in blood rheological and biochemical indicators among runners. Also, we assessed how the rheological and biochemical properties of blood [...] Read more.

Purpose: Physical activity induces numerous modifications in the morphological, rheological, and biochemical properties of blood. The purpose of this study was to evaluate changes in blood rheological and biochemical indicators among runners. Also, we assessed how the rheological and biochemical properties of blood in people who practised running characterised the range and direction of exercise modifications and allowed for the diagnosis of transient adaptive effects. Methods: This study included 12 athletes who regularly trained in middle- and long-distance running (6–8 times a week) and presented a high sports level (national and international class). The athletes performed a 30 min warm-up consisting of 15 min of jogging and exercises. After a 10 min rest, they completed a 3 km run with submaximal effort. Blood samples were collected at baseline and after the effort. Results: No statistically significant changes were revealed in erythrocyte, leukocyte, platelet, iron, ferritin, transferrin, erythropoietin, or C-reactive protein concentrations in the examined runners. The same applied to the elongation index at a shear stress within the range of 0.30–60.00 Pa, amplitude and total extent of aggregation, aggregation half-life, and aggregation index. A significant increase (within standard limits) was only observed in fibrinogen concentration after running. Conclusions: The lack of post-exercise changes in blood rheological and biochemical indicators in the investigated runners points at an efficient haemorheological system. This, in turn, reflects well-executed training and remarkably well-trained adaptive systems responsible for regeneration. Full article

(This article belongs to the Special Issue Translation of Laboratory Knowledge to the Daily Practice of Sports Science: Interpretation of Training and Physiological Adaptations)

24 pages, 3882 KiB

Open AccessArticle

Open-Set Recognition of Pansori Rhythm Patterns Based on Audio Segmentation

by Jie You and Joonwhoan Lee

Appl. Sci. 2024, 14(16), 6893; https://doi.org/10.3390/app14166893 (registering DOI) - 6 Aug 2024

Abstract

Pansori, a traditional Korean form of musical storytelling, is characterized by performances involving a vocalist and a drummer. It is well-known for the singer’s expressive narrative (aniri) and delicate gesture with fan in hand. The classical Pansori repertoires mostly tell love, satire, and [...] Read more.

Pansori, a traditional Korean form of musical storytelling, is characterized by performances involving a vocalist and a drummer. It is well-known for the singer’s expressive narrative (aniri) and delicate gesture with fan in hand. The classical Pansori repertoires mostly tell love, satire, and humor, as well as some social lessons. These performances, which can extend from three to five hours, necessitate that the vocalist adheres to precise rhythmic structures. The distinctive rhythms of Pansori are crucial for conveying both the narrative and musical expression effectively. This paper explores the challenge of open-set recognition, aiming to efficiently identify unknown Pansori rhythm patterns while applying the methodology to diverse acoustic datasets, such as sound events and genres. We propose a lightweight deep learning-based encoder–decoder segmentation model, which employs a 2-D log-Mel spectrogram as input for the encoder and produces a frame-based 1-D decision along the temporal axis. This segmentation approach, processing 2-D inputs to classify frame-wise rhythm patterns, proves effective in detecting unknown patterns within time-varying sound streams encountered in daily life. Throughout the training phase, both center and supervised contrastive losses, along with cross-entropy loss, are minimized. This strategy aimed to create a compact cluster structure within the feature space for known classes, thereby facilitating the recognition of unknown rhythm patterns by allocating ample space for their placement within the embedded feature space. Comprehensive experiments utilizing various datasets—including Pansori rhythm patterns (91.8%), synthetic datasets of instrument sounds (95.1%), music genres (76.9%), and sound datasets from DCASE challenges (73.0%)—demonstrate the efficacy of our proposed method to detect unknown events, as evidenced by the AUROC metrics. Full article

(This article belongs to the Special Issue Algorithmic Music and Sound Computing)

► Show Figures

Figure 1

14 pages, 1125 KiB

Open AccessArticle

Cortical and Subjective Measures of Individual Noise Tolerance Predict Hearing Outcomes with Varying Noise Reduction Strength

by Subong Kim, Susan Arzac, Natalie Dokic, Jenn Donnelly, Nicole Genser, Kristen Nortwich and Alexis Rooney

Appl. Sci. 2024, 14(16), 6892; https://doi.org/10.3390/app14166892 - 6 Aug 2024

Abstract

Noise reduction (NR) algorithms are employed in nearly all commercially available hearing aids to attenuate background noise. However, NR processing also involves undesirable speech distortions, leading to variability in hearing outcomes among individuals with different noise tolerance. Leveraging 30 participants with normal hearing [...] Read more.

Noise reduction (NR) algorithms are employed in nearly all commercially available hearing aids to attenuate background noise. However, NR processing also involves undesirable speech distortions, leading to variability in hearing outcomes among individuals with different noise tolerance. Leveraging 30 participants with normal hearing engaged in speech-in-noise tasks, the present study examined whether the cortical measure of neural signal-to-noise ratio (SNR)—the amplitude ratio of auditory evoked responses to target speech onset and noise onset—could predict individual variability in NR outcomes with varying strength, thus serving as a reliable indicator of individual noise tolerance. In addition, we also measured subjective ratings of noise tolerance to see if these measures could capture different perspectives on individual noise tolerance. Results indicated a significant correlation between neural SNR and NR outcomes that intensified with increasing strength of NR processing. While subjective ratings of noise tolerance were not correlated with the neural SNR, noise-tolerance ratings could predict outcomes with stronger NR processing and account for additional variance in the regression model, although the effect was limited. Our findings underscore the importance of accurately assessing an individual’s noise tolerance characteristics in predicting perceptual benefits from various NR processing methods and suggest the advantage of incorporating both cortical and subjective measures in the relevant methodologies. Full article

(This article belongs to the Section Applied Neuroscience and Neural Engineering)

25 pages, 5189 KiB

Open AccessArticle

Numerical Investigation of Bedding Rock Slope Potential Failure Modes and Triggering Factors: A Case Study of a Bridge Anchorage Excavated Foundation Pit Slope

by Songling Han and Changming Wang

Appl. Sci. 2024, 14(16), 6891; https://doi.org/10.3390/app14166891 - 6 Aug 2024

Abstract

The analysis of slope failure modes is essential for understanding slope stability. This study investigated the failure modes and triggering factors of a rock slope using the limit equilibrium method, finite differences method, and exploratory factor analysis. First, the limit equilibrium method was [...] Read more.

The analysis of slope failure modes is essential for understanding slope stability. This study investigated the failure modes and triggering factors of a rock slope using the limit equilibrium method, finite differences method, and exploratory factor analysis. First, the limit equilibrium method was used to identify potential sliding surfaces. Then, the finite differences method was employed to study deformation and failure features in a slope. Stability factors were calculated considering specific conditions such as rainfall, prestressing loss, and earthquakes using the strength reduction method. Finally, exploratory factor analysis was utilized to identify the triggering factors of each failure mode. The results revealed that failure modes were categorized into two types based on the positions of the sliding surface. The main triggering factors for Failure Mode 1 were rainfall and prestress loss, while for Failure Mode 2 they were earthquake loading and prestress loss. This study offers a comprehensive exploration of potential failure modes and their triggering factors from mechanical and statistical perspectives, enriching our understanding of potential failure modes in rock slopes. Full article

(This article belongs to the Special Issue Advanced Research on Tunnel Slope Stability and Land Subsidence)

14 pages, 1581 KiB

Open AccessArticle

Risk Assessment of Hydrogen Cyanide for Available Safe Egress Time in Fire Simulation

by Oh-Soo Kwon, Ho-Sik Han and Cheol-Hong Hwang

Appl. Sci. 2024, 14(16), 6890; https://doi.org/10.3390/app14166890 - 6 Aug 2024

Abstract

The majority of fatalities in building fires are attributed to asphyxiation caused by toxic gases. Hydrogen cyanide (HCN) is one of the toxic gases that can be released during a fire, posing a lethal risk to humans even at low concentrations. However, analysis [...] Read more.

The majority of fatalities in building fires are attributed to asphyxiation caused by toxic gases. Hydrogen cyanide (HCN) is one of the toxic gases that can be released during a fire, posing a lethal risk to humans even at low concentrations. However, analysis of the risk posed by HCN in fire risk assessments using fire simulations is relatively rare. This study conducted fire simulations to examine the potential risks of HCN to occupants during a fire. The simulations considered various fire conditions in residential buildings by varying fuel types, fire growth rates, and HCN yields. The relative risk score (RRS) was derived based on the time to reach the threshold values of parameters considered critical for life safety. The results of the fire simulations indicated that the RRS for HCN was approximately 20–40 points higher than that of O₂, CO, and CO₂, reaching a maximum of 92 points. However, the risk posed by HCN was found to be limited in comparison to the risks associated with temperature and visibility. Nevertheless, considering that the primary cause of fatalities in fires is asphyxiation due to toxic gases, HCN must be regarded as a critical factor in fire risk assessments. Additionally, since HCN yield values can increase up to nine times depending on temperature and ventilation conditions, the risk posed by HCN could be significantly higher. Full article

(This article belongs to the Special Issue Advanced Analysis and Technology in Fire Science and Engineering - 2nd Edition)

20 pages, 8199 KiB

Open AccessArticle

by Houzeng Han, Rongheng Li, Tao Xu, Meng Du, Wenxuan Ma and He Wu

Appl. Sci. 2024, 14(16), 6889; https://doi.org/10.3390/app14166889 - 6 Aug 2024

Abstract

Structural monitoring is crucial for assessing structural health, and high-precision deformation prediction can provide early warnings for safety monitoring. To address the issue of low prediction accuracy caused by the non-stationary and nonlinear characteristics of deformation sequences, this paper proposes a similarity clustering [...] Read more.

Structural monitoring is crucial for assessing structural health, and high-precision deformation prediction can provide early warnings for safety monitoring. To address the issue of low prediction accuracy caused by the non-stationary and nonlinear characteristics of deformation sequences, this paper proposes a similarity clustering (SC) deformation prediction model based on GNSS/accelerometer time-frequency analysis. First, the complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN) algorithm is used to decompose the original monitoring data, and the time-frequency characteristic correlations of the deformation data are established. Then, similarity clustering is conducted for the monitoring sub-sequences based on their frequency domain characteristics, and clustered sequences are combined subsequently. Finally, the Long Short-Term Memory (LSTM) model is used to separately predict GNSS displacement and acceleration with clustered time series, and the overall deformation displacement is reconstructed based on the predicted GNSS displacement and acceleration-derived displacement. A shake table simulation experiment was conducted to validate the feasibility and performance of the proposed CEEMDAN-SC-LSTM model. A duration of 5 s displacement prediction is analyzed after 153 s of monitoring data training. The results demonstrate that the root mean square error (RMSE) of predicted displacement is 0.011 m with the proposed model, which achieves an improvement of 64.45% and 61.51% in comparison to the CEEMDAN-LSTM and LSTM models, respectively. The acceleration predictions also show an improvement of 96.49% and 95.58%, respectively, the RMSE of the predicted acceleration-reconstructed displacement is less than 1 mm, with a reconstruction similarity of over 99%. The overall displacement reconstruction similarity can reach over 95%. Full article

► Show Figures

Figure 1

12 pages, 3324 KiB

Open AccessArticle

Detection and Tracking of Underwater Fish Using the Fair Multi-Object Tracking Model: A Comparative Analysis of YOLOv5s and DLA-34 Backbone Models

by Sang-Hyun Lee and Myeong-Hoon Oh

Appl. Sci. 2024, 14(16), 6888; https://doi.org/10.3390/app14166888 - 6 Aug 2024

Abstract

Modern aquaculture utilizes computer vision technology to analyze underwater images of fish, contributing to optimized water quality and improved production efficiency. The purpose of this study is to efficiently perform underwater fish detection and tracking using multi-object tracking (MOT) technology. To achieve this, [...] Read more.

Modern aquaculture utilizes computer vision technology to analyze underwater images of fish, contributing to optimized water quality and improved production efficiency. The purpose of this study is to efficiently perform underwater fish detection and tracking using multi-object tracking (MOT) technology. To achieve this, the FairMOT model was employed to simultaneously implement pixel-level object detection and re-identification (Re-ID) functions, comparing two backbone models: FairMOT+YOLOv5s and FairMOT+DLA-34. The study constructed a dataset targeting the popular black porgy in Korean aquaculture, using underwater video data from five different environments collected from the internet. During the training process, the FairMOT+YOLOv5s model rapidly reduced train loss and demonstrated stable performance. The FairMOT+DLA-34 model showed better results in ID tracking performance, with an accuracy of 44.1%, an IDF1 of 11.0%, an MOTP of 0.393, and an IDSW of 1. In contrast, the FairMOT+YOLOv5s model recorded an accuracy of 43.8%, an IDF1 of 14.6%, an MOTP of 0.400, and an IDSW of 10. The results of this study indicate that the FairMOT+YOLOv5s model demonstrated higher IDF1 and MOTP scores compared to the FairMOT+DLA-34 model, while the FairMOT+DLA-34 model showed superior performance in ID tracking accuracy and had fewer ID switches. Full article

(This article belongs to the Special Issue Integrating Artificial Intelligence in Renewable Energy Systems)

► Show Figures

Figure 1

25 pages, 2293 KiB

Open AccessArticle

Causation Correlation Analysis of Aviation Accidents: A Knowledge Graph-Based Approach

by Jihui Xu, Lu Chen, Huaixi Xing and Wenjie Tian

Appl. Sci. 2024, 14(16), 6887; https://doi.org/10.3390/app14166887 - 6 Aug 2024

Abstract

Summarizing the causation of an aviation accident is beneficial for improving aviation safety. Currently, accident analysis mainly focuses on causal analysis, while giving less consideration to the correlation between accident causal factors and other accident factors. To clarify accident causal factors and potential [...] Read more.

Summarizing the causation of an aviation accident is beneficial for improving aviation safety. Currently, accident analysis mainly focuses on causal analysis, while giving less consideration to the correlation between accident causal factors and other accident factors. To clarify accident causal factors and potential patterns affecting aviation safety and to optimize data mining methods for accident causal factors, this work proposes an aviation accident causation correlation analysis model based on a knowledge graph. Firstly, the accident causal factors are identified, and a knowledge graph is constructed. Subsequently, by utilizing multi-dimensional topological analysis metrics, an aviation accident causation correlation analysis model is established, using the relationships within accident causal factors as a foundation, to determine potential patterns among accident causal factors, flight phases, accident types, and consequences and to analyze the key accident causal factors influencing accident occurrences across different flight phases. Finally, preventive measures and recommendations are provided based on the analysis conclusions. Through a case study using 437 global aviation accidents from 2018 to 2022 as samples and employing the knowledge graph-based aviation accident causation correlation analysis model, the causation relationships among accident causal factors can be expressed more clearly, the potential risks of various accident causal factors can be identified, experiences can be gained from historical accident data, and underlying patterns can be unearthed. This work can provide auxiliary decision making and be an effective reference for the prevention of aviation accidents, playing a positive role in enhancing the level of aviation safety management. Full article

(This article belongs to the Section Transportation and Future Mobility)

33 pages, 8831 KiB

Open AccessArticle

A Novel Battery-Supplied AFE EEG Circuit Capable of Muscle Movement Artifact Suppression

by Athanasios Delis, George Tsavdaridis and Panayiotis Tsanakas

Appl. Sci. 2024, 14(16), 6886; https://doi.org/10.3390/app14166886 - 6 Aug 2024

Abstract

In this study, the fundamentals of electroencephalography signals, their categorization into frequency sub-bands, the circuitry used for their acquisition, and the impact of noise interference on signal acquisition are examined. Additionally, design specifications for medical-grade and research-grade EEG circuits and a comprehensive analysis [...] Read more.

In this study, the fundamentals of electroencephalography signals, their categorization into frequency sub-bands, the circuitry used for their acquisition, and the impact of noise interference on signal acquisition are examined. Additionally, design specifications for medical-grade and research-grade EEG circuits and a comprehensive analysis of various analog front-end architectures for electroencephalograph (EEG) circuit design are presented. Three distinct selected case studies are examined in terms of comparative evaluation with generic EEG circuit design templates. Moreover, a novel one-channel battery-supplied EEG analog front-end circuit designed to address the requirements of usage protocols containing strong compound muscle movements is introduced. Furthermore, a realistic input signal generator circuit is proposed that models the human body and the electromagnetic interference from its surroundings. Experimental simulations are conducted in 50 Hz and 60 Hz electrical grid environments to evaluate the performance of the novel design. The results demonstrate the efficacy of the proposed system, particularly in terms of bandwidth, portability, Common Mode Rejection Ratio, gain, suppression of muscle movement artifacts, electrostatic discharge and leakage current protection. Conclusively, the novel design is cost-effective and suitable for both commercial and research single-channel EEG applications. It can be easily incorporated in Brain–Computer Interfaces and neurofeedback training systems. Full article

(This article belongs to the Special Issue Brain-Computer Interfaces: Novel Technologies and Applications)

► Show Figures

Figure 1

17 pages, 1278 KiB

Open AccessArticle

Evaluation of In Vitro Antihypertensive and Anti-Inflammatory Properties of Dairy By-Products

by Eleni Dalaka, Georgios C. Stefos, Ioannis Politis and Georgios Theodorou

Appl. Sci. 2024, 14(16), 6885; https://doi.org/10.3390/app14166885 - 6 Aug 2024

Abstract

Sweet whey (SW) and yogurt acid whey (YAW) are dairy by-products of the cheese-making process and Greek-style yogurt production, respectively. Both of them are considered pollutants with huge volumes of SW and YAW produced due to the growing demand for dairy products worldwide. [...] Read more.

Sweet whey (SW) and yogurt acid whey (YAW) are dairy by-products of the cheese-making process and Greek-style yogurt production, respectively. Both of them are considered pollutants with huge volumes of SW and YAW produced due to the growing demand for dairy products worldwide. Moreover, whey-derived peptides, resulting from fermentation as well as from further hydrolysis during digestion, have been associated with various biological activities. In the present study, the angiotensin-converting enzyme (ACE)-inhibitory activity of 48 SW samples and 33 YAW samples from bovine, ovine, caprine, and ovine/caprine milk obtained were evaluated. Additionally, the SW and YAW digestates and two of their fractions (smaller than 10 kDa, SW-D-P10 and YAW-D-P10, and smaller than 3 kDa, SW-D-P3 and YAW-D-P3), which were obtained after in vitro digestion and subsequent ultrafiltration, were also subjected to evaluation. Our data indicated that the D-P10 and D-P3 fractions exhibited higher ACE-inhibitory activity compared to the corresponding values before digestion. The ACE-inhibitory capacity after in vitro digestion was higher for the ovine SW samples compared to their bovine and caprine counterparts. The effect of the D-P3 fraction on the inhibition of nitric oxide (NO) production and the expression of a selected panel of immune-response-related genes in LPS-stimulated RAW 264.7 macrophages was also evaluated. Fractions from both dairy by-products inhibited NO production in LPS-stimulated RAW 264.7 cells. Especially, ovine SW-D-P3 showed a strong NO inhibitory activity and suppressed inducible nitric oxide synthase (Nos2) mRNA levels. However, YAW-D-P3 could not trigger neither the gene expression of inflammatory macrophage mediators Nos2 and cyclooxygenase-2 (Ptgs2) nor tumor necrosis factor-α (Tnf) and interleukin 6 (Il6) in LPS-stimulated murine macrophages regardless of animal origin. These findings suggest that in vitro digestion could enhance the production of ACE-inhibitory peptides in both dairy by-products, while SW from ovine origin displays higher potential as an anti-inflammatory agent, effectively preventing excessive NO production. Full article

(This article belongs to the Special Issue Innovation in Dairy Products)

► Show Figures

Figure 1

13 pages, 6786 KiB

Open AccessArticle

Investigation of a Method for Identifying Unbalanced States in Multi-Disk Rotor Systems: Analysis of Axis Motion Trajectory Features

by Jianjun Peng, En Dong, Fang Yang, Yuxiang Sun and Zhidan Zhong

Appl. Sci. 2024, 14(16), 6884; https://doi.org/10.3390/app14166884 - 6 Aug 2024

Abstract

The operational state of a rotor system directly affects its working efficiency, and the axis trajectory can accurately characterize this state. Therefore, a method for extracting axis motion trajectory characteristics based on distance sequence representation is established. First, the axis trajectory sample signal [...] Read more.

The operational state of a rotor system directly affects its working efficiency, and the axis trajectory can accurately characterize this state. Therefore, a method for extracting axis motion trajectory characteristics based on distance sequence representation is established. First, the axis trajectory sample signal is constructed from the original vibration displacement signal. Singular value decomposition (SVD) is performed on the sample signal to obtain effective components, resulting in a purified and denoised axis motion trajectory signal. Next, the axis motion trajectory signal is centralized and normalized. Feature extraction is then performed on the axis motion trajectory signal. Based on the different curvatures of various regions in the axis motion trajectory graph, data points are adaptively selected. The distances between the selected data points and a unique fixed point are calculated in the two-dimensional plane, resulting in a feature signal that characterizes the axis motion trajectory graph. This completes the extraction of the axis motion trajectory characteristics. Different rotational speeds, additional weights, and changes in rotor arrangement types are applied to a multi-disk rotor test rig to obtain measured data for various unbalanced states, validating this method. The results show that this method effectively characterizes the axis motion trajectory with strong generality. Full article

► Show Figures

Figure 1

11 pages, 2475 KiB

Open AccessArticle

Natural Materials as Carriers of Microbial Consortium for Bioaugmentation of Anaerobic Digesters

by Blanka Dadic, Tomislav Ivankovic, Karlo Spelic, Jasna Hrenovic and Vanja Jurisic

Appl. Sci. 2024, 14(16), 6883; https://doi.org/10.3390/app14166883 - 6 Aug 2024

Abstract

The production of biogas is achieved during anaerobic digestion (AD) using organic matter as a substrate. In Mediterranean countries, a promising substrate is lignocellulose biomass of perennial grass Miscanthus x giganteus, due to its potentially high biogas yields, which could be comparable to [...] Read more.

The production of biogas is achieved during anaerobic digestion (AD) using organic matter as a substrate. In Mediterranean countries, a promising substrate is lignocellulose biomass of perennial grass Miscanthus x giganteus, due to its potentially high biogas yields, which could be comparable to maize silage. During AD, bacteria convert biomass into more minor compounds, which are further converted to methane by methanogenic archaea. The selection of appropriate microbes for the degradation of the substrate is crucial, and the enhancement of this step lies in the immobilization of microbes on biocarriers. Described here, a microbial consortium, de novo isolated and conditioned to degrade the Mischantus biomass, was immobilized onto several natural biocarriers: natural zeolitized tuff, ZeoSand^® (Velebit Agro, Zagreb, Croatia), perlite, and corncob. There was no statistically significant difference in the number of immobilized bacteria across the different materials. Therefore, all proved to be suitable for the immobilization of the consortium. In the consortium, five bacterial species with different shares in the consortium were identified: Enterobacter cloacae, Klebsiella pneumoniae, Enterobacter asburiae, Leclercia adecarboxylata, and Exiguobacterium indicum. After immobilization on each carrier, the share of each species changed when compared to starting conditions, and the most dominant species was E. cloacae (71–90%), while the share for other species ranged from 2 to 23%. The share of E. indicum was 14% at the start. However, it diminished to less than 1% because it was overgrown during the competition with other bacterial species, not due to an inability to immobilize. Full article

(This article belongs to the Special Issue Advances in Biofilms and Their Applications in Biotechnology)

► Show Figures

Figure 1

28 pages, 9121 KiB

Open AccessReview

Composition, Bioactivities, Microbiome, Safety Concerns, and Impact of Essential Oils on the Health Status of Domestic Animals

by Bhagavathi Sundaram Sivamaruthi, Periyanaina Kesika, Nitiwan Daungchana, Natarajan Sisubalan and Chaiyavat Chaiyasut

Appl. Sci. 2024, 14(16), 6882; https://doi.org/10.3390/app14166882 - 6 Aug 2024

Abstract

Essential oils (EOs) are highly concentrated and volatile blends of nonpolar substances that are derived from aromatic plant components and comprise terpenes, terpenoids, and phenylpropanoids, exhibiting diverse biological and pharmacological properties. The burgeoning pet industry is interested in EOs as a potential solution [...] Read more.

Essential oils (EOs) are highly concentrated and volatile blends of nonpolar substances that are derived from aromatic plant components and comprise terpenes, terpenoids, and phenylpropanoids, exhibiting diverse biological and pharmacological properties. The burgeoning pet industry is interested in EOs as a potential solution for common health issues in domestic animals, particularly in addressing antimicrobial resistance. The present literature review summarizes the composition, properties, benefits, safety considerations, and effects of EOs on domestic animals. The applications of EOs range from antimicrobial effects to antioxidant, anti-inflammatory, and anticancer activities, etc. The chemical constituents of EOs, exemplified by eucalyptus EO and rosemary EO, highlight their distinct aromatic profiles and potential benefits. Nevertheless, understanding the chemical makeup of EOs is fundamental to assessing their potential impacts on biological systems. The gut microbiota plays a crucial role in regulating various metabolic processes in the host, including energy homeostasis, glucose metabolism, and lipid metabolism. Safety considerations, including potential toxicity risk awareness, are essential when incorporating EOs into animal care routines. The feed additives incorporating EOs have shown promise in influencing gut microbiota balance, reducing inflammation, and acting as antioxidants. However, considering the potential risks associated with high doses or multiple administrations, cautious application is paramount. Preliminary studies suggest low toxicity levels, but further research is required to evaluate the safety of EOs. Though studies have reported the beneficial effects of EOs on pets and animals, further research is needed to validate the findings in real-world conditions. The paper also discussed the regulatory considerations and future perspectives on applying EOs in veterinary medicine. Full article

► Show Figures

Graphical abstract

18 pages, 5562 KiB

Open AccessArticle

A Stock Market Decision-Making Framework Based on CMR-DQN

by Xun Chen, Qin Wang, Chao Hu and Chengqi Wang

Appl. Sci. 2024, 14(16), 6881; https://doi.org/10.3390/app14166881 - 6 Aug 2024

Abstract

In the dynamic and uncertain stock market, precise forecasting and decision-making are crucial for profitability. Traditional deep neural networks (DNN) often struggle with capturing long-term dependencies and multi-scale features in complex financial time series data. To address these challenges, we introduce CMR-DQN, an [...] Read more.

In the dynamic and uncertain stock market, precise forecasting and decision-making are crucial for profitability. Traditional deep neural networks (DNN) often struggle with capturing long-term dependencies and multi-scale features in complex financial time series data. To address these challenges, we introduce CMR-DQN, an innovative framework that integrates discrete wavelet transform (DWT) for multi-scale data analysis, temporal convolutional network (TCN) for extracting deep temporal features, and a GRU–LSTM–Attention mechanism to enhance the model’s focus and memory. Additionally, CMR-DQN employs the Rainbow DQN reinforcement learning strategy to learn optimal trading strategies in a simulated environment. CMR-DQN significantly improved the total return rate on six selected stocks, with increases ranging from 20.37% to 55.32%. It also demonstrated substantial improvements over the baseline model in terms of Sharpe ratio and maximum drawdown, indicating increased excess returns per unit of total risk and reduced investment risk. These results underscore the efficiency and effectiveness of CMR-DQN in handling multi-scale time series data and optimizing stock market decisions. Full article

► Show Figures

Figure 1

28 pages, 8958 KiB

Open AccessArticle

A Study on the Factors Controlling the Kinematics of a Reactivated and Slow-Moving Landslide in the Eastern Liguria Region (NW Italy) through the Integration of Automatic Geotechnical Sensors

by Giacomo Pepe, Barbara Musante, Giovanni Rizzi, Greta Viola, Andrea Vigo, Alessandro Ghirotto, Egidio Armadillo and Andrea Cevasco

Appl. Sci. 2024, 14(16), 6880; https://doi.org/10.3390/app14166880 - 6 Aug 2024

Abstract

This paper deals with the investigation of factors influencing the movement patterns of a reactivated slow-moving landslide situated in the eastern Liguria region (NW Italy) through the analysis of extensive ground-based hydrological and geotechnical monitoring data. Subsurface horizontal displacement and pore water pressure [...] Read more.

This paper deals with the investigation of factors influencing the movement patterns of a reactivated slow-moving landslide situated in the eastern Liguria region (NW Italy) through the analysis of extensive ground-based hydrological and geotechnical monitoring data. Subsurface horizontal displacement and pore water pressure data were acquired simultaneously by means of automatic sensors positioned at pre-existing and localized failure zones. The joint examination of field measurements enabled us to explore the connections between rain, pore water pressure, and displacements. The results of continuous displacement monitoring showed that the landslide kinematics involved phases of extremely slow movements alternated with periods of relative inactivity. Both stages occurred prevalently at seasonal scale displaying similar durations. The slow-motion phases took place at relatively constant pore water pressure and were ascribed to mechanisms of viscous shear displacements along failure surfaces. Inactive phases entailed no significant deformations, mostly corresponding to prolonged dry periods. The two motion patterns were interrupted by episodic sharp deformations triggered by delayed (preparation periods from 4 to 11 days) rainfall-induced pore water pressure peaks, which were ascribed to sliding mechanisms taking place through rigid-plastic frictional behaviour. During these deformation events, hysteresis relationships between pore water pressure and displacement were found, revealing far more complex hydro-mechanical behaviour. Full article

(This article belongs to the Special Issue Advances in Disaster Prevention and Reduction for Geotechnical Engineering)

► Show Figures

Figure 1

18 pages, 7231 KiB

Open AccessArticle

Transmission Loss Characteristics of Dual Cavity Impedance Composite Mufflers for Non-Planar Wave Cavity Resonance

by Yizhe Huang, Bojin Yan, Huizhen Zhang, Chenlin Wang, Jun Wang, Zhifu Zhang, Qibai Huang and Xin Zhan

Appl. Sci. 2024, 14(16), 6879; https://doi.org/10.3390/app14166879 - 6 Aug 2024

Abstract

In conventional gasoline automobiles, the engine powers the air conditioning system and engine noise can somewhat mask the noise and vibration of the air conditioning system. In pure electric vehicles, however, the absence of an engine makes the air conditioning system’s noise more [...] Read more.

In conventional gasoline automobiles, the engine powers the air conditioning system and engine noise can somewhat mask the noise and vibration of the air conditioning system. In pure electric vehicles, however, the absence of an engine makes the air conditioning system’s noise more noticeable, concentrated in a limited frequency range at constant speeds. As a result, aerodynamic noise from the air conditioning system is a primary noise source in electric vehicles. Pipeline silencers are the main method for reducing this noise. The current silencer design uses plane wave acoustic theory but when cavity modal resonance occurs, the transmission loss error is relatively high. This article addresses the issue of non-planar wave cavity resonance, studying the cavity modal of a muffler using the finite element method to reveal the transmission loss under cavity mode resonance. A dual cavity expansion structure of an impedance composite muffler is proposed, with sound-absorbing materials placed in the cavity to enhance acoustic performance. The analysis of the transmission loss characteristics of the impedance composite muffler provides a theoretical basis for noise control in pure electric vehicle air conditioning systems. Full article

► Show Figures

Figure 1

13 pages, 2741 KiB

Open AccessArticle

A Lightweight Fire Detection Algorithm Based on the Improved YOLOv8 Model

by Shuangbao Ma, Wennan Li, Li Wan and Guoqin Zhang

Appl. Sci. 2024, 14(16), 6878; https://doi.org/10.3390/app14166878 - 6 Aug 2024

Abstract

Aiming at solving the issues that fire detection is prone to be affected by environmental factors, and the accuracy of flame and smoke detection remains relatively low at the incipient stage of fire, a fire detection algorithm based on GCM-YOLO is put forward. [...] Read more.

Aiming at solving the issues that fire detection is prone to be affected by environmental factors, and the accuracy of flame and smoke detection remains relatively low at the incipient stage of fire, a fire detection algorithm based on GCM-YOLO is put forward. Firstly, GhostNet is introduced to optimize the backbone network, enabling the model to be lightweight without sacrificing model accuracy. Secondly, the upsampling module is reorganized with content-aware features to enhance the detail capture and information fusion effect of the model. Finally, by incorporating the mixed local channel attention mechanism in the neck, the model can enhance the processing capability of complex scenes. The experimental results reveal that, compared with the baseline model YOLOv8n, the GCM-YOLO model in fire detection increases the [email protected] by 1.2%, and the number of parameters and model size decrease by 38.3% and 34.9%, respectively. The GCM-YOLO model can raise the accuracy of fire detection while reducing the computational burden and is suitable for deployment in practical application scenarios such as mobile terminals. Full article

► Show Figures

Figure 1

16 pages, 8548 KiB

Open AccessArticle

Strength and Ultrasonic Testing of Acrylic Foam Adhesive Tape

by Jakub Kowalczyk and Marian Jósko

Appl. Sci. 2024, 14(16), 6877; https://doi.org/10.3390/app14166877 - 6 Aug 2024

Abstract

Adhesive joints are some of the oldest inseparable connections, and were used much earlier than other non-separable connections (e.g., welded, soldered). Adhesives are widely used in the manufacture of vehicles, household appliances, aircraft, and medicine. One disadvantage of adhesive joints is their long [...] Read more.

Adhesive joints are some of the oldest inseparable connections, and were used much earlier than other non-separable connections (e.g., welded, soldered). Adhesives are widely used in the manufacture of vehicles, household appliances, aircraft, and medicine. One disadvantage of adhesive joints is their long bonding time (amounting, for example, to 72 h for polyurethane adhesives used in bus roof bonding), and another is their production of harmful waste. Tapes that are adhesive coated on both sides are increasingly being used to join parts during production. Such tapes have lower strength than traditional adhesives, but their bonding time is much shorter. In addition, the amount of waste remaining after production is minimized. Tapes, like adhesives, dampen vibrations well and seal the materials being joined. The purpose of this study was to evaluate the influence of selected factors on the quality of tape–steel sheet joints and to assess the possibility of testing acrylic tape–steel sheet joints using ultrasonic methods. It was found that the preparation of a surface for bonding has a significant effect on the quality of the joint, and it was confirmed that non-destructive evaluation of the quality of the tested joints by the ultrasonic method is possible. The decibel drop in the height of the first and fifth pulses obtained on the screen of the ultrasonic defectoscope was proposed as an ultrasonic measure. The highest-quality joints were characterized by a measure in the range of 12 dB, lower-quality areas of about 8 dB, and tape-free areas of about 5 dB. At the same time, it was noted that in the case of proper surface preparation, there was cohesive failure of the joint during breakage. Full article

(This article belongs to the Special Issue Structural Health Monitoring: Latest Applications and Data Analysis, 2nd Edition)

► Show Figures

Figure 1

15 pages, 3035 KiB

Open AccessArticle

Multicenter Analysis of Emergency Patient Severity through Local Model Evaluation Client Selection: Optimizing Client Selection Based on Local Model Evaluation

by Yong-gyom Kim, SeMo Yang and KangYoon Lee

Appl. Sci. 2024, 14(16), 6876; https://doi.org/10.3390/app14166876 - 6 Aug 2024

Abstract

In multi-institutional emergency room settings, the early identification of high-risk patients is crucial for effective severity management. This necessitates the development of advanced models capable of accurately predicting patient severity based on initial conditions. However, collecting and analyzing large-scale data for high-performance predictive [...] Read more.

In multi-institutional emergency room settings, the early identification of high-risk patients is crucial for effective severity management. This necessitates the development of advanced models capable of accurately predicting patient severity based on initial conditions. However, collecting and analyzing large-scale data for high-performance predictive models is challenging due to privacy and data security concerns in integrating data from multiple emergency rooms. To address this, our work applies federated learning (FL) techniques, maintaining privacy without centralizing data. Medical data, which are often non-independent and identically distributed (non-IID), pose challenges for existing FL, where random client selection can impact overall FL performance. Therefore, we introduce a new client selection mechanism based on local model evaluation (LMECS), enhancing performance and practicality. This approach shows that the proposed FL model can achieve comparable performance to centralized models and maintain data privacy. The execution time was reduced by up to 27% compared to the existing FL algorithm. In addition, compared to the average performance of local models without FL, our LMECS improved the AUC by 2% and achieved up to 23% performance improvement compared to the existing FL algorithm. This work presents the potential for effective patient severity management in multi-institutional emergency rooms using FL without data movement, offering an innovative approach that satisfies both medical data privacy and efficient utilization. Full article

(This article belongs to the Special Issue Empowering Interactions: Advancing Human-Centred AI for Transparent, Collaborative and Accessible Applications)

► Show Figures

Figure 1

15 pages, 3450 KiB

Open AccessArticle

Adaptive Truncation Threshold Determination for Multimode Fiber Single-Pixel Imaging

by Yangyang Xiang, Junhui Li, Mingying Lan, Le Yang, Xingzhuo Hu, Jianxin Ma and Li Gao

Appl. Sci. 2024, 14(16), 6875; https://doi.org/10.3390/app14166875 - 6 Aug 2024

Abstract

Truncated singular value decomposition (TSVD) is a popular recovery algorithm for multimode fiber single-pixel imaging (MMF-SPI), and it uses truncation thresholds to suppress noise influences. However, due to the sensitivity of MMF relative to stochastic disturbances, the threshold requires frequent re-determination as noise [...] Read more.

Truncated singular value decomposition (TSVD) is a popular recovery algorithm for multimode fiber single-pixel imaging (MMF-SPI), and it uses truncation thresholds to suppress noise influences. However, due to the sensitivity of MMF relative to stochastic disturbances, the threshold requires frequent re-determination as noise levels dynamically fluctuate. In response, we design an adaptive truncation threshold determination (ATTD) method for TSVD-based MMF-SPI in disturbed environments. Simulations and experiments reveal that ATTD approaches the performance of ideal clairvoyant benchmarks, and it corresponds to the best possible image recovery under certain noise levels and surpasses both traditional truncation threshold determination methods with less computation—fixed threshold and Stein’s unbiased risk estimator (SURE)—specifically under high noise levels. Moreover, target insensitivity is demonstrated via numerical simulations, and the robustness of the self-contained parameters is explored. Finally, we also compare and discuss the performance of TSVD-based MMF-SPI, which uses ATTD, and machine learning-based MMF-SPI, which uses diffusion models, to provide a comprehensive understanding of ATTD. Full article

(This article belongs to the Special Issue Optical Imaging and Sensing: From Design to Its Practical Use)

► Show Figures

Figure 1

24 pages, 4405 KiB

Open AccessArticle

Physicochemical Characterization and Antioxidant Activity of Jara Honey Produced in Western Georgia

by Nona Abashidze, Indira Djafaridze, Maia Vanidze, Meri Khakhutaishvili, Maia Kharadze, Inga Kartsivadze, Ruslan Davitadze and Aleko Kalandia

Appl. Sci. 2024, 14(16), 6874; https://doi.org/10.3390/app14166874 - 6 Aug 2024

Abstract

The purpose of this research article was to study the physicochemical characteristics of semi-wild Jara honey grown in Western Georgia. Jara honey is produced in the alpine and sub-alpine forest zone of high mountain Adjara, which is distinguished by its variety of honey [...] Read more.

The purpose of this research article was to study the physicochemical characteristics of semi-wild Jara honey grown in Western Georgia. Jara honey is produced in the alpine and sub-alpine forest zone of high mountain Adjara, which is distinguished by its variety of honey plants. The physicochemical characteristics were examined concerning the Alimemtarius Code and EU regulations: moisture content, total carbohydrates, free acidity, pH, electrical conductivity, microelements (Li, Na, K, Mg, Ca), color, total phenols, total phenolic acids, total flavonoids, proline, diastase activity, proteins, and microscopic study of pollens. Using the UPLC-MSB method, grayanotoxin-III was identified in the semi-wild Jara honey samples. The findings demonstrated that the honey has significant concentrations of phenols, phenolic acids, and flavonoids. A directly proportional relationship was established between the quantitative content of phenolic compounds and the antioxidant activity of honey. This article is the first study of the characteristics of Jara honey produced in Western Georgia. Full article

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

► Show Figures

Figure 1

20 pages, 41447 KiB

Open AccessArticle

Fault Diagnosis of Planetary Gear Train Crack Based on DC-DRSN

by Le Luo and Yu Liu

Appl. Sci. 2024, 14(16), 6873; https://doi.org/10.3390/app14166873 - 6 Aug 2024

Abstract

To solve the problem that the existing planetary gear train fault diagnosis methods have, namely their low diagnostic accuracy under low signal-to-noise ratio (SNR), a fault diagnosis method based on a double channel-deep residual shrinkage network (DC-DRSN) is proposed. The short-time Fourier transform [...] Read more.

To solve the problem that the existing planetary gear train fault diagnosis methods have, namely their low diagnostic accuracy under low signal-to-noise ratio (SNR), a fault diagnosis method based on a double channel-deep residual shrinkage network (DC-DRSN) is proposed. The short-time Fourier transform (STFT) is used to convert the original vibration signal into a two-dimensional time-frequency graph, which effectively enhances the ability to express information. A DC-DRSN model is constructed, and the optimal number of residual shrinkage modules is determined by combining the diagnostic characteristics with different noises, which effectively improves the accuracy and anti-noise ability of fault diagnosis. The results of bearing and planetary gear train crack fault diagnosis show that the diagnosis method based on DC-DRSN has higher diagnostic accuracy while realizing fault diagnosis, which is better than other deep learning diagnosis methods. At the same time, the method can adapt to fault diagnosis in different noise environments, and has good expression ability and generalization ability. Full article

► Show Figures

Figure 1

20 pages, 3294 KiB

Open AccessArticle

Blockchain-Based Model for Incentivized Cyber Threat Intelligence Sharing

by Algimantas Venčkauskas, Vacius Jusas, Dominykas Barisas and Boriss Misnevs

Appl. Sci. 2024, 14(16), 6872; https://doi.org/10.3390/app14166872 - 6 Aug 2024

Abstract

Sharing cyber threat intelligence (CTI) can significantly improve the security of information technology (IT) in organizations. However, stakeholders and practitioners are not keen on sharing CTI data due to the risk of exposing their private data and possibly losing value as an organization [...] Read more.

Sharing cyber threat intelligence (CTI) can significantly improve the security of information technology (IT) in organizations. However, stakeholders and practitioners are not keen on sharing CTI data due to the risk of exposing their private data and possibly losing value as an organization on the market. We present a model for CTI data sharing that maintains trust and confidentiality and incentivizes the sharing process. The novelty of the proposed model is that it combines two incentive mechanisms: money and reputation. The reputation incentive is important for ensuring trust in the shared CTI data. The monetary incentive is important for motivating the sharing and consumption of CTI data. The incentives are based on a subscription fee and a reward score for activities performed by a user. User activities are considered in the following three fields: producing CTI data, consuming CTI data, and reviewing CTI data. Each instance of user activity is rewarded with a score, and this score generates some value for reputation. An algorithm is proposed for assigning reward scores and for recording the accumulated reputation of the user. This model is implemented on the Hyperledger Fabric blockchain and the Interplanetary File System for storing data off-chain. The implemented prototype demonstrates the feasibility of the proposed model. The provided simulation shows that the selected values and the proposed algorithm used to calculate the reward scores are in accordance with economic laws. Full article

(This article belongs to the Special Issue Blockchain Technologies: Trends, Challenges, Potentials and Applications)

► Show Figures

Figure 1

19 pages, 17392 KiB

Open AccessArticle

Identification of Land Use Mix Using Point-Based Geospatial Data in Urban Areas

by Mehmet Ali Akyol, Tuğba Taşkaya Temizel, Sebnem Duzgun and Nazife Baykal

Appl. Sci. 2024, 14(16), 6871; https://doi.org/10.3390/app14166871 - 6 Aug 2024

Abstract

Identifying land use mix (LUM) in urban areas is challenging, often requiring extensive human intervention and fieldwork. Accurate classification of LUM is crucial for various disciplines, including urban planning, urban economics, and public health. This study addresses this need by employing Voronoi triangulation [...] Read more.

Identifying land use mix (LUM) in urban areas is challenging, often requiring extensive human intervention and fieldwork. Accurate classification of LUM is crucial for various disciplines, including urban planning, urban economics, and public health. This study addresses this need by employing Voronoi triangulation and an entropy-based LUM formula using point-based geospatial data collected from publicly available sources. The methodology was tested in two distinct urban settings: Ankara and Kadıköy. Ankara, the capital city, provides a large and diverse urban environment, while Kadıköy, a district in Istanbul known for its dynamic urban life, offers a contrasting scenario. Results were analyzed concerning local spatial autocorrelation and point of interest (POI) intensity. The comparative analysis demonstrated that the approach performs well across different urban contexts, with improved results observed in Kadıköy due to its higher density of mixed-use development. Specifically, we managed to identify mixed land use areas with an accuracy of up to 78% and an F1-score of 83% in urban regions. These findings highlight the robustness and applicability of our approach in diverse urban environments, providing valuable insights for city planners and policymakers in optimizing the allocation of urban resources and enhancing land use efficiency. Full article

(This article belongs to the Special Issue Green/Geographic Information Systems (GIS) for Sustainable Development)

► Show Figures

Figure 1

14 pages, 1739 KiB

Open AccessArticle

Vestibular Training to Reduce Dizziness

by Heiko Hecht, Carla Aulenbacher, Laurin Helmbold, Henrik Eichhorn and Christoph von Castell

Appl. Sci. 2024, 14(16), 6870; https://doi.org/10.3390/app14166870 - 6 Aug 2024

Abstract

Many situations can induce dizziness in healthy participants, be it when riding a carrousel or when making head movements while wearing a head-mounted display. Everybody—maybe with the exception of vestibular loss patients—is prone to dizziness, albeit to widely varying degrees. Some people get [...] Read more.

Many situations can induce dizziness in healthy participants, be it when riding a carrousel or when making head movements while wearing a head-mounted display. Everybody—maybe with the exception of vestibular loss patients—is prone to dizziness, albeit to widely varying degrees. Some people get dizzy after a single rotation around the body axis, while others can perform multiple pirouettes without the slightest symptoms. We have developed a form of vestibular habituation training with the purpose of reducing proneness to dizziness. The training consists of a short (8 min) exercise routine which is moderate enough that it can easily be integrated into a daily routine. Twenty volunteers performed the training over the course of two weeks. We measured subjective dizziness before and after each daily session. We also performed several vestibular tests before (pre-test) and after (post-test) the two-week training period. They included exposure to a rotating and pitching visual environment while standing upright, as well as a physical rotation that was abruptly stopped. The results show that the dizziness induced during a given daily session decreased over the course of the two weeks. The dizziness induced by the rotating visual stimulus was significantly less after completion of the training period compared with the initial pre-test. Also, postural stability and post-rotatory spinning sensations had improved when comparing the post-test with the pre-test. We conclude that a short regular vestibular training can significantly improve proneness to dizziness. Full article

(This article belongs to the Topic Simulations and Applications of Augmented and Virtual Reality, 2nd Edition)

► Show Figures

Figure 1

19 pages, 1310 KiB

Open AccessArticle

Comparative Analysis of Neuromuscular Activation Patterns Associated with Force between Semi-Professional Female Soccer Players with Previous Anterior Cruciate Ligament Surgery and Healthy Players in Thigh Musculature Related to Valgus Collapse

by Loreto Ferrández-Laliena, Rocío Sánchez-Rodríguez, Lucía Vicente-Pina, María Orosia Lucha-López, Mira Ambrus, César Hidalgo-García, Sofía Monti-Ballano and José Miguel Tricás-Moreno

Appl. Sci. 2024, 14(16), 6869; https://doi.org/10.3390/app14166869 - 6 Aug 2024

Abstract

This study investigates electromyography activation and force development differences in key lower limb muscles between female football players with previous anterior cruciate ligament injuries compared with healthy players. Twenty-two semi-professional players were divided into ACL-injured (n = 11) and non-injured groups ( [...] Read more.

This study investigates electromyography activation and force development differences in key lower limb muscles between female football players with previous anterior cruciate ligament injuries compared with healthy players. Twenty-two semi-professional players were divided into ACL-injured (n = 11) and non-injured groups (n = 11). Participants underwent maximal voluntary isometric contractions while electromyography activation, peak and average, and peak torque of force were measured. Results indicated significant differences in electromyography activation patterns between anterior cruciate ligament players and non-injured players, particularly in biceps femoris and gluteus maximus muscles. These differences were also evident when comparing between limbs within anterior cruciate ligament players. Interestingly, both groups exhibited similar peak torque of force during maximal contractions, suggesting a compensatory neuromuscular strategy that supports a return to sport based on kinetic and kinematic factors. However, these findings underscore persistent muscle integration imbalances potentially contributing to the high rate of anterior cruciate ligament reinjury. In conclusion, this study highlights the importance of evaluating electromyography activation alongside force development in understanding neuromuscular adaptations post anterior cruciate ligament injury. These insights emphasize the need for comprehensive rehabilitation strategies that address muscle imbalance to mitigate the risk of recurrent anterior cruciate ligament injuries in female football players. Full article

(This article belongs to the Special Issue Advances in Sensor-Based Devices and Wearables for Clinical Rehabilitation)

► Show Figures

Figure 1

15 pages, 507 KiB

Open AccessArticle

Automatic Age and Gender Recognition Using Ensemble Learning

by Ergün Yücesoy

Appl. Sci. 2024, 14(16), 6868; https://doi.org/10.3390/app14166868 - 6 Aug 2024

Abstract

The use of speech-based recognition technologies in human–computer interactions is increasing daily. Age and gender recognition, one of these technologies, is a popular research topic used directly or indirectly in many applications. In this research, a new age and gender recognition approach based [...] Read more.

The use of speech-based recognition technologies in human–computer interactions is increasing daily. Age and gender recognition, one of these technologies, is a popular research topic used directly or indirectly in many applications. In this research, a new age and gender recognition approach based on the ensemble of different machine learning algorithms is proposed. In the study, five different classifiers, namely KNN, SVM, LR, RF, and E-TREE, are used as base-level classifiers and the majority voting and stacking methods are used to create the ensemble models. First, using MFCC features, five base-level classifiers are created and the performance of each model is evaluated. Then, starting from the one with the highest performance, these classifiers are combined and ensemble models are created. In the study, eight different ensemble models are created and the performances of each are examined separately. The experiments conducted with the Turkish subsection of the Mozilla Common Voice dataset show that the ensemble models increase the recognition accuracy, and the highest accuracy of 97.41% is achieved with the ensemble model created by stacking five classifiers (SVM, E-TREE, RF, KNN, and LR). According to this result, the proposed ensemble model achieves superior accuracy compared to similar studies in recognizing age and gender from speech signals. Full article

(This article belongs to the Special Issue Advances and Applications of Audio and Speech Signal Processing)

► Show Figures

Figure 1

Journal Menu

Journal Browser

Appl. Sci., Volume 14, Issue 16 (August-2 2024) – 46 articles

Further Information

Guidelines

MDPI Initiatives

Follow MDPI