bluuebunny/crossref_metadata_2025 huggingface dataset:
Study and Design of Distributed Badminton Agility Training and Test System
Authors: Tan Baohua , Wang Enpu , Cao Kan , Xiao Lu , Luo Lina
Published: January 2023

In order to improve the agility of college students, this paper designs a distributed agility training system. The system includes an upper computer and nine lower computers, in which the lower computer realizes the functions of data acquisition and communication with the upper computer and calculates the reaction time. The Android-based system software was installed in the upper computer to complete the functions of network connection, setting training times and showing the exercise time. In order to test the effectiveness of the equipment, nine university students were invited to complete agility training over 8 weeks with the help of agility training equipment in preparatory, enhancement and special stages. A t-test (Student’s t test) was conducted on the test results at different positions on the front and middle and back areas of the court before and after the training. The results show that the agility of the experimental objects was significantly improved after training, from the midpoint to any point at the front, middle and back court (p < 0.01). This shows that using equipment designed to develop agility for long-term training can promote the sensitive quality in badminton learners.
The Changes of Antioxidant Activity of Three Varieties of ‘Nalewka’, a Traditional Polish Fruit Alcoholic Beverage during Long-Term Storage
Authors: Nowak Anna , Duchnik Wiktoria , Muzykiewicz-Szymańska Anna , Kucharski Łukasz , Zielonka-Brzezicka Joanna , Nowak Andrzej , Klimowicz Adam
Published: January 2023

The diet rich in fruits is widely recommended for health-promoting properties. Regular consumption of fruits could reduce the risk of many diseases. The fruit-based alcoholic beverages have been produced for centuries and, in many countries, are still very popular. ‘Nalewka’ is a traditional name of Polish liqueur, i.e., an alcoholic beverage made by maceration of fruits. Homemade nalewkas are often stored for a long time before consumption, which can affect the content of valuable secondary metabolites. The aim of the study was to compare the effect of long-time storage on antioxidant activity and total polyphenol, total anthocyanin, tannin as well as gallic acid content in three homemade nalewkas. Cherry, plum, and multifruit nalewka were produced in 1997 and between 2013–2019 years. The antioxidant activity was measured by the DPPH, ABTS, FRAP, and CUPRAC methods. The content of gallic acid was estimated by high-performance liquid chromatography (HPLC). The oldest nalewkas (from 1997) showed significantly lower antioxidant activity as well as a lower content of polyphenols, anthocyanins, and gallic acid compared to the later-produced nalewkas, in particular those produced in 2016–2019. In most cases, a correlation was also found between the parameters of antioxidant activity as well as the total content of polyphenols and anthocyanins. Long-term storage of nalewkas reduces the content of valuable secondary metabolites responsible for the antioxidant activity and, thus, the health properties of the beverage.
Biomac3D: 2D-to-3D Human Pose Analysis Model for Tele-Rehabilitation Based on Pareto Optimized Deep-Learning Architecture
Authors: Maskeliūnas Rytis , Kulikajevas Audrius , Damaševičius Robertas , Griškevičius Julius , Adomavičienė Aušra
Published: January 2023

The research introduces a unique deep-learning-based technique for remote rehabilitative analysis of image-captured human movements and postures. We present a ploninomial Pareto-optimized deep-learning architecture for processing inverse kinematics for sorting out and rearranging human skeleton joints generated by RGB-based two-dimensional (2D) skeleton recognition algorithms, with the goal of producing a full 3D model as a final result. The suggested method extracts the entire humanoid character motion curve, which is then connected to a three-dimensional (3D) mesh for real-time preview. Our method maintains high joint mapping accuracy with smooth motion frames while ensuring anthropometric regularity, producing a mean average precision (mAP) of 0.950 for the task of predicting the joint position of a single subject. Furthermore, the suggested system, trained on the MoVi dataset, enables a seamless evaluation of posture in a 3D environment, allowing participants to be examined from numerous perspectives using a single recorded camera feed. The results of evaluation on our own self-collected dataset of human posture videos and cross-validation on the benchmark MPII and KIMORE datasets are presented.
Improved PBFT Algorithm Based on Comprehensive Evaluation Model
Authors: Jiang Wangxi , Wu Xiaoxiong , Song Mingyang , Qin Jiwei , Jia Zhenhong
Published: January 2023

Blockchain technology is well known due to the advent of Bitcoin. With the development of recent years, blockchain technology has been widely used in medicine, digital currency, energy, etc. The practical Byzantine fault-tolerant (PBFT) algorithm is a consensus algorithm widely used in consortium blockchains. Aiming to address the problems of the PBFT algorithm, low consensus efficiency due to high communication complexity, and malicious behavior of the primary node leading to consensus failure, an improved PBFT algorithm based on a comprehensive evaluation model (TB-PBFT) is proposed. First, nodes are divided into several groups based on the multi-formation control strategy of an unmanned aerial vehicle (UAV) cluster, which significantly reduces the communication complexity. Second, a comprehensive evaluation model combining the entropy method, TOPSIS method, and Borda count is proposed, which uses the behavior of nodes as an evaluation index, and the comprehensive score of nodes is obtained according to the preferences of other nodes. Finally, the highest ranking node is selected as the primary node through the comprehensive evaluation model to ensure the security and stability of the blockchain network. We analyze TB-PBFT algorithms and compare them with other Byzantine fault tolerance algorithms. Theoretical analysis and simulation results show that the TB-PBFT algorithm can improve node scalability and fault tolerance and reduce communication complexity and view switching probability. We also prove that the comprehensive evaluation model can improve the consensus success rate of the algorithm, and the feasibility and effectiveness of the improved consensus algorithm are verified. Hence, it can be applied to the consortium blockchain system effectively and efficiently.
Application of SSIR Method for the Design of Fungicides
Authors: de Julián-Ortiz Jesus Vicente , Besalú Emili
Published: January 2023

The design of fungicides is a central topic in agricultural chemistry. In this manuscript, it is shown how the Superposition of Significant Interaction Rules (SSIR) method can serve the generation of new potentially active molecules. By using SSIR, it is shown how the process becomes a simple symbolic procedure without the intervention of sophisticated statistical methods, although the results obtained are comparable.
Some Dynamic Aspects of a Sextic Galactic Potential in a Rotating Reference Frame
Authors: Alfadhli Munirah , Elmandouh Adel , Al Nuwairan Muneerah
Published: January 2023

This work aims to explore some dynamic aspects of the problem of star motion that is impacted by the rotation of the galaxy, which we model as a bisymmetric potential based on a two-dimensional harmonic oscillator with sextic perturbations. We demonstrate analytically that the motion is non-integrable when certain conditions are met. The analytical results for the non-integrability are confirmed by showing the irregularity of the behavior of the motion through utilizing the Poincaré surface of a section as a numerical method. The motion equilibrium positions are detected, and their stability is discussed. We show that the force generated by the rotating frame acts as a stabilizer for the maximum equilibrium points. We display graphically that the size of the stability regions relies on the angular velocity magnitude for the frame. Through the application of Lyapunov’s theorem, periodic solutions can be constructed which are close to the equilibrium positions. Furthermore, we demonstrate that there are one or two families of periodic solutions relying on whether the equilibrium point is a saddle or stable, respectively.
Review of Responsiveness and Sustainable Concepts in Cellular Manufacturing Systems
Authors: Renna Paolo , Materi Sergio , Ambrico Michele
Published: January 2023

Cellular manufacturing systems are widely used due to their advantageous capability of combining the flexibility of the job-shop and the productivity of the flow-shop. In recent years, the reduction of the product life cycle, variation in demand products, and introduction of new technologies, have driven the manufacturing companies to improve responsiveness, thus reducing the cellular manufacturing life cycle with a focus on re-designing the cells. Another issue concerns the sustainability of the manufacturing systems due to the introduction of energy costs in the design model of cellular manufacturing systems. This study is an overview of the more recent works on design approaches to improve the responsiveness and the models to support the sustainability of cellular manufacturing systems. The analysis of the literature review highlights the main findings and suggests future development paths considering the open problems in this field.
A Real Option Pricing Decision of Construction Project under Group Bidding Environment
Authors: Liu Mengkai , Zhu Chenwei
Published: January 2023

The bidding price is one of the important factors for construction enterprises in winning a bid. In the context of public bidding in the construction industry, in the process of group competition, how to estimate the individual bids to calculate their maximum value and the best price to improve the winning probability has become an important issue. In this research, based on the real option theory, the concept of group bidding environment is introduced to establish a real option price decision-making model for construction projects. The function of the model covers two external competitive environments: independent and coupled. Finally, through model inspection and parameter sensitivity analysis, the model is discussed in depth, and suggestions for model application are obtained. The research results show that the rule of the model results has optimization characteristics, and the numerical solution is consistent with the analytical solution, which has a certain price guidance role. In the independent bidding environment, their optimal bidding price is inversely proportional to the volatility level and the option period, and it is directly proportional to the estimated costs but has no obvious relationship with the number of competitors. Moreover, the average sensitivity of the optimal bidding price to the estimated costs, the volatility level and the option period are 35.06%, 9.77% and 7.70%, respectively; the optimal mark-up ratio is 1.078. In the coupled bidding environment, the concentration of competitors’ prices and the optimal price will increase significantly, by about 2.37%, and the corresponding winning probability and weighted option value will increase by about 9.36% and 28.03%, respectively. The research results can provide price optimization for bidding activities with real option characteristics and improve the price winning rate, but the selection of price mode and parameter setting need to be set by enterprises according to industry characteristics and actual conditions.
Effect of Compression Tights on Skin Temperature in Women with Lipedema
Authors: Sanchez-Jimenez Jose Luis , Priego-Quesada Jose Ignacio , Gisbert-Ruiz María José , Cibrian-Ortiz de Anda Rosa M. , Perez-Soriano Pedro , Aparicio Inmaculada
Published: January 2023

The aim was to analyze the effect of compression tights on skin temperature in women with lipedema and to assess the effect of different knitting on skin temperature. Twenty-four women with lipedema (Grade I = 25%; Grade II = 75%) were divided into three groups according to the compression tights prototype assigned: control (n = 9), Flat (n = 7) and circular (n = 8). The participants performed a gait test two times, separated by 15 days: before wearing the tights of the study and after the treatment (15 days employing compression tights). Skin temperature was measured using infrared thermography before and after the gait test on both days, and six regions of interest were determined in the anterior and posterior leg. The skin temperature decreased in the different regions of interest after exercise in all the groups (e.g., anterior thigh (IC95% (−1.1, −0.7 °C) p < 0.001), but no differences were observed in skin temperature between groups before and after walking (p > 0.05). The use of compressing tights for 15 days does not alter skin temperature in women with lipedema before and after walking. The absence of differences in skin temperature between tights in the different assessments allows for obtaining the benefits of wearing compression tights during exercise without negative thermal effects.
Stability Analysis of Equilibrium Point and Limit Cycle of Two-Dimensional Nonlinear Dynamical Systems—A Tutorial
Authors: Wei Bin
Published: January 2023

The equilibrium state of a dynamical system can be divided into the equilibrium point and limit cycle. In this paper, the stability analysis of the equilibrium point and limit cycle of dynamical systems are presented through different and all possible approaches, and those approaches are compared as well. In particular, the author presented the stability analysis of the equilibrium point through phase plane approach, Lyapunov–LaSalle energy-based approach, and linearization approach, respectively, for two-dimensional nonlinear system, while the stability analysis of the limit cycle is analyzed by using the LaSalle local invariant set theorem and Poincaré–Bendixson theorem, which is only valid in two-dimensional systems. Different case studies are used to demonstrate the stability analysis of equilibrium point and limit cycle.
Air Quality Versus Perceived Comfort and Health in Office Buildings at Western Macedonia Area, Greece during the Pandemic Period
Authors: Sakellaris Ioannis , Papadopoulos Giannis , Saraga Dikaia , Xenofontos Thalia , Tolis Evangelos , Panaras Giorgos , Bartzis John
Published: January 2023

This study investigated the indoor environment quality (IEQ) of eight office buildings of interest due to: (a) their location at the region of Western Macedonia, Greece, which is an area characterized by aggravated air quality and is currently in a transition phase because of changes in the energy production strategy to reduce the use of lignite as an energy fuel; and (b) the survey’s timing, characterized by new working conditions implemented during the COVID-19 pandemic period. In-site measurements were performed to identify the indoor air pollutants to which the occupants were exposed, while questionnaires were collected regarding the participants’ perception of the working environment conditions, indoor air quality, and health symptoms. The statistical analysis results showed that the most-reported health symptoms were headache, dry eyes, and sneezing. The acceptance of new working conditions showed a significant correlation with their overall comfort and health perception. Occupants in offices with higher pollutant concentrations, such as NO2, benzene and toluene, were more likely to report health symptoms. The evaluation of the plausible health risks for the occupants of the buildings with carcinogenic and no-cancer models showed that health problems could exist despite low pollutant concentration levels.
The Effect of Dead-Time and Damping Ratio on the Relative Performance of MPC and PID on Second Order Systems
Authors: Sha’aban Yusuf Abubakar
Published: January 2023

Most industrial processes are regulated using PID control. However, many such processes often operate far from optimally because PID may not be the most suitable control method. Moreover, second-order models represent a large class of all controlled systems. This work studies the performance of some commonly used industrial PID controllers relative to MPC to understand when it is more suitable to use Model predictive control. MPC is used for this comparison because it has been the most successful industrial controller after PID. It can be concluded from the studies that improved performance can be achieved with MPC, even for modest dead time and when the damping ratio is relatively low. These improvements are prominent for dead-time dominant systems, whose dead-time to time-constant ratio is at least three.
Heatmap Analysis to Differentiate Diverse Player Types in Table Tennis—A Training and Tactical Strategy Development Potential
Authors: Haas Fabiola , Baumgartner Tobias , Klein-Soetebier Timo , Seifriz Florian , Klatt Stefanie
Published: January 2023

(1) Background: Computer-based analyses have been widely used to study aspects of various team and racket sports. However, such analyses have so far eluded table tennis, except in special competition forms, under fixed laboratory conditions or have only tracked the ball. The aim was to detect a basic, global, positional behavior, independent of the score. (2) Methods: We investigated the player position of professional male table tennis players with respect to handedness (right/left), playing system (offensive/defensive) and racket holding (shakehand/penholder) to determine the applicability of automated analysis systems. We used existing video data of competitive matches (N = 198 sets; 2006–2020) and transliterated them into an x–y coordinate system. From this, we were able to conduct a heatmap analysis for different types of players. (3) Results: The comparison between right- and left-handed players resulted in a significant difference in the positioning of the x coordinate (D = 0.5663; p = 0.001). Both groups positioned themselves on average in their own backhanded half of the table (Re: x = −0.22 m, Li: x = 0.39 m). (4) Conclusions: Our results have yielded valuable insights into the importance of analyzing positional behavior in a differentiated manner depending on handedness, playing strategy and racket holding posture.
An Efficient Finite-Difference Stencil with High-Order Temporal Accuracy for Scalar Wave Modeling
Authors: Chen Guiting , Peng Zhenming , Li Yalin
Published: January 2023

Solving a scalar wave equation by the finite-difference (FD) method is a key step for advanced seismic imaging, in which the numerical accuracy is significantly affected by the FD stencil. High-order spatial and temporal approximations of the FD stencil can effectively improve the numerical accuracy and mitigate dispersion error. However, the huge costs of high-order stenciling in computation and storage hinder the application of large-scale modeling. In this paper, we propose a new efficient FD stencil with high-order temporal accuracy for numerical seismic modeling. The new stencil has a radial shape, including a standard cross-stencil and a rotated cross-stencil with a (π/4) degree, and it can reach sixth-order accuracy in the time approximation. Compared with the well-known temporal high-order cross-rhombus stencil, the new stencil involves fewer grid nodes and thus has higher computational efficiency, especially in high-order cases. Dispersion and stability analyses show that the new stencil has great improvements in mitigating the dispersion error and stability problem compared with the conventional methods. Numerical accuracy and execution time analyses show that the new stencil is an economical and feasible method for large-scale modeling.
Research on Tracking and Identification of Typical Protective Behavior of Cows Based on DeepLabCut
Authors: Li Jia , Kang Feilong , Zhang Yongan , Liu Yanqiu , Yu Xia
Published: January 2023

In recent years, traditional farming methods have been increasingly replaced by more modern, intelligent farming techniques. This shift towards information and intelligence in farming is becoming a trend. When they are bitten by dinoflagellates, cows display stress behaviors, including tail wagging, head tossing, leg kicking, ear flapping, and skin fluttering. The study of cow protective behavior can indirectly reveal the health status of cows and their living patterns under different environmental conditions, allowing for the evaluation of the breeding environment and animal welfare status. In this study, we generated key point feature marker information using the DeepLabCut target detection algorithm and constructed the spatial relationship of cow feature marker points to detect the cow’s protective behavior based on the change in key elements of the cow’s head swinging and walking performance. The algorithm can detect the protective behavior of cows, with the detection accuracy reaching the level of manual detection. The next step in the research focuses on analyzing the differences in protective behaviors of cows in different environments, which can help in cow breed selection. It is an important guide for diagnosing the health status of cows and improving milk production in a practical setting.
Numerical Method Using Homotopic Iterative Functions Based on the via Point for the Joint-Space Trajectory Generation
Authors: Quiñonez Yadira , Zatarain Oscar , Lizarraga Carmen , Aguayo Raquel , Mejía Jezreel
Published: January 2023

In recent years, many methods have been developed to calculate the trajectory of a robotic arm in the joint-space. These methods have many advantages, such as a soft motion and infinite jerk avoidance. Nevertheless, these methods present other problems that must be avoided, such as an unnatural motion while generating the trajectory and producing unsafe planning. In this sense, this work presents a numerical method named iterative optimal solution trajectory via (ζ)v-homotopy former (IOSTV (ζ)v-HF). It is proposed to reduce and avoid oscillation while obtaining trajectories with different shapes to perform better, reliable, smooth, and long-life robotic systems. The algorithm with the proposed method is described, and examples of the trajectories obtained with different parameters are presented. In addition, these were mapped and a trajectory with a continuous velocity and a reduced oscillation and another trajectory with the same restrictions but with a continuous acceleration and zero oscillations were shown; the method is versatile since it allows for choosing and finding the most optimal solutions according to the application. Finally, the article ends with a critical discussion of the experimental results.
All-Year Dropout Prediction Modeling and Analysis for University Students
Authors: Song Zihan , Sung Sang-Ha , Park Do-Myung , Park Byung-Kwon
Published: January 2023

The core of dropout prediction lies in the selection of predictive models and feature tables. Machine learning models have been shown to predict student dropouts accurately. Because students may drop out of school in any semester, the student history data recorded in the academic management system would have a different length. The different length of student history data poses a challenge for generating feature tables. Most current studies predict student dropouts in the first academic year and therefore avoid discussing this issue. The central assumption of these studies is that more than 50% of dropouts will leave school in the first academic year. However, in our study, we found the distribution of dropouts is evenly distributed in all academic years based on the dataset from a Korean university. This result suggests that Korean students’ data characteristics included in our dataset may differ from those of other developed countries. More specifically, the result that dropouts are evenly distributed throughout the academic years indicates the importance of a dropout prediction for the students in any academic year. Based on this, we explore the universal feature tables applicable to dropout prediction for university students in any academic year. We design several feature tables and compare the performance of six machine learning models on these feature tables. We find that the mean value-based feature table exhibits better generalization, and the model based on the gradient boosting technique performs better than other models. This result reveals the importance of students’ historical information in predicting dropout.
A Systematic Approach for Energy-Efficient Design of Rolling Bearing Cages
Authors: Gaydamaka Anatoliy , Klitnoi Volodymyr , Dobrotvorskiy Sergey , Basova Yevheniia , Matos Demétrio , Machado José
Published: January 2023

Several aspects must be considered in the design of rolling bearing cages. One of the most important considerations relates to studying and developing a stationary approach for solving problems of heat and mass transfer during convection. In this context, this paper proposes, among other achievements, the development and validation of a model of heat generation that is used, as the basis for an energy-efficient cage design in the context of the roller bearings of axle boxes for rail transport. The forces of interaction of the cage with the bearing parts are determined. The energy-efficient design of the cage is performed with modified friction surfaces in the form of convex contours of the pockets and micro-hollows on the surfaces of the pockets and support rings. On the basis of a flat model, of the interaction between the cage and the bearing parts, the pressure forces on the driving and driven rolling elements in the zone of radial loading are determined. The frictional moment of the bearing has been determined based on the integral design of the cage without taking into account lubrication during the interaction of the cage with the jumpers and with the sides of the basing ring. The calculation of the temperature gradient with standard and improved designs of bearing cages has been performed while taking air blowing into account; results showed a decrease in the average level and growth rate of the bearings’ temperature gradient with an energy-efficient cage design. Based on the obtained results, and on the developed heat generation model, a systematic approach for energy-efficient design of rolling bearing cages is proposed. The proposed approach, as well as the respective developed models, were validated by obtaining and analyzing the experimental results.
Topology- and Geometry-Controlled Functionalization of Nanostructured Metamaterials
Authors: Fomin Vladimir M. , Marquardt Oliver
Published: January 2023

The study of topological matter is one of the most fascinating areas of modern physics [...]
Effect of Randomness of Parameters on Amplification of Ground Motion in Saturated Sedimentary Valley
Authors: He Ying , Liu Xu , Liu Zhongxian , Chen Xueling , Yin Benchi
Published: January 2023

Based on Biot’s theory and the indirect boundary element method (IBEM), the Monte Carlo method is utilized to generate random samples to calculate the displacement response of a saturated sedimentary valley under SV wave incidence. The purpose of this paper is to explore the effects of randomness of porosity, permeability coefficient, and geometric shape on the seismic amplification effect of saturated complex sites. It is shown that the change of media porosity in the saturated site with defined boundary has relatively little influence on the ground motion, and the influence of the permeability coefficient is slightly larger. While in the site with a random boundary, the influence of both the porosity and permeability coefficient are significant, which cannot be ignored. The conclusion plays an important guiding role in earthquake disaster prevention and mitigation, such as seismic risk analysis and earthquake microzonation in saturated sedimentary valleys.
The Use of TECAR Therapy on Meibomitis Disease and Optical Nerve Flow
Authors: Tramontana Alfonso , Tedesco Giovanni Roberto , Gurgone Sergio , Acri Giuseppe , Meduri Alessandro
Published: January 2023

Meibomitis is an ocular disease which leads to a dysfunction of the meibomian glands. This ophthalmologic disease may cause severe pain and obvious vision loss. The therapeutic protocol used in the treatment of this pathology consists in local and systemic antibiotic therapy. The results obtained using this approach are scarce and, in many cases, result in adverse events. In this study, we propose an alternative and original approach using TECAR therapy in the treatments of meibomitis disease. The endogenous heat produced by the TECAR device produced beneficial effects from both a histological and anatomical point of view. Different parameters (TBUT, interferometry, tear meniscus height, meibography and OCTA) were evaluated before the TECAR treatments, immediately afterwards, and 15 days after the end of the treatments. The obtained results suggest a new possible use of TECAR therapy on ophthalmological patients, opening an innovative scenario in a non-invasive manner.
Implicit to Explicit Algorithm for ABAQUS Standard User-Subroutine UMAT for a 3D Hashin-Based Orthotropic Damage Model
Authors: Arruda M. R. T. , Trombini M. , Pagani A.
Published: January 2023

This study examines a new approach to facilitate the convergence of upcoming user-subroutines UMAT when the secant material matrix is applied rather than the conventional tangent (also known as Jacobian) material matrix. This algorithm makes use of the viscous regularization technique to stabilize the numerical solution of softening material models. The Newton–Raphson algorithm predictor-corrector of ABAQUS then applies this type of viscous regularization to a UMAT using only the secant matrix. When the time step is smaller than the viscosity parameter, this type of regularization may be unsuitable for a predictor-corrector with the secant matrix because its implicit convergence is incorrect, transforming the algorithm into an undesirable explicit version that may cause convergence problems. A novel 3D orthotropic damage model with residual stresses is proposed for this study, and it is analyzed using a new algorithm. The method’s convergence is tested using the proposed implicit-to-explicit secant matrix as well as the traditional implicit and explicit secant matrices. Furthermore, all numerical models are compared to experimental data. It was concluded that both the new 3D orthotropic damage model and the new proposed time step algorithm were stable and robust.
The Effect of the Core on the Absorption in a Hybrid Semiconductor Quantum Dot—Metal Nanoshell System
Authors: Kosionis Spyridon G. , Kontakos Alexandros , Paspalakis Emmanuel
Published: January 2023

We examine the optical absorption in a hybrid structure composed of a metal nanoshell and a semiconductor quantum dot, while interacting with a linearly polarized probe electromagnetic field. First, we derive the equations of motion, in the rotating wave approximation. Then we procced to the derivation of analytical expressions for the linear susceptibility of the metal nanoshell and the semiconductor quantum dot. The imaginary part of the susceptibility expresses the absorption coefficient. We find that by properly engineering the thickness of the metal nanoshell, the material of the dielectric core and the interparticle distance, we may achieve an optimum response. We identify the emergence of two distinct types of hybrid exciton states. One of them emerges in the strong exciton–plasmon coupling regime for low values of the dielectric constant and the radius of the dielectric core. This type of hybrid exciton exhibits an amplified gain without population inversion and a quenched absorption resonance accompanied by a suppressed exciton lifetime. The second type of hybrid exciton emerges in the weak exciton–plasmon coupling regime and presents the opposite spectral characteristics. Here, the exciton lifetime presents a substantial increase, especially for small interparticle distances, in which case the semiconductor quantum dot and the metal nanoshell are strongly coupled with one another.
A Prediction Method for Height of Water Flowing Fractured Zone Based on Sparrow Search Algorithm–Elman Neural Network in Northwest Mining Area
Authors: Gao Xicai , Liu Shuai , Ma Tengfei , Zhao Cheng , Zhang Xichen , Xia Huan , Yin Jianhui
Published: January 2023

The main Jurassic coal seams of the Ordos Basin of northwest mining area have special hosting conditions and complex hydrogeological conditions, and the high-intensity coal mining of the coal seams is likely to cause groundwater loss and negative effects on the surface ecological environment. The research was aimed at predicting the height of the water-flowing fractured zone (WFFZ) in high-intensity coal mining in that area and gave instructions for avoiding water inrush accidents and realizing damage reduction mining during the actual mining procedure of the coal mine. In this study, 18 samples of the measured height of WFFZ in Jurassic coal seams were systematically collected. In the mining method, the ratio of the thickness of the hard rock to the thickness of the soft rock in the bedrock, buried depth, mining height, and working face length was selected as the input vectors, applied the sparrow search algorithm (SSA) to iteratively optimize the weights and thresholds of the Elman neural network (ENN), constructed an SSA-Elman neural network model. The results demonstrate that the improved SSA-Elman neural network model has higher accuracy in predicting the height of the WFFZ compared with traditional prediction algorithms. The results of this study help guide damage-reducing, water-preserving mining of the middle-deep buried Jurassic coal seams in the northwest mining areas.
Optimal Heart Sound Segmentation Algorithm Based on K-Mean Clustering and Wavelet Transform
Authors: Xu Xingchen , Geng Xingguang , Gao Zhixing , Yang Hao , Dai Zhiwei , Zhang Haiying
Published: January 2023

The accurate localization of S1 and S2 is essential for heart sound segmentation and classification. However, current direct heart sound segmentation algorithms have poor noise immunity and low accuracy. Therefore, this paper proposes a new optimal heart sound segmentation algorithm based on K-means clustering and Haar wavelet transform. The algorithm includes three parts. Firstly, this method uses the Viola integral method and Shannon’s energy-based algorithm to extract the function of the envelope of the heart sound energy. Secondly, the time–frequency domain features of the acquired envelope are extracted from different dimensions and the optimal peak is searched adaptively based on a dynamic segmentation threshold. Finally, K-means clustering and Haar wavelet transform are implemented to localize S1 and S2 of heart sounds in the time domain. After validation, the recognition rate of S1 reached 98.02% and that of S2 reached 96.76%. The model outperforms other effective methods that have been implemented. The algorithm has high robustness and noise immunity. Therefore, it can provide a new method for feature extraction and analysis of heart sound signals collected in clinical settings.
Tunicate Swarm Algorithm with Deep Learning Based Land Use and Cover Change Detection in Nallamalla Forest India
Authors: Lavanya K. , Mahendran Anand , Selvanambi Ramani , Mazzara Manuel , Hemanth Jude D
Published: January 2023

Every biological system on the planet is severely impacted by environmental change, and its primary driver is deforestation. Meanwhile, quantitative analysis of changes in Land Use and Land Cover (LULC) is one of the prominent ways to manage and understand land transformation; thus, it is essential to inspect the performance of various techniques for LULC mapping to recognize the better classifier to more applications of earth observation. This article develops a Tunicate Swarm Algorithm with Deep Learning Enabled Land Use and Land Cover Change Detection (TSADL-LULCCD) technique in Nallamalla Forest, India. The presented TSADL-LULCCD technique mainly focuses on the identification and classification of land use in the Nallamalla forest using LANDSAT images. To accomplish this, the presented TSADL-LULCCD technique employs a dense EfficientNet model for feature extraction. In addition, the Adam optimizer is applied for the optimal hyper parameter tuning of the dense EfficientNet approach. For land cover classification, the TSADL-LULCCD technique exploits the Deep Belief Network (DBN) approach. To tune the hyper parameters related to the DBN system, the TSA is used. The experimental validation of the TSADL-LULCCD algorithm is tested on LANDSAT-7-based Nallamalla region images. The experimental results stated that the TSADL-LULCCD technique exhibits better performance over other existing models in terms of different evaluation measures.
A Granular Computing Classifier for Human Activity with Smartphones
Authors: Mahmood Mahmood A. , Almuayqil Saleh , Alsalem Khalaf Okab , Gasmi Karim
Published: January 2023

Recently, smart home devices have been widely used to assist and facilitate the lives of human beings. Human activity recognition (HAR) aims to identify human activities using sensors in smartphones. Therefore, it can be employed in many applications, such as remote health monitoring for disabled and elderly people. This paper proposes a granular computing-based approach to classifying human activities using wearable sensing devices. The approach has two main phases: feature selection and classification. In the feature selection phase, the approach attempts to remove redundant and irrelevant attributes. At the same time, the classification phase makes use of granular computing concepts to build the granules and find the relationships between granules at different levels. To evaluate the approach, we applied the dataset to five famous machine learning models. For the comparative evaluation, we also tested other well-known machine learning methods. The experimental results presented in this paper show that the approach outperformed common traditional classifiers in terms of classification precision recall, f-measure, and MCC for most recognized human activities by approximately 97.3%, 94%, 95.5%, and 94.8%, respectively. However, in terms of processing time, it performs comparably.
CAST-YOLO: An Improved YOLO Based on a Cross-Attention Strategy Transformer for Foggy Weather Adaptive Detection
Authors: Liu Xinyi , Zhang Baofeng , Liu Na
Published: January 2023

Both transformer and one-stage detectors have shown promising object detection results and have attracted increasing attention. However, the developments in effective domain adaptive techniques in transformer and one-stage detectors still have not been widely used. In this paper, we investigate this issue and propose a novel improved You Only Look Once (YOLO) model based on a cross-attention strategy transformer, called CAST-YOLO. This detector is a Teacher–Student knowledge transfer-based detector. We design a transformer encoder layer (TE-Layer) and a convolutional block attention module (CBAM) to capture global and rich contextual information. Then, the detector implements cross-domain object detection through the knowledge distillation method. Specifically, we propose a cross-attention strategy transformer to align domain-invariant features between the source and target domains. This strategy consists of three transformers with shared weights, identified as the source branch, target branch, and cross branch. The feature alignment uses knowledge distillation, to address better knowledge transfer from the source domain to the target domain. The above strategy provides better robustness for a model with noisy input. Extensive experiments show that our method outperforms the existing methods in foggy weather adaptive detection, significantly improving the detection results.
A Serious Mixed-Reality Game for Training Police Officers in Tagging Crime Scenes
Authors: Acampora Giovanni , Trinchese Pasquale , Trinchese Roberto , Vitiello Autilia
Published: January 2023

Recognizing and collecting evidence at a crime scene are essential tasks for gathering information about perpetrators and/or the dynamics of a criminal event. Hence, the success of a crime investigation is strongly based on the ability of forensic investigators to perform these tasks. Recent studies observing and comparing the performance of experts and novices have highlighted the importance of experience and training for search and recovery strategies at crime scenes. Therefore, relevant training programs in evidence-recovery techniques should be attended by novices to improve their skills. However, the knowledge transfer between skills acquired in the classroom and their practical application in the field is a challenging task. In order to relieve this problem, this paper proposes a serious mixed-reality game, which is called TraceGame, aiming to support the training activities of novice forensic investigators by improving their skills related to the search and recovery of evidence at crime scenes. The purpose of the game is to identify the greatest number of useful traces present in a crime scene that is physically reconstructed at the training site as quickly as possible. As shown in an experimental session, TraceGame is a promising tool for supporting the training of novice forensic investigators.
Deep Transfer Learning-Based Animal Face Identification Model Empowered with Vision-Based Hybrid Approach
Authors: Ahmad Munir , Abbas Sagheer , Fatima Areej , Issa Ghassan F. , Ghazal Taher M. , Khan Muhammad Adnan
Published: January 2023

The importance of accurate livestock identification for the success of modern livestock industries cannot be overstated as it is essential for a variety of purposes, including the traceability of animals for food safety, disease control, the prevention of false livestock insurance claims, and breeding programs. Biometric identification technologies, such as thumbprint recognition, facial feature recognition, and retina pattern recognition, have been traditionally used for human identification but are now being explored for animal identification as well. Muzzle patterns, which are unique to each animal, have shown promising results as a primary biometric feature for identification in recent studies. Muzzle pattern image scanning is a widely used method in biometric identification, but there is a need to improve the efficiency of real-time image capture and identification. This study presents a novel identification approach using a state-of-the-art object detector, Yolo (v7), to automate the identification process. The proposed system consists of three stages: detection of the animal’s face and muzzle, extraction of muzzle pattern features using the SIFT algorithm and identification of the animal using the FLANN algorithm if the extracted features match those previously registered in the system. The Yolo (v7) object detector has mean average precision of 99.5% and 99.7% for face and muzzle point detection, respectively. The proposed system demonstrates the capability to accurately recognize animals using the FLANN algorithm and has the potential to be used for a range of applications, including animal security and health concerns, as well as livestock insurance. In conclusion, this study presents a promising approach for the real-time identification of livestock animals using muzzle patterns via a combination of automated detection and feature extraction algorithms.
The Honeybee (Apis mellifera L.) Is an Efficient Pollinator for Paeonia lactiflora Pall in the Field
Authors: Tian Lixia , Ren Jun , Li Ruxu , Di Ning , Huang Xi , Wang Su , Fang Xihong , Xu Xilian
Published: January 2023

The herbaceous peony (Paeonia lactiflora Pall.) has high ornamental and nutritional value, and the seeds of P. lactiflora can be used to produce high-quality edible oil. However, low seed yield limits the application of P. lactiflora. This can be mitigated by insect pollinators. Here, we evaluated the pollination services of honeybees (Apis mellifera L.) in a P. lactiflora field. We found that A. mellifera provided pollination for P. lactiflora throughout the day especially in the period from 10:00–15:00. Seed number and weight were significantly increased when P. lactiflora was pollinated by A. mellifera. Furthermore, a DNA barcode, the rbcL gene, was used to analyze pollen samples from the corbiculae (pollen baskets) of A. mellifera (bee pollen, BP) and P. lactiflora flowers (flower pollen, FP). High homology of rbcL genes in the BP and FP suggested that BP was collected from P. lactiflora. Based on our results, A. mellifera provided efficient pollination for P. lactiflora. Therefore, A. mellifera could be a good candidate pollinator for P. lactiflora and could be applied in the field.
Standard Wave Scatter Table Limitation for Evaluating SGISC Based on Hindcast Data Analysis
Authors: Mangalathu Raj Samuel , Enshaei Hossein , Abdussamie Nagi
Published: January 2023

The operational measure (OM) of the Second-Generation Intact Stability Criteria (SGISC) is the initial step toward the design of a performance-based dynamic stability assessment of the ship by considering the vessel’s operation, loading condition and weather parameters. The SGISC recommends the standard wave scatter table (WST) for the environmental data, an indefinite requirement for a simplified assessment pathway, which provides the probability of wave occurrence. The existing standard WST was developed based on the North Atlantic Ocean. The study aims to identify the discrepancy in the probability of wave occurrence in the IMO-recommended WST when compared with developed hindcast WST for smaller regions of the North Atlantic Ocean for the application of the SGISC. This study is one of a kind and very significant, given that the assessment using the standard WST provided unrestricted operational ability to ship under the SGISC. The findings of this research provide insights into significant differences in the existing standard WST when compared graphically with hindcast data, especially across different seasons of the North Atlantic Ocean. A case study of OMs on the C11 class post-Panamax container ship for excessive acceleration is provided to better represent the study. In the case study, the operational limitation defined by the hindcast WST for individual sea areas and seasons is compared with the standard WST. This investigation shows that regional and seasonal operational limitations are required for season 4 operation beyond the standard WST safety estimation and that the operational limitation achieved with standard WST is not adequate. The findings suggest that the identified limitations significantly limit the use of a standard WST for unrestricted operational validation in the SGISC. The provided recommendation is very relevant in improving the safety assessment using vulnerability criteria, given that the hindcast data are reliable and available for the season and are also region-specific, and hence the accuracy of the ship stability can be improved while using the SGISC.