bluuebunny/crossref_metadata_2025 huggingface dataset:
Optimized Ensemble Machine Learning Approach for Emotion Detection from Thermal Images
Authors: Katual Jayaprakash , Kaul Amit
Published: January 2024

Emotions indicate the feelings of the individual which are linked with personal experiences, moods, and affective states. Detection of emotion can be helpful in many fields like maintaining a patient’s psychological well-being, surveillance, driver monitoring, etc. In this paper, an effective machine learning approach has been put forth for emotion detection where an ensemble of three out of five best-performing classifiers has been formed to enhance the classification accuracy. Two deep learning models (AlexNet and ResNet) have been optimally combined with [Formula: see text]-nearest neighbor (KNN). The optimal weights for ensemble weighted averaging of classifiers have been computed with aid of particle swarm optimization (PSO) and genetic algorithm (GA) optimization. The developed framework has been tested on two publicly available datasets. An overall accuracy of above 95% has been achieved on the testing set for both datasets. The best performance was obtained by training the classifiers with segmented images and combining them by using the weights obtained through PSO. The results depicted the efficiency of the optimized ensemble machine learning approach for all performance measures used in this study in comparison to the performance of individual classifiers and majority voting fusion.
A Novel Multi-Data-Augmentation and Multi-Deep-Learning Framework for Counting Small Vehicles and Crowds
Authors: Tsai Chun-Ming , Shih Frank Y.
Published: January 2024

Counting small pixel-sized vehicles and crowds in unmanned aerial vehicles (UAV) images is crucial across diverse fields, including geographic information collection, traffic monitoring, item delivery, communication network relay stations, as well as target segmentation, detection, and tracking. This task poses significant challenges due to factors such as varying view angles, non-fixed drone cameras, small object sizes, changing illumination, object occlusion, and image jitter. In this paper, we introduce a novel multi-data-augmentation and multi-deep-learning framework designed for counting small vehicles and crowds in UAV images. The framework harnesses the strengths of specific deep-learning detection models, coupled with the convolutional block attention module and data augmentation techniques. Additionally, we present a new method for detecting cars, motorcycles, and persons with small pixel sizes. Our proposed method undergoes evaluation on the test dataset v2 of the 2022 AI Cup competition, where we secured the first place on the private leaderboard by achieving the highest harmonic mean. Subsequent experimental results demonstrate that our framework outperforms the existing YOLOv7-E6E model. We also conducted comparative experiments using the publicly available VisDrone datasets, and the results show that our model outperforms the other models with the highest AP50 score of 52%.
A Rate Control Scheme for VVC Intercoding Using a Linear Model
Authors: Wang Heqiang , Wei Xuekai , Xian Weizhi , Luo Jun , Pu Huayan , Chu Zhigang , Wang Xin , Xu Xueyong , Lu Chang , Zhou Mingliang
Published: January 2024

Versatile video coding (VVC) aims to achieve high compression but also issues like varying content/network conditions. Existing rate control (RC) methods struggle to achieve optimal quality under these complex scenarios. This paper proposes a novel RC scheme for VVC based on a linear model. The Lagrange minimization multiplier is introduced under bit budget constraints, allowing optimized bit allocation. RC optimization is formulated as a convex solution, and is derived into the optimal quantization parameter (QP) for RC. Experimental analysis demonstrates the proposed linear model-based RC algorithm performances are better compared to other state-of-the-art methods due to their use of a linear model and optimal QP determination.
A Domain Variable Prior Based Multi-Style Transfer Network for Data Augmentation of Tidal Stream Turbine Rotor Image Dataset
Authors: Jiang Guohan , Wang Tianzhen , Yang Dingding , You Jingyi
Published: January 2024

The style of the underwater images varies according to the region of the sea. However, Tidal Stream Turbine (TST) rotor images captured in the laboratory environment cannot reflect the real underwater environment in image style, resulting in poor generalization of image signal-based fault detection algorithms. Due to the fixed capture position of the camera, the TST rotor image dataset has a high semantic similarity between images, resulting in content loss in conventional image-to-image translation networks. Meanwhile, the one-to-one translation feature in other works cannot meet our requirements. In this work, a Domain Variable Prior-based Multi-style Transfer Network (DVP-MSTN) is proposed to achieve TST rotor image style augmentation. First, the backbone network is trained using a public paired dataset to acquire prior knowledge of domain variable (Knowledge Acquiring, KA). Next, a Multi-domain Transfer Unit (MDT unit) is introduced to enable the conversion of style representations in low-dimensional space. Finally, the prior knowledge is shared to train the MDT unit by fixing the parameters of the backbone network optimized from the KA process (Knowledge Sharing, KS). In addition, an algorithm based on the dark channel of the image is proposed to improve the transfer of low-contrast features. Specifically, a discriminator is used to discriminate the image dark channel to guide the MDT unit to generate low-contrast style representation conditionally. Meanwhile, color loss is employed to preserve the color feature of the image. By controlling the weights of the style code, this method enables control over the image style transfer process, thereby expanding the variety of image styles in the dataset for the purpose of data augmentation.
Research on Multi-Source Heterogeneous Big Data Fusion Method Based on Feature Level
Authors: Chen Yanyan , Wang Chenxi , Zhou Yuchen , Zuo Yuhang , Yang Zixuan , Li Hui , Yang Juan
Published: January 2024

With the development of research on multi-modal data fusion and its combination with online data management, the application of multi-modal big data fusion in information management systems is more and more extensive. How to integrate multi-modal big data effectively is the key technology to building an efficient information management system. In this paper, based on the combination of a multi-support vector machine and convolution neural network, the feature-level data fusion of multi-source heterogeneous big data is implemented, and it is applied to the real data set to test the relevant model. Experimental results show that this method can not only realize heterogeneous integration of big data, but also has high accuracy and reliability.
Head Pose Estimation Based on Multi-Level Feature Fusion
Authors: Yan Chunman , Zhang Xiao
Published: January 2024

Head Pose Estimation (HPE) has a wide range of applications in computer vision, but still faces challenges: (1) Existing studies commonly use Euler angles or quaternions as pose labels, which may lead to discontinuity problems. (2) HPE does not effectively address regression via rotated matrices. (3) There is a low recognition rate in complex scenes, high computational requirements, etc. This paper presents an improved unconstrained HPE model to address these challenges. First, a rotation matrix form is introduced to solve the problem of unclear rotation labels. Second, a continuous 6D rotation matrix representation is used for efficient and robust direct regression. The RepVGG-A2 lightweight framework is used for feature extraction, and by adding a multi-level feature fusion module and a coordinate attention mechanism with residual connection, to improve the network’s ability to perceive contextual information and pay attention to features. The model’s accuracy was further improved by replacing the network activation function and improving the loss function. Experiments on the BIWI dataset 7:3 dividing the training and test sets show that the average absolute error of HPE for the proposed network model is 2.41. Trained on the dataset 300W_LP and tested on the AFLW2000 and BIWI datasets, the average absolute errors of HPE of the proposed network model are 4.34 and 3.93. The experimental results demonstrate that the improved network has better HPE performance.
CFOA-Based Sinusoidal Oscillator with Complete Resistive Tuning and Low Parametric Sensitivity
Authors: Nagachandrika Gandikota , Gurumurthy Komanapalli
Published: January 2024

In this paper, a second-order sinusoidal oscillator (SO) has been presented using current-feedback operational amplifiers (CFOAs) as the active element. The proposed oscillator uses five resistors and two grounded capacitors in its circuit design, making it simple and cost-effective to implement. Its design allows for greater control and flexibility in designing the oscillator circuit, making it an attractive option for a variety of applications. It also provides independent resistive tuning, allowing for greater control and flexibility in designing the oscillator circuit. Additionally, it offers low parameter sensitivity, makes it more stable and reliable. These features make it a valuable tool for engineers and designers in a variety of applications, including signal processing, communication systems, and control systems. The frequency tuning expression achieved has the ability to tune frequencies in a broad range of frequencies. PSPICE tool is used to simulate and analyze the behavior of the proposed circuit. The total harmonic distortion recorded was 5[Formula: see text].
Spatial–Spectral Total Variation-Regularized Low-Rank Tensor Representation for Hyperspectral Anomaly Detection
Authors: Du ZhiGuo , Chen Xingyu , Jia Minghao , Qiu Xiaoying , Chen Zelong , Zhu Kaiming
Published: January 2024

Hyperspectral anomaly detection is a vital aspect of remote sensing as it focuses on identifying pixels with distinct spectral–spatial properties in comparison to their background representations. However, existing methods for anomaly detection in HSIs often overlook the spatial correlation between pixels by converting the three-dimensional tensor data into its folded form of independent signatures, which may lead to insufficient detection performance. To address this limitation, we develop an anomaly detection algorithm from a tensor representation perspective, which begins by separating the observed hyperspectral image into background and anomaly cubes. We leverage the tensor nuclear norm (TNN) to capture the inherent low-rank structure of background cube globally. This allows us to effectively model and represent the background information. To further improve the detection performance, we introduce spatial–spectral total variation (SSTV) for effectively promoting piecewise smoothness of the background tensor, aiding in the identification of anomalies. Additionally, we incorporate RX-derived attention weights-guided [Formula: see text] norm. This encourages group sparsity of anomalous pixels, improving the precision of anomaly detection. To solve our proposed method, we employ the alternating direction method of multipliers (ADMM), ensuring guaranteed convergence and efficient computation. Through experiments on different kinds of hyperspectral real datasets, we have demonstrated that our method surpasses several state-of-the-art detectors.
Resistive Switching Property of Euforbia Cotinifolia Plant Extract for Potential Use in Eco-Friendly Memory Devices
Authors: Dlamini Zolile Wiseman , Vallabhapurapu Sreedevi , Vallabhapurapu Srinivasu Vijaya
Published: January 2024

Resistive switching memory devices based on organic materials are intriguing. These devices are biodegradable and nontoxic to living organisms. In this work, using euphorbia cotinifolia plant extract was investigated for its applicability as an active layer of a resistive switching memory device consisting of silver top electrode and indium-doped tin oxide bottom electrode. This study selected Euphorbia cotinifolia because it is a common, prolific and simple-to-grow plant in many South African homes. When the euphorbia cotinifolia plant is broken, an extract resembling milk is emitted. This extract was collected directly onto the bottom electrode, which was then dried at ambient temperature. For top electrode, silver paste was applied. The entire fabrication process was devoid of heat and electricity. The fabricated device showed impressive properties such as memory hysteresis with [Formula: see text], endurance of over [Formula: see text] write/erase cycles, and an impressive retention of [Formula: see text]. Therefore, this system may be a candidate for a nonvolatile and disposable memory device.
Nanotube TFET Biosensor with High-Frequency FOMs as Sensing Parameter
Authors: Gedam Anju , Acharya Bibhudendra , Mishra Guru Prasad
Published: January 2024

This paper proposes a new dielectrically modulated (DM) twin cavity nanotube biosensor and its sensitivity evaluation suitability by the transit time [Formula: see text] and device efficiency [Formula: see text]. In addition, the vertical structure of the device also helps the uniform spreading of biomolecules within the nanogap cavity region. The inner cavity of the proposed biosensor offers more space for the stabilization of biomolecules and uses the benefits of material solubility. In this paper, the sensing ability of the biosensor is examined in terms of [Formula: see text] and [Formula: see text] for five neutral biomolecules. Furthermore, the charged biomolecule and deoxyribonucleic acid (DNA) are separately investigated for positive as well as negative charge densities. Also, various optimizations on the device are analyzed for different biomolecules in this paper.
Sentiment-Time Heterogeneous Residual Graph Attention Transformer for Session-Based Recommendation
Authors: Wang Jun , Zhang Shuang
Published: January 2024

Session-Based Recommendation (SBR) systems are facing considerable challenges, with their primary objective being to implement precise recommendations based on users’ historical behavior sequences. Graph Neural Networks (GNNs) have emerged as powerful tools for processing graph-structured data in recommendation systems. Although recent research has advanced in this area, a significant gap remains in the in-depth exploration of transitional relationships between user interests. Additionally, real-world recommendation scenarios typically involve various heterogeneous relationships, which contain a wealth of information that can significantly enhance the learning of user preferences. To address this research gap, in this paper, we introduce a model termed the Sentiment-Time Heterogeneous Residual Graph Attention Transformer (STH-ResGAT), which is designed to capture the dynamic nature of user interests and the complexity inherent in heterogeneous graphs. In STH-ResGAT, we develop a Sentiment-Time-Heterogeneous Graph (STH-Graph) that integrates sentiment and time factors into the edges of the graph structure. Furthermore, the Residual Graph Attention Transformer for Heterogeneous Networks (ResGAT-Het) is designed to manage diverse node and edge types based on the STH-Graph. Extensive experiments are conducted on four widely-used benchmark datasets: Ciao, Yelp, Epinions and LibraryThing. The results demonstrate that our proposed STH-ResGAT method significantly outperforms previous state-of-the-art baseline approaches.The implementation of ResGAT-Het is available in https://github.com/zhangyu2234/ResGAT-Het.git .
STRUCTURES, ELECTRONIC, AND MAGNETIC PROPERTIES OF TRANSITION METAL-INSERTED H2DBP CLUSTERS
Authors: LI ZHI , YANG SHU-QI , YIN JIA-HUI , LI JIA-CONG , ABBASI SEDIGHEH
Published: January 2024

The configurations, electronic, and magnetic properties of the H2DBP-M clusters have been investigated via density functional theory. The results reveal that the TM atoms for the H2DBP-M ([Formula: see text], Y, Zr, Nb, Lu, and Hf) clusters deviate from the center planes of the clusters. The H2DBP-M ([Formula: see text], Y, and Lu) clusters display the largest dipole magnitudes. Based on the binding energy per atom and HOMO-LUMO gap, the H2DBP-Ni and H2DBP-Lu clusters are the most favorable for synthesis. The charge transfer amounts of the TM ([Formula: see text], Zn, Y, Cd, Hf, and Hg) atoms for the H2DBP-M clusters are larger. The TM-d orbitals of the H2DBP-M ([Formula: see text]Co and Cu) clusters contribute significantly to the Fermi levels. The spin densities of the TM atoms for the H2DBP-M clusters reduce to 0 except for that ([Formula: see text]) of the H2DBP-V clusters.
A STUDY ON MULTI-OBJECTIVE OPTIMIZATION OF PULSED TIG WELDING PARAMETERS AND THEIR EFFECT ON JOINT PROPERTIES OF HIGH MANGANESE STEELS USING TAGUCHI-BASED GRA APPROACH
Authors: SAHOO A. , TRIPATHY S. , TRIPATHY D. K.
Published: January 2024

This investigation focuses on the study of the effect of process parameters like peak current ([Formula: see text], base current ([Formula: see text], pulse frequency ([Formula: see text], shielding gas flow rate ([Formula: see text] on mechanical properties like yield strength (YS), ultimate tensile strength (UTS) and flexural strength (FS) of the welded joints during pulsed TIG welding of SAILMA 450 and EN14 B steels. Taguchi’s L[Formula: see text] orthogonal array has been used for conducting the tests. Multi-objective optimization has been performed using Grey relational analysis (GRA) in order to maximize the mechanical strength and to find out the optimal set of parameters. The optimum parametric combination is obtained at a peak current of 220[Formula: see text]Amps, base current of 120[Formula: see text]Amps, pulse frequency of 5[Formula: see text]Hz and shielding gas flow rate of 17[Formula: see text]l/min. Analysis of variance (ANOVA) is used to predict the significant process parameters. It has been observed from the ANOVA analysis that peak current and pulse frequency have more influence on the output responses than the shielding gas flow rate and base current. The results of the confirmatory test show an improvement of 0.5801 in the GRG, which is satisfactory. A microstructure study has been performed using scanning electron microscopy (SEM) for the optimal set of process parameters.
PHOTOTHERMAL DEFLECTION ANALYSIS OF β-In2S3 THIN FILMS: THE EFFECT OF S/In MOLAR RATIOS
Authors: ISMAIL S. , BCHIRI Y. , HALIDOU I. , BOUGUILA N. , KRAINI M. , YACOUBI N. , VÁZQUEZ CARLOS VÁZQUEZ , ALAYA S.
Published: January 2024

[Formula: see text]-In2S3 thin films ([Formula: see text], 2 and 4) were prepared using the pneumatic spray pyrolysis (PSP) route to analyze the effect of the S/In ratio on the physical properties. These properties were conducted using the photothermal deflection spectroscopy (PDS) method. The PDS signal amplitudes as a function of wavelength show multiple reflections which appear for all prepared In2S3 films. Such multiple reflections indicate homogeneity and high crystalline quality of the films. The deduced values of the optical band gap vary in the range 2.55–2.65[Formula: see text]eV. The highest thermal diffusivity is obtained for [Formula: see text]. The product ([Formula: see text]) is found in order of 10[Formula: see text][Formula: see text]cm[Formula: see text]/V. The estimated carrier diffusion lengths are 0.06, 0.11 and 0.09[Formula: see text][Formula: see text]m for films corresponding to [Formula: see text], 2 and 4, respectively. Defect absorption in [Formula: see text]-In2S3 films is also investigated by PDS. Five absorption peaks are observed. These absorption peaks contain defect information in the band gap. Hence, this work evidences that [Formula: see text]-In2S3 is a multi-functional material that can be used in optoelectronic, photovoltaic and visible-irradiation photocatalyst applications.
EXPERIMENTAL STUDY AND MONITORING OF TEMPERATURE AND SURFACE ROUGHNESS AND MICRO-HARDNESS OF THE WHEEL–RAIL CONTACT IN THE DESERT REGION OF THE OUARGLA TRAMWAY
Authors: ABDELKRIM MOURAD , CHIBA ELHOCINE , BELLOUFI ABDERRAHIM , REZGUI IMANE
Published: January 2024

Public transport via trams has become increasingly important in daily life to meet the growing demand for economic and environmental considerations. In order to ensure the safety of the railway system and reduce service costs, it is necessary to understand the tribological behavior of the system. There are various types of damage such as fatigue, wear, and cracking that can harm the wheels and rails. To determine the wear mechanisms and identify the situations in which wear movements occur, it is crucial to monitor factors such as temperature, surface roughness, and contact micro-hardness between the wheel and the rail. The objective of this study is to analyze the tribological behavior and the impact of climatic conditions on the wheel–rail contact system in the desert area of the Ouargla tramway in Algeria. To achieve this, an intelligent sensor programmed by a microcontroller was utilized to measure the temperature of the wheel–rail contact. Additionally, a hardness tester was used to measure the micro-hardness of the rail, and a roughness tester was utilized to monitor the surface condition of the rail. The measured temperature values during the passage of the tramway varied between ambient temperature and a temperature of 450∘C. The micro-hardness values ranged from 270 Hv to 440 Hv, and the roughness values varied between 0.4[Formula: see text][Formula: see text]m and 2.7[Formula: see text][Formula: see text]m.
MULTIVARIATE HAWKES-BASED MODELS IN LIMIT ORDER BOOK: EUROPEAN AND SPREAD OPTION PRICING
Authors: GUO QI , SWISHCHUK ANATOLIY , RÉMIlLARD BRUNO
Published: January 2024

In this paper, we consider the pricing problem of European options and spread options for the Hawkes-based model in the limit order book (LOB). We introduce a variant of Hawkes process and consider its limit theorems, namely the exponential multivariate general compound Hawkes process (EMGCHP). We also consider a special case of one-dimensional EMGCHP and its limit theorems. Option pricing with one-dimensional EMGCHP in LOB and numerical examples are presented. We also discuss implied volatility and implied order flow. It reveals the relationship between stock volatility and the order flow in the LOB system. In this way, the Hawkes-based model can provide more market forecast information than the classical Black–Scholes model. Margrabe’s spread options valuations with two one-dimensional and one two-dimensional Hawkes-based models for two assets are presented.
Geodesics on adjoint orbits of SL(n, ℝ)
Authors: Grajales Brian , Grama Lino , Prado Rafaela F.
Published: January 2024

In this paper, we examine the geodesics on adjoint orbits of [Formula: see text] that are equipped with [Formula: see text]-invariant metrics, where [Formula: see text] is the maximal compact subgroup. Our primary technique involves translating this problem into a geometric problem in the tangent bundle of certain [Formula: see text]-flag manifolds and describing the geodesic equations with respect to the Sasaki metric on the tangent bundle. Additionally, we utilize tools from Lie Theory to obtain explicit descriptions of families of geodesics. We provide a detailed analysis of the case for [Formula: see text].
Toroidal extended affine Lie algebras and vertex algebras
Authors: Chen Fulin , Li Haisheng , Tan Shaobin
Published: January 2024

In this paper, we study nullity-[Formula: see text] toroidal extended affine Lie algebras in the context of vertex algebras and their [Formula: see text]-coordinated modules. Among the main results, we introduce a variant of toroidal extended affine Lie algebras, associate vertex algebras to the variant Lie algebras, and establish a canonical connection between modules for toroidal extended affine Lie algebras and [Formula: see text]-coordinated modules for these vertex algebras. Furthermore, by employing some results of Billig, we obtain an explicit realization of a class of irreducible modules for the variant Lie algebras.
Well-posedness and analyticity of solutions for the sixth-order Boussinesq equation
Authors: Esfahani Amin , Tesfahun Achenef
Published: January 2024

In this paper, the sixth-order Boussinesq equation is studied. We extend the local well-posedness theory for this equation with quadratic and cubic nonlinearities to the high dimensional case. In spite of having the “bad” fourth term [Formula: see text] in the equation, we derive some dispersive estimates leading to the existence of local solutions which also improves the previous results in the cubic case. In addition, we show persistence of spatial analyticity of solutions for the cubic nonlinearity.
Multi-Mode Vibration Control of Super-Long Stay Cables with Negative Stiffness and Stockbridge Dampers
Authors: Wang Zhihao , Liu Yang , Gao Hui , Cheng Zhipeng , Wang Hao , Xu Yanwei
Published: January 2024

Installing mechanical dampers near the cable anchorage is a commonly used measure for suppressing rain-wind-induced vibrations (RWIVs) of stay cables. However, the high-mode vortex-induced vibrations (VIVs) are still observed on super-long stay cables installed with dampers. To this end, the study presents the combination of a negative stiffness damper (NSD) and Stockbridge dampers (SDs) to simultaneously suppress cable RWIVs and VIVs. In the proposed cable–NSD–SDs system, the NSD is installed near the cable anchorage to suppress cable RWIVs, and the SDs are installed at a higher location to suppress cable VIVs. First, the generalized characteristic equation of the cable–NSD–SDs system is derived for computing the coupled damping effect. Subsequently, a novel design method of an NSD and two SDs for mitigating cable multi-mode vibrations is proposed, and its effectiveness is numerically verified on an ultra-long stay cable of the Sutong Bridge. Finally, the control performance of an NSD and two SDs for the cable under white noise and harmonic excitations is emphatically evaluated and compared. Results indicate that the NSD–SDs system is quite effective for mitigating high-mode vibrations of super-long stay cables. Compared with the cable–NSD system, the cable acceleration response of the cable–NSD–SDs system is reduced by over 35%.
Finite p-groups in which the cores of all the nonnormal subgroups are in the center
Authors: Zhao Libo , Li Yangming , Gong Lü , Guo Xiuyun
Published: January 2024

Let [Formula: see text] be a finite [Formula: see text]-group. Then [Formula: see text] is said to be a [Formula: see text]-group if [Formula: see text] for every nonnormal subgroup [Formula: see text] of [Formula: see text]. In this paper, we study the [Formula: see text]-group [Formula: see text] and get [Formula: see text]. It is proved that [Formula: see text] if [Formula: see text] and [Formula: see text] if [Formula: see text].
On the norm of the lower central series in a finite group
Authors: Gong Lü , Jing Ziru , Zhao Libo , Li Baojun
Published: January 2024

In this paper, the norm [Formula: see text] of the lower central series in a finite group [Formula: see text] is introduced, which unifies the norm of derived subgroups and nilpotent residuals. Some propositions of [Formula: see text] are obtained, and some related subgroups as well as their equivalent propositions can also be found.
CORRELATION OF KNEE PAIN AMONG SUBJECTS WITH OSTEOARTHRITIS TAKING GRAPHENE-BASED THERMOTHERAPY FOR HEALTH IMPROVEMENT
Authors: LAU JUN HAO , USMAN JULIANA , HUM YAN CHAI , LAI KHIN WEE
Published: January 2024

Leg health is an important consideration in a person’s overall well-being, and knee osteoarthritis (OA) is one of the problems that reduces leg health. Thermotherapy therapy has long been recognized as one of the methods for treating knee OA pain. This study recruited 30 subjects with OA (aged 45–80, height of 155–175[Formula: see text]cm, weight of 60–95[Formula: see text]kg and body mass index of 18–40) to participate in a repeated measure for inter-subject and intra-subject analysis on pre- and post-treatment-based thermotherapy sessions where SpO2, pulse rate (PR) and Knee Injury and Osteoarthritis Outcome Score (KOOS) were measured within 4 weeks of explorative study. When a subject is subjected to thermotherapy, SpO2 increases and PR decreases compared with those of the control group, which did not present significant differences. The findings show a high degree of inter- and intra-subject repeatability. When a subject received thermotherapy for 4 weeks, his or her overall leg health improved, as indicated by a high KOOS and high KOOS-pain score. This is demonstrated by an increase in KOOS over the course of 4 weeks of thermotherapy.
COMPOUND TRAINING: A STUDY ON THE INFLUENCE ON THE BOUNCING FORCE OF VOLLEYBALL PLAYERS WHEN THEY JUMP AND SPIKE THE BALL
Authors: GE YUHUI , YIN JUAN , SONG QINGYAO
Published: January 2024

Objective: This paper aims to investigate the impact of compound training (CT) on the jumping spike performance of volleyball players. Methods: Twenty athletes were randomly assigned to either the CT group or the resistance training (RT) group. After eight weeks of training, the results for in-situ jump and reach, run-up jump and reach, as well as squat jump (SJ), counter-movement jump (CMJ), and run-up jump measured using the Just Jump test system were compared between the two groups. Results: Prior to the experiment, there were no significant differences in any of the test parameters between the two groups ([Formula: see text]). Following the experiment, the one-repetition maximum (1RM) weighted deep squat result for the CT group was [Formula: see text][Formula: see text]kg, the in-situ jump and reach height was [Formula: see text][Formula: see text]m, and the run-up jump and reach height was [Formula: see text][Formula: see text]m, all with [Formula: see text] compared to pre-experiment values and the RT group. Additionally, the duration and height of flight of SJ in the CT group were [Formula: see text][Formula: see text]s and [Formula: see text][Formula: see text]cm, respectively; the duration and height of flight of CMJ were [Formula: see text][Formula: see text]s and [Formula: see text][Formula: see text]cm, respectively; the duration and height of flight of run-up jumps were [Formula: see text][Formula: see text]s and [Formula: see text][Formula: see text]cm, respectively. All of the above results were significantly higher than those before the experiment and those of the RT group ([Formula: see text]). Conclusion: The superior results observed in the CT group’s jumping tests suggest that the effects of CT on bouncing force are more pronounced, making it a viable approach for practical training.
INSIGHTS INTO HUMAN LOCOMOTION STRATEGIES AND MOTOR LEARNING FOR AN AGEING POPULATION USING TRANSFER TESTING AND COUPLED SIMULATIONS
Authors: NOWAKOWSKI KATHARINE , CARVALHO PHILIPPE , EL KIRAT KARIM , DAO TIEN-TUAN
Published: January 2024

The elucidation of human locomotion strategies has potential applications in the prevention of sarcopenia and in the reduction of falls. Given the diverse biochemical, mechanical and functional age-related changes seen in the neuro-musculoskeletal system, the decline in motor function is difficult to study experimentally. In this study, we use transfer testing and coupled simulation strategies within a deep reinforcement learning environment to better understand the complex problem of motor control adaptation to age-related changes. Using transfer testing, a 3D musculoskeletal model is separately trained on parameters of the young adult model (Y) for either forward or backward falls after completing two steps forward, and tested using a 30% age-related reduction for all parameters (M_all). This strategy produces a backward fall for a forwardly trained simulation, showing potential sensitivity of these parameters to a given fall direction. Second, a coupled simulation solution is used to simulate recovery from falls by considering the center-of-mass position relative to the base of support. Results for the M_all trained model showed a longer simulation time and a greater vertical pelvis velocity with a maximal value of 4.26[Formula: see text]m/s. In particular, the results of the coupled simulations clearly show that both the young and M_all condition models respond with a step back and stronger leg extensor activations to propel the model forward to recover from the simulated fall. We developed a novel coupling between transfer testing and coupled simulation strategies to improve upon muscle models for characterizing muscle function, and also to begin testing different hypotheses, such as the strategy and force required to avoid a fall at different limits. This opens new avenues for precision rehabilitation with patient-specific muscle-driven recovery exercises.
A PRECISE RESPIRATORY AND HEART RATE DETECTION METHOD FOR MILLIMETER-WAVE RADAR
Authors: WAN XIANGKUI , LIAO TAO , GONG WENXIN , LIANG YAMENG , WU MINGHU , WANG BINHUI
Published: January 2024

Millimeter wave radar as a type of noncontact sensor can more conveniently and insensibly obtain breathing and heartbeat signals. However, due to the weak radar echo signal and the influence of noise, there may be phase ambiguity and separation distortion of breathing and heartbeat signals during the processing, which affects the accuracy of detection. In this paper, an enhanced extended differential and cross multiplication (EDACM) algorithm is presented to obtain chest position signals without phase ambiguity. A specific order finite impulse response (FIR) filter with a Blackman window is applied to extract breath signals without waveform distortion from phase signals, and the heartbeat signal without rate distortion is extracted from the phase signal by means of the designed Chebyshev II filter. The measured results show that the proposed method achieves 96.78% accuracy for heart rate detection and 94.44% accuracy for respiratory rate detection, and improves the accuracy of heart rate detection by 2.22% and respiratory rate detection by 4.06% compared to the band-pass filter method under the same parameter conditions.
PERFORMANCE IMPROVEMENT OF TRANSIENT PULSATING FLOW IN ROOT CANAL IRRIGATION AND FLOW MECHANISM ANALYSIS
Authors: TAN YOUWEI , SUN XIAOYU , LIU RUIRUI , LI PING
Published: January 2024

Inflow conditions dominate the process of root canal irrigation, and the application of pulsating inflow in dentistry is necessary to be explored due to its mass transfer enhancement capability. A prepared root canal model with a 30G side-vented needle is numerically investigated under pulsating inflow with different frequencies and amplitudes. Root canal apical pressure, extending depth, and effective cleaning area are adopted to evaluate the safety, mass transfer capacity, and clean efficiency of the irrigation system. Time-averaged results show that the irrigation performance is improved with pulsating flow maintaining safety. Compared with steady cases, the extending depth and effective cleaning area are increased by up to 43.6% and 11.42%, respectively. Three typical cases with significant improvement are selected for transient analysis. Transient results show that the apical pressure and extending depth have instant response features, while the effective cleaning area has a time-lag response characteristic. It is convinced that the transient characteristic of the system results from the coupling effects of the pulsating effect, instantaneous flow rate, and Coanda effect. The internal flow distribution of root canal system is prompted under the optimal parameters combinations of pulsating conditions, in which mass transfer capacity and clean efficiency are enhanced with guaranteed safety.
A novel wavelet transform in the quaternion quadratic-phase domain
Authors: Bhat M. Younus , Alamri Osama Abdulaziz , Dar Aamir H.
Published: January 2024

In this paper, we propose a novel integral transform coined as quaternion quadratic-phase wavelet transform (QQPWLT) by invoking the elegant convolution structure associated with the quaternion quadratic-phase Fourier transform. First, we explore some mathematical properties of the QQPWLT, including the orthogonality relation, inversion formula, reproducing kernel and some notable inequalities. Second, we study Heisenberg’s uncertainty principles and the logarithmic uncertainty principle associated with the quadratic-phase wavelet transform in quaternion domain. We culminate our investigation by presenting some illustrative examples.
Gabor frame multipliers and Parseval duals on the half real line
Authors: Yang Ming , Li Yun-Zhang
Published: January 2024

Recently, Gabor analysis on locally compact abelian (LCA) groups has become the focus of an active research. In practice, the time variable cannot be negative. The half real line [Formula: see text] is an LCA group under multiplication and the usual topology, with the Haar measure [Formula: see text]. This paper addresses Gabor frame multipliers and Parseval duals for [Formula: see text]. We introduce and characterize Gabor frame multipliers and Parseval Gabor frame multipliers based on Zak transform matrices. Our Zak transform matrix is essentially different from the conventional Zibulski–Zeevi matrix. It allows us to define Gabor frame generators by designing suitable matrix-valued functions of finite size. We also prove that an arbitrary Gabor frame [Formula: see text] admits a Parseval dual frame/tight dual frame whenever [Formula: see text] are rational numbers not greater than [Formula: see text].
Discrete linear canonical shearlet transform
Authors: Bhat Younis A. , Sheikh N. A.
Published: January 2024

In this paper, we introduce the continuous and discrete version of the linear canonical shearlet transform (LCST). The authors begin with the definition of the LCST and then establish a relationship between the linear canonical transform (LCT) and the LCST. Next, the paper derives several basic properties like Parseval’s Formula, inversion formula, and the characterization of the transform’s range. In addition to the continuous version of the transform, the authors also present a discrete version of the LCST. This discrete version allows for practical implementation and efficient computation of the transform in digital signal processing systems. Lastly, the paper establishes a frame condition for the discrete LCST, which thereby helps in establishing the reconstruction formula for the discrete LCST. The paper ends with a conclusion.
An improved model for wavelet coefficients estimation and its application to image denoising
Authors: Li Xueqing , Deng Caixia , Li Shasha , Pi Lu
Published: January 2024

Image denoising is a significant procedure in image processing, and a good denoising method can improve the image quality. This study focuses on enhancing the estimation model of wavelet coefficients by improving the threshold function. Thus, a general construction method for a class of threshold functions is introduced, and sufficient conditions are given to ensure that the threshold functions are continuous, first-order differentiable and higher-order differentiable. It makes an existing class of improved threshold functions a particular case and enables the construction of other needed threshold functions based on this general approach. Experiments have shown that using the new threshold functions yields better denoising results for images containing salt and pepper noise, Gaussian noise and speckle noise. Moreover, as the smoothness of the threshold function is enhanced, the denoising effect is also improved. The improved wavelet coefficients estimation model can effectively boost the quality of image denoising, further enhancing the accuracy and effectiveness of computer vision algorithms.
Joint remote state preparation protocol for non-maximally entangled W-states and fidelity analysis in noisy environments
Authors: Choudhury Binayak S. , Mandal Manoj Kumar , Samanta Soumen
Published: January 2024

In this paper, we discuss a protocol for preparing a non-maximally entangled W-state at a distant location where there are two parties intending such creation each of whom possesses only partial information about the state. These two parties along with a third party Controller, participate in a single protocol in order to create the intended state in the hands of a fourth party. The role of the controller is to fabricate an 8-qubit entangled state and distribute the respective qubits involved in the entangled state to the relevant parties and thereby creating a noisy quantum channel. The protocol is first ideally discussed in the noise-free case which is then a perfect joint remote state preparation protocol with fidelity 1. Then, we discuss the performance of the protocol in the presence of noise in which the fidelity is diminished. We consider three different types of noises and analyze the variation of fidelity of the process.
Shape Modeling with a Cubic Trigonometric Beta B-Spline with Local Support Basis Functions
Authors: Samreen Shamaila , Khan Arslan Khalid , Sarfraz Muhammad
Published: January 2024

The modeling capabilities of trigonometric B-spline curves with form parameters are comparable to those of classical B-spline curves in terms of their significance and use. Through the application of basic functions and shape parameters, this method presents the cubic trigonometric B-spline curves. Constructed by these functions, the concept of designing curves and surfaces possesses all the ideal geometric qualities, such as the partition of unity, convex hull, affine invariance, and variation decreasing. The parameters that are used in the creation of the recommended approach are helpful for several important form characteristics. These vital form aspects include local, global, and biased tension qualities, which provide good control over the curve and allow for shape change as required. In addition, the [Formula: see text] strategy is the one that is suggested for use.
Characterizations of η–ρ-Einstein solitons in spacetimes and f(ℛ)-gravity
Authors: De Uday Chand , Sardar Arpan , Mofarreh Fatemah
Published: January 2024

A generalized Robertson–Walker spacetime is not, in general, a perfect fluid spacetime and the converse is not, in general, true. In this paper, we show that if a perfect fluid spacetime admits an [Formula: see text]–[Formula: see text]-Einstein soliton, then the integral curves generated by the velocity vector field [Formula: see text] are geodesics and the acceleration vector vanishes. Also, we show that if a perfect fluid spacetime with Killing velocity vector field admits a gradient [Formula: see text]–[Formula: see text]-Einstein soliton, then the spacetime represents either dark matter era or, the acceleration vector vanishes. Next, we show that if a generalized Robertson–Walker spacetime admits an [Formula: see text]–[Formula: see text]-Einstein soliton, then it becomes a perfect fluid spacetime. Finally, we prove that in a dark matter fluid with vanishing vorticity satisfying gradient [Formula: see text]–[Formula: see text]-Einstein soliton in [Formula: see text]-gravity with constant Ricci scalar, either the energy density and isotropic pressure are constant or, the potential function [Formula: see text] remains invariant under the velocity vector [Formula: see text]. Also, for two models [Formula: see text] and [Formula: see text] ([Formula: see text] = constant and [Formula: see text] is the Ricci scalar of the spacetime), various energy conditions in terms of the Ricci scalar are examined and state that the Universe is in an accelerating phase and satisfies the weak, null and dominant energy conditions, but violate the strong energy condition.
Least Absolute Deviations Estimation for an Uncertain Moving Average Model
Authors: Wang Lin , Gao Xin
Published: January 2024

The existing parameter estimation methods of the uncertain moving average model are the least square method and ridge estimation. However, for some data with outliers, the least square method cannot eliminate the influence of outliers very well. In order to solve this problem, this paper discusses how to use the parameter estimation method of least absolute deviation to solve the uncertain moving average model, and calculate the mean and variance of the residuals, so as to find the confidence interval of the predicted value. Finally, two examples are given to demonstrate that the uncertain moving average model estimated by the least absolute deviation can predict closer values to the actual values than other estimation methods.
A Novel Tri-Magnet Levitating Bistable Electromagnetic Energy Harvester with Variable Potential Wells to Promote Snap-Through Behavior
Authors: Xu Junjie , Su Xukun , Chen Xiaoyu , Leng Yonggang , Sun Shuailing
Published: January 2024

To achieve broadband energy harvesting under weak excitations, this paper comprehensively investigates a novel tri-magnet levitating bistable electromagnetic energy harvester with variable potential wells (BEEH-VP). The bistable nonlinear mechanism is realized using the single-sided bipolarity of the ring magnets. Auxiliary springs are integrated into the ring magnets to dynamically self-adjust the spacing of the ring magnets, causing variable potential wells. The analytical model of BEEH-VP is derived and verified experimentally. The performance of the proposed BEEH-VP is compared with that of the bistable electromagnetic energy harvester with featuring fixed potential wells (BEEH-FP). The comparative results clearly demonstrate that the BEEH-VP exhibits superior capabilities in terms of energy output under weak excitation and possesses a broader frequency bandwidth. Bifurcation analysis for the excitation conditions reveals that the proposed structure features complex dynamic behaviors, such as intra-well, chaotic, harmonic inter-well and subharmonic inter-well vibrations. In comparison to BEEH-FP, BEEH-VP requires lower acceleration to perform the snap-through and has a larger vibration amplitude, facilitating improved output performance.
Multiscale Simulation of the Coupled Chemo-Mechanical Behavior of Porous Electrode Materials by Direct FE2 Method
Authors: Lan Yizhou , Ma Lianhua , Du Xiyan , Zhou Wei
Published: January 2024

Application of porous electrode materials has sparked significant interest as a strategy to mitigate traditional electrode mechanical failure arising from its intercalation-induced large volume change. In this work, a thermal analogy method is employed for implementing the coupled chemo-mechanical model into the finite element (FE) package ABAQUS via user subroutines UMATHT and UMAT, which is used to model the lithium (Li) diffusion and the resulting deformation of the electrode during charge-discharge cycling. This work presents a Direct FE2 method for modeling the chemo-mechanically coupled behavior of porous electrode materials by establishing the macro-microscopic scale transitions through concentration and displacement DOFs and the representative volume element (RVE) volume scaling relationship. The two-scale numerical simulations can be implemented in a single computational scheme. Within the present computational framework, the Li diffusion and mechanical deformation in the porous silicon electrode during charging and discharging are easily simulated in the typical FE package. Benchmarked against the traditional direct full-field numerical computational method, the Direct FE2 method is validated to present significant computational efficiency improvements through two numerical examples, the constrained expansion and the pre-compression expansion of porous electrode, by 99.27% and 94.55%, respectively, while maintaining the high precision.