Rotation Matrix Research Articles

Machine Learning Based Analysis and Prediction of Emotional Expressions in Dance Movements

Abstract Dance movement is a powerful way to convey human emotions, and analyzing and predicting the emotional expression of dance movement through machine learning has become a hotspot in the field of artificial intelligence research nowadays. This paper employs the Seagull optimization algorithm to enhance the SVM classification model, laying the algorithmic groundwork for the research, and refines it to align with the research requirements. The classification of dance movements is accomplished by the nonlinear regression algorithm in the support vector machine regression algorithm, while the task of capturing dance movements is realized by means of Euler angles to describe the orientation, rotation matrices to transform vectors between different coordinate systems, and quaternions to optimize the Euler angles. Finally, this paper analyses and predicts the emotional expression of dance movements using a classification loss model (LSTMBO) and a W-RNN model that incorporates the weights of emotion words. In this paper, tests on the classification algorithm revealed that the algorithm's classification accuracy is above 90% for all datasets used in the research. Moreover, the performance and effectiveness of dance action capture are significantly better than other comparative algorithms. Simultaneously, this paper's algorithm achieves an accuracy of over 80% in predicting emotions expressed through dance movements. Numerous experiments have proven the effectiveness and superiority of the algorithm model in this paper, thereby promoting the research and development of the field.

COUPLED C-ESPRIT-BASED AZIMUTH AND ELEVATION ANGLE ESTIMATION WITH MINIMUM VARIANCE

This paper presents a method for conjugate estimation of azimuth and elevation angles based on the minimum variance C-ESPRIT method. The conjugate estimation method with minimum variance is a modification of the robust method based on the ESPRIT method with minimum variance and differs from it in that it does not require prior matching of signal duplicates. When modeling the signal acquisition from a unmanned aerial vehicle and processing it with the ESPRIT method, the data were distorted. Several signals were not displayed and noise appeared, which prevented the estimation of the signal arrival direction. The paper presents an efficient algorithm that can estimate the direction of arrival based on uncorrelated and one-dimensional signals. The method of conjugate estimation with minimum variance, when compared to the method of conjugate estimation without minimum variance, has been shown to improve the signal by a factor of 10. This improvement in signal quality allows one to conclude that the method is highly efficient. The C-ESPRIT-based minimum variance conjugate azimuth and location angle estimation method uses a robust minimum variance method with a conjugate rotation matrix to process a second subarray of data. An important aspect of the method is that it uses information from all array elements without grouping them and without computing the mean of the covariance matrices.

Exploring the Critical Barriers Towards Women Participation in Surveying and Geo-Informatics Practices

Surveying and geo-informatics stand as a significant field at the intersection of science, technology, and spatial management, playing a crucial role in informing decision-making across various industries. However, the surveying and geo-informatics field suffers from the underrepresentation of women professionals. This underrepresentation carries significant implications hindering diversity of knowledge and skills. In order to build a more inclusive and equitable professional environment, the study aims to identify and analyse the identified barriers to offer insight and strategies to enhance women's participation. Data were gathered using a mixed-methods (sequential exploratory) approach, which included interviews and structured questionnaires (five Likert scale) with professionals in the field. Twenty-five participants and 138 responses were considered for the study. Statistical tests such as Cronbach's Alpha, mean ranking, one sample t-test, Chi-square, Kruskal Wallis, and factor analysis were conducted to investigate the significance and relationship between the identified barriers. The result shows that the participation of women in the surveying and geo-informatics field is low. Similarly, the study shows that the barriers are critical to the participation of women in the field, considering their significance level. In addition, a rotation of the component matrix reveals three dimensions: equity and inclusion, career advancement and assistance, and gender equality and empowerment. These factors offer a thorough foundation for comprehending the many difficulties women in the field encounter. The study developed various strategies tailored to mitigate each barrier component. The findings of this study add to the body of knowledge on gender differences in surveying and geo-informatics practises and offer policymakers, organisations, and stakeholders valuable insights. Eliminating these obstacles will improve gender diversity, encourage inclusivity, and fully utilise the talents of women, ultimately resulting in a more innovative and sustainable surveying and geo-informatics profession in Nigeria.

Peningkatkan QoS Layanan Video Call dengan Metode DASTFBC Sistem MIMO2x2 pada Jaringan LTE

ABSTRACT
 The DASTFBC (Diagonal Algebraic Space Time Frequency Block Code) method is a coding scheme that utilizes different diversity sources, namely space, time and frequency. This method is one method that can be used to improve video call services. The DASTFBC method uses a rotation matrix in the DAST code which is formed using algebraic number field theory. The code matrix structure consists of rotated information symbols, expanded using a square diagonal code matrix. This method is used to overcome signal power fluctuations at the receiver which cause the service quality to decrease (not comply with) BER video call standards. The DASTFBC method is applied to the LTE network MIMO system with 64 QAM modulation. This method will be simulated in the Matlab program to obtain results to improve video call services. The DASTFBC method simulation of BER was carried out for 4 user speed scenarios, namely 5km/hour, 40km/hour, 100km/hour, 120km/hour. Significant results of the DASTFBC method can already be seen when the user moves at 40km/ hour. With this method, a smaller BER value is obtained, namely 2x10-4, this shows that with the DASTFBC method the video call BER standard (10-3) can be met. The value of BER obtained when using DASTFBC with a speed of 120km/h is 8.5x10-3 this value almost exceeds the standard BER video call. So that the maximum speed of the user when using the DASTFBC method is 120km/h above that speed the standard value of the BER video call cannot be fulfilled.
 Keywords: video call, LTE network, MIMO, DASTFBC

Integrating Abnormal Gait Detection with Activities of Daily Living Monitoring in Ambient Assisted Living: A 3D Vision Approach.

Gait analysis plays a crucial role in detecting and monitoring various neurological and musculoskeletal disorders early. This paper presents a comprehensive study of the automatic detection of abnormal gait using 3D vision, with a focus on non-invasive and practical data acquisition methods suitable for everyday environments. We explore various configurations, including multi-camera setups placed at different distances and angles, as well as performing daily activities in different directions. An integral component of our study involves combining gait analysis with the monitoring of activities of daily living (ADLs), given the paramount relevance of this integration in the context of Ambient Assisted Living. To achieve this, we investigate cutting-edge Deep Neural Network approaches, such as the Temporal Convolutional Network, Gated Recurrent Unit, and Long Short-Term Memory Autoencoder. Additionally, we scrutinize different data representation formats, including Euclidean-based representations, angular adjacency matrices, and rotation matrices. Our system's performance evaluation leverages both publicly available datasets and data we collected ourselves while accounting for individual variations and environmental factors. The results underscore the effectiveness of our proposed configurations in accurately classifying abnormal gait, thus shedding light on the optimal setup for non-invasive and efficient data collection.

Geo-Quantitative Analysis of Violent Crime Intervention Strategies in Kaduna State, Nigeria

The complexities and consequences of violent crimes require a robust and effective approach to achieve a sustainable reduction of violence in our society. This paper, therefore, presents an avenue to provide the geo-quantitative analysis of violent occurrences in Kaduna State of Nigeria to determine the pragmatic interventionist strategies for managing violent crime incidence among the people of the study area. Geo-quantitative analysis entails transforming numerical data about criminal activities into a map of proportional circles to depict the distribution pattern of criminal activities and using scree plots and factor loading to show higher-order intervention measures for managing violent crimes. Five Local Government Areas (LGAs) with relatively high levels of violent incidence were purposively selected while snowball sampling method was used to administer questionnaires to 384 respondents. From the findings, the spatial distribution of violent crimes revealed that Birni-Gwari and Kachia LGAs accounted for the highest incidence of kidnapping and village raids respectively while Kajuru LGA is known for the highest cases of cattle rustling and armed robbery. The critical interventions in managing violent crimes are reconciliation efforts to restore order and normalcy, negotiation between aggrieved parties, and adoption of a traditional conflict resolution system with a rotated factor matrix of 0.828, 0.581, and 0.544 respectively. Furthermore, the strongest positive correlation exists between good government policies and equity with fairness in representation and establishment of developmental projects (r = 0.524, and p ˂ 0.001). Therefore, the study recommended establishing conflict mediation centers across the communities. Similarly, it is essential to have a good governance system that will give people their fair share of national resources and adequate policing of communities that could guarantee the reduction of violent incidents to the barest minimum.

SL-RI: Integration of supervised learning in robots for industry 5.0 automated application monitoring

Robotic technology holds a significant role within the realm of smart industries, wherein all functionalities are executed within real-time systems. The verification of robot operations is a crucial aspect in the context of Industry 5.0. To address this requirement, a distinctive design methodology known as SL-RI is proposed. This article aims to establish the significance of incorporating robots in the Industry 5.0 framework through analytical representations. In the context of this industrial monitoring system, the implementation of a supplementary algorithm is essential for effective management, as it enables the robots to acquire knowledge through the analysis and adaptation of restructured commands. The analytical model of robots is designed to accurately monitor the precise position and accelerations of robots, resulting in full-scale representations with minimal error conditions. The uniqueness of the proposed method in robotic monitoring system is related to the application process that is directly applied in Industry 5.0 by using various parametric cases where active movement of robots are monitored with rotational matrix representations. In this type of representations the significance relies in the way to understand the full movement of robots across various machines and its data handling characteristics that provides low loss and error factors.

An obstacle detection method for dual USVs based on SGNN-RMEN registration of dual-view point clouds

This paper proposes an unsupervised obstacle detection method for dual unmanned surface vessels (USVs) using the SGNN-RMEN framework. The method utilizes dual-view point clouds captured by two USVs to improve the detection of small obstacles under the condition of a visible shore. Firstly, a siamese graph neural network (SGNN) is designed to extract global contour features. A specialized task of global contour consistency classification is employed to ensure the interpretability of these features. Secondly, a rotation matrices estimation network (RMEN) is utilized to estimate the optimal rotation transformation for aligning point clouds based on the global contour features of the dual-view point clouds. The overlap degree between the dual-view point clouds before and after registration is used as feedback to train the model, enabling unsupervised learning. Finally, a " gridding - filtering - clustering” method is applied to annotate the size and position of obstacles based on the registration of the dual-view point clouds. Comparative experiments on two datasets demonstrate the effectiveness of the proposed method in accurately extracting contour features, achieving precise dual-view point cloud registration, and improving the detection rate of small obstacles in nearshore environments. The method also exhibits strong adaptability in unfamiliar marine environments.

Improved biological neural network approach for path planning of differential drive agricultural robots with arbitrary shape

To improve the path planning ability of a differential drive agricultural robot with arbitrary shape, a novel path planning method based on improved biological neural dynamics approach is proposed. Taking a T-shaped robot as an example, its shape features at different orientations are described through kernel matrix rotation. The coordinates and orientation of the robot are used as neuron position parameters to construct a 3-D neural network, and the neuron state is determined by convolutional calculation. Neural connections are defined based on the translational and rotational motion properties of the robot. By subdividing the workspace network, more flexible rotation options for the robot are obtained. Then, biological neural dynamics is established to determine a stable neural activity landscape, and a collision-free path can be obtained by consecutively selecting the adjacent neuron with maximum activity. The two key factors to improve the path planning ability are the flexible rotation options of the robot in a grid workspace and the consideration of the interaction between the robot body and the surrounding obstacles. It is proved that the proposed approach can find a feasible path within the range of rational numbers. Finally, its strong path planning ability is demonstrated by several experiments in narrow and complex environments.

Continuous fiber reinforced meta-composites with tailorable Poisson’s ratio and effective elastic modulus: Design and experiment

Auxetic metamaterials, i.e., with negative Poisson’s ratio are attracting increasing attention. This study develops a novel method to design and investigate continuous fiber-reinforced meta-composites with tailorable negative Poisson’s ratio and effective elastic modulus. First, the design scheme based on parametric level set method, is proposed by combining fast marching method, filtering technology and matrix rotation for attaining the two-dimensional isotropic composites. A novel objective function considering both negative Poisson’s ratio and effective elastic modulus is introduced and the result demonstrate that it is effective to not only accelerate the numerical convergence but also achieve a larger negative Poisson’s ratio when compared with that using the currently-used objective function. By tailoring a weight ratio for balancing the negative Poisson’s ratio and effective elastic modulus, a general contradictive trend was captured. Experimentally, the specimens are accordingly fabricated via 3D printing. Then, the axial compression tests are performed with the aid of digital image correlation technology to characterize the deformation behaviors and evaluate the mechanical properties of the designed meta-composites. Experimental results show that, as the weight ratio increases from 0.02 to 1.57, the effective elastic modulus increases from 180.5 MPa to 310.3 MPa (enhanced by 71.9 %) while the negative Poisson’s ratio decreases from − 0.41 to − 0.036 (reduced by 91.4 %), proving the effectiveness of the design method. The design methods and experimental results can provide effective approaches and important information for designing novel continuous fiber reinforced meta-composites with tailorable mechanical performance.

RoFormer: Enhanced transformer with Rotary Position Embedding

Position encoding has recently been shown to be effective in transformer architecture. It enables valuable supervision for dependency modeling between elements at different positions of the sequence. In this paper, we first investigate various methods to integrate positional information into the learning process of transformer-based language models. Then, we propose a novel method named Rotary Position Embedding (RoPE) to effectively leverage the positional information. Specifically, the proposed RoPE encodes the absolute position with a rotation matrix and meanwhile incorporates the explicit relative position dependency in the self-attention formulation. Notably, RoPE enables valuable properties, including the flexibility of sequence length, decaying inter-token dependency with increasing relative distances, and the capability of equipping linear self-attention with relative position encoding. Finally, we evaluate the enhanced transformer with rotary position embedding, also called RoFormer, on various long text classification benchmark datasets. Our experiments show that it consistently overcomes its alternatives. Furthermore, we provide a theoretical analysis to explain some experimental results. RoFormer is already integrated into Huggingface: https://huggingface.co/docs/transformers/model_doc/roformer.

Modeling single-phase transverse flows in a PWR rod bundle at low Reynolds number

In normal functioning conditions, the primary component of the flow within the rod bundle of a PWR core is in the axial direction, along the rods. However, in accidental situations, such as the refilling or reflooding phase during a Loss of Coolant Accident, or a Steam Line Break accident, transverse flows may significantly affect thermal-hydraulic properties in the core. Such effects have received little attention in system codes such as CATHARE, particularly in anisotropic rod structures at low Reynolds numbers. Here, we develop macroscopic pressure drop models for flows spanning from the creeping regime to unsteady vortex shedding. The averaged model is a generalized Darcy–Forchheimer equation with an apparent permeability including a rotation matrix and a non-linear dimensionless coefficient. The constitutive relations for the intrinsic permeability matrix are derived from polynomial regressions based on results obtained from microscale numerical simulations at different flow directions and Reynolds numbers. We finally test our approach in a case where transverse flow is imposed through a differential of inlet velocities and validate by comparing results from CATHARE with those obtained from a finite element toolbox.

The Thermal Conductivity Coefficient of a Square Thermal Invisibility Cloak Cell and Its Application in Periodic Plate

In this paper, the thermal conductivities of the square thermal invisibility cloak are constructed in two ways. One is the direct method, another is the rotation matrix method. The thermal conductivity coefficients obtained by the two methods are the same. The cloud map of thermal conductivity coefficient of the thermal cloak is drawn, which can help us understand more intuitively how the thermal invisibility cloak works. Besides, to manipulate heat flow in a larger area, the cloaks are arranged periodically by introducing the position parameters into the calculation of the thermal conductivity coefficient of the thermal invisibility cloak. The heat insulation function of both the single thermal cloak and the thermal cloak periodic plate are tested under different heat boundary conditions using COMSOL Multiphysics. For different heat boundary conditions, heat flux direction of the simulation result is given. The results show that both the single thermal cloak and the thermal cloak periodic plate have the function of avoiding heat flow under different heat boundary conditions. The heat fluxes travel around the inner domain with good thermal stealth effect.

Establishment of iterative modeling method for spherical tensegrity structure using rotational symmetry and regular polyhedron configuration

Tensegrity structures are attractive light-weight structures. In particular, spherical tensegrity structures are expected to be applied in various fields. This article proposes a simple method for modeling spherical tensegrities. Firstly, the nodal coordinates of the spherical tensegrity are systematically determined based on rotational symmetry and regular polyhedral configuration. This approach enables the systematic acquisition of the nodal coordinates of spherical tensegrities of all sizes by introducing a three-dimensional rotation matrix and the dihedral angle of the regular polyhedron. Secondly, the prestress ratio is determined iteratively. For the stability analysis of the spherical tensegrity, nonlinear analysis with prestress is required. For the analysis considering the prestress, a tangent stiffness matrix is applied in this study. The simple determination method enables the modeling of spherical tensegrities. The natural frequencies and mode shapes of the spherical tensegrity are identified by frequency analysis. A vibration experiment is conducted as a verification experiment. The natural frequencies from the analysis are compared to the resonance frequencies from the experiment. This comparison confirms the validity of the frequency analysis results, based on the two proposed methods.

Intersatellite and Downlink Agile Attitude Maneuvers

This research is focused on the problem of agile attitude maneuvering, aimed at the precise pointing of a satellite forming a typical constellation in low Earth orbit. We consider two different operational scenarios: (a) pointing toward a specific ground station, located on the Earth surface (for downlink data routing), and (b) pointing toward a companion satellite (for establishing an intersatellite connection). The two preceding operational requirements can both be formulated as attitude tracking problems. In this study, we use an inertia-free nonlinear attitude control algorithm based on rotation matrices and possessing remarkable stability properties, in conjunction with a pyramidal array of single-gimbal control momentum gyroscopes. Numerical simulations, in both nominal and nonnominal flight conditions, demonstrate that the attitude control architecture proposed in this work is effective for the purpose of performing agile attitude maneuvering, aimed at precise pointing during downlink and intersat data routing.

Theoretical investigation of electron capture processes in slow O7+–H collisions

Aims. The total and n-, l-, and S -resolved single-electron-capture cross sections for the collisions of O7+ with atomic hydrogen are studied in the energy region from 10−3eV u−1−5keV u−1. Methods. These state-selective cross sections were calculated by employing the full quantum-mechanical molecular-orbital close-coupling (QMOCC) method. The ab initio multireference single- and double-excitation configuration interaction approach, with optimized atomic basis sets to accurately describe the highly excited states, was used to obtain the adiabatic potentials and the radial and rotational coupling matrix elements that are required in the QMOCC calculation. Results. Our results are compared with other available theoretical and experimental data. The n = 5 manifold is the dominant reaction channel for the chasrge-transfer process for this collision system over the entire energy range, and our results agree better with the experimental data than the other theoretical results in the energy region in which they overlap because we included the necessary highly excited states in the expansion basis set. These charge-exchange cross-section data are useful for understanding and modeling the X-ray emission in astrophysical environments.

Research on radial velocity and airspace position calculations of target in airborne active radar simulation

The detection of the target in the airborne active radar simulation is simplified to the calculations of the radial velocity, the maximum detecting range of the airborne active radar corresponding to the RCS, and the airspace position of the target. However, the coordinate transformations related to the calculations of the radial velocity and the airspace position are usually bewildering due to the different referenced coordinate systems. This paper introduces the radial velocity and airspace position calculations of the target in the airborne active radar simulation to illuminate the transformation process containing the specific rotation matrices, suggesting the unifying transformation to the north-up-east (NUE) rectangular coordinate system of the aircraft for both the radial velocity calculation and airspace position calculation of the target.

Frailty in rheumatoid arthritis: prevalence, fenotype signs and associated factors

The aim – to establish the frequency of frailty and the ratio of its main phenotypic features in patients with rheumatoid arthritis (RA), as well as to identify associated factors. Material and methods. The study included 101 patients (86 women and 15 men) with RA at the age of 60 [52; 66] years; the average duration of the disease – 8 [3; 15] years. Frailty syndrome was diagnosed by the phenotypic model of L.P. Fried et al. In addition, the strength of the quadriceps femoris muscle was assessed using the test of getting up from a chair, functional status according to HAQ-DI (Health Assessment Questionnaire – Disability Index); Charlson comorbidity index, presence of cardiovascular disease (CVD); dementia severity and nutritional status. Factors associated with frailty were identified by the principal component method with the rotation of the correlation matrix using the Varimax raw method. Results. Frailty syndrome was detected in 40.6%, prefrailty in 55.4% of patients with RA, robust patients were 4.0%. The dominant signs of frailty in RA patients are reduced hand strength, fatigue, and weight loss. Four clusters of factors associated with frailty syndrome in RA have been identified: reduced hand strength, HAQ-DI impairment, and RA activity; reduced survival, comorbid cardiovascular disease and age; the total dose of glucocorticoids (GC) taken, an increase in walking time by 4 m and hypodynamia; eating disorders. Conclusion. Frailty and prefrailty dominate in patients with RA and have certain phenotypic features. Factors associated with frailty and it’s diagnostic features include impairment of vital activity, RA activity; premature mortality, CVD comorbidity, older age; taking GCS and malnutrition.

A Method for Measuring the Absolute Position and Attitude Parameters of a Moving Rigid Body Using a Monocular Camera

To verify the dynamic model of a paddy-field laser grader and solve the problem of the unstable high-speed operation of the grader, a method for measuring the absolute pose parameters of a moving rigid body using a monocular camera is proposed. The proposed method does not require calibration beforehand. Using more than six non-coplanar control points symmetrically arranged in the rigid-body and world coordinate systems, the matrices of rotation and translation between the camera and two coordinate systems are obtained and the absolute pose of the rigid body is measured. In this paper, formulas of the absolute pose measurement of a moving rigid body are deduced systematically and the complete implementation is presented. Position and attitude measurement experiments carried out on a three-axis precision turntable show that the average absolute error in the attitude angle of a moving rigid body measured by an uncalibrated camera at different positions changes by no more than 0.2 degrees. An analysis of the three-dimensional coordinate errors of the centroid of a moving rigid body shows little deviation in measurements taken at the three camera positions, with the maximum deviation of the average absolute error being 0.53 cm and the maximum deviation of the standard deviation being 0.66 cm. The proposed method can measure the absolute pose of a rigid body and is insensitive to the position of the camera in the measurement process. This work thus provides guidance for the repeated measurement of the absolute pose of a moving rigid body using a monocular camera.

Cavsiopy: a Python package to calculate and visualize spacecraft instrument orientation

Spacecraft attitude plays an important role in the observations of various atmospheric, planetary, and terrestrial parameters and phenomena that are of interest to the scientific community. Precise measurements from imagers, particle sensors, and antennas require accurate knowledge of instrument orientation. cavsiopy is an easy-to-install and use, light-weight open-source Python package for researchers who need to consider instrument pointing direction and observation geometry. cavsiopy contains the coordinate transformation routines and the corresponding rotation matrices from the spacecraft orbital reference frame (ORF) to any of the geocentric equatorial inertial for epoch J2000 (GEI J2K)/International Celestial Reference Frame (ICRF), Earth-centered, Earth-fixed (ECEF), International Terrestrial Reference Frame (ITRF), geodetic north-east-down, and geocentric north-east-center coordinate systems. Additionally, cavsiopy includes routines for importing Swarm-E ephemeris and generic two-line-element (TLE) data files; for the calculation of spacecraft azimuth, elevation, and orbital parameters; as well as for the 2D/3D visualization of the geometry between the instrument and the target. Functionality and utilization of cavsiopy for research problems are demonstrated with examples and visualizations for the Radio Receiver Instrument (RRI) and the Fast Auroral Imager (FAI) of e-POP/Swarm-E.