Characteristic-based Method Research Articles

Optimising virtual object position for efficient eye-gaze interaction in Hololens2

ABSTRACT Our study explored eye-tracking technology in the Hololens2 HMD. We assessed the effectiveness of eye-gaze interactions in a 3D environment, particularly in text entry applications. Existing recommendations for the placement and size of virtual objects are often followed without empirical validation. Therefore, we evaluated text entry target selection rates within the manufacturer’s specified optimal gaze interaction zone. We measured the spatial accuracy and precision of eye gaze data and optimised target positions for enhanced text entry performance. By establishing confidence ellipses covering 95% of gaze points per target, we derived an Area of Interest (AOI) recalibration function. Applying a receiver operating characteristic-based method, we quantified the recalibrated tracker’s performance at various AOIs. Our results indicate an optimal recalibrated AOI radius is 0.036 m, and the ideal object-plane distance from the eye-plane is 2.25 m. This recalibrated specification allows to efficiently interact with Hololens2 via eye movement, achieving target selection rates exceeding 90%.

Enhancing user experience in home networks with machine learning-based classification

With the rapid development of mobile Internet, home broadband has been integrated into people's daily lives, and the market has become increasingly saturated. User experience and broadband quality have become the key factors determining market competitiveness, and consequently, most operators currently are increasing attention to network quality issues and how to improve user experience. This paper proposes an efficient machine learning model to accurately evaluate home user network experiences. The dataset used encompasses network indicator data from 500 anonymized users, and presents a set of formidable challenges including a non-standard sampling rate and time range, an uneven distribution of observations, multiple recorded observations for identical timestamps, a constrained sample size, a subjective definition of Internet experience, and a lack of essential information regarding the data collection setup. Our novel time series characteristic-based method extracts thousands of descriptive statistics from the time series sequences which reveal that, even in the face of the dataset's inherent complexities, our proposed method excels, achieving an impressive 67% validation accuracy. This represents a substantial 3% enhancement over the performance of conventional models on this dataset. Furthermore, we explore the potential of a Recurrent Neural Network (RNN) model, which also yields promising results with a validation accuracy of 58%. It is important to underscore that the performance of the RNN model could be substantially enhanced with a larger dataset. [...]

Radiation transport methods in star formation simulations

Radiation transport plays a crucial role in star formation models, as certain questions within this field cannot be accurately addressed without taking it into account. Given the high complexity of the interstellar medium from which stars form, numerical simulations are frequently employed to model the star formation process. This study reviews recent methods for incorporating radiation transport into star formation simulations, discussing them in terms of the used algorithms, treatment of radiation frequency dependence, the interaction of radiation with the gas, and the parallelization of methods for deployment on supercomputers. Broadly, the algorithms fall into two categories: i) moment-based methods, encompassing the flux-limited diffusion approximation, M1 closure, and variable Eddington tensor methods, and ii) methods directly solving the radiation transport equation, including forward and reverse ray tracing, characteristics-based methods, and Monte Carlo techniques. Beyond discussing advantages and disadvantages of these methods, the review also lists recent radiation hydrodynamic codes implemented the described methods.

Pooled Minimal Clinically Important Differences of the Mini-Balance Evaluation Systems Test in Patients With Early Subacute Stroke: A Multicenter Prospective Observational Study.

Balance problems are common in patients with stroke, and the Mini-Balance Evaluation Systems Test (Mini-BESTest) is a reliable and valid assessment tool for measuring balance function. Determining the minimal clinically important difference (MCID) is crucial for assessing treatment effectiveness. This study aimed to determine the MCID of the Mini-BESTest in patients with early subacute stroke. In this prospective multicenter study, 53 patients with early subacute stroke undergoing rehabilitation in inpatient units were included. The mean age of the patients was 72.6 (SD = 12.2) years. The Mini-BESTest, which consists of 14 items assessing various aspects of balance function, including anticipatory postural adjustments, postural responses, sensory orientation, and dynamic gait, was used as the assessment tool. The global rating of change (GRC) scales completed by the participants and physical therapists were used as external anchors to calculate the MCID. The GRC scale measured subjective improvement in balance function, ranging from -3 (very significantly worse) to +3 (very significantly better), with a GRC score of ≥+2 considered as meaningful improvement. Four methods were used to calculate the MCID: mean of participants with GRC of 2, receiver operating characteristic-based method, predictive modeling method, and adjustment of the predictive modeling method based on the rate of improvement. From the MCID values obtained using these methods, a single pooled MCID value was calculated. The MCID values for the Mini-BESTest obtained through the 4 methods ranged from 3.2 to 4.5 points when using the physical therapist's GRC score as the anchor but could not be calculated using the participant's GRC score. The pooled MCID value for the Mini-BESTest was 3.8 (95% CI = 2.9-5.0). The Mini-BESTest MCID obtained in this study is valuable for identifying improvements in balance function among patients with early subacute stroke. Determination of the MCID is valuable for evaluating treatment effectiveness. The study findings provide clinicians with practical values that can assist in interpreting Mini-BESTest results and assessing treatment effectiveness.

Multimedia information retrieval using artificial neural network

<span lang="EN-US">The importance of the multimedia information retrieval (MIR) is highlighted by the extensive amount of the information on the internet. Image, audio, video, and text are all examples of the characteristics of the raw multimedia data. It is greatly challenging to represent a concept of human perception and how the machine-level language can grasp it (semantic gap of MIR). However, this paper aims to improve the information retrieval model that retrieves data from multimedia. This can be implemented by leveraging the use of variety of algorithms that go through training and testing to extract the model. One of these algorithms extracts text information based on the query language's nature as the vector space model (VSM) and the latent semantic index (LSI) were used. The other technique uses curvelet decomposition and statistic parameters like mean, standard deviation, and signal energy to recover these properties. Additionally, a discrete wavelet transforms (DWT) and signal characteristics-based method is used to retrieve audio signals. Finally, the neural network learning is modeled and trained on a collection of different multimedia images. The learned features have been utilized for presenting a highly sufficient system of multimedia retrieval which operates for a large set of multi-modal datasets. </span>

Continuous Rotor Position Estimation for SRM Based on Transformed Unsaturated Inductance Characteristic

In this letter, a transformed unsaturated inductance characteristic-based method is proposed for the rotor position of the switched reluctance machine. Due to the magnetic saturation effect, the phase inductance characteristics have a narrow linear region, which increases the difficulty of their analytical expression. To reduce the complexity of the analytical expression, the unsaturated inductance characteristic is transformed from the phase inductance characteristics. Then, a linear model is presented to explicitly describe the relationship between the rotor position and unsaturated phase inductance. Experimental verification is carried out to verify the effectiveness and accuracy of the proposed method. The proposed method can serve as a low-effort way to provide the accurate rotor position for the industry application at medium and high-speed ranges.

A Strong-Form Off-Lattice Boltzmann Method for Irregular Point Clouds

Radial basis function generated finite differences (RBF-FD) represent the latest discretization approach for solving partial differential equations. Their benefits include high geometric flexibility, simple implementation, and opportunity for large-scale parallel computing. Compared to other meshfree methods, typically based upon moving least squares (MLS), the RBF-FD method is able to recover a high order of algebraic accuracy while remaining better conditioned. These features make RBF-FD a promising candidate for kinetic-based fluid simulations such as lattice Boltzmann methods (LB). Pursuant to this approach, we propose a characteristic-based off-lattice Boltzmann method (OLBM) using the strong form of the discrete Boltzmann equation and radial basis function generated finite differences (RBF-FD) for the approximation of spatial derivatives. Decoupling the discretizations of momentum and space enables the use of irregular point cloud, local refinement, and various symmetric velocity sets with higher order isotropy. The accuracy and computational efficiency of the proposed method are studied using the test cases of Taylor–Green vortex flow, lid-driven cavity, and periodic flow over a square array of cylinders. For scattered grids, we find the polyharmonic spline + poly RBF-FD method provides better accuracy compared to MLS. For Cartesian node layouts, the results are the opposite, with MLS offering better accuracy. Altogether, our results suggest that the RBF-FD paradigm can be applied successfully also for kinetic-based fluid simulation with lattice Boltzmann methods.

A Diagnosis Method of Implementation State Management in Large-Scale Construction Projects

In the diagnosis researches on the implementation status of construction engineering projects (CEP), two major problems remain unsolved yet by far. On one hand, there is not a scientific approach to extract and determine the diagnosis indicators for the implementation status. On the other hand, it still lacks an effective method to analyze and diagnose the implementation status. As an improvement, in this paper these two problems are studied respectively. According to the three required conditions for the implementation status diagnosis, the determination approach based on quantitative scoring for the index setup is firstly presented. All of the indicators are transformed and standardized into the range value forms within [0,1]. Then, the recursive analysis method and model of the diagnosis indicators, which combines the model-based method together with the characteristic based method at the meantime, is proposed, and the grading judgment standards for the implementation status of CEP are presented based on the windage principle. Finally, an indemnificatory housing project which contains 21 residential buildings is taken for a case study to validate the proposed method. It is shown that the proposed method is able to effectively obtain the actual implementation status of large-scale construction projects and find out the exact problems as well as the targeted measures.

Sensitivity Analysis on Thermal Performance of Gas Heater with Finned and Finless Tubes using Characteristics-based Method

Natural gas must be preheated to prevent phase change and gas hydrate in pressure reduction stations. This paper aims to investigate the effect of the fins of gas tubes and their configuration, arrangement, and shape on the heat transfer and thermal efficiency of gas. To conduct a parametric study, two tube cases with fins and without fins, and in the finned case for the fin’s configuration, two longitudinal and circular arrangements, and the formation of the fins, two solid and interrupted forms were analyzed. Also, three types of cross-sections, including rectangular, convergent parabolic, and divergent parabolic, for the shape of the fins have been studied. For this simulation, the three-dimensional, incompressible, and steady flow was considered, and for analysis and discretization of convective heat equations, the characteristic-based method was applied. FORTRAN software was also used to implement and solve the equations. The results show that in solid and interrupted fins and increasing the number of fins in parallel, the dimensionless heat transfer coefficient increases. Also, the dimensional heat transfer coefficient decreases with increasing the ratio of fin height to the tube’s diameter. Also, the most significant heat transfer improvement was related to the divergent parabolic cross-section.

Thermo-flow Analysis of Cylinder with Crossed Splitter Plates with a Characteristics-based Scheme

In the present work, the laminar flow through a circular cylinder with two crossed splitter plates is analyzed. The characteristic-based method has been used along with the unstructured grid. The current research has been done to detect the proper conditions according to the geometrical parameters in which the optimal heat transfer is taking place. Geometric control parameters are the angle of splitter plates (\theta) and the ratio of length of the splitter plate to cylinder radius (n=L/D). It was found that the use of a two-branched splitter plate is not wise in Reynolds number less than 100 due to its insignificant effect in flow properties. In angle 30° between two plates, the least drag force is witnessed with respect to other angles. Application of double branched splitter with angles more than 60° is not recommended, which will increase the total drag significantly. Since the splitter plate increases, the overall heat transfer from the cylinder and splitter set is enhanced. Minimum drag over the cylinder, and maximum convection drop from it is taken place when the dimension length is 0.75. Between dimensionless lengths 1.25 and 1.5, the Nusselt number oscillates with least amplitude and such behavior is also observed when two splitters are 60°apart.

Hybrid Plasma Simulations of Farley‐Buneman Instabilities in the Auroral E‐Region

AbstractWe implemented a hybrid continuous solver for fluid electrons and kinetic ions. Because the simulation is continuous, numerical noise is not an issue as it is for particle‐in‐cell approaches. Moreover, given that the ion kinetic equation is solved using a characteristic based method, no particle pushes have to be done. Our main goals are to reduce the computational cost of the simulations proposed by Kovalev (Kovalev et al., 2008, https://doi.org/10.5194/angeo2628532008) and reproduce the main experimental features of Farley‐Buneman instabilities measured by radars and rockets. The equations were derived from first principles using the approximations that are satisfied in the auroral E‐region. Various tests will be presented to assess numerical accuracy. With the proposed numerical framework, we are able to recover important nonlinear features associated with Farley‐Buneman instabilities: wave turning of dominant modes, and saturation of density irregularities at values consistent with experiments.

An improved non-reflecting outlet boundary condition for weakly-compressible SPH

Implementation of an outlet boundary condition is challenging in the context of the weakly-compressible Smoothed Particle Hydrodynamics method. We perform a systematic numerical study of several of the available techniques for the outlet boundary condition. We propose a new hybrid approach that combines a characteristics-based method with a simpler frozen-particle (do-nothing) technique to accurately satisfy the outlet boundary condition in the context of wind-tunnel-like simulations. In addition, we suggest some improvements to the do-nothing approach. We introduce a new suite of test problems that make it possible to compare these techniques carefully. We then simulate the flow past a backward-facing step and circular cylinder. The proposed method allows us to obtain accurate results with an order of magnitude less particles than those presented in recent research. We provide a completely open source implementation and a reproducible manuscript.

Maintainability improvement using allocation methods for railway system

An optimal maintenance policy is an essential condition of many industrial products in order to save resources and to minimize operational costs and system downtime. Some maintenance actions (e.g.CM, PM and CBM) are illustrated in the first part of the paper. The paper focuses on maintainability allocation techniques: four procedures are analyzed (Failure Rate-based allocation method; Trade-off of failure rate and design feature-based allocation method; Fuzzy maintainability allocation based on interval analysis; Time characteristic-based MA model). The traditional procedures are characterized by several drawbacks; therefore the attention is focalized on the time characteristic-based method, which turned out to be the best and the most complete procedure because it exceeds the others methods limitations. The last part of the paper proposes a case study analyzed using the techniques implemented in the MA optimal method. Two different cases are studied: they differ for the objective Mean Time To Repair, initially the requirement could vary inside a range, then it is fixed to the value 6 hours.

A Characteristic-based Numerical Simulation of Water-titanium Dioxide Nano-fluid in Closed Domains

A new characteristic-based method is developed and used for solving the mixed and forced convection problems. The nano-fluid flow with heat transfer is simulated with a novel characteristic-based scheme in closed domains with different aspect ratios. For this purpose, a FORTRAN code has been written and developed. Water as a pure fluid and water-titanium dioxide as a nano-fluid were considered. The governing equations are solved by the finite volume utilizing a characteristic-based scheme for the convective fluxes. The simulation is done at Grashof numbers from 100 to 104, Reynolds numbers from 100 to 1000, and volume fractions of nano-particles from 0% to 10%. Streamlines, isotherms, friction factor, and mean Nusselt number are obtained in various conditions. The convective behavior of nano-fluid is explored as a function of several parameters, such as Grashof number and geometrical parameters. Results indicate that the mean Nusselt number for the nanofluid is up to 23% more than that of pure water.

A Systematic Literature Review of Android Malware Detection Using Static Analysis

Android malware has been in an increasing trend in recent years due to the pervasiveness of Android operating system. Android malware is installed and run on the smartphones without explicitly prompting the users or without the user's permission, and it poses great threats to users such as the leakage of personal information and advanced fraud. To address these threats, various techniques are proposed by researchers and practitioners. Static analysis is one of these techniques, which is widely applied to Android malware detection and can detect malware quickly and prohibit malware before installation. To provide a clarified overview of the latest work in Android malware detection using static analysis, we perform a systematic literature review by identifying 98 studies from January 2014 to March 2020. Based on the features of applications, we first divide static analysis in Android malware detection into four categories, which include Android characteristic-based method, opcode-based method, program graph-based method, and symbolic execution-based method. Then we assess the malware detection capability of static analysis, and we compare the performance of different models in Android malware detection by analyzing the results of empirical evidence. Finally, it is concluded that static analysis is effective to detect Android malware. Moreover, there is a preliminary result that neural network model outperforms the non-neural network model in Android malware detection. However, static analysis still faces many challenges. Thus, it is necessary to derive some novel techniques for improving Android malware detection based on the current research community. Moreover, it is essential to establish a unified platform that is used to evaluate the performance of a series of techniques in Android malware detection fairly.

Study on distributed lithium-ion power battery grouping scheme for efficiency and consistency improvement

The service life, safety, and capacity of lithium-ion power battery packs relies heavily on the consistency among battery cells. Grouping is an effective procedure to improve consistency by screening cells with similar performance and assembling them into an identical group. Battery grouping can be achieved via clustering techniques based on characteristics like static capacity, internal resistance etc. The dynamic characteristics-based method considers the battery performance during the entire charging-discharging process and has become one of the most promising grouping method. However, it suffers from high computational complexity. Nowadays, facing stricter quality standards and the increasing demand for battery products, existing dynamic characteristics-based grouping scheme cannot meet the performance and time requirement of the modern high-quality, large-scale battery manufacturing. In this paper, a novel grouping scheme based on distributed time-series clustering is proposed to match the need of both efficiency and consistency improvement. The proposed scheme designs an effective cloud-edge mode and utilizes an innovative two-stage trick to achieve parallel processing, which split the original centralized clustering approach into local clustering and global merging. The host computers for data acquisition and battery control are regarded as distributed edge computing resources to implement local clustering on the acquired battery discharging voltage sequence set. Cluster contours are extracted via a denoising contour extraction algorithm considering the irregularity of the discharging voltage sequences. The results of the above preliminary processing are uploaded to a cloud data center. A pragmatic merging scheme based on an integrated merging indicator is established to solve the decision-making problem of global merging on the cloud data center. The final global cluster set is transmitted back to host computers to instruct cell unloading operation. Experimental results based on real battery discharging voltage sequence data suggest that the proposed scheme can reduce the inconsistency rate by 43.56% and the time cost by 92.87%. The computing efficiency and resource utilization rate of the distributed scheme is much higher than the centralized scheme. Meanwhile, compared with three existing advanced grouping approaches, our scheme perform the best in reducing inconsistency rate. (C) 2019 Published by Elsevier Ltd.

Defining No Pain, Mild, Moderate, and Severe Pain Based on the Faces Pain Scale-Revised and Color Analog Scale in Children With Acute Pain.

The aims of this study were to define the Faces Pain Scale-Revised (FPS-R) and Color Analog Scale (CAS) scores associated with no pain, mild pain, moderate pain, and severe pain in children with acute pain, and to identify differences based on age, sex, and ethnicity. We conducted a prospective observational study in 2 pediatric emergency departments of children aged 4 to 17 years with painful and nonpainful conditions. We assessed their pain intensity using the FPS-R, CAS, and qualitative measures. Pain score cut points that best differentiated adjacent categories of pain were identified using a receiver operating characteristic-based method. Cut points were compared within subgroups based on age, sex, and ethnicity. We enrolled 620 patients, of whom 314 had painful conditions. The mean age was 9.2 years; 315 (50.8%) were in the younger age group (aged 4-7 years); 291 (46.8%) were female; and 341 (55%) were Hispanic. The scores best representing categories of pain for the FPS-R were as follows: no pain, 0 and 2; mild pain, 4; moderate pain, 6; and severe pain, 8 and 10. For the CAS, these were 0 to 1, 1.25 to 2.75, 3 to 5.75, and 6 to 10, respectively. Children with no pain frequently reported nonzero pain scores. There was considerable overlap of scores associated with mild and moderate pain. There were no clinically meaningful differences of scores representing each category of pain based on age, ethnicity, and race. We defined pain scores for the FPS-R and CAS associated with categories of pain intensity in children with acute pain that are generalizable across subgroups based on patient characteristics. There were minor but potentially important differences in pain scores used to delineate categories of pain intensity compared to prior convention.

Pseudo-characteristic upwind scheme for incompressible flows

For enhancing the performance of the characteristic-based method, the multidimensional characteristics of incompressible flows are applied for developing a novel efficient bicharacteristic-based method. The multidimensionality of information propagation is embedded in the convective flux computation by the directional derivatives along the bicharacteristics in conjunction with the cross derivative. The well-known benchmark problems (i.e. the cross flow around a circular cylinder, the lid-driven cavity flow, and the flow around a sphere) are solved to validate the proposed scheme in the presence of strong multidimensional interaction of separated vortical flow. The results represent significant consensus with the benchmark solutions. Furthermore, the proposed scheme results in significantly faster convergence and higher resolution in comparison with the characteristic-based method.

Unconditional stability and error estimates of modified characteristics FEMs for the Navier–Stokes equations

The paper is concerned with the unconditional stability and convergence of characteristics type methods for the time-dependent Navier---Stokes equations. We present optimal error estimates in $$L^2$$L2 and $$H^1$$H1 norms for a typical modified characteristics finite element method unconditionally, while all previous works require certain time-step restrictions. The analysis is based on an iterated characteristic time-discrete system, with which the error function is split into a temporal error and a spatial error. With a rigorous analysis to the characteristic time-discrete system, we prove that the difference between the numerical solution and the solution of the time-discrete system is $$\tau $$?-independent, where $$\tau $$? denotes the time stepsize. Thus numerical solution in $$W^{1,\infty }$$W1,? is bounded and optimal error estimates can be obtained in a traditional way. Numerical results confirm our analysis and show clearly the unconditional stability and convergence of the modified characteristics finite element method for the time-dependent Navier---Stokes equations. The approach used in this paper can be easily extended to many other characteristics-based methods.

Numerical analysis of single pad of thrust bearing with the energy equation solved by the characteristic-based split method

The solution of the energy equation of thermo-elasto-hydrodynamic analysis for bearings by the finite element method usually leads to convergence difficulties due to the presence of convection terms inherited from the Navier–Stokes equations. In this work, the numerical analysis is performed with finite element method universally by adopting the characteristic-based split method to solve the energy equation. Five case studies of fixed pad thrust bearings have been set up with different geometries, loads, and lubricants. The two-dimensional film pressure is obtained by solving the Reynolds equation with pre-defined axial load on the pad. The energy equation of the lubricant film and the heat transfer equation of the bearing pad are handled by characteristic-based split method and conventional finite element method in three-dimensional space, respectively. Hot oil carry-over effect and variable lubricant viscosity are considered in the simulations. The results of the temperature distributions in the lubricant film and the bearing pad are presented. The possible usability of characteristic-based split method for future thermo-elasto-hydrodynamic analysis is discussed.