Computer Simulation Experiments Research Articles

Launching a meteorological rocket as an instructive object of computer simulation in the school informatics course

Since the first Russian school textbook on computer science edited by A. P. Ershov and V. M. Monakhov came out in 1985, the subject of “Computer simulation and computer experiment” has been explored through the simulation of physical processes unfolding in time and accessible to direct observation in many textbooks on Informatics. For such processes, the idea of temporal discretization can be introduced visually with the help of the videotaping metaphor. Russian Informatics textbooks examined a small oscillation of a load on a spring, water flowing out of a cubic tank, a fall of a person without a parachute (“delayed jump”) in the atmosphere considering air resistance as well as the flight of a small object thrown by a person disregarding air resistance as physical processes simulated by computer programs. These examples are informative, but they do not contain any unobvious conclusions that cannot be reached without computer simulation. The article suggests a more attractive simulation object for the school Informatics course, namely the process of vertical takeoff of a one-stage rocket delivering scientific equipment to the upper air of the Earth and the adjacent near-Earth space. Such rockets are called meteorological. The proposed computer simulation object is good because computer experiments with a developed model make it possible to obtain new results. These include designing a rocket whose maximum lift height paradoxically grows with an increase in the payload as well as showing that the lift height of one-stage meteorological rockets could be significantly increased if we only learned to stop the rocket engine for a few seconds during acceleration.

A new visual-guided and partition-based multi-setup 3D printing system

Additive manufacturing, also known as 3D printing, has become a powerful and versatile means of manufacturing for almost any applications in our daily lives. A frequently encountered problem in printing, particular in consumer or lower-end applications, is how to print a workpiece whose dimensions exceed the working space of the printer at hand. Rather than opting for the costly solution of getting a new and larger printer (and hence more expensive and also other induced hassles), a more plausible solution would be an algorithmic one, which is the objective of this paper. We present a partition-based multi-setup printing process planning algorithm that, given the CAD model of an oversized workpiece, will be able to determine a continuous printing path with multiple workpiece setups to correctly print out the workpiece on the same printer. To answer the challenge of workpiece localization during the change of workpiece setups in the middle of printing, we propose a visual-guided workpiece localization system. Both computer simulation and physical printing experiments are carried out, and the results give a positive confirmation on the feasibility and effectiveness of the proposed multi-setup printing methodology and our enabling printing process planning algorithm.

A red thermally activated delayed fluorescence emitter based on benzo[c][1,2,5]thiadiazole

Herein, a series of materials (BTD-PXZ, BTD-PTZ, and BTD-DMAC) were designed and synthesized with the merit of the facile synthesis process, high synthesis yield, and small molecular weight through directly connecting electron donor to position 5 of benzo[c][1,2,5]thiadiazole (BTD) rather than adopting extensive conjugated structure strategy. The thermally activated delayed fluorescence property of BTD-PXZ was proven and the photophysical characteristics were discussed through the single crystal, computational simulation, and photophysical experiments. The doped organic light-emitting diode with the BTD-PXZ as the emissive layer shows an emitting peak of 620 nm, Commission Internationale de L'Eclairage coordinate of (0.65, 0.25), and external quantum efficiency of 2.4%.

Comparative Effects of Computer-Simulated Strategy and Real Laboratory Experiment on Students’ Achievement and Retention in Electricity Practical

The study investigated the comparative effects of computer-simulated strategy and real laboratory experiment on students’ achievement and retention in electricity practical. Quasi-experimental design of the pre-test, post-test, post-post-test, non-equivalent control group design was used for the study. The study was guided by 2 research questions and 2 null hypotheses. The hypotheses were tested at 0.05 level of significance. Two intact classes were randomly selected, one of which was the control group and the other experimental group. The experimental group was taught using Computer-Simulated Experiment (CSE)while the control group was taught using Real Laboratory Experiment (RLE/ conventional method). The instrument of data collection was Electricity Practical Achievement Test (EPAT). EPAT was reshuffled for post-post-test and named Electricity Practical Retention Test (EPRT). The reliability coefficient of EPAT was computed using Spearman-Brown’s prophecy formula and was found to be 0.78. The instrument was validated by 3 experts. Data collected were analyzed using mean, standard deviation and analysis of covariance (ANCOVA). The findings of the study revealed that the students taught electricity practical using CSE achieved and retained better than those taught using RLE. One of the recommendations is that teachers should adopt CSE in teaching physics practical.

A cross-spectral target tracking method based on a hidden Markov model

Aiming at the problem of target tracking stability in the case of low signal-to-noise ratio and multi-target cross-motion, this paper combines the hidden Markov model and complementary tracking and proposes a new automatic tracking method. The stability of the new algorithm is proved by theoretical analysis and computer simulation experiments. In the case of low signal-of-noise ratio and multi-target cross-motion, the new algorithm has good performance.

Backstepping CBF Design for Collision Avoidance of Electric Wheelchair

To avoid collisions, human assist control based on a control barrier function (CBF) attracts attentions in recent years. A lot of human assist control method have been proposed, particularly using a relaxed CBF and a strict zeroing CBF (SZCBF). However, to design CBFs is still a difficult task. Hence in this study, we propose a method to design a SZCBF via transformation of a control Lyapunov function (CLF) derived by the backstepping. The effectiveness of the human assist control using the SZCBF is confirmed by computer simulation and actual experiments using an electric wheelchair.

UAV-Based P-Band SAR Tomography With Long Baseline: A Multimaster Approach

Due to the advantage of flexible and rapid deployment, unmanned aerial vehicle (UAV)-based synthetic aperture radar (SAR) tomography (TomoSAR) is a promising technology in 3-D urban mapping. The long baseline is indispensable for P-band SAR systems to achieve high elevation resolution. It will introduce two problems. On the one hand, the unavoidable spatial decorrelation brings serious phase noise and sidelobes in 3-D imaging. On the other hand, the noticeable image distortion fails the image registration and the TomoSAR data stack (TDS) construction. Aiming at the above problems, this article proposes a multimaster (MM) TomoSAR approach via three main contributions. First, the traditional TomoSAR signal model is extended to the MM case to improve the number of baselines and the average image coherence of the TDS and suppress the sidelobes. Second, a short-baseline-recursion image registration method is proposed to achieve high-precision image registration. Third, a TDS optimization processing consisting of interferometric SAR (InSAR) phase screening and baseline sign reassignment is introduced. Moreover, a clustering-based outliers’ elimination method is also adopted to ensure the 3-D imaging quality. Computer simulation and long-baseline P-band UAV-SAR experiment validate the proposed approach.

DOA Estimation Method in Echo-localization Ability for Human-beings

The principle of echo-localization processing of human beings is quite similar with animals like bats and dolphins, which has been widely applied in sonar. Direction of Arrival (DOA) methods plays an important role in estimating the radar, sonar and many other echo-localization communication fields. Typical methods in resolving echo-localization problems including classical (Multiple Signal Classification) MUSIC, (Estimation of Signal Parameter via Rotational Invariance Technique), ESPRIT and compressed sensing. The echo-localization methods and the resolving ambiguity methods via uniform array are systematically introduced in this paper. On this basis, the fast and accurate algorithms for human-being echo-localization in parameter (azimuth angle, elevation angle and range) estimation of signal are further introduced from time domain and frequency domain. The accuracy of the angle and distance estimation of the algorithm calculated by computer simulation experiment is over 99.9% and 97% respectively. The effectiveness of DOA method was verified according to MUSIC algorithm, which provides a rapid and accuracy information in echo-localization ability of human being.

Class-associative multiple target recognition for highly compressed color images in a joint transform correlator

We propose a practical near real-time compression-based class-associative multiple target detection technique for color images. The size of the color images is reduced to its utmost ratio to speed up the processing time and to increase the storage capacity of the recognition system. A fringe-adjusted joint transform correlation technique is employed to successfully detect the compression-based multiple targets in colored images. In addition, to eliminate the false alarms and zero-order terms due to multiple desired and undesired objects in an input scene, we have used the shifted phase-encoded and the reference phase-encoded techniques. The performance of detecting the class-associative multiple targets for large compression ratios (up to 94%) and under strong noisy conditions (Gaussian and salt and pepper noises) is assessed through many computer simulations experiments. Furthermore, detecting small targets or even a small part of a target is presented for images occluded up to 90%.

A 2D-GRAPPA Algorithm with a Boomerang Kernel for 3D MRI Data Accelerated along Two Phase-Encoding Directions

For the reconstruction of 3D MRI data that are accelerated along the two phase-encoding directions, the 2D-generalized autocalibrating partially parallel acquisitions (GRAPPA) algorithm can be used to estimate the missing data in the k-space. We propose a new boomerang-shaped kernel based on theoretic and systemic analyses of the shape and dimensions of the kernel. The reconstruction efficiency of the 2D-GRAPPA algorithm with the proposed boomerang-shaped kernel (i.e., boomerang kernel (BK)-2D-GRAPPA) was compared with other 2D-GRAPPA algorithms that utilize different types of kernels (i.e., EX-2D-GRAPPA and SK-2D-GRAPPA) based on computer simulation, phantom and in vivo experiments. The proposed method was validated for different sets of ACS lines with acceleration factors from four to eight and various sizes of the kernels. A quantitative analysis was also performed by comparing the normalized root mean squared error (nRMSE) in the images and the undersampled edges. Computer simulation, in vivo and phantom experiments, and the quantitative analysis, showed that the proposed method could reduce aliasing artifacts without reducing the SNRs of the reconstructed images.

Potential Universal Engineering Component: Tetracycline Response Nanoswitch Based on Triple Helix-Graphene Oxide.

The overuse of antibiotics can lead to the emergence of drug resistance, preventing many common diseases from being effectively treated. Therefore, based on the special composite platform of P1/graphene oxide (GO) and DNA triple helix, a programmable DNA nanoswitch for the quantitative detection of tetracycline (TC) was designed. The introduction of GO as a quenching agent can effectively reduce the background fluorescence; stabilizing the trigger strand with a triplex structure minimizes errors. It is worth mentioning that the designed model has been verified and analyzed by both computer simulation and biological experiments. NUPACK predicts the combined mode and yield of each strand, while visual DSD flexibly predicts the changes in components over time during the reaction. The feasibility analysis preliminarily confirmed the realizability of the designed model, and the optimal reaction conditions were obtained through optimization, which laid the foundation for the subsequent quantitative detection of TC, while the selective experiments in different systems fully demonstrated that the model had excellent specificity.

Information theoretic performance evaluation of 3D integral imaging.

Integral imaging (InIm) has proved useful for three-dimensional (3D) object sensing, visualization, and classification of partially occluded objects. This paper presents an information-theoretic approach for simulating and evaluating the integral imaging capture and reconstruction process. We utilize mutual information (MI) as a metric for evaluating the fidelity of the reconstructed 3D scene. Also we consider passive depth estimation using mutual information. We apply this formulation for optimal pitch estimation of integral-imaging capture and reconstruction to maximize the longitudinal resolution. The effect of partial occlusion in integral imaging 3D reconstruction using mutual information is evaluated. Computer simulation tests and experiments are presented.

Continuum Manipulator With Rigid-Flexible Coupling Structure

Pneumatic-driven soft manipulator has great flexibility and adaptability, which makes it can do some complex tasks that traditional robots can't do such as minimally invasive surgery, detection, search and rescue, et al. However, due to the low stiffness of pneumatic-drive soft manipulator, it faces some problems such as poor load ability and vibration, and the structural flexibility of the soft manipulators make the kinematics modeling complicated. To solve these problems, in this letter, we proposed a novel structure of continuum manipulator that couples with rigid and flexible structure, i.e., rigid-flexible coupling manipulator (RFCM). The RFCM consists of three modules, each containing a rotating unit and a bending unit, so that the RFCM can move flexibly in the workspace. Compared with the purely soft manipulators, RFCM has higher stiffness, and the unique driving structure enables it to have simpler control logic. In addition, we proposed an inverse kinematic solver based on numerical optimization to deal with the redundant problem of continuum manipulators. Preliminary experiments in both computer simulation and physical demonstration of RFCM are conducted, and the proposed kinematics algorithm can effectively establish the mapping from workspace to joints space for RFCM.

The study on high temperature exhaust orifice infrared suppression

A type of gas turbine generator unit has lots of advantages, such as small size, light weight, advanced technical performance, strong environment adaptability, rapid start. However, the high temperature exhaust gas generated during the operation of the machine leads to the high temperature and obvious infrared radiation characteristics near the exhaust port. The objective of this paper is to investigate the infrared suppression of the exhaust orifice of the gas turbine generator unit. Meanwhile, some schemes about infrared suppression are proposed, that is, redesigning the exhaust cover or adding grid regenerator of high temperature phase change materials(HTPCMs). The method of computer simulation experiment, relying on Gambit and Fluent for modeling, is used to demonstrate the feasibility of the scheme. Results indicate that the first enrichment of gas turbine exhaust heat can be completed and the exhaust temperature can be reduced by about 200°C when the grid is set as a three-layer pattern crisscrossed up and down.

Feasibility of epidural temporal interference stimulation for minimally invasive electrical deep brain stimulation: simulation and phantom experimental studies

Objective. Temporal interference stimulation (TIS) has shown the potential as a new method for selective stimulation of deep brain structures in small animal experiments. However, it is challenging to deliver a sufficient temporal interference (TI) current to directly induce an action potential in the deep area of the human brain when electrodes are attached to the scalp because the amount of injection current is generally limited due to safety issues. Thus, we propose a novel method called epidural TIS (eTIS) to address this issue; in this method, the electrodes are attached to the epidural surface under the skull. Approach. We employed finite element method (FEM)-based electric field simulations to demonstrate the feasibility of eTIS. We first optimized the electrode conditions to deliver maximum TI currents to each of the three different targets (anterior hippocampus, subthalamic nucleus, and ventral intermediate nucleus) based on FEM, and compared the stimulation focality between eTIS and transcranial TIS (tTIS). Moreover, we conducted realistic skull-phantom experiments for validating the accuracy of the computational simulation for eTIS. Main results. Our simulation results showed that eTIS has the advantage of avoiding the delivery of TI currents over unwanted neocortical regions compared with tTIS for all three targets. It was shown that the optimized eTIS could induce neural action potentials at each of the three targets when a sufficiently large current equivalent to that for epidural cortical stimulation is injected. Additionally, the simulated results and measured results via the phantom experiments were in good agreement. Significance. We demonstrated the feasibility of eTIS, facilitating more focalized and stronger electrical stimulation of deep brain regions than tTIS, with the relatively less invasive placement of electrodes than conventional deep brain stimulation via computational simulation and realistic skull phantom experiments.

Determination of growth exponent for percolating clusters of various lattices

A computer simulation experiment has been carried out near the critical region of percolation clusters of various lattices. This certain growth exponent/spreading velocity exponent has been determined by put on the scaling theory on this percolating cluster near the critical region (i.e., P = Pc ). This exponent is named in a different way in not the same context. Owing to this enormous usage of this exponent to the real physical system, we focus our attention to find this exponent. The value of this exponent is determined for the normal conducting lattices like square, triangular & honey comb and superconducting Ortho I phase & Ortho II phase for different lattice dimensions. From the experiment it is detected that, if the concentration of the site occupancy increases, the spreading velocity or the value of growth exponent is also increases naturally. All the values are found to be less than one, indicating large spreading nature or growth nature physically as per the scaling laws. From our experiments it is found to be the exponent values fall between 0.2 and 0.5 for all lattice dimensions irrespective of lattice type.

A Novel Artificial Visual System for Motion Direction Detection in Grayscale Images

How specific features of the environment are represented in the mammalian brain is an important unexplained mystery in neuroscience. Visual information is considered to be captured most preferentially by the brain. As one of the visual information elements, motion direction in the receptive field is thought to be collected already at the retinal direction-selective ganglion cell (DSGC) layer. However, knowledge of direction-selective (DS) mechanisms in the retina has remained only at a cellular level, and there is a lack of complete direction-sensitivity understanding in the visual system. Previous studies of DS models have been limited to the stage of one-dimensional black-and-white (binary) images or still lack biological rationality. In this paper, we innovatively propose a two-dimensional, eight-directional motion direction detection mechanism for grayscale images called the artificial visual system (AVS). The structure and neuronal functions of this mechanism are highly faithful to neuroscientific perceptions of the mammalian retinal DS pathway, and thus highly biologically reasonable. In particular, by introducing the horizontal contact pathway provided by horizontal cells (HCs) in the retinal inner nuclear layer and forming a functional collaboration with bipolar cells (BCs), the limitation that previous DS models can only recognize object motion directions in binary images is overcome; the proposed model can solve the recognizing problem of object motion directions in grayscale images. Through computer simulation experiments, we verified that AVS is effective and has high detection accuracy, and it is not affected by the shape, size, and location of objects in the receptive field. Its excellent noise immunity was also verified by adding multiple types of noise to the experimental data set. Compared to a classical convolutional neural network (CNN), it was verified that AVS is completely significantly better in terms of effectiveness and noise immunity, and has various advantages such as high interpretability, no need for learning, and easy hardware implementation. In addition, activation characteristics of neurons in AVS are highly consistent with those real in the retinal DS pathway, with strong neurofunctional similarity and brain-like superiority. Moreover, AVS will also provide a novel perspective and approach to understanding and analyzing mechanisms as well as principles of mammalian retinal direction-sensitivity in face of a cognitive bottleneck on the DS pathway that has persisted for nearly 60 years.

Neural excitatory rebound induced by valproic acid may predict its inadequate control of seizures

SummaryBackgroundValproic acid (VPA) represents one of the most efficient antiseizure medications (ASMs) for both general and focal seizures, but some patients may have inadequate control by VPA monotherapy. In this study, we aimed to verify the hypothesis that excitatory dynamic rebound induced by inhibitory power may contribute to the ineffectiveness of VPA therapy and become a predictor of post-operative inadequate control of seizures.MethodsAwake craniotomy surgeries were performed in 16 patients with intro-operative high-density electrocorticogram (ECoG) recording. The relationship between seizure control and the excitatory rebound was further determined by diagnostic test and univariate analysis. Thereafter, kanic acid (KA)-induced epileptic mouse model was used to confirm that its behavior and neural activity would be controlled by VPA. Finally, a computational simulation model was established to verify the hypothesis.FindingsInadequate control of seizures by VPA monotherapy and post-operative status epilepticus are closely related to a significant excitatory rebound after VPA injection (rebound electrodes≧5/64, p = 0.008), together with increased synchronization of the local field potential (LFP). In addition, the neural activity in the model mice showed a significant rebound on spike firing (53/77 units, 68.83%). The LFP increased the power spectral density in multiple wavebands after VPA injection in animal experiments (p < 0.001). Computational simulation experiments revealed that inhibitory power-induced excitatory rebound is an intrinsic feature in the neural network.InterpretationDespite the limitations, we provide evidence that inadequate control of seizures by VPA monotherapy could be associated with neural excitatory rebounds, which were predicted by intraoperative ECoG analysis. Combined with the evidence from computational models and animal experiments, our findings suggested that ineffective ASMs may be because of the excitatory rebound, which is mediated by increased inhibitory power.FundingThis work was supported by National Natural Science Foundation of China (62127810, 81970418), Shanghai Municipal Science and Technology Major Project (2018SHZDZX03) and ZJLab; Science and Technology Commission of Shanghai Municipality (18JC1410403, 19411969000, 19ZR1477700, 20Z11900100); MOE Frontiers Center for Brain Science; Shanghai Key Laboratory of Health Identification and Assessment (21DZ2271000); Shanghai Shenkang (SHDC2020CR3073B).

Partition-based 3 + 2-axis tool path generation for freeform surface machining using a non-spherical tool

Abstract When machining a complex freeform part, using a non-spherical tool could significantly improve the machining efficiency, as one can adaptively adjust the tool posture to maximize its contact area with the part surface. However, since adjusting the tool posture requires changing the tool orientation, a five-axis machine tool is needed, which is extremely expensive as compared to a conventional three-axis machine tool. Moreover, for a complex freeform surface with high curvature variation, to match its curvature change, the tool axis has to drastically change accordingly, thus inducing high velocity and acceleration on the machine tool’s rotary axes. To address these issues, in this paper we propose a partition-based 3 + 2-axis strategy for machining a general complex freeform surface with a non-spherical tool. As only a finite small number of distinct tool orientations are needed for 3 + 2-axis machining, an indexed three-axis machine tool suffices, thus relieving the need of an expensive five-axis machine tool. In addition, the much-increased rigidity of the three linear axes of the machine tool will greatly improve the kinematics and dynamics of the machine tool and thus enhance the machining accuracy. Experiments in both computer simulation and physical machining are carried out, whose results confirm that, when compared to using a conventional spherical cutter, by using a non-spherical cutter and adaptively adjusting the contacting tool posture and the feed direction, significant improvement in machining efficiency could be achieved, e.g., more than 50% achieved in our experiments.

Examining the trade-offs in potential retail benefits of different expiration date modes: Insights into multidimensional scenarios

A significant challenge in today's food system is variable and unknown food quality affected by various temperatures, resulting in unreliable fixed expiration dates (FED) printed on food packaging. The dynamic expiration date (DED) mode is proposed as an alternative to the FED mode; however, practitioners must guard against some major uncertainties when setting expiration dates (shelf life) for fresh food. As such, we firstly developed a computer-simulated experiment based on a shelf life prediction model for multiple scenarios (i.e., fresh food's initial quality, quality change rate, and shelf temperature) to evaluate potential retail benefits of both date modes. The results show that the DED mode is a promising approach; yet a significant difference in retail benefits emerged between the DED and FED modes. On the one hand, the DED mode could reduce food waste by 10.02% at low temperatures (0−8 °C), but it may increase food waste by 15.94% and 31.71% under the temperature abuse conditions of 12−18 °C and 20−28 °C, respectively. On the other hand, the expired food sold rate within the FED mode is influenced by shelf temperatures, quality change rate, and initial quality of fresh foods. A one-at-a-time perturbation analysis finds that fresh food's shelf life associated with food quality is particularly sensitive to the food waste rate and expired food sold rate in both date modes. This study supports the trade-offs in retail benefits between the two modes while encouraging retailers to proactively optimize DED use.