Simple Motion Research Articles

Teaching physics using Microsoft Excel-II

Conventional teaching is rapidly changing, and online and simulated software are adding up in teaching. Simulations on spreadsheets have become popular due to their ubiquitous and easily understandable. In this paper, we demonstrate three physics topics: the motion of a charged particle in a uniform magnetic field, the motion of a projectile, and the simple harmonic motion of a simple pendulum. The third example is a demonstration of an experiment on a simple pendulum to find the time period of a simple pendulum and study the amplitude’s effect on it. Students can perform the whole experiment on the spreadsheet in real-time.

Analysis of Undamped Free Vibration Parameters using GeoGebra

Through this article, a teaching methodology will be designed using a simulation in Geo Gebra, arose due to the need to contribute to the achievement of significant learning in the field of Mechanical Predictive Maintenance of the Industrial Maintenance Career at the Technological University of Xicotepec de Juárez, In this research, a teaching methodology was designed using a simulation in Geo Gebra since the university students could not understand the concepts about simple harmonic motion (MAS) as it is also known as undamped free vibration. Vibrations occur in systems that try to return to their state of rest or equilibrium when they are disturbed, or move away from their equilibrium state. It is about presenting how a simple harmonic motion problem was solved, highlighting the physical characteristics of the phenomenon. The current educational format has led teachers to use GeoGebra to analyze the behavior of some physical variables, proposing to students to interact with a simulation. With this it can be verified that, in relation to a simulation, it helps to facilitate the understanding of the concepts

Support Effect and Simulation Evaluation of Lifting Motion Using Non-Wearing Type Power Assist Device

One of the serious problems that Japan has been facing is its growing aging society, which causes a shortage of young workers in the nursing field to support care recipients and in other industries that require heavy labor. Many workers in these workplaces experience back pain. To reduce the burden on the lower back, the squat method is generally recommended when workers lift heavy objects. Many assist devices have been developed to reduce the burden on the body; however, most wearing type devices have difficulty performing the squat method owing to their mechanical constraints. In a previous study, we developed a non-wearing type pneumatic power assist device that considers the squat method and evaluated its support effects during a simple lifting motion. In this study, we developed a passive type assist device and a previously developed active type device and quantitatively evaluated their effectiveness in lifting motions. In addition, we analyzed muscle activity using a musculoskeletal simulator.

A Soft Reconfigurable Circulator Enabled by Magnetic Liquid Metal Droplet for Multifunctional Control of Soft Robots.

Integrated control circuits with multiple computation functions are essential for soft robots to achieve diverse complex real tasks. However, designing compliant yet simple circuits to embed multiple computation functions in soft electronic systems above the centimeter scale is still a tough challenge. Herein, utilizing smooth cyclic motions of magnetic liquid metal droplets (MLMD) in specially designed and surface-modified circulating channels, a soft reconfigurable circulator (SRC) consisting of three simple and reconfigurable basic modules is described. Through these modules, MLMD can utilize their conductivity and extreme deformation capabilities to transfer their simple cyclic motions as input signals to programmable electrical output signals carrying computing information. The obtained SRCs make it possible for soft robots to perform complex computing tasks, such as logic, programming, and self-adaptive control (a combination of programming and feedback control). Following, a digital logic-based grasping function diagnosis, a locomotion reprogrammable soft car, and a self-adaptive control-based soft sorting gripper are demonstrated to verify SRCs' capabilities. The unique attributes of MLMD allow complex computations based on simple configurations and inputs, which provide new ways to enhance soft robots' computing capabilities.

I3D Light - A Simple Motion Information Stream for I3D

Vision-based Human Activity Recognition (HAR) aims to recognize human activities based on the analysis of video data, and has extensive applications in modern industry and human life. Inflated 3D (I3D) is a deep learning architecture that is commonly used for action recognition by using two-stream video data: RGB stream and optical flow stream. I3D achieved great success on a variety of action recognition benchmarks. However, the use of optical flow incurs high computational cost, making the approach unsuitable for real-time applications. We propose an alternative simple motion information extractor to replace the optical flow branch and reduce the computational cost. It is a modified I3D that uses 128 frames of 112x112 images as input. The low spatial resolution and long temporal range of the proposed I3D RGB stream can reduce the spatial information and enhance the motion information. Experiments show that this simple motion stream can increase the accuracy of the original I3D spatial stream by 4.09% on the Kinetics 400 dataset.

Electric-driven flexible-roller nanoimprint lithography on the stress-sensitive warped wafer

Surface nanopatterning of semiconductor optoelectronic devices is a powerful way to improve their quality and performance. However, photoelectric devices’ inherent stress sensitivity and inevitable warpage pose a huge challenge on fabricating nanostructures large-scale. Electric-driven flexible-roller nanoimprint lithography for nanopatterning the optoelectronic wafer is proposed in this study. The flexible nanoimprint template twining around a roller is continuously released and recovered, controlled by the roller’s simple motion. The electric field applied to the template and substrate provides the driving force. The contact line of the template and the substrate gradually moves with the roller to enable scanning and adapting to the entire warped substrate, under the electric field. In addition, the driving force generated from electric field is applied to the surface of substrate, so that the substrate is free from external pressure. Furthermore, liquid resist completely fills in microcavities on the template by powerful electric field force, to ensure the fidelity of the nanostructures. The proposed nanoimprint technology is validated on the prototype. Finally, nano-grating structures are fabricated on a gallium nitride light-emitting diode chip adopting the solution, achieving polarization of the light source.

Vision-Based Real-Time Motion Estimation of Ground Vehicles from Aerial Imagery

This research presents vision-based maneuvering object motion estimation in case of occlusion. Unequal dimension Interactive Multiple Model (UDIMM) approach is applied to increase the motion prediction accuracy when no measurement is available. Current deep learning-based multi-object tracking algorithms cannot track the objects when an occlusion exists, even for quite a short time. The main reason is the motion model used in tracking algorithms. If the measurement coming from the object detector is not available, the prediction model propagates the Kalman Filter’s motion model. In this period, the object may maneuver or accelerate/decelerate so that the tracker cannot assign the tracklets successfully. Eventually, the ID switch occurs, and object tracking gets lost. Using the UDIMM approach, track loss due to the ID switch is highly reduced compared to the simple constant velocity motion model used in the StrongSort multi-object tracker algorithm. A two-dimensional simulation environment is created to compare the ground truth data with the estimation results. Performance results of different filters are compared.

3D printable resin/carbon nanotube composites for wearable strain sensors: Enhancing mechanical and electrical properties

Electrically conductive composite materials are widely used for several applications, particularly flexible strain sensors for wearable electronic devices to detect human motions or apply to soft robotic technologies. Among the carbon nanotube (CNT) composites for strain sensors, the CNT composites with polypyrrole (PPy) have been scarcely found for electromechanical property improvement via digital light processing (DLP) 3D printing. Thus, this research presents a 3D printing fabrication of flexible polyurethane/CNT/PPy (FPU/CNT/PPy) composites for high complexity and model specifications, particularly strain sensing. The FPU/CNT/PPy composites were prepared as photopolymer resin with various proportions of the three components. The composites successfully achieved a gauge factor of 91.9 at 20 percent strain with high durability in 100 stretching-releasing cycles. More than 85% of printing accuracy was also found under the DLP 3D printing method. The small deformation of the composites could be detected during the stretching-releasing process during time-dependent testing. Examples of simple human activity and complex spring motion could be successfully detected due to the high responsibility and reproducibility of the finger motion. The composites mentioned in this study could reach the field of strain sensing and can further be applied to other fields such as healthcare and soft robotics.

POE (Predict, Observe, Explain) Model-Based Teaching Materials on Simple Harmonic Motion with a Virtual/Real Laboratory

Referring to the problem of using conventional learning model and teaching material that were less supportive as learning sources, especially in the physics subject, this study aimed to develop POE (Predict, Observe, Explain) model-based teaching materials on simple harmonic motion with a virtual/real laboratory. The type of research used in this study was research and development based on Borg and Gall's framework, which consisted of five steps. The validation subjects consisted of physics lecturers at FMIPA UM, high school physics teachers, and fifteen students from SMA Laboratorium Malang. The research instruments used were an assessment questionnaire and a questionnaire for comments and suggestions. Data analysis techniques used quantitative data by calculating the average and qualitative analysis with suggestions or comments as the result of readability data. The results of validating the student and teacher teaching materials showed a result of 3.62 and 3.63 respectively, indicating that the materials were deemed feasible. The results of readability validation by students indicated that the students agreed that the concept map, material, and sample questions were easy to understand and did not cause double meanings. Therefore, the teaching materials are considered appropriate to be used as learning resources that support student learning and understanding of simple harmonic motion.

On the Kelvin–Voigt model in anisotropic viscoelasticity

We propose an anisotropic and nonlinear generalization of the Kelvin–Voigt viscoelastic model obtained considering the additive splitting of the Cauchy stress tensor in an elastic and a dissipative part. The former one corresponds to a fiber-reinforced hyperelastic material while the dissipative effect is described by the most general linear transverse-isotropic tensorial function of symmetric part of the velocity gradient. In a such a way we characterize the dissipative contribution via three viscoelastic moduli. We then show, by a detailed analysis of the simple shear quasistatic motion and the corresponding creep phenomena, that this motion may be used to determine experimentally the viscoelastic parameters.

How to measure and enhance the resilience of energy systems?

Resilience of energy system is the premise of sustainable economic development. However, the measurements and determinants of the resilience of energy systems are not well understood. To this end, our study first estimated the resilience of the energy systems of 50 countries/regions using a measure based on the simple harmonic motion theory and regime-switching vector autoregressive model. A panel regression was conducted to empirically study the determinants of the resilience of energy systems in 2008 and 2014. The results show that the resilience of energy systems is specific to energy-economy systems, and its determinants include energy diversity, infrastructure, research and development (R&D), and governance. Our findings can be insightful in developing policies to enhance the resilience of energy systems and promote sustainable economic development.

Optimization Design and Performance Analysis of a Bionic Knee Joint Based on the Geared Five-Bar Mechanism.

Animal joint motion is a combination of rotation and translational motion, which brings high stability, high energy utilization, and other advantages. At present, the hinge joint is widely used in the legged robot. The simple motion characteristic of the hinge joint rotating around the fixed axis limits the improvement of the robot's motion performance. In this paper, by imitating the knee joint of a kangaroo, we propose a new bionic geared five-bar knee joint mechanism to improve the energy utilization rate of the legged robot and reduce the required driving power. Firstly, based on image processing technology, the trajectory curve of the instantaneous center of rotation (ICR) of the kangaroo knee joint was quickly obtained. Then, the bionic knee joint was designed by the single-degree-of-freedom geared five-bar mechanism and the parameters for each part of the mechanism were optimized. Finally, based on the inverted pendulum model and the Newton-Euler recursive method, the dynamics model of the single leg of the robot in the landing stage was established, and the influence of the designed bionic knee joint and hinge joint on the robot's motion performance was compared and analyzed. The proposed bionic geared five-bar knee joint mechanism can more closely track the given trajectory of the total center of mass motion, has abundant motion characteristics, and can effectively reduce the power demand and energy consumption of the robot knee actuators under the high-speed running and jumping gait.

Convolutional Neural Network-Based Speckle Tracking for Ultrasound Strain Elastography: An Unsupervised Learning Approach

Accurate and computationally efficient motion estimation is a critical component of real-time ultrasound strain elastography (USE). With the advent of deep-learning neural network models, a growing body of work has explored supervised convolutional neural network (CNN)-based optical flow in the framework of USE. However, the above-said supervised learning was often done using simulated ultrasound data. The research community has questioned whether simulated ultrasound data containing simple motion can train deep-learning CNN models that can reliably track complex in vivo speckle motion. In parallel with other research groups' efforts, this study developed an unsupervised motion estimation neural network (UMEN-Net) for USE by adapting a well-established CNN model named PWC-Net. Our network's input is a pair of predeformation and postdeformation radio frequency (RF) echo signals. The proposed network outputs both axial and lateral displacement fields. The loss function consists of a correlation between the predeformation signal and the motion-compensated postcompression signal, smoothness of the displacement fields, and tissue incompressibility. Notably, an innovative correlation method known as the globally optimized correspondence (GOCor) volumes module developed by Truong et al. was used to replace the original Corr module to enhance our evaluation of signal correlation. The proposed CNN model was tested using simulated, phantom, and in vivo ultrasound data containing biologically confirmed breast lesions. Its performance was compared against other state-of-the-art methods, including two deep-learning-based tracking methods (MPWC-Net++ and ReUSENet) and two conventional tracking methods (GLUE and BRGMT-LPF). In summary, compared with the four known methods mentioned above, our unsupervised CNN model not only obtained higher signal-to-noise ratios (SNRs) and contrast-to-noise ratios (CNRs) for axial strain estimates but also improved the quality of the lateral strain estimates.

Development of Interactive Physics E-Book to Reduce Student Misconception

This research develops an interactive physics e-book to provide innovation in physics learning at schools. The purpose of the study was to determine the feasibility of a physics e-book on simple harmonic motion material, to determine the reduction of student misunderstandings after learning using e-books, and to determine the practicality of the e-books developed. This research uses research and development (R&D) methods with the research subjects of class X students. Based on learning innovations that have been carried out, it was concluded that e-book learning media has been developed to reduce student misunderstandings. E-book has been validated by 3 experts and the result are very good so it is suitable for use in learning. There is a reduction in student misunderstandings in modeling and implementation classes. The largest decrease occurred in the implementation class which was 11.00% while the modeling class was 9.00%. The e-books used successfully improved students' understanding by 18.00% in classroom modeling and 48.00% in implementation classes. The effectiveness of e-books in reducing student misconceptions belongs to the medium criteria in all classes. The practicality of e-books in modeling and implementation classes belongs to very good criteria.

Design, Modeling, and Control of a New Multi-Motion Mobile Robot Based on Spoked Mecanum Wheels.

This paper presents an exciting and meaningful design to make mobile robots capable of adapting to various terrains. We designed a relatively simple and novel composite motion mechanism called the flexible spoked mecanum (FSM) wheel and created a mobile robot, LZ-1, with multiple motion modes based on the FSM wheel. Based on the motion analysis of the FSM wheel, we designed an omnidirectional motion mode for this robot, allowing it to move flexibly in all directions and successfully traverse rugged terrains. In addition, we designed a crawl motion mode for this robot, which can climb stairs effectively. We used a multilayer control method to move the robot according to the designed motion modes. Multiple experiments showed that these two motion modes for the robot are effective on various terrains.

The Rüchardt experiment revisited: using simple theory, accurate measurement and python based data analysis

This project uses the Rüchardt experiment to determine the ratio of specific heats and hence the number of degrees of freedom f of different gases by measuring the frequency of damped simple harmonic motion where the gas provides the Hooke's law like spring of a cylinder–piston system. This project links mechanics, electromagnetism, thermodynamics, statistical mechanics and quantum mechanics making it an excellent synoptic experiment for a year 2 undergraduate student and we detail our implementation of this team-based learning project. We present, for the Rüchardt experiment, simple derivations of the main relationships that govern the experiment, a detailed data analysis of the physics of the apparatus and the experimental data. We find f(He) = 3.48 ± 0.14, f(N2) = 4.92 ± 0.24, f(Air) = 4.96 ± 0.25, f(CO2) = 6.46 ± 0.39 at room temperature and atmospheric pressure. The results for CO2 requires a statistical analysis of its vibrational modes. These results show that the expected results can be measured using fairly simple apparatus, coupled with careful analysis of large data sets.

E-Assistant for Paralyzed Patients using Internet of Things

There are lots of hospitals and clinics that serve paralytic patients who have their entire or part of their body disabled by the Paralysis attack. In most of the cases, these people are not able to convey their needs as they are neither able to talk properly nor do they convey through sign language due to loss in the motor control by their brain. Many innovations are developed to improve the quality of life. So, the aim of our system is to develop a system or a device which is easy to use and should also be affordable to all kind of people. It should also consist of a person’s basic health care monitoring system. This paper presents the development of an E-Assistant device for paralytic patients, aimed at improving their quality of life by providing an affordable and easy-to-use system that can monitor basic health care and assist in communicating their needs. The device uses simple motions, such as finger movements or angle-based controls, to enable patients to display messages. This device can be designed in such a way to be mounted on the back of their hands and their fingers, or other voluntary organ. The device has the potential to significantly improve the lives of paralytic patients by addressing their communication and healthcare needs. In this way the E-assistant for Paralyzed Patients automates the care taking ability of the patient which makes sure a healthy and periodic attention to the patient and thus results in a good health of the patient.

HFR-Video-Based Stereo Correspondence Using High Synchronous Short-Term Velocities.

This study focuses on solving the correspondence problem of multiple moving objects with similar appearances in stereoscopic videos. Specifically, we address the multi-camera correspondence problem by taking into account the pixel-level and feature-level stereo correspondences, and object-level cross-camera multiple object correspondence. Most correspondence algorithms rely on texture and color information of the stereo images, making it challenging to distinguish between similar-looking objects, such as ballet dancers and corporate employees wearing similar dresses, or farm animals such as chickens, ducks, and cows. However, by leveraging the low latency and high synchronization of high-speed cameras, we can perceive the phase and frequency differences between the movements of similar-looking objects. In this study, we propose using short-term velocities (STVs) of objects as motion features to determine the correspondence of multiple objects by calculating the similarity of STVs. To validate our approach, we conducted stereo correspondence experiments using markers attached to a metronome and natural hand movements to simulate simple and complex motion scenes. The experimental results demonstrate that our method achieved good performance in stereo correspondence.

How Pendular Is Human Brachiation? When Form Does Not Follow Function.

Brachiation is a form of suspensory locomotion observed only in Primates. The non-human hominoids (e.g., gibbons, orangutans, chimpanzees, and gorillas) are considered specialized brachiators, yet peculiar among the living apes are anatomically modern humans (Homo sapiens), who have forgone this locomotor mode in favor of bipedal striding. Humans can, however, brachiate and seem to have retained the locomotor capabilities of their arboreal ancestors. However, the mechanics of human brachiation have not been quantified. In this study, we evaluate how closely human brachiation conforms to the expectations of simple pendular motion using triaxial accelerometry and high-speed videography. These data are compared to specialized brachiating non-human primates. We found that humans have lower energy recovery than siamangs (Symphalangus syndactylus) during brachiation and have shorter observed pendular periods than expected compared to other primates. We demonstrate that relatively long forelimb length and high grip forces, a proxy for global forelimb force-generating potential, act as the main driving factors to reduce energetic costs through effective pendular recovery. These data are the first to assess the strategies humans adopt to perform a behavior they are not anatomically specialized to execute and places them within a comparative framework amongst other brachiating primates. We show that although humans demonstrate behavioral flexibility during brachiation (e.g., differing mediolateral and vertical center of mass positional movement patterns), anatomical features are the primary driver of variation in brachiation performance.

Numerical modelling of oil containment process under current and waves

This study presents a novel three-phase Fluid–Structure Interaction (FSI) model for simulating the containment of oil spills. The model uses Level Sets to capture the evolution of multiple interfaces and incorporates spring forces on the structure under hybrid wave–current boundary conditions. The implementation of spring forces has been validated through simple harmonic motion models and a wedge falling simulation demonstrates the model’s ability to handle multi-phase deformation. The study compares numerical results with experimental data to study the response of oil spills to wave–current hybrid conditions. Our simulations reveal that when the current exceeds 0.2 m/s, the movement of the boom is dominated by the current and not by the waves or their inertia, providing important information for the design of effective oil spill containment systems.