Mechanical movement data acquisition method based on the multilayer neural networks and machine vision in a digital twin environment

Background: Digital twin requires virtual reality mapping and optimization iteration between physical devices and virtual models. The mechanical movement data collection of physical equipment is essential for the implementation of accurate virtual and physical synchronization in a digital twin environment. However, the traditional approach relying on PLC (programmable logic control) fails to collect various mechanical motion state data. Additionally, few investigations have used machine visions for the virtual and physical synchronization of equipment. Thus, this paper presents a mechanical movement data acquisition method based on multilayer neural networks and machine vision. Methods: Firstly, various visual marks with different colors and shapes are designed for marking physical devices. Secondly, a recognition method based on the Hough transform and histogram feature is proposed to realize the recognition of shape and color features respectively. Then, the multilayer neural network model is introduced in the visual mark location. The neural network is trained by the dropout algorithm to realize the tracking and location of the visual mark. To test the proposed method, 1000 samples were selected. Results: The experiment results shows that when the size of the visual mark is larger than 6mm, the recognition success rate of the recognition algorithm can reach more than 95%. In the actual operation environment with multiple cameras, the identification points can be located more accurately. Moreover, the camera calibration process of binocular and multi-eye vision can be simplified by the multilayer neural networks. Conclusions: This study proposes an effective method in the collection of mechanical motion data of physical equipment in a digital twin environment. Further studies are needed to perceive posture and shape data of physical entities under the multi-camera redundant shooting.

APPLICATION OF EDUCATIONAL ROBOTICS IN THE PEDAGOGICAL PROCESS

Educational robotics and its trends determine the innovative and creative educational context. This article discusses the current issues of rethinking educational robotics. Attention is focused on the potential for expanding the capabilities of educational robotics and the pedagogical capacity building of intelligent technologies in this area. Examples of the introduction of robotics in education, namely in physics and computer science classes, based on the Lego Education and Arduino are considered. Specific topics for the physics teachers are presented in the following section:" Mechanical movement "based on Lego;" Sound and sound waves. Speed wave", "Theory of electrical circuits" based on electronic components. For computer science teachers-programming on the Arduino IDE and drawing diagrams based on the Sprint Layout 6.0 program are offered. At the same time, the article can be a prototype for the application of educational robotics in other disciplines and the implementation of interdisciplinary connections.

Biomechanical Properties of Bone and Mucosa for Design and Application of Dental Implants

Dental implants’ success comprises their proper stability and adherence to different oral tissues (integration). The implant is exposed to different mechanical stresses from swallowing, mastication and parafunctions for a normal tooth, leading to the simultaneous mechanical movement and deformation of the whole structure. The knowledge of the mechanical properties of the bone and gingival tissues in normal and pathological conditions is very important for the successful conception of dental implants and for clinical practice to access and prevent potential failures and complications originating from incorrect mechanical factors’ combinations. The challenge is that many reported biomechanical properties of these tissues are substantially scattered. This study carries out a critical analysis of known data on mechanical properties of bone and oral soft tissues, suggests more convenient computation methods incorporating invariant parameters and non-linearity with tissues anisotropy, and applies a consistent use of these properties for in silico design and the application of dental implants. Results show the advantages of this approach in analysis and visualization of stress and strain components with potential translation to dental implantology.

Development of nonmotorized mechanisms for lower limb rehabilitation

This paper concerns with the development of three nonmotorized individual lower limb joints rehabilitation mechanisms based on a four-bar linkage, and mechanical movement transmission from the motion of the patient’s upper limb. Initially, mathematical and computational models are built based on the desired angular motions for the hip, knee, and ankle. A prototype for the knee mechanism was constructed for initial experimental tests. The first test with wooden mannequin show that this prototype is lightweight, has an output movement compatible with the amplitudes, is easy to build and operate, being thus ready for clinical tests with healthy and impaired subjects.

Aggression in the Workplace Makes Social Distancing Difficult

Background: The coronavirus disease (COVID-19) is still spreading. While social distancing has attracted attention as a measure to prevent the spread of infection, some occupations find it difficult to practice it. Therefore, we decided to investigate the differences in the ease of practicing social distancing depending on the occupation using the data on O*NET, an occupational information site.Methodology: Eight factors were extracted by performing exploratory factor analysis based on certain rules while eliminating arbitrariness as much as possible: adverse conditions, leadership, information processing, response to aggression, mechanical movement, autonomy, communication with the outside, and horizontal teamwork.Results: Adverse conditions, response to aggression, and horizontal teamwork had a positive correlation with physical proximity, while information processing, mechanical movement, autonomy, and communication with the outside had a negative correlation with it. Furthermore, multiple regression analysis showed that response to aggression, not just teamwork, as assumed in previous studies, had the greatest influence on physical proximity.Conclusion: To maintain social distancing, it is necessary to constrain aggression in the workplace.

Experimental Verification of General Validity of Non-force Interaction Formula

In the present work, the physical and mathematical principles of the non-force interaction theory are presented. It is shown that in the basis of this theory there are computer experiments within which there was simulated movement and interaction of material objects through the change of their hypothetical informational contents. The formulae of transformation of the hypothetical informational contents of material objects received from the information-probabilistic interpretation of mechanical movement were used in the experimental research to demonstrate that they also correspond to the processes of speech production in a human brain. The hypothesis, objective and tasks of the experimental research were defined. The methods and software tools were developed to conduct the experiments. To compare different results of the simulation of the processes in a human brain during speech production, there was a range of methods proposed to calculate the estimate of sequence of fragments of natural language texts including the methods based on linear approximation. The conducted experiments have proved that the formulae received from information-probabilistic interpretation of mechanical movement reflect the processes of speech production. It is shown that the offered approach can successfully be used to create systems of reactive artificial intelligence machines. Experimental and, presented in this work, practical results constitute that the non-force (informational) interaction formulae are generally valid.

Gaussian-preserved, non-volatile shape morphing in three-dimensional microstructures for dual-functional electronic devices

Motile plant structures such as Mimosa pudica leaves, Impatiens glandulifera seedpods, and Dionaea muscipula leaves exhibit fast nastic movements in a few seconds or less. This motion is stimuli-independent mechanical movement following theorema egregium rules. Artificial analogs of tropistic motion in plants are exemplified by shape-morphing systems, which are characterized by high functional robustness and resilience for creating 3D structures. However, all shape-morphing systems developed so far rely exclusively on continuous external stimuli and result in slow response. Here, we report a Gaussian-preserved shape-morphing system to realize ultrafast shape morphing and non-volatile reconfiguration. Relying on the Gaussian-preserved rules, the transformation can be triggered by mechanical or thermal stimuli within a microsecond. Moreover, as localized energy minima are encountered during shape morphing, non-volatile configuration is preserved by geometrically enhanced rigidity. Using this system, we demonstrate a suite of electronic devices that are reconfigurable, and therefore, expand functional diversification.

Experimental Verification of General Validity of Non-force Interaction Formula

In the present work, the physical and mathematical principles of the non-force interaction theory are presented. It is shown that in the basis of this theory there are computer experiments within which there was simulated movement and interaction of material objects through the change of their hypothetical informational contents. The formulae of transformation of the hypothetical informational contents of material objects received from the information-probabilistic interpretation of mechanical movement were used in the experimental research to demonstrate that they also correspond to the processes of speech production in a human brain. The hypothesis, objective and tasks of the experimental research were defined. The methods and software tools were developed to conduct the experiments. To compare different results of the simulation of the processes in a human brain during speech production, there was a range of methods proposed to calculate the estimate of sequence of fragments of natural language texts including the methods based on linear approximation. The conducted experiments have proved that the formulae received from information-probabilistic interpretation of mechanical movement reflect the processes of speech production. It is shown that the offered approach can successfully be used to create systems of reactive artificial intelligence machines. Experimental and, presented in this work, practical results constitute that the non-force (informational) interaction formulae are generally valid.

Developing Global Relevant Skills in the Fourth Industrial Revolution

This chapter carries out extensive review of literature on the 4th Industrial Revolution. In the last decades, many stakeholders such as industries, governments, employers and employers' organisations, workers and their unions, and academics have expressed divergent opinion of the 4th Industrial Revolution. The 4th industrial revolution is the 4th stage of a mechanical movement process that began towards the end of the 18th century where mechanised production replaced manual production process. Research shows that the 4th Industrial Revolution brought about ‘disruptive technologies' such as artificial intelligence, robotics, blockchain, and 3D printing, which transforms social, economic, and political systems, often in unpredictable ways.