Development of dual-arm mobile robot platform based on ROS

Background: With the increasing demand of mobile robots in warehousing, logistics and service fields, simple planar motion is difficult to meet the task requirements of complex environment. The combination of mobile robot and cooperative robot is helpful to improve the dexterity of robot movement and expand the application of robots. Methods: Aiming at the application requirements of dual-arm robots and mobile robots in practical applications, this paper designed the hardware of a platform, built a simulation platform based on ROS (Robot Operating System), and designed the actual software control framework. Finally, the feasibility of the platform design was verified by the coupling motion experiment of the two robots. Results: We have established a simulation of the dual-arm mobile platform in ROS, designed the actual software control framework, and verified the feasibility of the platform design through experiments. Conclusions: The mobile platform can meet a variety of application requirements and lay the foundation for subsequent development.

Digital Image Art Style Transfer Algorithm and Simulation Based on Deep Learning Model

In order to solve the problems of poor region delineation and boundary artifacts in Indian style migration of images, an improved Variational Autoencoder (VAE) method for dress style migration is proposed. Firstly, the Yolo v3 model is used to quickly identify the dress localization of the input image, and then the classical semantic segmentation algorithm (FCN) is used to finely delineate the desired dress style migration region twice, and finally the trained VAE model is used to generate the migrated Indian style image using a decision support system. The results show that, compared with the traditional style migration model, the improved VAE style migration model can obtain finer synthetic images for dress style migration, and can adapt to different Indian traditional styles to meet the application requirements of dress style migration scenarios. We evaluated several deep learning based models and achieved BLEU value of 0.6 on average. The transformer-based model outperformed the other models, achieving a BLEU value of up to 0.72.

Terahertz meta-chip switch based on C-ring coupling

Terahertz switch is one of the key components of future communication, radar, and imaging systems. Limited by the strong electromagnetic coupling in subwavelength scale, the traditional terahertz switch is difficult to meet the increasing application requirements. In this paper, a parallel topology terahertz meta-chip switch based on the combination of equivalent circuit theory and electromagnetic coupling is proposed. The meta-chip is realized by adjusting the density of two-dimensional electron gas of InP-HEMT, which converts the electromagnetic coupling between the microstructure and microstrips. By using the 90 nm gate length InP-HEMT process, a C-ring loaded meta-chip is fabricated and tested in this paper. The results show an insertion loss lower than 1 dB with a 10 dB switching ratio, which is 20% higher than that without C-ring while ensuring the rather low insertion loss. It shows that the presented mechanism has positive significance for the design of terahertz band functional devices.

Adaptive Deep Rider LSTM-enabled Objective Functions for RPL routing in IoT applications

This paper presents a proposed Objective Function (OF) design using various routing metrics for improving the performance of IoT applications. The most important idea of the proposed design is the selection of the routing metrics with respect to the application requirements. The various metrics, such as Energy, Distance, Delay, Link quality, Trust (EDDLT) are used for improving the objective function design of the RPL in various IoT applications. Here, the Adaptive Deep rider LSTM is newly employed for the energy prediction where the Adaptive Deep Rider LSTM is devised by the combination of the adaptive theory with the Rider Adam Algorithm (RAA), and the Deep-Long Short Memory (Deep-LSTM). However, the evaluation of the proposed method is carried out energy dissipation, throughput, and delay by achieving a minimum energy dissipation of 0.549, maximum throughput of 1, and a minimum delay of 0.191, respectively.

One Health and Information Management Using Big Data in Health

In an increasingly connected world, information regarding the contagion and spread of COVID-19 has been an important weapon to enable better coping with the disease. The use of information technology can assist in the prevention, care, and monitoring of patients. In addition, remote service using applications avoids the overload of health centers and contagion. This research reports the experience of a research project initiated in Brazil at the Oswaldo Cruz Foundation, with the objective of developing an application and big data for the new coronavirus in a public health clinic using information management and One Health concepts. Initially, the application requirements were defined through interviews with users and health professionals. The partial results obtained so far demonstrate improvements in the different processes of the health center with the use of the application. The use of big data for the analysis of information makes it possible to define better health policies for the population in a more precise way and in a shorter time.

Forgetting in Answer Set Programming – A Survey

Forgetting – or variable elimination – is an operation that allows the removal, from a knowledge base, of middle variables no longer deemed relevant. In recent years, many different approaches for forgetting in Answer Set Programming have been proposed, in the form of specific operators, or classes of such operators, commonly following different principles and obeying different properties. Each such approach was developed to address some particular view on forgetting, aimed at obeying a specific set of properties deemed desirable in such view, but a comprehensive and uniform overview of all the existing operators and properties is missing. In this article, we thoroughly examine existing properties and (classes of) operators for forgetting in Answer Set Programming, drawing a complete picture of the landscape of these classes of forgetting operators, which includes many novel results on relations between properties and operators, including considerations on concrete operators to compute results of forgetting and computational complexity. Our goal is to provide guidance to help users in choosing the operator most adequate for their application requirements.

Plant Factory: A New Playground of Industrial Communication and Computing

Plant Factory is a newly emerging industry aiming at transforming crop production to an unprecedented model by leveraging industrial automation and informatics. However, today’s plant factory and vertical farming industry are still in a primitive phase, and existing industrial cyber-physical systems are not optimal for a plant factory due to diverse application requirements on communication, computing and artificial intelligence. In this paper, we review use cases and requirements for future plant factories, and then dedicate an architecture that incorporates the communication and computing domains to plant factories with a preliminary proof-of-concept, which has been validated by both academic and industrial practices. We also call for a holistic co-design methodology that crosses the boundaries of communication, computing and artificial intelligence disciplines to guarantee the completeness of solution design and to speed up engineering implementation of plant factories and other industries sharing the same demands.

A Hierarchical Integrated Modeling Method for the Digital Twin of Mechanical Products

With the development of information and communication technology, massive amounts of data are generated during the entire lifecycle of mechanical products. However, their isolated and fragmented state hinders further empowerment of smart manufacturing. Digital twins have attracted considerable attention as they enable a user to rebuild all elements of a physical entity in a virtual space, targeted at the effective fusion of data from multiple sources with different formats, while its modeling method still needs further research. In this context, we propose a native, full-element digital twin modeling method for mechanical products. This ontology-based method establishes a unified and computer-understandable model framework for mechanical products by abstracting the essential content and relationships of data and by storing them in a graph database efficiently. The developed model could serve as a data center for the entire lifecycle of the product or could be combined with existing data management systems, integrating the previously isolated, fragmented, and scattered data on various platforms. In addition, the model utilizes the structural characteristics of mechanical products and is developed as a hierarchical digital mapping to better meet the application requirements. Finally, a case study of a helicopter digital twin is presented to verify the proposed method.

Lightweight, Secure, Similar-Document Retrieval over Encrypted Data

Applications for document similarity detection are widespread in diverse communities, including institutions and corporations. However, currently available detection systems fail to take into account the private nature of material or documents that have been outsourced to remote servers. None of the existing solutions can be described as lightweight techniques that are compatible with lightweight client implementation, and this deficiency can limit the effectiveness of these systems. For instance, the discovery of similarity between two conferences or journals must maintain the privacy of the submitted papers in a lightweight manner to ensure that the security and application requirements for limited-resource devices are fulfilled. This paper considers the problem of lightweight similarity detection between document sets while preserving the privacy of the material. The proposed solution permits documents to be compared without disclosing the content to untrusted servers. The fingerprint set for each document is determined in an efficient manner, also developing an inverted index that uses the whole set of fingerprints. Before being uploaded to the untrusted server, this index is secured by the Paillier cryptosystem. This study develops a secure, yet efficient method for scalable encrypted document comparison. To evaluate the computational performance of this method, this paper carries out several comparative assessments against other major approaches.

Electrostatic Zipping Actuators—Analysis of the Pull-In Effect Depending on the Geometry Parameters

Continuous work on a new generation of actuators, referred to as artificial muscles, resulted in the initiation of work on electrostatic zipping actuators, the concept of which is derived from micro electro-mechanical devices. Despite partial knowledge of their basic operating parameters, a question remains whether electrostatic zipping actuators are able to meet the expectations in the context of generated forces and control possibilities. In order to get closer to the answer to this question, the authors of this work created a solution method using FEM, which allowed them to conduct a series of concentric contraction tests of the desired solution. In addition to the basic features of the actuators tested, such as their length, thickness and width, for the first time the size of the weld surface, to which the loading force was applied, was taken into account. The results of the investigations show the possibility of adjusting the supply voltage range to the application requirements, but most importantly, they present the variability of the pull-in strain parameter. In extreme configurations, its value increases from ~10% to ~26%. The results obtained emphasize the need for further analysis of electrostatic zipping actuators using FEM. It will make it possible to precisely define the characteristics of this technology as well as its limits. These activities will provide the ultimate answer to the potential of electrostatic zipping actuators as artificial muscles.