Operator Interface Research Articles

Special Issue on Robotic, Mechatronic and Information Systems for Decommissioning

The Fukushima Daiichi Nuclear Power Plant accident, triggered by the Great East Japan Earthquake and the tsunami, has had a major impact on societies across the world. The subsequent focus on decommissioning efforts has attracted worldwide attention. It has been consistently asserted since the aftermath of the accident that the decommissioning of the Fukushima Daiichi Nuclear Power Plant will take approximately 30 to 40 years. The promotion of decommissioning work means that we will continue to face the problems with uncertainties in the work, as sometimes referred to as Unknown Unknowns. Typical elemental technologies required in remotely operated robotic systems for decommissioning include mobile mechanisms and their control, handling mechanisms and their control, information communication, operation interface (information presentation and command input), shielding (radiation resistance) and so on. Although many tasks using remotely operated robotic systems have been carried out with noteworthy results, there are lingering issues yet to be clarified. To ensure the safe and effective execution of various types of decommissioning tasks over a period of several decades, continuous research and development of each elemental technology are imperative, and these technologies must be integrated into a system appropriately to the assumed tasks. In addition, human resource development and the transfer of knowledge and experience are also important issues. From such viewpoint, this special issue is titled “Robotic, Mechatronic and Information Systems for Decommissioning.” It contains papers and development reports on robotics, mechatronics, information processing, and information systems technologies relevant to decommissioning work. It also features recent activities of nuclear emergency response organizations. We hope this special issue will acquaint readers with the latest research and development results and organizational activities related to decommissioning. At the same time, we hope that we were able to provide readers interested in robots, mechatronics, and information technology with an opportunity to become aware of the issues and necessary perspectives related to decommissioning and nuclear disasters. Lastly, we would like to thank the editorial board of the Journal of Robotics and Mechatronics, the editorial team of Fuji Technology Press, and the reviewers for their support in the planning and publication of this special issue. Their dedicated efforts are deeply appreciated.

Development and Flight Testing of Guidance, Navigation, Control, and Operator Interface for Shipboard Helicopter Operations

Unmanned Aircraft Systems (UASs) have become increasingly important assets for naval and maritime law enforcement operations. In response to the ever-increasing demand for autonomous systems, this paper presents a design, development, integration, and flight testing of an unmanned rotorcraft system capable of operating with a moving ship. The system was developed initially by playing back ship motion data in a simulation environment. Ship motion prediction, relative guidance, operator control interface, and landing flight management system were developed and tested against simulated sea state motion. The system was then flight tested using a 15-kg electric helicopter operating off a US Naval Academy’s yard patrol craft. The craft was instrumented with IMU and GPS for the craft’s own state estimation. The craft was also used as a moving-base station for Real-time Kinematic (RTK) relative positioning. The flight operation was done in the Chesapeake Bay. Autonomous capabilities including takeoff, landing, station-keeping, and maneuvering relative to a moving ship were successfully demonstrated.

Enhancing MPI remote memory access model for distributed-memory systems through one-sided broadcast implementation

Efficiently processing vast and expanding data volumes is a pressing challenge. Traditional high-performance computers, utilizing distributed-memory architecture and a message-passing model, grapple with synchronization issues, hampering their ability to keep up with the growing demands. Remote Memory Access (RMA), often referred to as one-sided MPI communications, offers a solution by allowing a process to directly access another process’s memory, eliminating the need for message exchange and significantly boosting performance. Unfortunately, the existing MPI RMA standard lacks a collective operation interface, limiting efficiency. To overcome this constraint, we introduce an algorithm design that enables efficient parallelizable collective operations within the RMA framework. Our study focuses primarily on the advantages of collective operations, using the broadcast algorithm as a case study. Our implementations surpass traditional methods, highlighting the promising potential of this technique, as indicated by initial performance tests.

Flan: An Expressive and Efficient Datalog Compiler for Program Analysis

Datalog has gained prominence in program analysis due to its expressiveness and ease of use. Its generic fixpoint resolution algorithm over relational domains simplifies the expression of many complex analyses. The performance and scalability issues of early Datalog approaches have been addressed by tools such as Soufflé through specialized code generation. Still, while pure Datalog is expressive enough to support a wide range of analyses, there is a growing need for extensions to accommodate increasingly complex analyses. This has led to the development of various extensions, such as Flix, Datafun, and Formulog, which enhance Datalog with features like arbitrary lattices and SMT constraints. Most of these extensions recognize the need for full interoperability between Datalog and a full-fledged programming language, a functionality that high-performance systems like Soufflé lack. Specifically, in most cases, they construct languages from scratch with first-class Datalog support, allowing greater flexibility. However, this flexibility often comes at the cost of performance due to the conflicting requirements of prioritizing modularity and abstraction over efficiency. Consequently, achieving both flexibility and compilation to highly-performant specialized code poses a significant challenge. In this work, we reconcile the competing demands of expressiveness and performance with Flan, a Datalog compiler fully embedded in Scala that leverages multi-stage programming to generate specialized code for enhanced performance. Our approach combines the flexibility of Flix with Soufflé’s performance, offering seamless integration with the host language that enables the addition of powerful extensions while generating specialized code for the entire computation. Flan’s simple operator interface allows the addition of an extensive set of features, including arbitrary aggregates, user-defined functions, and lattices, with multiple execution strategies such as binary and multi-way joins, supported by different indexing structures like specialized trees and hash tables, with minimal effort. We evaluate our system on a variety of benchmarks and compare it to established Datalog engines. Our results demonstrate competitive performance and speedups in the range of 1.4× to 12.5× compared to state-of-the-art systems for workloads of practical importance.

Automatic detection of stereotypical behaviors of captive wild animals based on surveillance videos of zoos and animal reserves

The timely detection of the depressive and stereotypical behaviors often observed in captive wild animals and the subsequent intervention can contribute to improving their living environment in enclosures, which is crucial for safeguarding animal welfare, enhancing animal husbandry practices, regulating human–animal relationships. Several studies have analyzed factors that influence animal stereotypical behaviors and identified preventive measures via regular animal observations. An automatic detection method based on video technology can yield long-term automatic recordings of motion trajectories of animals after a professionally trained automatic detection software is integrated into the human–machine interaction operation interface of animal management. As an initial exploration of this research paradigm, we propose a novel method for automatically tracking and recognizing the stereotypical behavior of animals in surveillance videos based on the periodic analysis of motion trajectories. First, we introduced a Siamese relation network to track the motion trajectories of animals. This network accurately tracked animals and distinguished different individuals in complex environments. Second, an autocorrelation function was used to analyze the periodicity of the motion trajectory, which was divided into several periodic curves. Finally, a cross-correlation function was introduced to determine the linear correlation between the two variables of the periodic curves. This function distinguished the three types of motion trajectories. The success rate and precision of the animal-tracking method adopted in this study were 67.4% and 90.4%, respectively, which were superior to those of common Siamese tracking networks. The average prediction error of the cycle time was 0.095 s. Therefore, the proposed method can accurately track the motion trajectories of animals and identify their stereotypical behaviors. Furthermore, this study provides data to facilitate the scientific management of animals and improve animal welfare. The codes and datasets used in the study are available at https://github.com/yinyinzixuan/animal-stereotypical-behavior.git.

Development and validation of a predictive model for prolonged length of stay in elderly type 2 diabetes mellitus patients combined with cerebral infarction.

This study aimed to identify the predictive factors for prolonged length of stay (LOS) in elderly type 2 diabetes mellitus (T2DM) patients suffering from cerebral infarction (CI) and construct a predictive model to effectively utilize hospital resources. Clinical data were retrospectively collected from T2DM patients suffering from CI aged ≥65 years who were admitted to five tertiary hospitals in Southwest China. The least absolute shrinkage and selection operator (LASSO) regression model and multivariable logistic regression analysis were conducted to identify the independent predictors of prolonged LOS. A nomogram was constructed to visualize the model. The discrimination, calibration, and clinical practicality of the model were evaluated according to the area under the receiver operating characteristic curve (AUROC), calibration curve, decision curve analysis (DCA), and clinical impact curve (CIC). A total of 13,361 patients were included, comprising 6,023, 2,582, and 4,756 patients in the training, internal validation, and external validation sets, respectively. The results revealed that the ACCI score, OP, PI, analgesics use, antibiotics use, psychotropic drug use, insurance type, and ALB were independent predictors for prolonged LOS. The eight-predictor LASSO logistic regression displayed high prediction ability, with an AUROC of 0.725 (95% confidence interval [CI]: 0.710-0.739), a sensitivity of 0.662 (95% CI: 0.639-0.686), and a specificity of 0.675 (95% CI: 0.661-0.689). The calibration curve (bootstraps = 1,000) showed good calibration. In addition, the DCA and CIC also indicated good clinical practicality. An operation interface on a web page (https://xxmyyz.shinyapps.io/prolonged_los1/) was also established to facilitate clinical use. The developed model can predict the risk of prolonged LOS in elderly T2DM patients diagnosed with CI, enabling clinicians to optimize bed management.

Macros in Excel

Excel itself has very powerful functions: including printing documents, file processing, formatting and text editing; Exl has a large number of built-in functions, its operation interface is very familiar to the public, and can connect to a variety of databases. Therefore, it has become a widely used application development platform. For a task that needs to be repeated frequently in Excel, you can record all the steps of executing these tasks in the macro and turn the macro into an automatically executable task. In this way, it is unnecessary to repeat the operation, save a lot of manpower and improve the work efficiency. Today, I will study the relevant knowledge of Excel macros with you.

Development of the Lifelike Head Unit for a Humanoid Cybernetic Avatar ‘Yui’ and its Operation Interface

Development of the Lifelike Head Unit for a Humanoid Cybernetic Avatar ‘Yui’ and its Operation Interface

PhageBox: An Open Source Digital Microfluidic Extension With Applications for Phage Discovery.

Recent advancements demonstrate the significant role of digital microfluidics in automating laboratory work with DNA and on-site viral testing. However, since commercially available instruments are limited to droplet manipulation, our work addresses the need for accelerated integration of other components, such as temperature control, that can expand the application domain. We developed PhageBox-an accessible device that can be used as a biochip extension. At hardware level, PhageBox integrates temperature and electromagnetic control modules. At software level, PhageBox is controlled by embedded software containing a unique model for bio-protocol programming, and a graphical user interface for visual device feedback and operation. To evaluate PhageBox's efficacy for biomedical applications, we performed functional testing. Similarly, we validated the temperature control using thermography, obtaining a range of ±0.2[Formula: see text]. The electromagnets produced a magnetic force of 15 milliTesla, demonstrating precise immobilization of magnetic beads. We show the potential of PhageBox for bacteriophage research through three initial protocols: a universal framework for PCR, T7 bacteriophage restriction enzyme digestion, and concentrating ϕX174 RF genomic DNA. Our work presents an open-source hardware and software extension for digital microfluidics devices. This extension integrates temperature and electromagnetic modules, demonstrating efficacy in biomedical applications and potential for bacteriophage research. We developed PhageBox to be accessible: the components are off-the-shelf at a low cost ( ≤ $200), and the hardware designs and software code are open-source. With the long aim of ensuring reproducibility and accelerating collaboration, we also provide a DIY-build document.

Design, Development and Testing of a Hospital Website

With the deepening of Internet applications, patients expect hospitals to make appointments, communicate information and obtain reports anytime and anywhere through websites. To solve this problem, we have designed and developed a “Hospital” website, which uses iterative and incremental process models and “natural observation method”, and uses React, Node, JavaScript, MongoDB and other Web tools for front-end and back-end development, including hospital dynamic description, The website achieves a 24-hour appointment and communication channel between patients and doctors, with a concise and safe operation interface through repeated testing, and real-time access to test reports. This “Hospital” website can be promoted and used in large traditional Chinese medicine hospitals.

New Injection Controls Environment for the Taiwan Light Source

Taiwan Light Source (TLS) has been service for user service since 1993. Several legacy systems have recently been updated in order to remove obsolescent parts and provide higher operating efficiency. Proprietary designed timing modules were recently replaced by an event based timing system. The magnets of the booster synchrotron were configured as three White circuits and driven by resonance excitation. The original control of the White circuits, which included an analogue amplitude loop and digital phase loop for regulation, has been replaced by full digital regulation loops. The successful upgrade of both systems has led to easy and smooth injection control with enhanced functionality and flexibility. The injection control includes foreground and background processes that coordinate the operation of e-gun, linear accelerator, booster synchrotron, and storage ring with the help of timing system. The injection control GUI provides an intuitive operation interface that includes parameter setting and all necessary information displays, such as various timing value, stored beam current/lifetime, injection efficiency, filling pattern, kickers waveform and so on. Energy saving mode of White circuits operation are supported and embedded into injection control to save electricity. Lifetime calculation of the storage ring is also synchronized with the injection process. Implementation details and operation experience will be presented.

ADVANCED AUTOMATIC SYSTEM FOR REMOTE CONTROL IN THE OIL AND GAS INDUSTRY

The purpose of this work is to design and implement a cascade control system of the level with the flow rate, with remote supervision, in an industrial type installation, located in the Laboratory of Measurement Techniques, Department of Automation, Computers and Electronics, within the Faculty of Mechanical and Electrical Engineering. The operating parameters of the installation are as follows: suction pressure: 0 – 2 bar; discharge pressure: 0 -10 bar; water flow: 0-30 m3/h; transported liquid: water. The automation system is structured on three hierarchical levels: level 1: the instrumentation mounted on the installation (transducers, signaling devices, etc.); level 2: includes the TGA System; level 3: constitutes the upper hierarchical level and includes the HMI (Human Machine Interface). The TGA system is a computerized system that ensures the monitoring, command and control functions of all the stand's component elements. It contains a programmable logic controller PLC 1214 – Siemens, which communicates via an Ethernet IP network with an operator interface and with the network of the Faculty of Mechanical and Electrical Engineering, which allows remote control of the installation. It also includes the protection system in case of failure, which involves stopping the rotating equipment, isolating the pipes by closing the control valve and alarming the operators. The HMI (Human Machine Interface) interface presents 3 options on the start page, from where the operator can select which application he wants to test: flow control loop application; level adjustment loop application; cascade adjustment loop application. The HMI equipment integrates SCADA functions, database update, evolution curves of analog quantities, sound and monitor alarm system, keyboard command, periodic records, event records, alarm records and technological schemes at the human-machine interface. The entire software is made in an open architecture, recommended by ISO norms. The PLC communicates in the network by adopting the protocol TCP/IP. An executable program used for the real-time application program was developed.

3-D Interface for Humanoid Robot Operation

3-D Interface for Humanoid Robot Operation

CRUD Operation on WordPress Database Using C# SQL Client

Purpose: Sometimes, the researcher stores sensor data inside the cloud to access the data globally. The widespread cloud infrastructures are AWS, Azure, Google, IBM, etc. This type of Cloud server is not free. We need to pay through subscription. Here, we demonstrate how to manage our sensor data using our existing WordPress Website database. The primary example of CRUD operation on the WordPress Database is provided here. The database class is portable. The researcher can easily integrate more functionality. Using the C# language, we created the “WordPressDB.cs” library with the help of an inbuilt SQL client module. On top of that, we developed a graphical user interface for easy operation. We use Flywheel to install WordPress websites locally for safe operation. Once the development is over, we can deploy online without any issues. The completed project code is available to download for quick integration. Design/Methodology/Approach: To keep our research work free, we installed Flywheel Local software suitable for local WordPress Website installation. We installed a WordPress Website using the Flywheel. Once the Website is fully installed, we run the site from the Flywheel local interface. Now, we open our C# projects. We need to provide the Database credentials to connect with the WordPress Database. Once the connection is successful, we can create a table read, update, and delete the record. Findings/Result: We demonstrated how to keep our sensor data using our existing WordPress database. We tested the provided approach, a good and efficient way to control and manage the sensor data. Our communication stack is as tiny as possible, so it is fast. We can keep our real-time data inside this Database with minimum delay. Originality/Value: Several procedures are available to keep the sensor's data. Using this procedure, we can maintain the data at the least cost possible. We are paying for our website to run. We are getting online cloud storage to keep our sensor data without extra cost. The Website runs around the clock, so our research data is available anytime and anywhere. This approach differs slightly from the traditional approach, like purchasing subscription cloud hosting infrastructure. We can also run the IoT activities using this approach. To exchange the dynamic data between two nodes is also effective without buying a static IP. Paper Type: Experimental-based Research.

A novel code generator for graphical user interfaces

Graphical user interfaces (GUIs) are widely used in human–computer interaction, providing a convenient interface for operation. Automating the conversion of GUI design images into source code can significantly reduce the coding workload for front-end developers. Detecting elements in GUI images is a key challenge in achieving automatic GUI code generation and is crucial for tasks such as GUI automation and testing. However, current state-of-the-art methods do not fully consider the unique characteristics of GUI images and elements, and they lack the required high localization accuracy, resulting in low detection accuracy for GUI element boxes. In this paper, we propose GUICG, an automatic GUI code generator that combines deep neural networks with image processing techniques to efficiently detect GUI elements from GUI images and generate front-end code. We empirically investigate various deep learning approaches and image processing methods for GUI component detection. Based on a comprehensive understanding of their performance and characteristics, we design GUICG by fusing image processing with a deep learning-based target detection model, achieving state-of-the-art performance. GUICG outperforms existing methods in accuracy and F1 score for component detection tasks, while producing human-readable code with a logical structure. Furthermore, we conduct an ablation study to quantitatively assess the impact of each key element in GUICG.

Relativistic particle measurement in jupiter’s magnetosphere with Pix.PAN

Pix.PAN is a compact cylindrical magnetic spectrometer, intended to provide excellent high energy particle measurements under high rate and hostile operating conditions in space. Its principal design is composed of two Halbach-array magnetic sectors and six Timepix4-based tracking layers; the latest hybrid silicon pixel detector readout ASIC designed. Due to Pix.PAN’s compact and relatively simple design, it has the potential to be used for space missions exploring with measurements of unprecedented precision, high energy particles in radiation belts and the heliophere (solar energetic particles, anomalous and galactic cosmic rays). In this white paper, we discuss the design and expected performance of Pix.PAN for COMPASS (Comprehensive Observations of Magnetospheric Particle Acceleration, Sources, and Sinks), a mission concept submitted to NASA’s Call “B.16 Heliophysics Mission Concept Studies (HMCS)” in 2021 that targets the extreme high energy particle environment of Jupiter’s inner radiation belts. We also discuss PixPAN’s operational conditions and interface requirements. The conceptual design shows that is possible to achieve an energy resolution of<12% for electrons in the range of 10 MeV-1 GeV and<35% for protons between ∼\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\sim $$\\end{document}200 MeV to a few GeV. Due to the timestamp precision of Timepix4, a time resolution (on an instrument level) of about 100 ps can be achieved for time-of-flight measurements. In the most intense radiation environments of the COMPASS mission, Pix.PAN is expected to have a maximum hit rate of 44MHzcm2\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\frac{\ ext {MHz}}{\ ext {cm}^2}$$\\end{document} which is below the design limit of 360MHzcm2\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\frac{\ ext {MHz}}{\ ext {cm}^2}$$\\end{document} of Timepix4. Finally, a sensor design is proposed which allows the instrument to operate with a power budget of 20W without the loss of scientific performance.

Research on a Classification Method for Strip Steel Surface Defects Based on Knowledge Distillation and a Self-Adaptive Residual Shrinkage Network

Different types of surface defects will occur during the production of strip steel. To ensure production quality, it is essential to classify these defects. Our research indicates that two main problems exist in the existing strip steel surface defect classification methods: (1) they cannot solve the problem of unbalanced data using few-shot in reality, (2) they cannot meet the requirement of online real-time classification. To solve the aforementioned problems, a relational knowledge distillation self-adaptive residual shrinkage network (RKD-SARSN) is presented in this work. First, the data enhancement strategy of Cycle GAN defective sample migration is designed. Second, the self-adaptive residual shrinkage network (SARSN) is intended as the backbone network for feature extraction. An adaptive loss function based on accuracy and geometric mean (Gmean) is proposed to solve the problem of unbalanced samples. Finally, a relational knowledge distillation model (RKD) is proposed, and the functions of GUI operation interface encapsulation are designed by combining image processing technology. SARSN is used as a teacher model, its generalization performance is transferred to the lightweight network ResNet34, and it is conveniently deployed as a student model. The results show that the proposed method can improve the deployment efficiency of the model and ensure the real-time performance of the classification algorithms. It is superior to other mainstream algorithms for fine-grained images with unbalanced data classification.

Lattice Boltzmann simulations for the drying of porous media with gas–side convection–diffusion boundary

One of the most significant challenges in describing the drying of porous materials is the realistic integration of internal transport phenomena into mathematical models, coupled with the external free flow. However, the intricacies of pore-scale geometry make experimentation and observation very difficult in practice, thereby making modeling techniques a useful tool for the analysis of the drying process. Among the many modeling techniques developed for drying, the lattice Boltzmann method (LBM)-based modeling approach has gained favor in recent years due to its ability to incorporate realistic geometry and transport at the pore scale. Our previous works on Shan–Chen LBM for drying of capillary porous media were based on the Bhatnagar–Gross–Krook collision operator and diffusion interface boundary conditions. This study elucidates the drying of a capillary porous medium under the influence of convection–diffusion boundary conditions at the gas side, using Shan–Chen LBM. The pore-scale effects of convection–diffusion conditions during the drying process are presented in relation to the macroscale drying kinetics. Moreover, the differences between the convection–diffusion kinetics and purely diffusion–dominated kinetics of the drying process are also presented here. This work also aims to incorporate the convection–diffusion transport phenomena into the drying process of a porous medium under the influence of an imposed thermal gradient, establishing and studying the phenomena of stabilization and destabilization of the drying front under the influence of a temperature gradient, thereby extending the lattice Boltzmann method of modeling for the simulation of convection–diffusion drying, both for the isothermal case and the imposition of a thermal gradient.

Design and Implementation of Environmental Monitoring System for Substation Based on Internet of Things

At present, the environmental monitoring of the substation suffers from complex wiring, low intelligence, high staff work intensity, and a lack of information-based overall management. Moreover, the distribution of substations is relatively scattered, making it complex and costly to set up a dedicated communication network. In response to these problems, this paper combines modern communication technology, sensor technology, and mobile intelligent terminal development technology to study an overall information-based substation environmental monitoring system. The monitoring system proposed in this paper includes a main controller, a data collection terminal, and a mobile communication terminal. The environmental data collected by the main controller is sent to the server through the communication method of subscription and substation using wireless communication technology, and the interface of the mobile communication terminal can display indoor environmental monitoring data. When the environmental data of the Substation exceeds the set threshold value to issue an early warning alert, the user can control it remotely through the mobile communication terminal to improve the indoor environment of the Substation. The system has a simple operation interface, low power consumption, and strong expansion compatibility, which effectively realizes remote monitoring and control of the substation environment and has good engineering application value.

KRT高阶动态双向教学模式及其在《卫生法学》中的应用

This article explores, summarizes and inducts the KRT advanced dynamic bidirectional teaching mode and its application in “Health Law”. The research shows that this new teaching mode, which integrates advanced teaching, dynamic teaching and bidirectional teaching, has significant advantages in cultivating students' advanced thinking ability, promoting self-directed learning, updating teaching content and improving learning interest. However, there are also some areas that need improvement, such as optimizing the operation interface of online teaching platforms and tools, balancing the depth and breadth of teaching content to meet the needs of students in different majors. Further optimizing and perfecting the KRT teaching mode is of great significance and value for cultivating students' advanced thinking ability and practical ability in the field of health law.