Novel AR-based interface for human-robot interaction and visualization

Intuitive and efficient interfaces for humanrobot interaction(HRI) have been a challenging issue in robotics as it is essential for the prevalence of robots supporting humans in key areas of activities.This paper presents a novel augmented reality(AR) based interface to facilitate human-virtual robot interaction.A number of human-virtual robot interaction methods have been formulated and implemented with respect to the various types of operations needed in different robotic applications.A EucUdean distance-based method is developed to assist the users in the interaction with the virtual robot and the spatial entities in an AR environment.A monitor-based visualization mode is adopted as it enables the users to perceive the virtual contents associated with different interaction methods,and the virtual content augmented in the real environment is informative and useful to the users during their interaction with the virtual robot.Case researches are presented to demonstrate the successful implementation of the AR-based HRI interface in planning robot pick-and-place operations and path following operations.     

Production line 3D visualization monitoring system design based on OpenGL

New production line management technologies are required and adopted recently with the development of modern manufacturing industry. In this study, a production line three-dimensional (3D) visualization monitoring system based on OpenGL modeling, open database connectivity (ODBC), and database management technology is established on a VC++6.0 platform to satisfy effective production. A client/server model is adopted in the system, and data on processing information, interactive operation, and failure process are stored in the server side database. A client reads the workpiece process information from the server, and the machining process of every workpiece is visually represented in the form of 3D visualization. Production line 3D visualization provides production capacity simulation to optimize the parameter settings. When compared with the analysis results of production line capacity, the key parameters possess the same optimal values, and this proves the accuracy of production line 3D visualization monitoring system. The system provides effective data support for production line monitoring and management in enterprises. The full text can be downloaded at https://link.springer.com/article/10.1007/s40436-018-0217-x     

Revisiting digital twins: Origins,fundamentals, and practices

The digital twins (DT) has quickly become a hot topic since it was proposed. It appears in all kinds of commercial propaganda and is widely quoted by academic circles. However, the term DT has misstatements and is misused in business and academics. This study revisits DT and defines it to be a more advanced system/product/service modeling and simulation environment that combines most modern information communication technologies (ICTs) and engineering mechanism digitization and characterized by system/product/service life cycle management, physically geometric visualization, real-time sensing and measurement of system operating conditions, predictability of system performance/safety/lifespan, and complete engineering mechanisms-based simulations. The idea of DT originates from modeling and simulation practices of engineering informatization, including virtual manufacturing (VM), model predictive control, and building information modeling (BIM). On the basis of the two-element VM model, we propose a three-element model to represent DT. DT does not have its unique technical characteristics. The existing practices of DT are extensions of the engineering informatization embracing modern ICTs. These insights clarify the origin of DT and its technical essentials.     

Development and use of augmented reality and 3D printing in consulting patient with complex skull base cholesteatoma

Temporal bone and skull base anatomy is complex and can pose difficulties in patient’s perception of disease and anatomy, perceived risks, and complications of surgery. We wish to demonstrate the development and use of augmented reality (AR) technology and three-dimensional (3D) printing to assist in preoperative patient consultation in the case of a complex skull base cholesteatoma. A series of 3D models were constructed from a patient’s petrous temporal bone computed tomography (CT) scans using CAD (computer-aided design) software to display the cholesteatoma affected temporal bone and related structures. Supplementary labels and titles were also created. A two-dimensional (2D) image was created as an AR recognition marker. Both 3D and 2D assets were uploaded, linked in an AR development platform called Hyperspaces which was then published to the Hyperspaces cloud server to build an AR application for free access using a predefined keyword on an iOS mobile device. Patient’s temporal bone was also fabricated through a fused deposition modelling 3D printer using polylactic acid filament for patient consultation. AR and 3D printing allow patient-specific clinical information and complexities to be made readily available to the patient and doctor at low cost, and aid in understanding complex skull base anatomy and progressive disease such as cholesteatoma. The advancement of AR and 3D printing technologies are making complex and patient-specific 3D medical data visualisation feasible and tangible on a mobile device and in hand. Thus, these technologies can be used as an invaluable patient education and counselling tool offering a powerful medium in specialties where difficult anatomical challenges are encountered.Abbreviations: ABS: acrylonitrile–butadiene–styrene; AM: additive manufacturing; AR: augmented reality; CAD: computer-aided design; CT: computed tomography; DICOM: Digital Imaging and Communication in Medicine; FBX: Filmbox; FDM: fused deposition modelling; JPEG: joint photographic experts group; MRI: magnetic resonance imaging; PLA: polylactic acid; ROI: region of interest; STL: Stereolithography     

Integrating TTF and UTAUT2 theories to investigate the adoption of augmented reality technology in education: Perspective from a developing country

Augmented reality (AR) has gained increased recognition in varying fields, in particular educational contexts. In the wake of the Covid-19 pandemic, home-based learning becomes a reality and is already in place across the globe, and learning via augmented reality technology will help learners comprehend learning content in a more creative frame of mind than ever before. Very little research has examined the adoption behavior of augmented reality in developing country perspectives. Therefore, there is a pressing necessity to understand the dynamics of augmented reality adoption for the benefit of motivating and inspiring students to adopt this highly innovative and impactful type of technology in the learning process. Against this background, the authors proposed and tested a model based on integrating Task-Technology Fit (TTF) and UTUAT2 theories. The results reveal the positive effect of task technology fit, performance expectancy, effort expectancy, social influence, facilitating condition, and hedonic motivation on behavioral intention (BI) in the adoption process of augmented reality in educational settings, where price value is found to exert little influence on behavioral intention. This model explains 49% of the variance in intentional behavior to adopt AR technology in the educational context. The conclusions of this study will add to the literature more informative knowledge leading to increased awareness of the dynamics and behaviors of AR adoption in a developing country perspective. We present and discuss the theoretical contributions and practical implications of our findings.     

AR-assisted robot welding programming

Robotic welding demands high accuracy and precision. However, robot programming is often a tedious and time-consuming process that requires expert knowledge. This paper presents an augmented reality assisted robot welding task programming (ARWP) system using a user-friendly augmented reality (AR) interface that simplifies and speeds up the programming of robotic welding tasks. The ARWP system makes the programming of robot welding tasks more user-friendly and reduces the need for trained programmers and expertise in specific robotic systems. The AR interface simplifies the definition of a welding path as well as the welding gun orientation, and the system; the system can locate the welding seam of a workpiece quickly and generate a viable welding path based on the user input. The developed system is integrated with the touch-sensing capability of welding robots in order to locate the welding path accurately based on the user input, for fillet welding. The system is applicable to other welding processes and methods of seam localization. The system implementation is described and evaluated with a case study.The full text can be downloaded at https://link.springer.com/content/pdf/10.1007%2Fs40436-019-00283-0.pdf     

Research progress in the use of ferrate(VI) for the environmental remediation

The aim of this paper is to review the research progress of using ferrate(VI) in following fields of environmental remediation: (1) water disinfection; (2) degradation of synthetic organic pollutants; (3) treatment of emerging organic pollutants; (4) oxidation of inorganic pollutants; (5) removing humic substance; (6) wastewater treatment and disinfection; and (7) sewage sludge treatment. Whilst the superior performance of potassium ferrate(VI) as an oxidant/disinfectant for the environmental remediation has been demonstrated in various recent researches, challenges have existed to the implementation of ferrate(VI) technology in full-scale water, wastewater and sewage sludge treatment owing to either the instability property of a ferrate(VI) solution or a high preparation cost of a solid ferrate(VI). In addition to this, there are some fundamental issues which have not yet been studied thoroughly which are crucial for the implementation of ferrate(VI)-these lead to the future research work recommended by this paper.     

Novel Architecture of OneM2M-Based Convergence Platform for Mixed Reality and IoT

There have been numerous works proposed to merge augmented reality/mixed reality (AR/MR) and Internet of Things (IoT) in various ways. However, they have focused on their specific target applications and have limitations on interoperability or reusability when utilizing them to different domains or adding other devices to the system. This paper proposes a novel architecture of a convergence platform for AR/MR and IoT systems and services. The proposed architecture adopts the oneM2M IoT standard as the basic framework that converges AR/MR and IoT systems and enables the development of application services used in general-purpose environments without being subordinate to specific systems, domains, and device manufacturers. We implement the proposed architecture utilizing the open-source oneM2M-based IoT server and device platforms released by the open alliance for IoT standards (OCEAN) and Microsoft HoloLens as an MR device platform. We also suggest and demonstrate the practical use cases and discuss the advantages of the proposed architecture.     

Integrated molecule-format bioluminescent probe for visualizing androgenicity of ligands based on the intramolecular association of androgen receptor with its recognition Peptide

Ligand-induced conformational changes of nuclear hormone receptors (NRs) are an important start-up of various hormone signaling. However, little is known of the bioanalytical use of the hormone-induced conformational changes of NRs. Here, we describe a generally applicable bioluminescence assay with a genetically encoded bioluminescent indicator to determine androgenicity of ligands based on the intramolecular association of the ligand binding domain of androgen receptor (AR LBD) with the "FQNLF" motif in the N-terminal domain of AR (AR NTD). Firefly luciferase (FLuc) was dissected into N-terminal (1-415 AA) and C-terminal (416-550 AA) fragments. The AR LBD and FQNLF motif of AR NTD were sandwiched between the dissected fragments of FLuc to construct a single molecule-format bioluminescent probe. Androgens induce the association of AR LBD with the FQNLF motif in the NTD, and the subsequent complementation of N- and C-terminal fragments of FLuc partially restores the activities of FLuc. A 10-5 M solution of 5alpha-dihydroxytestosterone (DHT) induced a quick increase in the luminescence intensities from cervical carcinoma-derived HeLa cells carrying the genetic indicator, which reached a plateau in 9 min, whereas DHT withdrawal from the cells by a medium change decreased the luminescence with a slower time course, i.e., approximately 2 h until returning to the background luminescence. The present luminescent indicator was found to exhibit high agonist selectivity and reproducible recovery of the luminescence to a repeated androgen addition and withdrawal. This is the first contribution that cellular signaling steps can be imaged with bioluminescence using a single molecule-format bioluminescence probe (Simbi), in which all the components required for a signal sensing and visualization are integrated. Simbi is applicable to developing biotherapeutic agents effecting to the AR signaling, and for screening adverse chemicals that possibly influence the signal transduction of AR.     

Kinetics of decolorization of an azo dye in UV alone and UV/H(2)O(2) processes

The decolorization of C.I. Acid Red 27 (AR27), a monoazo anionic dye, was studied in the ultraviolet radiation (UV) alone and UV plus hydrogen peroxide (UV/H(2)O(2)) processes. The experimental results indicated that the kinetics of both oxidation processes fit well by pseudo-first order kinetics. The reaction rate was sensitive to the operational parameters and increased with increasing H(2)O(2) concentration and light intensity. The reaction orders of H(2)O(2) concentration and light intensity in both processes were obtained with linear regression method. A regression model was developed for pseudo-first order rate constant (k(ap,UV/H(2)O(2))) as a function of the Cconcentration and UV light intensity. (k(ap,UV/H(2)O(2)))=(2 x 10(-4)I(0.75)(0) + k(3)I(1.38)(0)[H(2)O(2)](n)(0))phi(AR27). As a result of two opposing effects of H(2)O(2) concentration at low and high concentrations, n has a value of 0.49 and -0.39 and k(3) has a value of 3 x 10(-4) and 0.1 for the regions of 0 mg l(-1) < [H(2)O(2)](0) < 650 mg l(-1) and 650 mg l(-1) < [H(2)O(2)](0) < 1500 mg l(-1)1, respectively. PhiAR27 is the initial dye concentration correlation index for developing of model for different initial concentrations of AR27. This rate expression can be used for predicting k(ap,UV/H(2)O(2) at different conditions in UV alone and UV/H2O2 processes. The results show that UV alone cannot be an efficient method for decolorization of AR27 in comparison with UV/H(2)O(2) process, therefore the first term of the model can be neglected.     

Rule generation for protein secondary structure prediction with support vector machines and decision tree

Support vector machines (SVMs) have shown strong generalization ability in a number of application areas, including protein structure prediction. However, the poor comprehensibility hinders the success of the SVM for protein structure prediction. The explanation of how a decision made is important for accepting the machine learning technology, especially for applications such as bioinformatics. The reasonable interpretation is not only useful to guide the "wet experiments," but also the extracted rules are helpful to integrate computational intelligence with symbolic AI systems for advanced deduction. On the other hand, a decision tree has good comprehensibility. In this paper, a novel approach to rule generation for protein secondary structure prediction by integrating merits of both the SVM and decision tree is presented. This approach combines the SVM with decision tree into a new algorithm called SVM/spl I.bar/DT, which proceeds in three steps. This algorithm first trains an SVM. Then, a new training set is generated through careful selection from the output of the SVM. Finally, the obtained training set is used to train a decision tree learning system and to extract the corresponding rule sets. The results of the experiments of protein secondary structure prediction on RS126 data set show that the comprehensibility of SVM/spl I.bar/DT is much better than that of the SVM. Moreover, the generalization ability of SVM/spl I.bar/DT is better than that of C4.5 decision trees and is similar to that of the SVM. Hence, SVM/spl I.bar/DT can be used not only for prediction, but also for guiding biological experiments.     

A comprehensive survey of augmented reality assembly research

In the past two decades, augmented reality(AR) has received a growing amount of attention by researchers in the manufacturing technology community, because AR can be applied to address a wide range of problems throughout the assembly phase in the lifecycle of a product, e.g., planning, design, ergonomics assessment, operation guidance and training. However, to the best of authors' knowledge, there has not been any comprehensive review of AR-based assembly systems. This paper aims to provide a concise overview of the technical features, characteristics and broad range of applications of ARbased assembly systems published between 1990 and 2015. Among these selected articles, two thirds of them were published between 2005 and 2015, and they are considered as recent pertinent works which will be discussed in detail. In addition, the current limitation factors and future trends in the development will also be discussed.     

基于替代电镀硬铬的WC增强金属复合涂层疲劳性能的研究现状

传统电镀硬铬涂层存在网纹裂纹缺陷、抗疲劳性能不足以及环境污染严重等问题,针对新一代航空工业急需新技术替代传统电镀硬铬这一迫切需求,研发新型的耐磨耐蚀涂层体系及其先进环保的再制造技术迫在眉睫。根据先进涂层技术的发展情况,研发出了基于高温熔化-凝固技术的物理气相沉积、超音速火焰喷涂以及激光熔覆技术,这在绿色制备航空工业用耐磨耐蚀涂层上表现出了一定的应用前景,并表现出了比传统电镀硬铬更长的疲劳寿命,但其仍存在内应力过高而开裂、粉末氧化或相变导致疲劳性能下降等一系列关键问题。近年来,冷喷涂涂层技术作为先进环保的新技术,凭借其低温固态沉积特性在制备金属基复合涂层上展现出了显著的冶金优势,其中冷喷涂涂层的残余压应力有助于提高零件的疲劳性能。此外,从起落架防护涂层沉积到其修复再制造环节,冷喷涂技术均可参与其中。因此,作为固态沉积工艺的冷喷涂,其在替代传统电镀铬的新型涂层制备工艺方面具有显著的应用潜力,未来的研究将集中于优化冷喷涂涂层材料和工艺上,以进一步提高其力学性能和疲劳性能。     

Design technology transfer

Design technology and its transfer are defined and their significance stated. The history of design technology (DT) is outlined, noting a recent change in nature. Factors influencing the development and spread of DT are investigated, first by the use of pieces of available research results, and then through analysis of 12 case summaries assembled for the purpose. Hypotheses are advanced regarding the i influence of large ‘front-runner’ companies and, particularly, of companies in the information technology fields. Suggestions are offered to university departments wiching to participate more fully in design technology transfer.     

Deep learning diffusion by infusion into preexisting technologies – Implications for users and society at large

Artificial Intelligence (AI) in the form of Deep Learning (DL) technology has diffused in the consumer domain in a unique way as compared to previous general-purpose technologies. DL has often spread by infusion, i.e., by being added to preexisting technologies that are already in use. We find that DL-algorithms for recommendations or ranking have been infused into all the 15 most popular mobile applications (apps) in the U.S. (as of May 2019). DL-infusion enables fast and vast diffusion. For example, when a DL-system was infused into YouTube, it almost immediately reached a third of the world's population. We argue that existing theories of innovation diffusion and adoption have limited relevance for DL-infusion, because it is a process that is driven by enterprises rather than individuals. We also discuss its social and ethical implications. First, consumers have a limited ability to detect and evaluate an infused technology. DL-infusion may thus help to explain why AI's presence in society has not been challenged by many. Second, the DL-providers are likely to face conflicts of interest, since consumer and supplier goals are not always aligned. Third, infusion is likely to be a particularly important diffusion process for DL-technologies as compared to other innovations, because they need large data sets to function well, which can be drawn from preexisting users. Related, it seems that larger technology companies comparatively benefit more from DL-infusion, because they already have many users. This suggests that the value drawn from DL is likely to follow a Matthew Effect of accumulated advantage online: many preexisting users provide a lot of behavioral data, which bring about better DL-driven features, which attract even more users, etc. Such a self-reinforcing process could limit the possibilities for new companies to compete. This way, the notion of DL-infusion may put light on the power shift that comes with the presence of AI in society.     

Response surface methodological approach for the decolorization of simulated dye effluent using Aspergillus fumigatus fresenius

The aim of our research was to study, effect of temperature, pH and initial dye concentration on decolorization of diazo dye Acid Red 151 (AR 151) from simulated dye solution using a fungal isolate Aspergillus fumigatus fresenius have been investigated. The central composite design matrix and response surface methodology (RSM) have been applied to design the experiments to evaluate the interactive effects of three most important operating variables: temperature (25-35 degrees C), pH (4.0-7.0), and initial dye concentration (100-200 mg/L) on the biodegradation of AR 151. The total 20 experiments were conducted in the present study towards the construction of a quadratic model. Very high regression coefficient between the variables and the response (R(2)=0.9934) indicated excellent evaluation of experimental data by second-order polynomial regression model. The RSM indicated that initial dye concentration of 150 mg/L, pH 5.5 and a temperature of 30 degrees C were optimal for maximum % decolorization of AR 151 in simulated dye solution, and 84.8% decolorization of AR 151 was observed at optimum growth conditions.     

Nickel-titanium shape memory alloys made by selective laser melting:a review on process optimisation

Selective laser melting (SLM) is a mainstream powder-bed fusion additive manufacturing (AM) process that creates a three-dimensional (3D) object using a high power laser to fuse fine particles of various metallic powders such as copper, tool steel, cobalt chrome, titanium, tungsten, aluminium and stainless steel. Over the past decade, SLM has received significant attention due to its capability in producing dense parts with superior mechanical properties. As a premier shape memory alloy, the nickel-titanium (NiTi) shape memory alloy is attractive for a variety of biomedical applications due to its superior mechanical properties, superelasticity, corrosion resistance and biocompatibility. This paper presents a comprehensive review of the recent progress in NiTi alloys produced by the SLM process, with a particular focus on the relationship between processing parameters, resultant microstructures and properties. Current research gaps, challenges and suggestions for future research are also addressed.The full text can be downloaded at https://link.springer.com/article/10.1007/s40436-021-00376-9     

Recent research progress of master mold manufacturing by nanoimprint technique for the novel microoptics devices

The consumer demand for emerging technologies such as augmented reality (AR), autopilot, and three-dimensional (3D) internet has rapidly promoted the application of novel optical display devices in innovative industries. However, the micro/nanomanufacturing of high-resolution optical display devices is the primary issue restricting their development. The manufacturing technology of micro/nanostructures, methods of display mechanisms, display materials, and mass production of display devices are major technical obstacles. To comprehensively understand the latest state-of-the-art and trigger new technological breakthroughs, this study reviews the recent research progress of master molds produced using nanoimprint technology for new optical devices, particularly AR glasses, new-generation light-emitting diode car lighting, and naked-eye 3D display mechanisms, and their manufacturing techniques of master molds. The focus is on the relationships among the manufacturing process, microstructure, and display of a new optical device. Nanoimprint master molds are reviewed for the manufacturing and application of new optical devices, and the challenges and prospects of the new optical device diffraction grating nanoimprint technology are discussed.     

Electrophysiological assessment of primary cortical neurons genetically engineered using iron oxide nanoparticles

The development of safe technologies to genetically modify neurons is of great interest in regenerative neurology,for both translational and basic science applications.Such approaches have conventionally been heavily reliant on viral transduction methods,which have safety and production limitations.Magnetofection (magnet-assisted gene transfer using iron oxide nanoparticles as vectors) has emerged as a highly promising non-viral alternative for safe and reproducible genetic modification of neurons.Despite the high potential of this technology,there is an important gap in our knowledge of the safety of this approach,namely,whether it alters neuronal function in adverse ways,such as by altering neuronal excitability and signaling.We have investigated the effects of magnetofection in primary cortical neurons by examining neuronal excitability using the whole cell patch clamp technique.We found no evidence that magnetofection alters the voltage-dependent sodium and potassium ionic currents that underpin excitability.Our study provides important new data supporting magnetofection as a safe technology for bioengineering of neuronal cell populations.     

Strain and temperature effects in indium-tin-oxide sensors

Indium-tin-oxide (ITO) thin films strain gages were prepared by reactive sputtering onto both high purity alumina and lanthanum stabilized zirconia substrates. We report the piezoresistive response of these ITO gages in the temperature range 350-1500 °C up to 1000 microstrain (με). Strain response and gage factors are reported for ITO in both tension and compression. The data suggest that not only is there an annealing component but also a strain component of the piezoresistive change with time at temperature. The effects in both tension and compression are reported.