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The purpose of this study is to validate multiplicative cycle that exists between the job readiness and satisfaction model explored by Matthews et al. (2018), the satisfaction and performance paradigmatic nuances analyzed by Judge et al. (2001) and Gu and Chi (2009), in addition to the expectancy model theorized by Vroom (1964). The motivation to transfer learning serves as a conveyable variable transmitted within a learning continuum that sustains cyclical outputs.

An archetype to explore the connection between the three hypothesized theories is created through a neural network program. Exploring this connection develops deeper understandings of the derivatives of employee motivation as it pertains to its effect on readiness, satisfaction, performance and achievement dyads. A detailed analysis of the literature leads to the hypothesis that the motivation to transfer learning creates a multiplicative effect among hypothesized relationships.

The neural network program scaffolds the proposed general belief that positive effects of transfer motives cause a cyclical effect that continues to perpetuate among hypothesized dyads. Conversely, if this motivation decreases or ceases among one or more dyads, the cyclical effect will retract and, eventually stop.

Based on the neurologic outcome, one central theme emerged: managers must offer opportunities to acquire knowledge through assistive mechanisms (i.e. training) by providing external stability through controlled channels that activates the motivation to transfer learning into new opportunities. The transference of this knowledge produces reconstructive growth opportunities through continuous learning thus increasing performance.

本研究的目的、除了驗證弗魯姆 (Vroom) (1964) 建立的「期望模型」理論外，也去驗證存在於工作準備就緒與馬修斯等人 (Matthews et al.) (2018) 所探索的滿足感模型之間的倍增週期，及質治等人 (Judge et al.) (2001) 和古與池 (Gu & Chi) (2009) 所分析的滿足感及表現之範式細微差別。學習轉移的動機作為一個被傳送至學習漸變體內的可輸送變量而運作，而這個學習漸變體是會維持週期性的輸出的。

透過神經網絡程序，創造一個用以探索這三個假設性理論之間的關係的原型。探究這些關係，會使我們更能深入了解僱員動機的衍生品，因這涉及僱員動機對準備就緒、滿足感、表現及功績二元體的影響。仔細分析文獻帶出了一個假設，就是: 學習轉移的動機會在各假設的關係裏創造一個倍增的效果。

這個神經網絡程序續步闡釋了一個被倡議的普遍觀念，那就是轉移動機的正面影響會帶來一個在假設性的二元體中會繼續持續下去的週期性效應。相反地，如果這動機在一個或多個二元體中減弱或停止，這週期性效應將會撤回及最終停止。

基於神經病學的結果，一個核心主題浮現了， 就是：管理人員必須提供透過輔助機制 (就是說：培訓) 而獲取知識的機會。方法是給會引發把學習轉為新機會的動機之受控渠道、提供外在穩定性。這知識的轉移，透過不斷學習而創造重建的成長，表現因而得以提升。

This paper presents a survey of research into interactive robotic systems for the purpose of identifying the state of the art capabilities as well as the extant gaps in this emerging field. Communication is multimodal. Multimodality is a representation of many modes chosen from rhetorical aspects for its communication potentials. The author seeks to define the available automation capabilities in communication using multimodalities that will support a proposed Interactive Robot System (IRS) as an AI mounted robotic platform to advance the speed and quality of military operational and tactical decision making.

This review will begin by presenting key developments in the robotic interaction field with the objective of identifying essential technological developments that set conditions for robotic platforms to function autonomously. After surveying the key aspects in Human Robot Interaction (HRI), Unmanned Autonomous System (UAS), visualization, Virtual Environment (VE) and prediction, the paper then proceeds to describe the gaps in the application areas that will require extension and integration to enable the prototyping of the IRS. A brief examination of other work in HRI-related fields concludes with a recapitulation of the IRS challenge that will set conditions for future success.

Using insights from a balanced cross section of sources from the government, academic, and commercial entities that contribute to HRI a multimodal IRS in military communication is introduced. Multimodal IRS (MIRS) in military communication has yet to be deployed.

Multimodal robotic interface for the MIRS is an interdisciplinary endeavour. This is not realistic that one can comprehend all expert and related knowledge and skills to design and develop such multimodal interactive robotic interface. In this brief preliminary survey, the author has discussed extant AI, robotics, NLP, CV, VDM, and VE applications that is directly related to multimodal interaction. Each mode of this multimodal communication is an active research area. Multimodal human/military robot communication is the ultimate goal of this research.

A multimodal autonomous robot in military communication using speech, images, gestures, VST and VE has yet to be deployed. Autonomous multimodal communication is expected to open wider possibilities for all armed forces. Given the density of the land domain, the army is in a position to exploit the opportunities for human–machine teaming (HMT) exposure. Naval and air forces will adopt platform specific suites for specially selected operators to integrate with and leverage this emerging technology. The possession of a flexible communications means that readily adapts to virtual training will enhance planning and mission rehearsals tremendously.

Interaction, perception, cognition and visualization based multimodal communication system is yet missing. Options to communicate, express and convey information in HMT setting with multiple options, suggestions and recommendations will certainly enhance military communication, strength, engagement, security, cognition, perception as well as the ability to act confidently for a successful mission.

The objective is to develop a multimodal autonomous interactive robot for military communications. This survey reports the state of the art, what exists and what is missing, what can be done and possibilities of extension that support the military in maintaining effective communication using multimodalities. There are some separate ongoing progresses, such as in machine-enabled speech, image recognition, tracking, visualizations for situational awareness, and virtual environments. At this time, there is no integrated approach for multimodal human robot interaction that proposes a flexible and agile communication. The report briefly introduces the research proposal about multimodal interactive robot in military communication.

Two-handed automobile steering at low vehicle speeds may lead to reduced steering ability at large steering wheel angles and shoulder injury at high steering wheel rates (SWRs). As a first step toward solving these problems, this study aims, firstly, to design a surface electromyography (sEMG) controlled steering assistance interface that enables hands-free steering wheel rotation and, secondly, to validate the effect of this rotation on path-following accuracy.

A total of 24 drivers used biceps brachii sEMG signals to control the steering assistance interface at a maximized SWR in three driving simulator scenarios: U-turn, 90º turn and 45º turn. For comparison, the scenarios were repeated with a slower SWR and a game steering wheel in place of the steering assistance interface. The path-following accuracy of the steering assistance interface would be validated if it was at least comparable to that of the game steering wheel.

Overall, the steering assistance interface with a maximized SWR was comparable to a game steering wheel. For the U-turn, 90º turn and 45º turn, the sEMG-based human–machine interface (HMI) had median lateral errors of 0.55, 0.3 and 0.2 m, respectively, whereas the game steering wheel, respectively, had median lateral errors of 0.7, 0.4 and 0.3 m. The higher accuracy of the sEMG-based HMI was statistically significant in the case of the U-turn.

Although production automobiles do not use sEMG-based HMIs, and few studies have proposed sEMG controlled steering, the results of the current study warrant further development of a sEMG-based HMI for an actual automobile.

The successful and commercial use of self-driving/driverless/unmanned/automated car will make human life easier. The paper aims to discuss this issue.

This paper reviews the key technology of a self-driving car. In this paper, the four key technologies in self-driving car, namely, car navigation system, path planning, environment perception and car control, are addressed and surveyed. The main research institutions and groups in different countries are summarized. Finally, the debates of self-driving car are discussed and the development trend of self-driving car is predicted.

This paper analyzes the key technology of self-driving car and illuminates the state-of-art of the self-driving car.

The main research contents and key technology have been introduced. The research progress as well as the research institution has been summarized.

In recent years, owing to the rapidly increasing labor costs, the demand for robots in daily services and industrial operations has been increased significantly. For further applications and human–robot interaction in an unstructured open environment, fast and accurate tracking and strong disturbance rejection ability are required. However, utilizing a conventional controller can make it difficult for the robot to meet these demands, and when a robot is required to perform at a high-speed and large range of motion, conventional controllers may not perform effectively or even lead to the instability.

The main idea is to develop the control law by combining the SMC feedback with the ADRC control architecture to improve the robustness and control quality of a conventional SMC controller. The problem is formulated and solved in the framework of ADRC. For better estimation and control performance, a generalized proportional integral observer (GPIO) technique is employed to estimate and compensate for unmodeled dynamics and other unknown time-varying disturbances. And benefiting from the usage of GPIO, a new SMC law can be designed by synthesizing the estimation and its history.

The employed methodology introduced a significant improvement in handling the uncertainties of the system parameters without compromising the nominal system control quality and intuitiveness of the conventional ADRC design. First, the proposed method combines the advantages of the ADRC and SMC method, which achieved the best tracking performance among these controllers. Second, the proposed controller is sufficiently robust to various disturbances and results in smaller tracking errors. Third, the proposed control method is insensitive to control parameters which indicates a good application potential.

High-performance robot tracking control is the basis for further robot applications in open environments and human–robot interfaces, which require high tracking accuracy and strong disturbance rejection. However, both the varied dynamics of the system and rapidly changing nonlinear coupling characteristic significantly increase the control difficulty. The proposed method gives a new replacement of PID controller in robot systems, which does not require an accurate dynamic system model, is insensitive to control parameters and can perform promisingly for response rapidity and steady-state accuracy, as well as in the presence of strong unknown disturbances.

The study aims to promote independent mobility for persons with visual impairment or legal blindness (VIB) by developing a Web-based wayfinding application using geographic information systems (GIS). While the literature mainly focuses on technical devices presenting results for wayfinding, a lack of integration of user needs is identified. The inclusive, participative developed application offers step-by-step directions for pre-trip planning through an accessible user interface.

The paper presents a semi-automated approach to extract a pedestrian routing network data set based on open government data and field survey. User profiles calculate different routes using a weighting scheme for landmarks, orientation hints, infrastructure of crossings and sidewalks. The adoption of ArcGIS Web AppBuilder widgets allows access of the user interface additionally through keyboard-only navigation and therefore screen-reader capability.

GIS offers a powerful tool to design network analysis for persons with VIB. The routing algorithm accesses different user profiles, returning individualized turn-by-turn directions. The complex set of attributes, including shorelines, landmarks and barriers, can be integrated by semi-automated processes.

The paper illustrates the benefit of GIS applications for wayfinding of persons with VIB to raise self-determination and independence.

A ubiquitous pedestrian sidewalk network for a medium-size city comprises a novelty, as research has mainly focused on small areas. The integration of shorelines next to a various number of hints, landmarks and potential barriers through semi-automated processes allows reproducibility and transferability of the model to other cities.

Modern meat processing requires automation and robotisation to remain sustainable and adapt to future challenges, including those brought by global infection events. Automation of all or many processes is seen as the way forward, with robots performing various tasks instead of people. Meat cutting is one of these tasks. Smart novel solutions, including smart knives, are required, with the smart knife being able to analyse and predict the meat it cuts. This paper aims to review technologies with the potential to be used as a so-called “smart knife” The criteria for a smart knife are also defined.

This paper reviews various technologies that can be used, either alone or in combination, for developing a future smart knife for robotic meat cutting, with possibilities for their integration into automatic meat processing. Optical methods, Near Infra-Red spectroscopy, electrical impedance spectroscopy, force sensing and electromagnetic wave-based sensing approaches are assessed against the defined criteria for a smart knife.

Optical methods are well established for meat quality and composition characterisation but lack speed and robustness for real-time use as part of a cutting tool. Combining these methods with artificial intelligence (AI) could improve the performance. Methods, such as electrical impedance measurements and rapid evaporative ionisation mass spectrometry, are invasive and not suitable in meat processing since they damage the meat. One attractive option is using athermal electromagnetic waves, although no commercially developed solutions exist that are readily adaptable to produce a smart knife with proven functionality, robustness or reliability.

This paper critically reviews and assesses a range of sensing technologies with very specific requirements: to be compatible with robotic assisted cutting in the meat industry. The concept of a smart knife that can benefit from these technologies to provide a real-time “feeling feedback” to the robot is at the centre of the discussion.