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The brake controller is a key component of the locomotive brake system. It is essential to study its safety.

This paper summarizes and analyzes typical faults of the brake controller, and proposes four categories of faults: position sensor faults, microswitch faults, mechanical faults and communication faults. Suggestions and methods for improving the safety of the brake controller are also presented.

In this paper, a self-judgment and self-learning dynamic calibration method is proposed, which integrates the linear error of the sensor and the manufacturing and assembly errors of the brake controller to solve the output drift. This paper also proposes a logic for diagnosing and handling microswitch faults. Suggestions are proposed for other faults of brake controller.

The methods proposed in this paper can greatly improve the usability of the brake controller and reduce the failure rate.

This study experimentally aims to determine the degree of influence that mindfulness training exerts on learning capacity at the university level and contrasts it with previous observational or relational studies that have shown contradictory results.

A quasi-experiment was carried out to measure the variation of six academic learning abilities – a) self-efficacy, b) organization of and attention to studies, c) stress control due to time pressure and the environment, d) involvement with college activity, e) emotional satisfaction, and f) class communication – which together comprise the research questionnaire called the college learning effectiveness inventory (CLEI). The CLEI questionnaire was administered before and after the participants were trained in the mindfulness technique. The study was conducted in Ecuador, and the participants were selected from among the graduate students of a local university.

The learning ability measured by the CLEI was improved by a statistically significant margin in the two groups.

The treatment groups consisted of graduate students who did not have opportunities for full-time activities on campus, as they were limited to attending regular classes at specific times, usually at night. The dropout rate was 14% due to inconveniences caused by the pandemic. These conditions could have affected the study results both positively and negatively. In addition, the pandemic limited academic interactions, which are required to evaluate the learning results after applying the research instrument. This limitation was especially critical for people who had experienced online classes only.

Offering graduate students the opportunity to learn about and adopt a mindfulness practice helps to improve their academic outcomes, as reflected through the statistical measurement of the CLEI indicator.

This study is especially relevant within the context of sanitary conditions due to the pandemic and the intensive use of technology for managing academic interactions, both of which have replaced physical contact between participants.

The main contributions of this study are related to the determination of the practical effects of mindfulness training in postgraduate university settings and the identification of the mechanisms involving participants' reflecting upon, learning and understanding the importance of perfecting their soft skills to facilitate their learning processes and face today's uncertain environments.

本研究採用實驗方法、來釐定正念認知對在大學水平上的學習能力的影響程度，並對比於以往顯示了相互矛盾的研究結果的觀察性研究或關係研究。

研究人員進行準實驗、來量度六個學術學習能力的變化。這六個學習能力為：(一) 自我效能, (二) 學習的組織能力和注意力，(三) 控制因時間壓力和環境因素而產生的壓力, (四) 大學活動的參與，(五) 情緒方面的滿足、及 (六) 課堂之溝通。這六個學習能力合起來就構成本研究的調查問卷，我們稱之為大學學習效能清單。問卷調查工作分別於研究參與者接受正念認知技巧訓練之前及之後進行。本研究是在厄瓜多爾進行的，而參與者則選自當地一間大學的研究生。

研究結果顯示、根據大學學習效能清單的測量，有關的兩個組別均顯示明顯數據差額範圍上的學習能力提昇。

若為研究生提供學習正念認知技巧的機會，並讓他們應用這技巧，他們的學習成果將會得到提昇，這正是透過數據上量度有關的大學學習效能清單指標所顯示的現象。

本研究的結果，就現時的衛生狀況而言特具意義。這是由於大流行病的發生，以及在管理學術互動上大量使用應用技術，參與者之間的身體接觸也不需要了。

本研究的主要貢獻為、研究結果確認了在大學研究院的學習環境裡，正念認知的培訓是有其實用效果的;研究亦找出了參與者應如何有效地反省思考和學習提昇其軟技能的方法，並了解其重要性，以能增強他們的學習能力，以及更能應對今天不明確的環境。

The purpose of this paper is to propose a system dynamic simulated process model for maintenance work management incorporating the Fourth Industrial Revolution (4IR) technologies.

The extant literature in physical assets maintenance depicts that poor maintenance management is predominantly because of a lack of a clearly defined maintenance work management process model, resulting in poor management of maintenance work. This paper solves this complex phenomenon using a combination of conceptual process modeling and system dynamics simulation incorporating 4IR technologies. A process for maintenance work management and its control actions on scheduled maintenance tasks versus unscheduled maintenance tasks is modeled, replicating real-world scenarios with a digital lens (4IR technologies) for predictive maintenance strategy.

A process for maintenance work management is thus modeled and simulated as a dynamic system. Post-model validation, this study reveals that the real-world maintenance work management process can be replicated using system dynamics modeling. The impact analysis of 4IR technologies on maintenance work management systems reveals that the implementation of 4IR technologies intensifies asset performance with an overall gain of 27.46%, yielding the best maintenance index. This study further reveals that the benefits of 4IR technologies positively impact equipment defect predictability before failure, thereby yielding a predictive maintenance strategy.

The study focused on maintenance work management system without the consideration of other subsystems such as cost of maintenance, production dynamics, and supply chain management.

The maintenance real-world quantitative data is retrieved from two maintenance departments from company A, for a period of 24 months, representing years 2017 and 2018. The maintenance quantitative data retrieved represent six various types of equipment used at underground Mines. The maintenance management qualitative data (Organizational documents) in maintenance management are retrieved from company A and company B. Company A is a global mining industry, and company B is a global manufacturing industry. The reliability of the data used in the model validation have practical implications on how maintenance work management system behaves with the benefit of 4IR technologies' implementation.

This research study yields an overall benefit in asset management, thereby intensifying asset performance. The expected learnings are intended to benefit future research in the physical asset management field of study and most important to the industry practitioners in physical asset management.

This paper provides for a model in which maintenance work and its dynamics is systematically managed. Uncontrollable corrective maintenance work increases the complexity of the overall maintenance work management. The use of a system dynamic model and simulation incorporating 4IR technologies adds value on the maintenance work management effectiveness.

Both geometric and non-geometric parameters have noticeable influence on the absolute positional accuracy of 6-dof articulated industrial robot. This paper aims to enhance it and improve the applicability in the field of flexible assembling processing and parts fabrication by developing a more practical parameter identification model.

The model is developed by considering both geometric parameters and joint stiffness; geometric parameters contain 27 parameters and the parallelism problem between axes 2 and 3 is involved by introducing a new parameter. The joint stiffness, as the non-geometric parameter considered in this paper, is considered by regarding the industrial robot as a rigid linkage and flexible joint model and adds six parameters. The model is formulated as the form of error via linearization.

The performance of the proposed model is validated by an experiment which is developed on KUKA KR500-3 robot. An experiment is implemented by measuring 20 positions in the work space of this robot, obtaining least-square solution of measured positions by the software MATLAB and comparing the result with the solution without considering joint stiffness. It illustrates that the identification model considering both joint stiffness and geometric parameters can modify the theoretical position of robots more accurately, where the error is within 0.5 mm in this case, and the volatility is also reduced.

A new parameter identification model is proposed and verified. According to the experimental result, the absolute positional accuracy can be remarkably enhanced and the stability of the results can be improved, which provide more accurate parameter identification for calibration and further application.

Aircraft structures are mainly connected by riveting joints, whose quality and mechanical performance are directly determined by vertical accuracy of riveting holes. This paper proposed a combined vertical accuracy compensation method for drilling and riveting of aircraft panels with great variable curvatures.

The vertical accuracy compensation method combines online and offline compensation categories in a robot riveting and drilling system. The former category based on laser ranging is aimed to correct the vertical error between actual and theoretical riveting positions, and the latter based on model curvature is used to correct the vertical error caused by the approximate plane fitting in variable-curvature panels.

The vertical accuracy compensation method is applied in an automatic robot drilling and riveting system. The result reveals that the vertical accuracy error of drilling and riveting is within 0.4°, which meets the requirements of the vertical accuracy in aircraft assembly.

The proposed method is suitable for improving the vertical accuracy of drilling and riveting on panels or skins of aerospace products with great variable curvatures without introducing extra measuring sensors.

The purpose of this paper is to introduce an approach in measuring the shielding gas flow within laser powder bed fusion (L-PBF) machines under near-process conditions (regarding oxygen content and shielding gas flow).

The measurements are made sequentially using a hot-wire anemometer. After a short introduction into the measurement technique, the system which places the measurement probe within the machine is described. Finally, the measured shielding gas flow of a commercial L-PBF machine is presented.

An approach to measure the shielding gas flow within SLM machines has been developed and successfully tested. The use of a thermal anemometer along with an automated probe-placement system enables the space-resolved measurement of the flow speed and its turbulence.

The used single-normal (SN) hot-wire anemometer does not provide the flow vectors’ orientation. Using a probe with two or three hot-films and an improved placement system will provide more information about the flow and less disturbance to it.

A measurement system which allows the measurement of the shielding gas flow within commercial L-PBF machines is presented. This enables the correlation of the shielding gas flow with the resulting parts’ quality.

The authors analyze the equilibrium effects of non-tradable assets on optimal policy portfolios. They study how the existence of non-tradable assets impacts optimal asset allocation decisions of investors who own such assets and of investors who do not have access to non-tradable assets.

In this theoretical analysis, the authors analyze a model with tradable and non-tradable asset classes whose cash flows are jointly normally distributed. There are two types of investors, with and without access to non-tradable assets. All investors have constant absolute risk aversion preferences. The authors derive closed form solutions for optimal investor demand and equilibrium asset prices. They calibrated the model using US data for listed equity, bonds and private equity. Further, the authors illustrate the sensitivities of quantities and prices with respect to the main parameters.

The study finds that the existence of non-tradable assets has a large impact on optimal asset allocation. Investors with (without) access to non-tradable assets tilt their portfolios of tradable assets away from (toward) assets to which non-tradable assets exhibit positive betas.

The model provides important insights not only for investors holding non-tradable assets such as private equity but also for investors who do not have access to non-tradable assets. Investors who ignore the effect of non-tradable assets when reverse-engineering risk premia from asset covariances and market capitalizations might severely underestimate the equity risk premium.

The authors provide the first comprehensive analysis of the equilibrium effects of non-tradability of some assets on optimal policy portfolios. Thus, this paper goes beyond analyzing the effects of market imperfections on individual portfolio choices.

Aircraft assembly is the crucial part of aircraft manufacturing, and to meet the high-precision and high-efficiency requirements, cooperative measurement consisting of multiple measurement instruments and automatic assisted devices is being adopted. To achieve the complete data of all assembly features, measurement devices need to be placed at different positions, and the flexible and efficient transfer relies on Automated Guided Vehicles (AGVs) and robots in the large-size space and close range. This paper aims to improve the automatic station transfer in accuracy and flexibility.

A transferring system with Light Detection and Ranging (LiDAR) and markers is established. The map coupling for navigation is optimized. Markers are distributed according to the accumulated uncertainties. The path planning method applied to the collaborative measurement is proposed for better accuracy. The motion planning method is optimized for better positioning accuracy.

A transferring system is constructed and the system is verified in the laboratory. Experimental results show that the proposed system effectively improves positioning accuracy and efficiency, which improves the station transfer for the cooperative measurement.

A Transferring system for collaborative measurement is proposed. The optimized navigation method extends the application of visual markers. With this system, AGV is capable of the cooperative measurement of large aircraft structural parts.

This study aims to focus on the development of an experimental setup for testing tribological pairings under a gas atmosphere at pressures up to 10 bar.

A pressure chamber allowing oscillating movement through an outer shaft was constructed and mounted on an oscillating tribometer. Due to a metal spring bellows system, a methodology for the evaluation of the coefficient of friction values separately from the spring forces was developed.

The selected material concept was qualitatively and quantitatively assessed. An evaluation of the static and the dynamic coefficient of friction was performed, which was crucial for the understanding of the adhesion effects of the tested material pairing. The amount of information that is lost due to averaging the measured friction values is higher than one would expect.

The developed experimental setup is unique and, compared with the existing tribometers for testing under gas ambient pressures, allows testing under contact conditions that are closer to real applications, such as compressors and expanders. An in-depth observation of the adhesion and stick–slip effects of the tested material pairings is possible as well.

The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-06-2023-0173/

China's economic transition is essentially the process of China's institutional changes. During the changes, the appearance of institutional innovation is not regular; instead, it is intermittent and random. The purpose of this paper is to show that the fitful appearance of institutional innovation is the root of China's economic growth and fluctuations.

This paper constructs a real business cycle (RBC) model introducing the institutional factor expressed in the quantitative form under the dynamic stochastic general equilibrium (DSGE) framework by measuring China's institutional changes quantitatively.

By comparing the characteristics of the actual economic data with those of the simulated economic data, we find that this RBC model can explain 94.44%, 66.07%, 23.46%, 21.03% and 15.45% of the cyclical fluctuations in output, investment, labor, consumption and capital, respectively.

The impulse response analysis finds that the institutional shocks have a relatively long duration, lasting about 30 years, and decline slowly over time, while technological shocks decline relatively fast, lasting approximately ten years.