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Engineered material arresting systems (EMASs) are dedicated to stopping aircraft that overrun the runway before they enter dangerous terrain. The system consists of low-strength foamed concretes. The core component of the arresting system design is a reliable simulation model. Aircraft test verification is required before the practical application of the model. This study aims to propose a simulation model for the arresting system design and conducts serial verification tests.

Six verification tests were conducted using a Boeing 737 aircraft. The aircraft was equipped with an extra inertia navigation system and a strain gauge system to measure its motion and the forces exerted on the landing gears. The heights of the arrestor beds for these tests were either 240 or 310 mm, and the entering speeds of the aircraft ranged from 23.9 to 60.6 knots.

Test results revealed that both the aircraft and the pilots on board were safe after the tests. The maximum transient acceleration experienced by the dummies on board was 2.5 g, which is within the human tolerance. The model exhibited a satisfied accuracy to the field tests, as the calculation errors of the stopping distances were no greater than 7 per cent.

This study proposes a simulation model for the arresting system design and conducts serial verification tests. The model can be used in EMAS design.

The purpose of this study was to develop a TiAlSiCN coating with high bonding and hardness, ultra-low friction and good lubrication characteristics, which provided an experimental basis for the surface modification of YT14 cemented carbide cutting tools.

In this work, a TiAlSiCN coating was deposited on YT14 cemented carbide cutting tool through cathodic arc ion plating. The surface-interface morphologies, distributions of chemical elements, phases, bonding energy and surface roughness were analyzed using field emission scanning electron microscopy, energy-dispersive spectroscopy (EDS), X-ray diffraction, X-ray photoelectron spectroscopy and atomic force microscopy, respectively, and the coating the bonding strength were quantitatively characterized with a scratch.

The average COFs of the TiAlSiCN coating at 700°C, 800°C and 900°C were 0.68, 0.57 and 0.38, respectively, showing that the TiAlSiCN coating was an effective lubricant at a high temperature, and the wear rate of the coating increases with wear temperature. After wearing at 700°C, 800°C and 900°C, the Ti, Si and N elements form atom-poor regions, while Al forms an atom-rich region, showing that the oxides of Ti, Al and Si are formed to improve the wear resistance of the coating. The wear mechanism of TiAlSiCN coating at high temperatures was composed of abrasive wear and oxidation wear.

The friction-wear behaviors of TiAlSiN coating were investigated using an HT-1000-type high-temperature friction wear tester, and the worn tracks on the coatings were analyzed using an EDS plane scan, thus obtaining the wear mechanism of TiAlSiN coating.

While the phenomenon of technostress has received significant attention from researchers in recent years, empirical findings concerning the consequences of specific forms of techno-stressors have remained scattered and contradictory. The authors aim to integrate the conclusions of previous studies to understand the effects of specific techno-stressors on strain and job performance.

This study employs meta-analytic techniques to calibrate the findings of 67 studies investigating more than 63,100 employees.

In general, not all techno-stressors have adverse effects. In particular, techno-uncertainty does not impact job performance. In addition, relative weight analyses reveal the relative importance of techno-complexity and techno-insecurity as predictors of both strain and job performance. Finally, this study finds that the effects of specific techno-stressors on job performance vary depending on research participants' gender, educational attainment and employment status.

First, this study provides a more nuanced view of the effects of specific techno-stressors. Second, this research clarifies the relative importance of specific techno-stressors as predictors of strain and job performance. Finally, this study reveals the moderating effects of demographic variables on the relationships between specific techno-stressors and job performance.

The growing importance of the service sector in almost every economy in the world has created a significant amount of interest in service operations. In practice, many service sectors have sought and made use of various enhancement programs to improve their operations and performance in an attempt to hold competitive success. As most researchers recognize, service operations link with customers. The customers as participants act in the service operations system driven by the goal of sufficing his/her added values. This is one of the distinctive features of service production and consumption. In the paper, first, we propose the idea of service operations improvement by mapping objectively the service experience of customers from the view of customer journey. Second, a portraying scheme of service experience of customers based on the IDEF3 technique is proposed, and last, some implications on service operations improvement are given.

Attention is one of the most important factors to affect the academic performance of students. Effectively analyzing students' attention in class can promote teachers' precise teaching and students' personalized learning. To intelligently analyze the students' attention in classroom from the first-person perspective, this paper proposes a fusion model based on gaze tracking and object detection. In particular, the proposed attention analysis model does not depend on any smart equipment.

Given a first-person view video of students' learning, the authors first estimate the gazing point by using the deep space–time neural network. Second, single shot multi-box detector and fast segmentation convolutional neural network are comparatively adopted to accurately detect the objects in the video. Third, they predict the gazing objects by combining the results of gazing point estimation and object detection. Finally, the personalized attention of students is analyzed based on the predicted gazing objects and the measurable eye movement criteria.

A large number of experiments are carried out on a public database and a new dataset that is built in a real classroom. The experimental results show that the proposed model not only can accurately track the students' gazing trajectory and effectively analyze the fluctuation of attention of the individual student and all students but also provide a valuable reference to evaluate the process of learning of students.

The contributions of this paper can be summarized as follows. The analysis of students' attention plays an important role in improving teaching quality and student achievement. However, there is little research on how to automatically and intelligently analyze students' attention. To alleviate this problem, this paper focuses on analyzing students' attention by gaze tracking and object detection in classroom teaching, which is significant for practical application in the field of education. The authors proposed an effectively intelligent fusion model based on the deep neural network, which mainly includes the gazing point module and the object detection module, to analyze students' attention in classroom teaching instead of relying on any smart wearable device. They introduce the attention mechanism into the gazing point module to improve the performance of gazing point detection and perform some comparison experiments on the public dataset to prove that the gazing point module can achieve better performance. They associate the eye movement criteria with visual gaze to get quantifiable objective data for students' attention analysis, which can provide a valuable basis to evaluate the learning process of students, provide useful learning information of students for both parents and teachers and support the development of individualized teaching. They built a new database that contains the first-person view videos of 11 subjects in a real classroom and employ it to evaluate the effectiveness and feasibility of the proposed model.

Using Social Network Analysis (SNA), this paper examines the inter-country airline logistics relationships in East Asia. Based on the flight schedule data, which has been gathered by the authors, the overall features of airline logistics structure and the specific roles of each airport could be more clearly examined.

The main results of this paper are as follows: Beijing has the highest Degree Centrality, but excluding the domestic lines, Incheon has the highest Degree Centrality, which would imply that a relatively high Centrality of logistics for China’s airports is due to the greater number of domestic lines. The focal hub status of Incheon airport is also supported by the fact that Incheon contains the highest Betweenness Centrality.

Secondly, evaluated by the types of brokerage role, Incheon has a remarkably strong role as a liaison, which means Incheon airport functions as a transfer hub between two different regions outside of Korea. However, considering only the to/from China airline links, Hong Kong has the highest score as a liaison. These conflicting results imply that as China’s airline transportation continuously increases, Hong Kong will become a strong rival to Incheon.

Thirdly, in the analysis of Structural Hole which functions the broker and acts as a hub by linking unconnected airports, Incheon has the highest possibilities as a hub airport. However, only considering to/from China airlines, Hong Kong would dominate Incheon.

Using consumption value theory, this study aims to examine the impact of tourists’ perceived consumption value dimensions of tea beverages offered by Hong Kong (HK)-style cafés, including taste value, price value, health value and emotional value, on tourists’ memorable experience (ME), satisfaction and revisit intention.

Using an online survey, this study collected 225 usable data from tourists who had experience in visiting HK-style cafés. Partial least squares–structural equation modelling was used to examine the importance of tourists’ value dimensions, including taste value, price value, health value and emotional value, on tourists’ ME, satisfaction and revisit intention.

The results revealed that taste value, price value, health value and emotional value are significant predictors of tourists’ ME in HK-style cafés, which in turn drive their satisfaction and revisit intention.

This study focusses on a single context: HK-style cafés. Future research may enhance the generalisability of the findings by replicating the model in other countries with diverse cultures.

Tourism marketers may strengthen tourists’ ME, satisfaction and revisit intention by promoting tea beverages as well as HK-style cafés. Tourism marketers are recommended to communicate taste value, price value, health value and emotional value of HK-style tea beverages, which in turn encourages tourists to learn about the features of tea beverages. Subsequently, it drives tourists’ ME and satisfaction, thereby strengthening their intention to revisit.

This study contributes to the tourism marketing literature by providing an understanding of the role of tea beverage value in driving tourists’ ME, satisfaction and revisit intention. By empirically testing a research model, this study confirms that specific consumption value elements of tea beverages, namely, taste value, price value, health value and emotional value, are critical drivers in driving tourists’ ME, satisfaction and revisit intention.

This special “Anbar Abstracts” issue of the Leadership & Organization Development Journal is split into four sections covering abstracts under the following headings: Culture, Change and Intervention; Management Styles and Techniques; Leadership and Decision; Communications.

Customized product development is facing the challenges of maintaining mass producibility and exploring customer perception on target products. This paper reports an approach by combining virtual prototyping (VP) with design by manufacturing simulation techniques. By constructing virtual prototypes, accurate assessments of mass producibility and customer acceptance will enable better informed design of customized products. The primary goal of VP for customized product development is to provide a multidisciplinary design definition and rapid prototyping environment for concept development and a tailored, scenario‐based simulation environment for concept evaluation within a single facility. This design environment facilitates the capture and utilization of information generated during the design phase, and the simultaneous generation, at design time, of manufacturing, materials, costing, and scheduling data, together with visual evaluation of customer perception on target products, hence supporting the implementation of concurrent engineering.