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The purpose of this paper is to reduce the calculation burden and speed up the estimation process of Allan variance method while ensuring the exactness of the analysis results.

A series of six‐hour static tests have been implemented at room temperature, and the static measurements have been collected from MEMS IMU. In order to characterize the various types of random noise terms for the IMU, the basic definition and main procedure of the Allan variance method are investigated. Unlike the normal Allan variance method, which has the shortcomings of processing large data sets and requiring long computation time, a modified Allan variance method is proposed based on the features of data distribution in the log‐log plot of the Allan standard deviation versus the averaging time.

Experiment results demonstrate that the modified Allan variance method can effectively estimate the noise coefficients for MEMS IMU, with controllable computation time and acceptable estimation accuracy.

This paper proposes a time‐controllable Allan variance method which can quickly and accurately identify different noise terms imposed by the stochastic fluctuations.

The purpose of this paper is to propose a yard allocation model via objective programming. This is initially postulated based on a rolling‐horizon strategy, which aims at allotting outbound containers into yard.

To resolve the NP‐hard problem regarding the yard allocation model, a hybrid algorithm, which applies heuristic rules and distributed genetic algorithm (DGA), is then employed.

It could be observed from the case study that this proposed approach is proven effective for resolving the container yard allocation problem. The total loading time onto vessels, the total horizontal transportation distance and the imbalance among blocks are improved.

This paper does not deal with equipment scheduling.

This approach helps to minimize turnaround time; handling cost of vessels; the workloads among blocks are balanced for each vessel; and the total distance of container transportation.

This paper designs a hybrid algorithm, which integrates heuristic rules and DGA. In details, the heuristic rules are developed for generating feasible solutions, while the DGA was applied for optimizing these solutions.

The purpose of this study is to explore the association between eating patterns, social identity and the well-being of adolescents via a mixed methods study of Chinese teenagers. The specific research questions presented in this study are as follows: What is the relationship between social eating and well-being? How is the relationship between social eating and well-being mediated by social identity?

This study is based on a sequential mixed methods study, including interviews with 16 teenage–parent dyads, and a large-scale survey of over 1,000 teenagers on their eating patterns, conducted with the support of public schools. A model that tests relationships among social eating, social identity and subjective well-being is developed and tested.

The results show that dining with family members leads to improved subjective well-being for teenagers, through a partial mediator of stronger family identity. However, dining with peers is not found to influence subjective well-being.

The privileged position of family meals demonstrated through this study may be an artifact of the location of this study in one Chinese city. Further research is needed related to the connections among social identity, objective well-being and the social patterns of teenagers’ food consumption behavior.

To improve the subjective well-being of teenagers, families, public policy-makers and food marketers should support food consumption patterns that promote family meals.

While many food-related consumer studies focus on the individual, social and environmental influences of food choices of adolescents, few studies address how eating patterns affect overall well-being. These results reinforce the importance of understanding the effect of the social context of teenagers’ eating patterns on health and well-being.

Since the first automated container terminal (ACT) was introduced at Europe Container Terminals Delta Terminal in Port Rotterdam back in the year 1992, a lot of research had been done to improve the management of ACT. However, up until recently, the number of literature available still appeared scarce. Hence, this paper aims to review the collection of literature about ACT to generate an exhaustive summary to answer the formulated review question in this study.

Preferred reporting items for systematic reviews and meta-analyses to narrow down the search parameters of literature retrieved so that only relevant articles were only selected. The systematic literature reviews were applied to analyse the content of the articles retrieved to determine its journal ranking, research findings and timeline of publications.

The adoption of ACT technology by container terminal operators could increase the terminal efficiency in productivity, cost reduction and environmental sustainability. Owing to global environmental awareness, the research trend of container terminal field and container terminal operator in the terminal design is much more environmentally friendly oriented.

The limited numbers of experts in the management of ACT are causing challenges in data collections.

The analysis of the global ACT trend could help academicians and industrial investors to review the revolution timeline of maritime technology in port and shipping that is happening rapidly.

The analysis of timeline and collective literature leads to the propose of the conceptual framework to determine the relationship between increased productivity, cost reduction and environmentally sustainable.

The purpose of this paper is to provide a multi‐criteria bidding evaluation model based on Istanbul 2010 PR selection problem to strike a balance among conflicting criteria and to aggregate opinions held by a group of decision makers.

In the study, analytic hierarchy process (AHP) methodology was used to settle the conflict properly. The evaluation criteria were transformed into a hierarchical form and their relative weights were calculated and synthesized for the final ranking of the bidders. Then a linear interpolation‐based spreadsheet model was combined with findings of the AHP to fairly select best bidders.

The paper demonstrates that the hierarchical structure of the AHP methodology can successfully resolve the conflict among evaluation criteria and measure relative importance of the criteria by taking into account the preference of the decision makers. Moreover, a linear interpolation methodology can evaluate quoted bid prices fairly and can help to make the best decision.

In all areas of business management, there is a great need for fair bid evaluation systems. The method presented in the paper will help future studies in designing more intriguing systems and resolving conflicts in the area of bid evaluation.

This paper aims to present the result of a scientometric analysis conducted using studies on high-performance computing in computational modelling. This was done with a view to showcasing the need for high-performance computers (HPC) within the architecture, engineering and construction (AEC) industry in developing countries, particularly in Africa, where the use of HPC in developing computational models (CMs) for effective problem solving is still low.

An interpretivism philosophical stance was adopted for the study which informed a scientometric review of existing studies gathered from the Scopus database. Keywords such as high-performance computing, and computational modelling were used to extract papers from the database. Visualisation of Similarities viewer (VOSviewer) was used to prepare co-occurrence maps based on the bibliographic data gathered.

Findings revealed the scarcity of research emanating from Africa in this area of study. Furthermore, past studies had placed focus on high-performance computing in the development of computational modelling and theory, parallel computing and improved visualisation, large-scale application software, computer simulations and computational mathematical modelling. Future studies can also explore areas such as cloud computing, optimisation, high-level programming language, natural science computing, computer graphics equipment and Graphics Processing Units as they relate to the AEC industry.

The study assessed a single database for the search of related studies.

The findings of this study serve as an excellent theoretical background for AEC researchers seeking to explore the use of HPC for CMs development in the quest for solving complex problems in the industry.