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Inspired by the development of eco-friendly flexible electronics, this paper aims to present a series of paper-based electronics drawn by pencils, which can be used as favorable sensing elements in daily life.

Pencil traces are deposited on the porous surface of Xerox paper by the mechanical exfoliation during writing process, which can be used as basic components to construct functional electronics for daily sensing applications. By changing pencil grade, the obtained traces can work as conductive wires, electrodes, resistors and piezoresistive gauges.

The experimental results confirm their practical applications in sensing several daily activities, including finger motion, touching and the temperature of water in paper cup. Moreover, the used electronics can be easily handled and recycled.

The shortage in functionality, reliability and performance consistency induced by manual operation is an evident challenge, which makes the pencil-on-paper devices more suitable to work as a temporary solution to satisfying the demands from emergency circumstances.

The pencil-on-paper devices, motivated by the electroconductibility and piezoresistivity of pencil trace, can be explored as sensing prototypes in detecting daily activities. Meantime, their advances in easy accessibility, rapid fabrication, low cost and eco-fitness endow them excellent capacity of meeting the “on-site, real-time” demands.

This paper aims to provide a focused review on the geometrical designs for performance enhancement of piezoresistive microaccelerometers.

By analyzing working principle and conventional geometries, the improved research proposals are sorted into three groups in terms of their anticipated objectives, including sensitivity, resonant frequency and cross-axis sensitivity. Accessible methods are outlined and their merits and demerits are described.

Novel geometries obviously enhance the performance of accelerometers, and the efficacy can be further elevated by newer materials and fabrication processes.

This paper mainly focused on the improved geometrical designs for sensitivity, resonant frequency and cross-axis sensitivity. Other performance parameters or design schemes are not included in this paper.

This paper generalizes the available geometries and methods for the enhancement of sensitivity, resonant frequency and cross-axis sensitivity in piezoresistive accelerometers design.

Simulation is a well-known technique for using computers to imitate or simulate the operations of various kinds of real-world facilities or processes. The facility or process of interest is usually called a system, and to study it scientifically, we often have to make a set of assumptions about how it works. These assumptions, which usually take the form of mathematical or logical relationships, constitute a model that is used to gain some understanding of how the corresponding system behaves, and the quality of these understandings essentially depends on the credibility of given assumptions or models, known as VV&A (verification, validation and accreditation). The main purpose of this paper is to present an in-depth theoretical review and analysis for the application of VV&A in large-scale simulations.

After summarizing the VV&A of related research studies, the standards, frameworks, techniques, methods and tools have been discussed according to the characteristics of large-scale simulations (such as crowd network simulations).

The contributions of this paper will be useful for both academics and practitioners for formulating VV&A in large-scale simulations (such as crowd network simulations).

This paper will help researchers to provide support of a recommendation for formulating VV&A in large-scale simulations (such as crowd network simulations).

Over the past decades, there has been significant research effort dedicated to the development of autonomous vehicles. The decision-making system, which is responsible for driving safety, is one of the most important technologies for autonomous vehicles. The purpose of this study is the use of an intensive learning method combined with car-following data by a driving simulator to obtain an explanatory learning following algorithm and establish an anthropomorphic car-following model.

This paper proposed car-following method based on reinforcement learning for autonomous vehicles decision-making. An approximator is used to approximate the value function by determining state space, action space and state transition relationship. A gradient descent method is used to solve the parameter.

The effect of car-following on certain driving styles is initially achieved through the simulation of step conditions. The effect of car-following initially proves that the reinforcement learning system is more adaptive to car following and that it has certain explanatory and stability based on the explicit calculation of R.

The simulation results show that the car-following method based on reinforcement learning for autonomous vehicle decision-making realizes reliable car-following decision-making and has the advantages of simple sample, small amount of data, simple algorithm and good robustness.

As the grey systems theory has been widely used in the field of sustainable development (SD) research, in the following, a short literature overview will be put forward, starting from the usage of these theories in the economic development, social inclusion and environmental protection contributions to the evolving process of SD during 2011–2021. The purpose of this paper is to identify some key studies from all the SD areas in which the grey systems can be used in order to open and to bring the researchers to new domains in which they can reveal their interest and in which they can successfully use the methods offered by the grey systems theory.

Using the search engine offered by the Google Scholar and the Web of Science (WoS), a literature review has been performed for the grey systems applications on SD research on both grey relational analysis (GRA) and grey forecasting. In addition, some grey evaluation theories – clustering evaluation models and grey target decision models – have also been presented.

Many grey models are widely used in the field of SD. Compared with other methods such as grey prediction, grey evaluation and decision-making model, GRA technology is the most used method, and the research using this method is more than three times that of all other methods.

The present paper identifies some of the most representative examples in which the grey system theory (GST) has been used, but, in the same time, there are a lot of studies that have not been mentioned here due to the lack of space.

The present paper focuses on the SD applications in which GST has been successfully used, bringing to the reader a general overview on this field and, in the same time, enables new research perspectives.

This study aims to develop a mathematical programming model for preemptive multi-mode resource-constrained project scheduling problems in construction with the objective of levelling resources considering renewable and non-renewable resources.

The proposed model was solved by the exact method and the genetic algorithm integrated with the solution modification procedure coded with MATLAB software. The Taguchi method was applied for setting the parameters of the genetic algorithm. Different numerical examples were used to show the validation of the proposed model and the capability of the genetic algorithm in solving large-sized problems. In addition, the sensitivity analysis of two parameters, including resource factor and order strength, was conducted to investigate their impact on computational time.

The results showed that preemptive activities obtained better results than non-preemptive activities. In addition, the validity of the genetic algorithm was evaluated by comparing its solutions to the ones of the exact methods. Although the exact method could not find the optimal solution for large-scale problems, the genetic algorithm obtained close to optimal solutions within a short computational time. Moreover, the findings demonstrated that the genetic algorithm was capable of achieving optimal solutions for small-sized problems. The proposed model assists construction project practitioners with developing a realistic project schedule to better estimate the project completion time and minimize fluctuations in resource usage during the entire project horizon.

There has been no study considering the interruption of multi-mode activities with fluctuations in resource usage over an entire project horizon. In this regard, fluctuations in resource consumption are an important issue that needs the attention of project planners.

The purpose of this paper is to maraging 18Ni-300 steel fabricate by powder bed based selective laser melting (SLM) process. Microstructure and mechanical properties of the maraging steel part before and after heat treatment at a slow cooling rate were investigated.

The microstructure of the printed part was observed by optical microscopy and scanning electron microscopy. The phases were determined by X-ray diffraction. The surface roughness of the part was recorded by a profilometer. The tensile properties and microhardness of the parts before and after heat treatment were characterized by an electronic universal tensile testing machine and a Vickers hardness tester, respectively.

Maraging 18Ni-300 steel part comprised of the martensitic phase and a small fraction of austenite phase. After heat treatment, the volume fraction of austenite slightly increased. The surface roughness of the part was about 96 µm. The printed part was dense, but irregular pores were present. The yield strength, ultimate tensile strength (UTS), elongation and Young’s modulus of as-fabricated parts were 554.7 MPa, 1173.1 MPa, 10.9% and 128.9 GPa, respectively. The yield strength, UTS, elongation and Young’s modulus of as-treated parts were 2065 MPa, 2225 MPa, 4.2% and 142.5 GPa, respectively. The microhardness values of surface and cross-section of the as-fabricated part were 407.1 HV and 443.0 HV, respectively. After short-time heat treatment, the microhardness values of the surface and cross-section of the part were 542.7 HV and 567.3 HV, respectively. After long-time heat treatment, the microhardness values of the surface and cross-section of the part were 524.4 HV and 454.8 HV, respectively. The microhardness and tensile strength increased significantly with decreasing elongation due to the changes in phases and microstructure of the parts after heat treatment.

This work studied the effect of heat treatment at 550°C combined with a subsequent slow cooling rate on microstructure and mechanical properties of maraging 18Ni-300 steel obtained by the powder bed based SLM process.

This paper aims to study the corrosion inhibition behavior of imidazopyridine and its three derivatives on brass.

The authors performed weight loss experiments, electrochemical experiments including the polarization curve and electrochemical impedance spectrum, corrosion morphology observation using scanning electron microscope (SEM) and atomic force microscope (AFM) and surface composition analysis via X-ray photoelectron spectroscopy (XPS) to analyze the corrosion inhibition behavior of imidazopyridine and its three derivatives on brass by using quantum chemical calculation (Gaussian 09), molecular dynamics simulation (M-S) and Langmuir adsorption isotherm.

According to the results, imidazole-pyridine and its derivatives were found to be modest or moderately mixed corrosion inhibitors; moreover, they were spontaneously adsorbed on the metal surface in a single-layer, mixed adsorption mode.

The corrosion inhibition properties of pyrazolo-[1,2-a]pyridine and its derivatives on brass in sulfuric acid solution were analyzed through weight loss and electrochemical experiments. Moreover, SEM and AFM were simultaneously used to observe the corrosion appearance. Furthermore, XPS was used to analyze the surface. Then, Gaussian 09 and M-S were combined along with the Langmuir adsorption isotherm to investigate the corrosion inhibition mechanism of imidazole-[1,2-a]pyridine and its derivatives.

Cyber security incidents pose a major threat to organisations. Reporting cyber security incidents and providing organisations with information about their true nature, type and volume, is crucial to inform risk-based decisions. Despite the importance of reporting cyber security incidents, little research has addressed employees’ motivations to do so. Therefore, the purpose of this study is to investigate the factors that influence employees to report cyber security incidents using the theory of planned behaviour as a theoretical framework.

Survey data were collected from a sample of 549 working Australian adults. Demographics were gathered, in addition to data using the Cyber Security Incident Reporting Inventory (CSIRI; pronounced, “Siri”).

Attitude towards reporting, subjective norms and perceived behavioural control each significantly predicted intention-to-report cyber security incidents. Perceived behavioural control also significantly predicted actual reporting behaviour.

The results of this study validate the application of the theory of planned behaviour to the cyber security incident reporting context, also indicating that the relationship between intention to report a cyber security incident and actual reporting behaviour may be facilitated by perceived behavioural control.

These findings can be applied to inform the development of strategies that increase employees’ cyber security incident reporting behaviour.

This study outlines the development of a new tool to measure attitudes, subjective norms and perceived behavioural control in relation to the reporting of cyber security incidents. To the best of the authors’ knowledge, this is the first study of its kind to identify the relationship between these factors and intentions to report cyber security incidents.