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The purpose of this paper is to improve the computational speed of solving nonlinear dynamics by using parallel methods and mixed-precision algorithm on graphic processing units (GPUs). The computational efficiency of traditional central processing units (CPUs)-based computer aided engineering software has been difficult to satisfy the needs of scientific research and practical engineering, especially for nonlinear dynamic problems. Besides, when calculations are performed on GPUs, double-precision operations are slower than single-precision operations. So this paper implemented mixed precision for nonlinear dynamic problem simulation using Belytschko-Tsay (BT) shell element on GPU.

To minimize data transfer between heterogeneous architectures, the parallel computation of the fully explicit finite element (FE) calculation is realized using a vectorized thread-level parallelism algorithm. An asynchronous data transmission strategy and a novel dependency relationship link-based method, for efficiently solving parallel explicit shell element equations, are used to improve the GPU utilization ratio. Finally, this paper implements mixed precision for nonlinear dynamic problems simulation using the BT shell element on a GPU and compare it to the CPU-based serially executed program and a GPU-based double-precision parallel computing program.

For a car body model containing approximately 5.3 million degrees of freedom, the computational speed is improved 25 times over CPU sequential computation, and approximately 10% over double-precision parallel computing method. The accuracy error of the mixed-precision computation is small and can satisfy the requirements of practical engineering problems.

This paper realized a novel FE parallel computing procedure for nonlinear dynamic problems using mixed-precision algorithm on CPU-GPU platform. Compared with the CPU serial program, the program implemented in this article obtains a 25 times acceleration ratio when calculating the model of 883,168 elements, which greatly improves the calculation speed for solving nonlinear dynamic problems.

This paper aims to review in-memory computing (IMC) for machine learning (ML) applications from history, architectures and options aspects. In this review, the authors investigate different architectural aspects and collect and provide our comparative evaluations.

Collecting over 40 IMC papers related to hardware design and optimization techniques of recent years, then classify them into three optimization option categories: optimization through graphic processing unit (GPU), optimization through reduced precision and optimization through hardware accelerator. Then, the authors brief those techniques in aspects such as what kind of data set it applied, how it is designed and what is the contribution of this design.

ML algorithms are potent tools accommodated on IMC architecture. Although general-purpose hardware (central processing units and GPUs) can supply explicit solutions, their energy efficiencies have limitations because of their excessive flexibility support. On the other hand, hardware accelerators (field programmable gate arrays and application-specific integrated circuits) win on the energy efficiency aspect, but individual accelerator often adapts exclusively to ax single ML approach (family). From a long hardware evolution perspective, hardware/software collaboration heterogeneity design from hybrid platforms is an option for the researcher.

IMC’s optimization enables high-speed processing, increases performance and analyzes massive volumes of data in real-time. This work reviews IMC and its evolution. Then, the authors categorize three optimization paths for the IMC architecture to improve performance metrics.

This paper presents a reclassification of markers for mixed reality environments that is also applicable to the use of markers in robot navigation systems and 3D modelling. In the case of Augmented Reality (AR) mixed reality environments, markers are used to integrate computer generated (virtual) objects into a predominantly real world, while in Augmented Virtuality (AV) mixed reality environments, the goal is to integrate real objects into a predominantly virtual (computer generated) world. Apart from AR/AV classifications, mixed reality environments have also been classified by reality; output technology/display devices; immersiveness as well as by visibility of markers.

The approach adopted consists of presenting six existing classifications of mixed reality environments and then extending them to define new categories of abstract, blended, virtual augmented, active and smart markers. This is supported with results/examples taken from the joint Mixed Augmented and Virtual Reality Laboratory (MAVRLAB) of the Ulster University, Belfast, Northern Ireland; the Abdus Salam International Centre for Theoretical Physics (ICTP), Trieste, Italy and Santasco SrL, Regio Emilia/Milan, Italy.

Existing classification of markers and mixed reality environments are mainly binary in nature and do not adequately capture the contextual relationship between markers and their use and application. The reclassification of markers into abstract, blended and virtual categories captures the context for simple use and applications while the categories of augmented, active and smart markers captures the relationship for enhanced or more complex use of markers. The new classifications are capable of improving the definitions of existing simple marker and markerless mixed reality environments as well as supporting more complex features within mixed reality environments such as co-location of objects, advanced interactivity, personalised user experience.

It is thought that applications and devices in mixed reality environments when properly developed and deployed enhances the real environment by making invisible information visible to the user. The current work only marginally covers the use of internet of things (IoT) devices in mixed reality environments as well as potential implications for robot navigation systems and 3D modelling.

The use of these reclassifications enables researchers, developers and users of mixed reality environments to select and make informed decisions on best tools and environment for their respective application, while conveying information with additional clarity and accuracy. The development and application of more complex markers would contribute in no small measure to attaining greater advancements in extending current knowledge and developing applications to positively impact entertainment, business and health while minimizing costs and maximizing benefits.

The originality of this paper lies in the approach adopted in reclassifying markers. This is supported with results and work carried out at the MAV Reality Laboratory of Ulster University, Belfast–UK, the Abdus Salam International Centre for Theoretical Physics (ICTP), Trieste-Italy and Santasco SrL, Regio Emilia, Milan–Italy. The value of present research lies in the definitions of new categories as well as the discussions of how they improve mixed reality environments and application especially in the health and education sectors.

The increasing use of rapid prototyping (RP) which fabricates complicated models easily, has highlighted the desire for making metal models also with RP technology. However, direct RP technology for metal models is not established yet. This paper presents a technology for manufacturing sacrificial patterns using salt powder. By soaking in water the salt patterns can be removed from moulds very easily. They are converted to metal models very easily through investment casting. The feasibility of the method was examined by laminating salt powder with 3D printing method. In the preliminary test it turned out that pure salt powder is unsatisfactory. So flour was mixed with salt powder for the absorption of the binder, because it is insoluble in water and readily available at low cost. Controlling the mixing ratio tests were made to examine the quality of the salt patterns, and showed promising results not only as sacrificial patterns but also as conventional 3D models. Then metallic models with complicated shapes were fabricated by casting in plaster using these salt models as patterns, and it was proven that these salt models can be used in investment casting as sacrificial patterns.

The objective of this paper is to investigate the efficiency of hybrid solution methods when incorporated into large‐scale optimization problems solved by evolution strategies (ESs) and to demonstrate their influence on the overall performance of these optimization algorithms. ESs imitate biological evolution and combine the concept of artificial survival of the fittest with evolutionary operators to form a robust search mechanism. In this paper modified multi‐membered evolution strategies with discrete variables are adopted. Two solution methods are implemented based on the preconditioned conjugate gradient (PCG) algorithm. The first method is a PCG algorithm with a preconditioner resulted from a complete Cholesky factorization, and the second is a PCG algorithm in which a truncated Neumann series expansion is used as a preconditioner. The numerical tests presented demonstrate the computational advantages of the proposed methods, which become more pronounced in large‐scale optimization problems and in a parallel computing environment.

Investigates the efficiency of hybrid solution methods when incorporated into large‐scale topology and shape optimization problems and to demonstrate their influence on the overall performance of the optimization algorithms. Implements three innovative solution methods based on the preconditioned conjugate gradient (PCG) and Lanczos algorithms. The first method is a PCG algorithm with a preconditioner resulted from a complete or an incomplete Cholesky factorization, the second is a PCG algorithm in which a truncated Neumann series expansion is used as preconditioner, and the third is a preconditioned Lanczos algorithm properly modified to treat multiple right‐hand sides. The numerical tests presented demonstrate the computational advantages of the proposed methods which become more pronounced in large‐scale and/or computationally intensive optimization problems.

This study aims to determine the braking performance of limestone as a filler in brake friction materials.

Samples containing limestone material (30-35-40%), which can be an alternative to brake friction material filler, were produced. The samples were weighed on precision scales, mixed homogeneously and produced using the hot molding method. The physical and tribological properties of the produced samples were determined, and their microscopic analyzes were made with scanning electron microscopy.

As the amount of limestone increased, the density of the samples decreased. The friction coefficient and wear rates were close to each other and within the optimum limits for all samples. Limestone materials can be used instead of barite materials studied in the literature on brake linings. Microcracks were observed only in samples containing 30% and 35% limestone in microscopic images.

In this study, the wear rate, coefficient of friction and microstructures on the friction surfaces of brake friction materials containing limestone were investigated. The usability of limestone as a filler in brake friction materials provides valuable information to researchers and industrial organizations in the brake friction material field.

Last year Massey Ferguson Manufacturing Ltd. decided to upgrade the durability of the finish on the agricultural tractor chassis produced at Banner Lane, Coventry, by switching from conventional melamine stoving alkyds to a two‐page epoxy primer, followed by a two‐pack acrylic topcoat. Application of these two‐component materials calls for precise metering of each component and their efficient mixing in order to obtain consistent quality of finish. Additionally, the metering and mixing pump units must be easy to clean after use in order to prevent the coating hardening up within the equipment.

The purpose of this study is to examine accountants’ application of principles-based accounting standards to a lawsuit contingency recognition scenario and the potential role that accounting work experience plays in mitigating accountants’ aggressive financial reporting.

This study presents a 2 × 2 between-subjects experiment with accounting experience (measured as high vs low) and contingency type (asset vs liability) as independent variables and accountants’ lawsuit contingency conservatism likelihood judgments and US$ recognition recommendations as the dependent variables.

Consistent with expectations, findings indicate that more experienced accountants are more likely to recognize liabilities and items that decrease income and less likely to recognize assets and items that increase income than their less experienced counterparts. Accountants also recommended recognizing lower (higher) mean US$ amounts for assets (liabilities), as expected. Supplemental analyses show a significant moderated-mediated effect whereby the interactive effect of contingency type and accounting experience on individuals’ US$ recognition recommendations is partially mediated through the nature of the conservatism judgment.

The finding that less experienced accountants report more aggressively than more experienced accountants when applying a principles-based standard supports the call for using judgment frameworks in imprecise standard settings and suggests that firms may want to ensure that accountants with adequate work experience are on hand as U.S. generally accepted accounting principles become more principles-based over time.

To the best of the authors’ knowledge, this study is the first to examine the impact of accounting work experience on the application of principles-based accounting standards and the mitigation of aggressive financial reporting. Our supplemental analyses also identify the nature of the conservatism judgment as a mediating mechanism which partially explains more experienced accountants’ US$ asset and liability recognition recommendations.