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Gives a bibliographical review of the finite element methods (FEMs) applied for the linear and nonlinear, static and dynamic analyses of basic structural elements from the theoretical as well as practical points of view. The range of applications of FEMs in this area is wide and cannot be presented in a single paper; therefore aims to give the reader an encyclopaedic view on the subject. The bibliography at the end of the paper contains 2,025 references to papers, conference proceedings and theses/dissertations dealing with the analysis of beams, columns, rods, bars, cables, discs, blades, shafts, membranes, plates and shells that were published in 1992‐1995.

In this paper, the problem of the elasto‐viscoplastic dynamic and thermal behaviour of geometrically non‐linear plates and shells is studied under the assumption of small strains and large rotations. The first‐order shear deformation shell theory and the Chaboche constitutive viscoplastic model taking the temperature fields into account are used for computations. An effective procedure using the central difference method of solving the equations of motion is applied. The trapezoidal method is used to integrate the constitutive viscoplastic law. A nine node isoparametric shell element has been utilised for the finite element algorithm. Finally, some examples are presented and compared with the results obtained by moderate rotation theory.

The purpose of this paper is to investigate possibilities to adopt state-of-the-art computer graphics technologies for big data visualization in engineering applications. Toward this purpose, a conceptual heterogeneous system is proposed for graphical rendering, which is established with multiple central processing unit cores and multiple graphics processing unit GPUs.

The design of the system supports both general-purpose computation and graphics-related computation. Three processing components are discussed to fulfill the execution requirements in load balancing, data streaming and display. This design fully uses computational and memory resources and enhances the performance with the support of GPU-based parallelization.

The advantages and disadvantages of particular technical methods for each processing component are discussed. The possible ways to integrate them are analyzed.

This work has contributions of using computer graphics technologies in engineering applications.

The purpose of this paper is to develop a new and simple methodology for fabric collision detection and response.

A 3D triangle‐to‐triangle collision problem was converted to simple 2D point‐in‐triangle problem using pre‐computed 4×4 transformation matrices. The object space was partitioned using voxels to find easily collision pair triangles. k‐DOP was used to find inter‐pattern collisions.

Complex 3D collision detection problem is solved by simple matrix operations. Voxel‐based space partitioning and k‐DOP‐based hierarchical methods are successfully applied to garment simulation.

This paper shows that the collision matrix method can cover from triangle‐to‐point to triangle‐to‐triangle collision with mathematical validity and can be simply implemented in garment simulation.

The 3D dynamic clothing simulation is widely used in computer-added garment design. Collision detection and response are the essential component and also the efficiency bottleneck in the simulation. The purpose of this paper is to propose a high efficient collision detection algorithm for 3D clothing-human dynamic simulation to achieve both real-time and virtually real simulation effects.

The authors approach utilizes the offline data learning results to simplify the online collision detection complexity. The approach includes two stages. In the off-line stage, model triangles with most similar deformations are first, partitioned into several near-rigid-clusters. Clusters from the clothing model and the human model are matched as pairs according to the fact that they hold the potential to intersect. For each cluster, a hierarchical bounding box tree is then constructed. In the on-line stage, collision detection is checked and treated parallelly inside each cluster pairs. A multiple task allocation strategy is proposed in parallel computation to ensure efficiency.

Reasonably partitioning the 3D clothing and human model surfaces into several clusters and implementing collision detection on these cluster pairs can efficiently reduce the model primitive amounts that need be detected, consequently both improving the detection efficiency and remaining the simulation virtual effect.

The current methods only utilize the dynamic clothing-human status; the authors algorithm furthermore combines the intrinsic correspondence relationship between clothing and human clusters to efficiently shrink the detection query scope to accelerate the detection speed. Moreover, partitioning the model into several independent clusters as detection units is much more profitable for parallel computation than current methods those treat the model entirety as the unit.

The purpose of this paper is to present an analytical review of the educational innovation field in the USA. It outlines classification of innovations, discusses the hurdles to innovation, and offers ways to increase the scale and rate of innovation-based transformations in the education system.

The paper is based on a literature survey and author research.

US education badly needs effective innovations of scale that can help produce the needed high-quality learning outcomes across the system. The primary focus of educational innovations should be on teaching and learning theory and practice, as well as on the learner, parents, community, society, and its culture. Technology applications need a solid theoretical foundation based on purposeful, systemic research, and a sound pedagogy. One of the critical areas of research and innovation can be cost and time efficiency of the learning.

Several practical recommendations stem out of this paper: how to create a base for large-scale innovations and their implementation; how to increase effectiveness of technology innovations in education, particularly online learning; how to raise time and cost efficiency of education.

Innovations in education are regarded, along with the education system, within the context of a societal supersystem demonstrating their interrelations and interdependencies at all levels. Raising the quality and scale of innovations in education will positively affect education itself and benefit the whole society.

Originality is in the systemic approach to education and educational innovations, in offering a comprehensive classification of innovations; in exposing the hurdles to innovations, in new arguments about effectiveness of technology applications, and in time efficiency of education.

Humans use the written language to tell stories and exchange ideas across time and space, and it is the core innovation on which libraries are founded.

Even as the transmission of writing has evolved from hand-written scrolls to mass printing to digital distribution, it has remained one of primary communication methods in the world. Through websites, e-mails, news articles, Facebook posts and more, writing is core to how humans interact. Writing well is also an activity that many people find arduous.

This paper will explore some of the current technologies and emerging trends that are designed to assist with the writing process.

Along the way, the paper will highlight some specific applications that can be used now. Examining these technologies, many of which only currently serve niche audiences, serves another purpose as well, as they point the way to what the future of writing will look like.

The purpose of this paper is to conduct a survey on research in fabric and cloth simulation using mass spring model. Also in this paper some of the common methods in process of fabric simulation in mass spring model are discussed and compared.

This paper reviews and compares presented mesh types in mass spring model, forces applied on model, super elastic effect and ways to settle the super elasticity problem, numerical integration methods for solving equations, collision detection and its response. Some of common methods in fabric simulation are compared to each other. And by using examples of fabric simulation, advantages and limitations of each technique are mentioned.

Mass spring method is a fast and flexible technique with high ability to simulate fabric behavior in real time with different environmental conditions. Mass spring model has more accuracy than geometrical models and also it is faster than other physical modeling.

In the edge of digital, fabric simulation technology has been considered into many fields. 3D fabric simulation is complex and its implementation requires knowledge in different fields such as textile engineering, computer engineering and mechanical engineering. Several methods have been presented for fabric simulation such as physical and geometrical models. Mass spring model, the typical physically based method, is one of the methods for fabric simulation which widely considered by researchers.

Considering the varied and dynamic workload of vessel traffic service (VTS) operators, design an adaptive rotating shift solution to prevent them from getting tired while ensuring continuous high-quality services and finally guarantee a benign maritime traffic environment.

The problem of rotating shift in VTS and its influencing factors are analyzed first, then the framework of automatic identification system (AIS) data analytics is proposed, as well as the data model to extract spatial–temporal information. Besides, K-means-based anomaly detection method is adjusted to generate anomaly-free data, with which the traffic trend analysis and prediction are made. Based on this knowledge, strategies and methods for adaptive rotating shift design are worked out.

In VTS, vessel number and speed are identified as two most crucial factors influencing operators' workload. Based on the two factors, the proposed data model is verified to be effective on reducing data size and improving data processing efficiency. Besides, the K-means-based anomaly detection method could provide stable results, and the work shift pattern planning algorithm could efficiently generate acceptable solutions based on maritime traffic information.

This is a pioneer work on utilizing maritime traffic data to facilitate the operation management in VTS, which provides a new direction to improve their daily management. Besides, a systematic data-driven solution for adaptive rotating shift is proposed, including knowledge discovery method and decision-making algorithm for adaptive rotating shift design. The technical framework is flexible and can be extended for managing other activities in VTS or adapted in diverse fields.