Boundary element analysis of a plate on elastic foundations

The objective of this study is to examine the applicability of the boundary element method to analysing a plate on elastic foundation. The fundamental solution of the problem is presented as a Fourier-Bessel integral. For the computation of the values of the fundamental solution an algorithm was developed in which the Fourier-Bessel integral was decomposed into an alternative convergent sequence. Equations based on the direct and indirect boundary element method were derived for a plate situated on a one- or two-parametric elastic foundation. According to the theory presented, computer programs based on the direct and indirect boundary element method were developed. These programs can be used for examining the behaviour of a smooth-boundary plate on a one- or two-parametric elastic foundation. The computer programs were tested by several examples. The results obtained by using a small number of boundary elements compared favourably to the results obtained by a fine finite element mesh. The study shows that the boundary element method is applicable to the analysis of a plate on elastic foundation.     

Socially shared regulation of learning in CSCL: understanding and prompting individual- and group-level shared regulatory activities

The field of computer supported collaborative learning (CSCL) is progressing instrumentally and theoretically. Nevertheless, few studies examine the effectiveness and efficiency of CSCL with respect to cognitive, motivational, emotional, and social issues, despite the fact that the role of regulatory processes is critical for the quality of students’ engagement in collaborative learning settings. We review the four earlier lines in developing support in CSCL and show how there has been a lack of work to support individuals in groups to engage in, sustain, and productively regulate their own and the group’s collaborative processes. Our aim is to discuss how our conceptual work in socially shared regulation of learning (SSRL) contributes to effective and efficient CSCL, what tools are presently available, and what the implications of research on these tools are for future tool development.     

The movement patterns and the experiential components of virtual environments

Human movement in virtual environments (VEs) is a largely unstudied area, and there are no well-established methods of measuring it in VEs. Consequently, it is unclear how movement affects the experiential side of VEs. We introduce a novel method of measuring and modelling human movement. A specific information entropy-based modelling method enabled us to identify different movement patterns and analyse the experiential components related to them. The data was collected by registering the movement patterns of 68 participants who were in a virtual house doing a search task. The experiential side of the VE was measured with the Experimental Virtual Environment Questionnaire (EVEQ). Four movement patterns were identified. In addition, fluent movement in VEs was related to a high sense of presence. Moreover, the participants who moved fluently in the environment assessed their skills high. The results show how movement is related the way in which people experience the VE. The movement analysis method introduced here is applicable to other related research areas as well.     

Correction to: The effect of various simultaneous sources of mechanical error in the estimators of correlation causing deflation in reliability: seeking the best options of correlation for deflation-corrected reliability

Behaviormetrika - The article “The effect of various simultaneous sources of mechanical error in the estimators of correlation causing deflation in reliability: seeking the best options of...     

A coarse-grain reconfigurable architecture for multimedia applications supporting subword and floating-point calculations

Signal processors exploiting ASIC acceleration suffer from sky-rocketing manufacturing costs and long design cycles. FPGA-based systems provide a programmable alternative for exploiting computation parallelism, but the flexibility they provide is not as high as in processor-oriented architectures: HDL or C-to-HDL flows still require specific expertise and a hardware knowledge background. On the other hand, the large size of the configuration bitstream and the inherent complexity of FPGA devices make their dynamic reconfiguration not a very viable approach. Coarse-grained reconfigurable architectures (CGRAs) are an appealing solution but they pose implementation problems and tend to be application specific. This paper presents a scalable CGRA which eases the implementation of algorithms on field programmable gate array (FPGA) platforms. This design option is based on two levels of programmability: it takes advantage of performance and reliability provided by state-of-the-art FPGA technology, and at the same time it provides the user with flexibility, performance and ease of reconfiguration typical of standard CGRAs. The basic cell template provides advanced features such as sub-word SIMD integer and floating-point computation capabilities, as well as saturating arithmetic. Multiple reconfiguration contexts and partial run-time reconfiguration capabilities are provided, tackling this way the problem of high reconfiguration overhead typical of FPGAs. Selected instances of the proposed architecture have been implemented on an Altera Stratix II EP2S180 FPGA. On this system, we mapped some common DSP, image processing, 3D graphics and audio compression algorithms in order to validate our approach and to demonstrate its effectiveness by benchmarking the benefits achieved.     

数字图像的质量评价

图像质量评价的使用已成为图像信息工程的基础技术之一。本文对目前一些典型的数字图像质量介方法进行了简要综述,并着重介绍了一种基于视觉兴趣的图像质量评价方法,最后指出了图像质量评价研究可能发展的方向。     

Energy Harvesting Research: The Road from Single Source to Multisource

Energy harvesting technology may be considered an ultimate solution to replace batteries and provide a long‐term power supply for wireless sensor networks. Looking back into its research history, individual energy harvesters for the conversion of single energy sources into electricity are developed first, followed by hybrid counterparts designed for use with multiple energy sources. Very recently, the concept of a truly multisource energy harvester built from only a single piece of material as the energy conversion component is proposed. This review, from the aspect of materials and device configurations, explains in detail a wide scope to give an overview of energy harvesting research. It covers single‐source devices including solar, thermal, kinetic and other types of energy harvesters, hybrid energy harvesting configurations for both single and multiple energy sources and single material, and multisource energy harvesters. It also includes the energy conversion principles of photovoltaic, electromagnetic, piezoelectric, triboelectric, electrostatic, electrostrictive, thermoelectric, pyroelectric, magnetostrictive, and dielectric devices. This is one of the most comprehensive reviews conducted to date, focusing on the entire energy harvesting research scene and providing a guide to seeking deeper and more specific research references and resources from every corner of the scientific community.     

Framework for developing image-based dirt particle classifiers for dry pulp sheets

One important aspect of assessing the quality in pulp and papermaking is dirt particle counting and classification. Knowing the number and types of dirt particles present in pulp is useful for detecting problems in the production process as early as possible and for fixing them. Since manual quality control is a time-consuming and laborious task, the problem calls for an automated solution using machine vision techniques. However, the ground truth required to train an automated system is difficult to ascertain, since all of the dirt particles should be manually segmented and classified based on image information. This paper proposes a framework for developing and tuning dirt particle detection and classification systems. To avoid manual annotation, dry pulp sheets with a single dirt type in each were exploited to generate semisynthetic images with the ground truth information. To classify the dirt particles, a set of features were computed for each image segment. Sequential feature selection was employed to determine a close-to-optimal set of features to be used in classification. The framework was tested both with semisynthetically generated images based on real pulp sheets and with independent original real pulp sheets without any generation. The results of the experiments show that the semisynthetic procedure does not significantly change the properties of images and has little effect on the particle segmentation. The feature selection proved to be important when the number of dirt classes changes since it allows to improve the classification results. Using the standard classification methods, it is possible to obtain satisfactory results, although the methods modeling the data, such as the Bayesian classifier using the Gaussian Mixture Model, show better performance.     

Considerations for Synchronization in Body Area Networks for Human Activity Monitoring

In this paper, we highlight considerations for synchronization issues in body area networks. Requirements for the synchronization accuracy in body area networks depend on the application at hand. Synchronization may be needed for power management, sample ordering, calculation of stimulus responses and for sensor fusion. This paper provides a theoretical exercise to help understand the accuracy required for typical human motion sensing. It gives an overview of various synchronisation strategies used and implemented in prototype systems. Lessons learnt from practical implementations using Bluetooth, an IEEE 802.15.4 proprietary network and Nanonet are presented to illustrate the principles involved. The discussion provides some considerations and the requirements for typical WBAN applications.     

Identification of novel pyranoanthocyanins in berry juices

In most fruit and berry products the attractive red color is unstable and easily susceptible to degradation. The colors of strawberry and raspberry juices can be enhanced and stabilized by the addition of cinnamic acids. The aim of this study was to identify the novel anthocyanin products responsible for the improved juice color. The pyranoanthocyanins formed were detected using high-performance liquid chromatography, and the fractions from this were analyzed using a nano-ESI tandem MS technique. The pyranoanthocyanins identified were formed from reactions of the main anthocyanins of strawberry and raspberry juices with ferulic acid or sinapic acid. The new anthocyanin derivatives were the 4-vinylguaiacol and 4-vinylsyringol adducts of pelargonidin and cyanidin. This is the first time that pelargonidin 3-glucoside-based vinylphenol pyranoanthocyanins and pyranoanthocyanins with more complex sugar residues have been found. This is also the first time pyranoanthocyanins have been detected in strawberry and raspberry juices.