A method for evaluating the learning concentration in head-mounted virtual reality interaction

Virtual Reality - In education, learning concentration is closely related to the quality of learning, and teachers can adjust their teaching methods accordingly to improve the learning outcomes of...     

Knowledge processes in virtual teams: consolidating the evidence

This article takes stock of the current state of research on knowledge processes in virtual teams (VTs) and consolidates the extent research findings. Virtual teams, on the one hand, constitute important organisational entities that facilitate the integration of diverse and distributed knowledge resources. On the other hand, collaborating in a virtual environment creates particular challenges for the knowledge processes. The article seeks to consolidate the diverse evidence on knowledge processes in VTs with a specific focus on identifying the factors that influence the effectiveness of these knowledge processes. The article draws on the four basic knowledge processes outlined by Alavi and Leidner (2001 Alavi, M.Leidner, D.E., 2001. Review: knowledge management and knowledge management systems: conceptual foundations and research issues. MIS Quarterly, 25 (1), 107–136. doi: 10.2307/3250961[Crossref], [Web of Science ®] , [Google Scholar]) (i.e. creation, transferring, storage/retrieval and application) to frame the investigation and discuss the extent research. The consolidation of the existing research findings allows us to recognise the gaps in the understanding of knowledge processes in VTs and identify the important avenues for future research.     

面向高校教学云服务的虚拟机动态调度方法

随着教学信息化的不断深化,高校云平台越来越普及,但是实际应用中资源利用率仍然较低,核心问题在于当前的虚拟机调度机制未考虑高校教学应用的特征,从而导致负载不均和资源浪费。为了解决这一问题,从高校教学应用需求出发,提出了一种虚拟机动态调度算法(CRS),定义了课程虚拟机模型和物理机负载模型,并实现了基于OpenStack开源云平台的可对虚拟机进行动态调度的校园云平台。实验表明,提出的虚拟机动态调度方法达到了降低能耗及实现负载均衡的目标。     

An energy-aware virtual machines consolidation method for cloud computing: Simulation and verification

Cloud systems have become an essential part of our daily lives owing to various Internet-based services. Consequently, their energy utilization has also become a necessary concern in cloud computing systems increasingly. Live migration, including several virtual machines (VMs) packed on in minimal physical machines (PMs) as virtual machines consolidation (VMC) technique, is an approach to optimize power consumption. In this article, we have proposed an energy-aware method for the VMC problem, which is called energy-aware virtual machines consolidation (EVMC), to optimize the energy consumption regarding the quality of service guarantee, which comprises: (1) the support vector machine classification method based on the utilization rate of all resource of PMs that is used for PM detection in terms of the amount' load; (2) the modified minimization of migration approach which is used for VM selection; (3) the modified particle swarm optimization which is implemented for VM placement. Also, the evaluation of the functional requirements of the method is presented by the formal method and the non-functional requirements by simulation. Finally, in contrast to the standard greedy algorithms such as modified best fit decreasing, the EVMC decreases the active PMs and migration of VMs, respectively, 30%, 50% on average. Also, it is more efficient for the energy 30% on average, resources and the balance degree 15% on average in the cloud.     

DMM:A dynamic memory mapping model for virtual machines

Memory virtualization is an important part in the design of virtual machine monitors(VMM).In this paper,we proposed dynamic memory mapping(DMM) model,a mechanism that allows the VMM to change the mapping between a virtual machine's physical memory and the underlying hardware resource while the virtual machine is running.By utilizing DMM,the VMM can implement many novel memory management policies,such as Demand Paging,Swapping,Ballooning,Memory Sharing and Copy-On-Write,while preserving compatibility with va...     

A clustering method for evaluating the environmental performance based on slacks-based measure

The conventional clustering algorithms are mostly distance-based, which can lead to distorted results in the evaluation of production unit’s performance. As a non-parametric method, data envelopment analysis (DEA) has become a popular approach to measuring the production process performance. However, few researchers paid attention to the relationship between clustering approach and DEA. In this paper, we use a non-radial DEA framework (slacks-based measure, SBM) to classify the environmental performance of Chinese industry, forming a benchmark-based clustering approach. Additionally, we employ the context-dependent DEA method to get the sub-clusters for detailed managerial meaning. An application in real world is given to explain the usage and effectiveness of the proposed SBM-based clustering method, and the result is compared with the conventional distance-defined k-means clustering approach.     

A class-based scheme for E-commerce web servers: Formal specification and performance evaluation

This paper is an investigation into the performance of E-commerce applications. E-commerce has become one of the most popular applications of the web as a large population of web users is now benefiting from various on-line services including product searches, product purchases and product comparison. E-commerce provides users with 24-7 shopping facilities. However, the consequence of these benefits and facilities is the excessive load on E-commerce web servers and the performance degradation of E-commerce (eCom) requests they process. This paper addresses this issue and proposes a class-based priority scheme which classifies eCom requests into high and low priority requests. In E-commerce, some requests (e.g. payment) are generally considered more important than others (e.g. search or browse). We believe that by assigning class-based priorities at multiple service levels, E-commerce web servers can perform better and can improve the performance of high priority eCom requests. In this paper, we formally specify and implement the proposed scheme and evaluate its performance using multiple servers. Experimental results demonstrate that the proposed scheme significantly improves the performance of high priority eCom requests.     

A method of evaluating inspector's performance differences and job requirements

Large individual differences are among the most consistent findings in the study of industrial inspection. From a statistical point of view, a large proportion of the variation in inspection performance is attributed to this individual factor. Based on the conclusions obtained from the review of previous papers, the relations between subjects' cognitive factors and inspection performance were shown to be in need of further exploration. The objective of this paper is to introduce a method that can explore this large proportion of variation by concentrating on individuals' cognitive attributes and how each contributes to the efficiency and effectiveness of inspection performance. In an experiment, three inspection tasks and 11 cognitive pretests were included. Through factor analysis and Pearson correlations, some significant predictive relationships were found. The findings can be applied to set up selection criteria as well as training schemes for industrial inspectors.     

Sandpiper: Black-box and gray-box resource management for virtual machines

Virtualization can provide significant benefits in data centers by enabling dynamic virtual machine resizing and migration to eliminate hotspots. We present Sandpiper, a system that automates the task of monitoring and detecting hotspots, determining a new mapping of physical to virtual resources, resizing virtual machines to their new allocations, and initiating any necessary migrations. Sandpiper implements a black-box approach that is fully OS- and application-agnostic and a gray-box approach that exploits OS- and application-level statistics. We implement our techniques in Xen and conduct a detailed evaluation using a mix of CPU, network and memory-intensive applications. Our results show that Sandpiper is able to resolve single server hotspots within 20 s and scales well to larger, data center environments. We also show that the gray-box approach can help Sandpiper make more informed decisions, particularly in response to memory pressure.     

Quantifying and evaluating the space overhead for alternative C++ memory layouts

This paper develops a formalism that precisely characterizes when class tables are required for C++ memory layouts. A memory layout is a particular choice of data structures for implementing run‐time support for object‐oriented languages. We use this formalism to quantify and evaluate, on a set of benchmarks, the space overhead for a set of C++ memory layouts. In particular, this paper studies the space overhead due to three language features: virtual dispatch, virtual inheritance, and dynamic typing. To date, there has been no scientific quantification or evaluation of C++ memory layouts. Our approach can help C++ implementors. This work has already influenced the memory layout design choices in IBM's Visual Age C++ V5 compiler. Applying our approach to a set of five benchmarks, we demonstrate that the impact of object‐oriented space overhead can vary dramatically between applications (ranging from 0.42% to 99.79% for our benchmarks). In particular, applications whose object space is dominated by instances of classes that heavily use object‐oriented language features will be significantly impacted by the choice of a memory layout. Copyright © 2003 John Wiley & Sons, Ltd.     

Large-scale virtual machines provisioning in clouds: challenges and approaches

The scale of global data center market has been explosive in recent years. As the market grows, the demand for fast provisioning of the virtual resources to support elastic, manageable, and economical computing over the cloud becomes high. Fast provisioning of large-scale virtual machines (VMs), in particular, is critical to guarantee quality of service (QoS). In this paper, we systematically review the existing VM provisioning schemes and classify them in three main categories. We discuss the features and research status of each category, and introduce two recent solutions, VMThunder and VMThunder+, both of which can provision hundreds of VMs in seconds.     

基于软件定义网络的IaaS虚拟机通信访问控制方法

针对云计算基础设施即服务(IaaS)平台所面临的虚拟机网络通信访问控制问题,提出了一种可适于IaaS平台的虚拟机通信访问控制方法.该通信访问控制方法基于软件定义网络(SDN),实现针对虚拟机通信的L2~L4层访问控制.实验结果表明:该通信访问控制方法能够有效实现对租户虚拟机通信的灵活访问控制,保障IaaS平台中租户网络的安全.     

A new general method to compute virtual channels occupancy probabilities in wormhole networks

Virtual channels have been proposed to develop deadlock free routing algorithms and to overcome the performance degradation due to chains of blocked messages in wormhole switched networks. Hence, capturing the effect of virtual channels has always been an important issue in developing analytical performance models for these interconnection networks. Almost all previous models relayed on a method proposed by Dally to compute the probability of the number of busy virtual channels per physical channel. Dally's method is based on a Markov chain and after extensive investigation our results reveal that its accuracy degrades as traffic increases. In this study we propose and validate a new general method to compute this probability. The new general method is based on an M/G/1 queue and it exhibits a good degree of accuracy at different traffic conditions. We further showed that Dally's method can be deduced as a special case of the general method. Predictions from both, Dally's method and the new general method are validated against results obtained from an event-driven simulator that mimics the behaviour of wormhole-switch networks.     

The virtual playground: an educational virtual reality environment for evaluating interactivity and conceptual learning

The research presented in this paper aims at investigating user interaction in immersive virtual learning environments, focusing on the role and the effect of interactivity on conceptual learning. The goal has been to examine if the learning of young users improves through interacting in (i.e. exploring, reacting to, and acting upon) an immersive virtual environment (VE) compared to non-interactive or non-immersive environments. Empirical work was carried out with more than 55 primary school students between the ages of 8 and 12, in different between-group experiments: an exploratory study, a pilot study, and a large-scale experiment. The latter was conducted in a virtual environment designed to simulate a playground. In this “Virtual Playground,” each participant was asked to complete a set of tasks designed to address arithmetical “fractions” problems. Three different conditions, two experimental virtual reality (VR) conditions and a non-VR condition, that varied the levels of activity and interactivity, were designed to evaluate how children accomplish the various tasks. Pre-tests, post-tests, interviews, video, audio, and log files were collected for each participant, and analysed both quantitatively and qualitatively. This paper presents a selection of case studies extracted from the qualitative analysis, which illustrate the variety of approaches taken by children in the VEs in response to visual cues and system feedback. Results suggest that the fully interactive VE aided children in problem solving but did not provide a strong evidence of conceptual change as expected; rather, it was the passive VR environment, where activity was guided by a virtual robot, that seemed to support student reflection and recall, leading to indications of conceptual change.     

Modeling and evaluating the time overhead induced by BER in COMA multiprocessors

Designing multiprocessors based on distributed shared memory (DSM) architecture considerably increases their scalability. But as the number of nodes in a multiprocessor increases, the probability of encountering failures in one or more nodes of the system raises as a serious problem. Thus, every large-scale multiprocessor should be equipped with mechanisms that tolerate node failures. Backward error recovery (BER) is one of the most feasible strategies to build fault tolerant multiprocessors and it can be shown that among various DSM-based architectures, cache only memory architecture (COMA) is the most suitable for implementing BER. The main reason is the existence of built-in mechanisms for data replication in COMA memory system. BER is applicable to COMA multiprocessors with minor hardware redundancy, but it will obviously cause some other kinds of overheads. The most important overhead induced by BER is the time required to produce and store recovery data. This paper introduces an analytical model for predicting the amount of this time overhead and then verifies the correctness of the model through comparing the results predicted from this model with the previously published simulation results. Both the analytical model and simulation results show that the overhead is nearly independent of the number of nodes. The immediate result is that BER is a cost-effective strategy for tolerating node failures in large-scale COMA multiprocessors with large numbers of nodes.     

FS_SFS: A novel feature selection method for support vector machines

In many pattern recognition applications, high-dimensional feature vectors impose a high computational cost as well as the risk of “overfitting”. Feature Selection addresses the dimensionality reduction problem by determining a subset of available features which is most essential for classification. This paper presents a novel feature selection method named filtered and supported sequential forward search (FS_SFS) in the context of support vector machines (SVM). In comparison with conventional wrapper methods that employ the SFS strategy, FS_SFS has two important properties to reduce the time of computation. First, it dynamically maintains a subset of samples for the training of SVM. Because not all the available samples participate in the training process, the computational cost to obtain a single SVM classifier is decreased. Secondly, a new criterion, which takes into consideration both the discriminant ability of individual features and the correlation between them, is proposed to effectively filter out nonessential features. As a result, the total number of training is significantly reduced and the overfitting problem is alleviated. The proposed approach is tested on both synthetic and real data to demonstrate its effectiveness and efficiency.     

车用ABS制动性能评价技术

本文采用的是一种硬件在环仿真技术,将实物汽车嵌入到仿真系统中,利用单轮模型相关理论依据求出轮胎即时转速,将转速信号送入实物汽车ECU中,ECU便控制压力调节电磁阀动作,以达到调节制动油路压力的目的,仿真计算机采集回压力信号,达到跟踪轮速的目的,从而也就实现了跟踪汽车纵向滑移率的目的。     

车用ABS制动性能评价技术

本文采用的是一种硬件在环仿真技术,将实物汽车嵌入到仿真系统中,利用单轮模型相关理论依据求出轮胎即时转速,将转速信号送入实物汽车ECU中,ECU便控制压力调节电磁阀动作,以达到调节制动油路压力的目的,仿真计算机采集回压力信号,达到跟踪轮速的目的,从而也就实现了跟踪汽车纵向滑移率的目的.