共查询到18条相似文献,搜索用时 78 毫秒
1.
基于分布式认知理论的扩展资源模型 总被引:6,自引:0,他引:6
分布式认知理论通过协调人机对话,结合人和计算机各自的优势解决问题,在人机交互研究中扮演了指导者的角色.尽管分布式认知理论支持的资源模型在分析人机交互时取得了成功,但模型存在不能提供复杂用户任务支持、缺乏对模型中元素的准确定义等问题,在一定程度上导致了表现形式上的混乱.使用分布式认知理论构造了扩展资源模型,建立人机交互活动中的动作和表征之间的联系,从而指导界面的设计和实现.扩展资源模型从静态结构和交互策略两个方面对界面交互动作提供支持,在交互中减少人的认知负担.该研究对设计符合人的认知特点的界面具有一定的指导作用. 相似文献
2.
3.
近年来,包含动态任务的交互式系统得到了广泛的应用.基于现有对用户与动态任务交互的研究,提出一个面向动态任务的定量化可计算的交互模型ICOMDT,用于解释用户与动态任务的交互行为,并实现用户意图预测.更具体地,将ICOMDT应用于运动目标选择任务,设计了两个实验以验证模型的有效性.实验1收集用户数据对模型进行拟合并预测用户选择的错误率,实验结果表明,能够很好地拟合且预测值也与真实值接近;实验2将模型对用户意图的理解拓展为一种辅助运动目标选择技术ICOMPointer,通过在具体的游戏场景中与Windows原本的选择技术及两种现有的增强目标选择技术对比,发现使用ICOMPointer选中目标的平均完成时间更短,完成速度更快.ICOMDT模型的提出对计算机理解用户意图,提高用户与动态任务的交互效率有着重要意义. 相似文献
4.
5.
6.
分析了触控交互技术在移动手持设备及可穿戴设备应用的应用现状及存在的问题;基于交互动作的时间连续性及空间连续性,提出了将触控交互动作的接触面轨迹与空间轨迹相结合,同时具有空中手势及触控手势的特性及优点的混合手势输入方法;基于连续交互空间的概念,将混合交互手势,空中手势、表面触控手势进行统一,建立了包括空中层、表面层、混合层的连续交互空间分层处理模型;给出了统一的信息数据定义及数转换流程;构建了通用性的手势识别框架,并对轨迹切分方法及手势分类识别方法进行了阐述.最后设计了应用实例,通过实验,对混合交互手势的可用性及连续空间分层处理模型的可行性进行了验证.实验表明,混合手势输入方式同时兼具了表面触控输入及空中手势输入的优点,在兼顾识别效率的同时,具有较好的空间自由度. 相似文献
7.
以卫星综合信息网为研究背景,将面向任务的协作机制引入其网络管理系统,提出了基于分层管理的协作机制框架,包括协作模型、协作过程和协作通信机制的研究.论文设计了面向任务的协作分解语法和异步执行任务过程,根据不同的任务,动态生成协作产生者--响应者模型,并设计了信息同步机制以及协作通信机制的消息通信类型.该协作机制的实现可以提高卫星综合信息网的资源利用率,使卫星网网络管理更适应网络拓扑结构的变化,易于扩展. 相似文献
8.
一、引言在协作设计系统中,内部表示和推理机制是重要的。然而,外部表达以及知识与设计者的交流同样重要。当研究设计问题的一个子系统时,对该子系统的解释有助于问题的其它子系统的构造。同样,对设计推理和设计方案的解释有助于在未来设计中重新使用部分推理或方案。 相似文献
9.
分布式协作模型及应用研究 总被引:1,自引:0,他引:1
With the development of the Web technology,the application environment has acquired many new characters such as dynamic, openness,distribution and information uncertainty.The processing mode of application systems is more complicated than ever.For example,it requires application systems to have more community processing ability,interactive ability,distributed processing ability and collaborative ability.Accordingly the research and development of the computer application system transited from client/server information processing system into distributed collaborative processing system based on Web.Especially in the environment where the information and resources are highly distributed,the accomplishment of complicated tasks is dependent more on the resources coordination,information sharing and coordinator collaboration.The collaboration is one aspect of the group behavior and its goal is to provide a optimal method to utilize the resource through the information interaction and to solve the task which couldn't be accomplished by each coordinator alone and get the more total benefits than the sum of each benefit.The collaboration problem is the important one for distributed tasks processing.This paper surveys,the research and application status of distributed collaborative models and several representative architectures of distributed collaborative processing are proposed.However,the existing problems and the future researching direction are presented. 相似文献
10.
融合触、听、视觉的多通道认知和交互模型 总被引:2,自引:0,他引:2
以触觉相关的多通道交互研究为立足点,结合经典的多通道假设和最新的认知理论,提出一种融合触觉、听觉、视觉的多通道信息认知加工模型,并就计算机端的信息处理过程提出了多通道交互的分层处理模型,分析了相应的多通道整合方法.该模型对交互界面与程序主体功能定义不同的实现路径,区分交互设备和交互信息处理过程,有利于从不同角度对交互界面的研究工作进行简化,避免高耦合度带来的冗余工作量;实现了一个融合触、听、视觉交互的实例.实例结果表明,利用文中模型能够降低多通道交互研究的分析难度并提高实验效率. 相似文献
11.
Storm on YARN是目前主流的分布式资源调度框架,但其存在需要人工干预和无法根据资源可用性实时调整系统资源的不足。根据流数据处理的实时延迟计算系统负载情况,在Storm平台上基于YARN设计分布式资源调度和协同分配系统。建立包含系统层和任务层的双层调度模型,系统层通过对流数据处理负载的实时监测进行资源分配预测,任务层利用ZooKeeper和YARN对集群资源的高效管理能力进行动态资源管理。实验结果表明,该系统可以实时调整集群资源分布,有效减小系统延迟。 相似文献
12.
13.
受限资源网络环境的协同虚拟环境感知模型 总被引:2,自引:0,他引:2
AM—COVEN感知模型依据人的行为和感知特征,综合考虑位置、兴趣区、感知等级、感知QoS、感知相关性等问题,描述了受限资源网络环境下的虚拟环境的感知问题,为网络资源的合理应用提供支持.实验证明,AM—COVEN能缓解网络条件对感知的影响. 相似文献
14.
15.
Shiwei CHENG Jialing WANG Xiaoquan SHEN Yijian CHEN Anind DEY 《Frontiers of Computer Science》2022,16(3):163704
Code review is intended to find bugs in early development phases, improving code quality for later integration and testing. However, due to the lack of experience with algorithm design, or software development, individual novice programmers face challenges while reviewing code. In this paper, we utilize collaborative eye tracking to record the gaze data from multiple reviewers, and share the gaze visualization among them during the code review process. The visualizations, such as borders highlighting current reviewed code lines, transition lines connecting related reviewed code lines, reveal the visual attention about program functions that can facilitate understanding and bug tracing. This can help novice reviewers to make sense to confirm the potential bugs or avoid repeated reviewing of code, and potentially even help to improve reviewing skills. We built a prototype system, and conducted a user study with paired reviewers. The results showed that the shared real-time visualization allowed the reviewers to find bugs more efficiently. 相似文献
16.
17.
Collaborative Matrix Factorization with Soft Regularization for Drug-Target Interaction Prediction
下载免费PDF全文
![点击此处可从《计算机科学技术学报》网站下载免费的PDF全文](/ch/ext_images/free.gif)
Identifying the potential drug-target interactions (DTI) is critical in drug discovery.The drug-target interaction prediction methods based on collaborative filtering have demonstrated attractive prediction performance.However,many corresponding models cannot accurately express the relationship between similarity features and DTI features.In order to rationally represent the correlation,we propose a novel matrix factorization method,so-called collaborative matrix factorization with soft regularization (SRCMF).SRCMF improves the prediction performance by combining the drug and the target similarity information with matrix factorization.In contrast to general collaborative matrix factorization,the fundamental idea of SRCMF is to make the similarity features and the potential features of DTI approximate,not identical.Specifically,SRCMF obtains low-rank feature representations of drug similarity and target similarity,and then uses a soft regularization term to constrain the approximation between drug (target) similarity features and drug (target) potential features of DTI.To comprehensively evaluate the prediction performance of SRCMF,we conduct cross-validation experiments under three different settings.In terms of the area under the precision-recall curve (AUPR),SRCMF achieves better prediction results than six state-of-the-art methods.Besides,under different noise levels of similarity data,the prediction performance of SRCMF is much better than that of collaborative matrix factorization.In conclusion,SRCMF is robust leading to performance improvement in drug-target interaction prediction. 相似文献
18.
随着数字图像处理技术的发展,以及计算机支持的协同工作研究的深入,眼动跟踪开始应用于多用户协同交互.但是已有的眼动跟踪技术主要针对单个用户,多用户眼动跟踪计算架构不成熟、标定过程复杂,眼动跟踪数据的记录、传输以及可视化共享机制都有待深入研究.为此,建立了基于梯度优化的协同标定模型,简化多用户的眼动跟踪标定过程;然后提出面向多用户的眼动跟踪计算架构,优化眼动跟踪数据的传输和管理.进一步地,探索眼动跟踪数据的可视化形式在协同交互环境下对用户视觉注意行为的影响,具体设计了圆点、散点、轨迹这3种可视化形式,并验证了圆点形式能够有效地提高多用户协同搜索任务的完成效率.在此基础上,设计与开发了基于眼动跟踪的代码协同审查系统,实现了代码审查过程中多用户眼动跟踪数据的同步记录、分发,以及基于实时注视点、代码行边框和背景灰度、代码行之间连线的可视化共享.用户实验结果表明,代码错误的平均搜索时间比没有眼动跟踪数据可视化分享时减少了20.1%,显著提高了协同工作效率,验证了该方法的有效性. 相似文献