Using handhelds in a Jigsaw cooperative learning environment

Abstract This paper reports our implementation of a handheld wireless environment to support Jigsaw cooperative learning activities in a college setting. A quasi-experimental research design was conducted to investigate the effects of using handhelds, as well as issues associated with the use of handheld technology. Two intact classes of fourth-year students from a five-year junior nursing college participated in the experiment. Our findings showed that handheld tools enhanced both students' attitudes and performance in learning, and promoted better interactions among students and instructors. We also found that the handheld technology was not sophisticated enough to support cooperative learning goals without full support from a technology specialist.     

位置相关信息服务移动终端缓存替换研究

随着无线网络的快速发展,相应的无线应用服务越来越多,位置相关信息服务(LDISs)就是其中典型的例子。无线网络受信道带宽以及终端计算能力等因素的限制,缓存技术减少了网络开销并且支持在网络断接下使用数据的优点而成为研究热点。本文根据无线应用环境的特点,结合位置相关信息数据的特征,运用粗糙集(RoughSet,RS)这一强有力的数学工具,给出一种更加准确、实用的移动缓存替换策略。     

Time-Optimal Control of a Hovering Quad-Rotor Helicopter

The time-optimal control problem of a hovering quad-rotor helicopter is addressed in this paper. Instead of utilizing the Pontryagin's Minimum Principle (PMP), in which one needs to solve a set of highly nonlinear differential equations, a nonlinear programming (NLP) method is proposed. In this novel method, the count of control steps is fixed initially and the sampling period is treated as a variable in the optimization process. The optimization object is to minimize the sampling period such that it will be below a specific minimum value, which is set in advance considering the accuracy of discretization. To generate initial feasible solutions of the formulated NLP problem, genetic algorithms (GAs) are adopted. With the proposed method, one can find a time-optimal movement of the helicopter between two configurations. To show the feasibility of the proposed method, simulation results are included for illustration.     

Mixture Poisson regression models for heterogeneous count data based on latent and fuzzy class analysis

In this paper we propose a new approach, called a fuzzy class model for Poisson regression, in the analysis of heterogeneous count data. On the basis of fuzzy set concept and fuzzy classification maximum likelihood (FCML) procedures we create an FCML algorithm for fuzzy class Poisson regression models. Traditionally, the EM algorithm had been used for latent class regression models. Thus, the accuracy and effectiveness of EM and FCML algorithms for estimating the parameters are compared. The results show that the proposed FCML algorithm presents better accuracy and effectiveness and can be used as another good tool to regression analysis for heterogeneous count data.This work was supported in part by the National Science Council of Taiwan under Grant NSC-89-2213-E-033-007.     

一种城区LiDAR点云数据的抽稀算法

当城区LiDAR点云数据密度较大时,存在大量的数据冗余,造成了计算量大、效率低、显示不便等一系列问题,使得建筑物的三维可视化及三维重建等应用受到较大挑战。针对该问题,结合泊松碟采样在测地空间中的地形自适应特点,提出了适用于城区LiDAR点云数据的抽稀算法。泊松碟采样随机将与已有采样点的测地距离大于某一阈值的点加入采样点集,并不断重复这一过程直至没有新的采样点加入为止。在此基础上,依据LiDAR点云数据的特点,定义了一种新的与所选点与其邻域内其他点间高度差标准差相关的加权测地距离,改进了泊松碟采样算法。该方法能有效调整城区建筑物的采样率,从而尽可能地保持建筑物的原始特征,并保留良好的可视化效果。四组对比实验结果表明了该算法的适用性及高效性。     

Boosting learning and inference in Markov logic through metaheuristics

Markov Logic (ML) combines Markov networks (MNs) and first-order logic by attaching weights to first-order formulas and using these as templates for features of MNs. State-of-the-art structure learning algorithms in ML maximize the likelihood of a database by performing a greedy search in the space of structures. This can lead to suboptimal results because of the incapability of these approaches to escape local optima. Moreover, due to the combinatorially explosive space of potential candidates these methods are computationally prohibitive. We propose a novel algorithm for structure learning in ML, based on the Iterated Local Search (ILS) metaheuristic that explores the space of structures through a biased sampling of the set of local optima. We show through real-world experiments that the algorithm improves accuracy and learning time over the state-of-the-art algorithms. On the other side MAP and conditional inference for ML are hard computational tasks. This paper presents two algorithms for these tasks based on the Iterated Robust Tabu Search (IRoTS) metaheuristic. The first algorithm performs MAP inference and we show through extensive experiments that it improves over the state-of-the-art algorithm in terms of solution quality and inference time. The second algorithm combines IRoTS steps with simulated annealing steps for conditional inference and we show through experiments that it is faster than the current state-of-the-art algorithm maintaining the same inference quality.     

On discrete dynamic output feedback min-max controllers

The paper considers output feedback min-max controllers for non-square discrete time uncertain linear systems. Based on previous work, it is demonstrated that static output feedback min-max controllers are only realizable for a specific class of systems. To broaden this class, a compensator based framework is proposed to introduce additional degrees of freedom. The conditions for the existence of such dynamic output feedback min-max controllers are given and are shown to be relatively mild. Furthermore, a simple parameterization of the available design freedom is proposed. An explicit procedure is described which shows how a Lyapunov matrix, which satisfies both a discrete Riccati inequality and a structural constraint, can be obtained using Linear matrix inequality optimization. This Lyapunov matrix is used to calculate the robustness bounds associated with the closed-loop system. A simple aircraft example is provided to demonstrate the efficacy of the design approach.     

基于PC和FPGA的运动控制系统

针对运动控制系统对高速度与高精度的要求,基于二次插补原理及最小偏差插补法,提出一种以PC机为主控制器、FPGA为从控制器的主从式运动控制系统的设计。主控制器的功能是对系统运行过程进行控制规划和粗插补;从控制器的功能是对加工进行精插补和执行速度控制。该系统在Matlab环境下进行了插补仿真,并在两轴数控雕刻床上进行了加工测试,验证了系统的可靠性与高精度。加工精度可达0.01 mm,为高精度、高速插补数控系统提供了有效的解决方案。     

The “Always Best Packet Switching” architecture for SIP-based mobile multimedia services

This paper presents a distributed architecture for the provision of seamless and responsive mobile multimedia services. This architecture allows its user applications to use concurrently all the wireless network interface cards (NICs) a mobile terminal is equipped with. In particular, as mobile multimedia services are usually implemented using the UDP protocol, our architecture enables the transmission of each UDP datagram through the “most suitable” (e.g. most responsive, least loaded) NIC among those available at the time a datagram is transmitted. We term this operating mode of our architecture Always Best Packet Switching (ABPS). ABPS enables the use of policies for load balancing and recovery purposes. In essence, the architecture we propose consists of the following two principal components: (i) a fixed proxy server, which acts as a relay for the mobile node and enables communications from/to this node regardless of possible firewalls and NAT systems, and (ii) a proxy client running in the mobile node responsible for maintaining a multi-path tunnel, constructed out of all the node's NICs, with the above mentioned fixed proxy server. We show how the architecture supports multimedia applications based on the SIP and RTP/RTCP protocols, and avoids the typical delays introduced by the two way message/response handshake of the SIP signaling protocol. Experimental results originated from the implementation of a VoIP application on top of the architecture we propose show the effectiveness of our approach.