Design and implementation of an agent-based collaborative product design system

The evolution of computer science and technology has brought new opportunities for multidisciplinary designers and engineers to collaborate with each other in a concurrent and coordinated manner. The development of computational agents with unified data structures and software protocols contributes to the establishment of a new way of working in collaborative design, which is increasingly becoming an international practice. In this paper, based on the analysis of the dynamic nature of collaborative design process, a new framework for collaborative design is described. This framework adopts an agent-based approach and relocates designers, managers, systems, and the supporting agents in a unified knowledge representation scheme for product design. In order to model the constantly evolving design process and the rationales resulted from design collaboration, a Collaborative Product Data Model (CPDM) and a constraint-based Collaborative Design Process Model (CDPM) are proposed to facilitate the management and coordination of the collaborative design process as well as design knowledge management. A prototype system of the proposed framework is implemented and its feasibility is evaluated using a real design scenario whose objective is designing a set of dining table and chairs.     

A structured P2P network based on the small world phenomenon

In this paper, we propose a new structured P2P overlay network, named SW-Uinta(small-world). In order to reduce the routing latency, we firstly construct the Uinta network in which both physical characteristics of network and data semantic are considered. Furthermore, based on Uinta, a nondeterministic caching strategy is employed to allow for poly-logarithmic search time while having only a constant cache size. Compared with the deterministic caching strategy proposed by previous P2P systems, the nondeterministic caching strategy can reduce communication overhead for maintaining the routing cache table. Cache entries in the cache table of peer nodes can be updated by subsequent queries rather than only by running stabilization periodically. In the following, a novel cache replacement scheme, named the SW cache replacement scheme, is used to improve lookup performance, which has proved to satisfy the small-world principle. So we call this network SW-Uinta(small-world). After that, according to the theoretical analysis, it can be proved that SW-Uinta(small-world) can get O((log ² N)/k) search time with O(k) cache size. Lastly, the performance of SW-Uinta(small-world) is compared with those of other structured P2P networks such as Chord and Uinta. It shows that SW-Uinta(small-world) can achieve improved object lookup performance and reduce maintenance cost.

Adaptive binary tree for fast SVM multiclass classification

This paper presents an adaptive binary tree (ABT) to reduce the test computational complexity of multiclass support vector machine (SVM). It achieves a fast classification by: (1) reducing the number of binary SVMs for one classification by using separating planes of some binary SVMs to discriminate other binary problems; (2) selecting the binary SVMs with the fewest average number of support vectors (SVs). The average number of SVs is proposed to denote the computational complexity to exclude one class. Compared with five well-known methods, experiments on many benchmark data sets demonstrate our method can speed up the test phase while remain the high accuracy of SVMs.     

Design of moving magnet type pickup actuator using inserted coil

Recently, the demand of the information storage devices with large storage capacity such as Blu-ray Disc and high-definition television is increased. In keeping with this trend, the optical storage devices are also required to have high data transfer rate and large storage capacity. To satisfy these requirements, the actuator for optical disc drive should have a high servo bandwidth to compensate the vibration of optical disc. The servo bandwidth is limited by some flexible modes of the actuator, thus it is essential to make these frequencies of flexible modes to high frequency region. The frequency of flexible mode depends on materials and shape. Stiff materials and simple shape is useful to increase the frequency of flexible mode. In this paper, we suggested a moving magnet type actuator having flexible modes which are happened at high frequency region. Generally, the moving magnet type actuator has an advantage to increase the frequency of flexible mode because the moving magnet type actuator has simple structure and the Young’s modulus of magnet is high. However, large moving mass and inefficiency of Electromagnetic (EM) circuit cut down driving sensitivities of actuator. To improve driving sensitivities, we designed the model with the closed EM circuit for tracking actuation. The design of experiments (DOE) procedure is applied to get proper design parameters and the variable metric method (VMM) which is a technique of optimization is used to improve driving sensitivity. The lens holder is also improved based on the optimization result of EM circuit. And to make up for the low efficiency of EM circuit, the thermal stability is checked on condition that the input current is very high. At last, the final design of moving magnet type actuator is suggested and it is verified that the driving performance and the structural stiffness of the final design is sufficient.     

Design of micromirror actuator by ionic polymer metal composites

Microactuators for micromirror system have found many applications in various areas including projection displays, optical switches, RF switches and so on. In this paper we demonstrated micromirror actuator using ionic polymer metal composites (IPMC) that is a suitable candidate, since it has many attractive qualities such as durability, aquatic, miniature and light-weighted. Specially, IPMC has extraordinary advantages which are simple bending motion for low driving voltage (1–2 V), low power consumption, and simple structure. The IPMC actuator is made of Nafion NE-1110 (Dupont Co, Ltd., 260 µm thick) layer and electrode (platinum) layers and driven by 1–4 V. The displacement measured vertically is 0.25 mm and tilting angle is 11.3°. The angular motion, which is more than 10°, is a good advantage in the field of display module. This paper shows that the IPMC actuator has enough possibility for other applications.     

Analysis of the nonlinear dynamic stability for an electrically actuated viscoelastic microbeam

In this article, based on the standard linear solid model, the Euler-Bernoulli hypothesis and the Galerkin method, an analysis of the nonlinear dynamic stability for a clamped-guided viscoelastic microbeam under both a periodic axial force and a symmetric electrostatic load is presented. By using the incremental harmonic balanced method, the boundary of the principal region of instability is got. In the numerical calculation, the effect of the environmental and inner damping, geometric nonlinear, creep quantity and the symmetric electrostatic load on the principal region of instability is discussed.     

Structure identification of Bayesian classifiers based on GMDH

This paper introduces group method of data handing (GMDH) theory to Bayesian classification, and proposes GMBC algorithm for structure identification of Bayesian classifiers. The algorithm combines two structure identification ideas of search & scoring and dependence analysis, and is able to accomplish the process of adaptive structure identification. We experimentally test two versions of Bayesian classifiers (GMBC-BDe and GMBC-BIC) over 25 data sets. The results show that, the structure identification of the two Bayesian classifiers especially GMBC-BDe is very effective. And when the data sets contain lots of noise, the superiority of Bayesian classifiers learned by GMBC is more obvious. Finally, giving a classification domain without any prior information about the noise, we recommend adopting GMBC-BDe rather than GMBC-BIC.     

A method of stepwise benchmarking for inefficient DMUs based on the proximity-based target selection

DEA is a useful nonparametric method of measuring the relative efficiency of a DMU and yielding a reference target for an inefficient DMU. However, it is very difficult for inefficient DMUs to be efficient by benchmarking a target DMU which has different input use. Identifying appropriate benchmarks based on the similarity of input endowment makes it easier for an inefficient DMU to imitate its target DMUs. But it is rare to find out a target DMU, which is both the most efficient and similar in input endowments, in real situation. Therefore, it is necessary to provide an optimal path to the most efficient DMU on the frontier through several times of a proximity-based target selection process. We propose a dynamic method of stepwise benchmarking for inefficient DMUs to improve their efficiency gradually.The empirical study is conducted to compare the performance between the proposed method and the prior methods with a dataset collected from Canadian Bank branches. The comparison result shows that the proposed method is very practical to obtain a gradual improvement for inefficient DMUs while it assures to reach frontier eventually.     

State estimation in high-mix semiconductor manufacturing

The traditional way of state estimation in semiconductor manufacturing, known as “threaded” state estimation, segregates the process data into different bins and uses the ones that match the current event of the specific context information (such as tools, layers, products) to update the process state. The limitation of threaded state estimation is that a narrowly defined process stream can result in too many different threads and insufficient data for each thread. This limitation becomes more severe in high-mix manufacturing, where there can be many products and many tools. Hence there is great interest in estimation methods that utilize all available data in the analysis. In this work, the characteristics inherent in state estimation of high-mix semiconductor manufacturing processes are analyzed, and a general framework is introduced for the non-threaded state estimation methods, i.e., state estimation without segregating the process data into different bins. The framework is based on the best linear unbiased estimate (BLUE) of a simplified stationary singular Gauss–Markov process, and non-threaded state estimation methods based on the Kalman filter, least squares and recursive least squares (RLS) are analyzed using the general framework. Simulation examples are presented to illustrate the equivalence between different algorithms. As real processes are rarely stationary, modifications to the Kalman filter and RLS are discussed. We show that in non-threaded state estimation, how to regulate the estimate covariance plays a significant role in estimation performance. To handle nonstationary disturbances that often occur in semiconductor processes, Bayesian-enhanced adaptive versions of the Kalman filter and RLS are proposed. Both simulated and industrial nonstationary processes are used to demonstrate the effectiveness of the proposed adaptive methods.     

公交车智能报站系统的设计与实现

针对公交车驾驶员手动报站存在的安全隐患问题,提出了一种新的智能报站系统设计。该系统由SPCE061A单片机、GPS、LCD和键盘组成,通过实时比较GPS信号与存储在NAND Flash中的站点信息来确定当前站点信息,实现智能播报。与传统的手动语音播报方式相比,该系统具有更好的安全性、智能性、稳定性,并且播报结果准确可靠。