How to achieve leagility: A case study of a personal computer original equipment manufacturer in Taiwan

Taiwan is famous for its personal computer (PC) products, and this success demonstrates that Taiwanese manufacturers have effective strategies in managing supply chains of PC-related products. Among various strategies of supply chain management, achieving leagility is the main goal. The purpose of this study is to illustrate how a PC original equipment manufacturer (OEM) in Taiwan achieves leagility through reengineering its supply chain. The case study shows how the company adjusts its production processes from build-to-order (BTO) to configuration-to-order (CTO) to achieve leagility. Through this case study, some experiences of operating global logistics could be shared.     

Investigating acceptance toward mobile learning to assist individual knowledge management: Based on activity theory approach

Mobile devices could facilitate human interaction and access to knowledge resources anytime and anywhere. With respect to wide application possibilities of mobile learning, investigating learners’ acceptance towards it is an essential issue. Based on activity theory approach, this research explores positive factors for the acceptance of m-learning systems. In the research, we developed an m-learning system for learners’ knowledge management and invited 152 participants who knew how to use the m-learning system then report on their experience. The results show that enhancing learners’ satisfaction, encouraging learners’ autonomy, empowering system functions, and enriching interaction and communication activities have a significant positive influence on the acceptance of m-learning systems.     

Energy-efficient cooperative data aggregation for wireless sensor networks

Recently, cooperative communication mechanism is shown to be a promising technology to improve the transmit diversity only by a single transceiver antenna. Using this communication paradigm, multiple source nodes are able to coordinate their transmissions so as to obtain energy savings. As data aggregation is one of the most important operations in wireless sensor networks, this paper studies the energy-efficient data aggregation problem through cooperative communication. We first define the cooperative data aggregation (CDA) problem, and formally prove that this problem is NP-Hard. Due to the difficult nature of this problem, we propose a heuristic algorithm MCT for cooperative data aggregation. The theoretical analysis shows that this algorithm can reach the approximate performance ratio of 2. Moreover, the distributed implementation DMCT of the algorithm is also described. We prove that both centralized and distributed algorithms can construct the same topology for cooperative data aggregation. The experimental simulations show that the proposed algorithms will decrease the power consumption by about 12.5% and 66.3% compared with PEDAP and PEGASIS algorithms respectively.     

Distributed bandwidth allocation based on alternating evolution algorithm

In a network, end nodes have to compete for bandwidth through some distributed congestion control algorithms. It is a great challenge to ensure the efficiency and fairness of the distributed control algorithms. TCP congestion control algorithms do not perform well in terms of their efficiency and fairness in high speed networks. In this paper, we propose a novel asymptotic evolution algorithm based on the Logistic Model to allocate limited bandwidth resource. The algorithm introduces an explicit bandwidth pre-allocation factor. The factor is carried by the packet and is computed in routers based on the information of the router capacity, the aggregate load, and the instantaneous queue length; therefore the algorithm does not require the routers to keep the per-flow state. According to this pre-allocation bandwidth factor, the senders asymptotically adjust their sending rate and the bandwidth factor changes asymptotically along with the variation of the aggregate load and the queue length in the routers; therefore the sending rate and the pre-allocation bandwidth factor form alternating evolution and eventually reach a steady state.     

Adaptive Variational Method for Restoring Color Images with High Density Impulse Noise

In this paper, a new variational framework of restoring color images with impulse noise is presented. The novelty of this work is the introduction of an adaptively weighting data-fidelity term in the cost functional. The fidelity term is derived from statistical methods and contains two weighting functions as well as some statistical control parameters of noise. This method is based on the fact that impulse noise can be approximated as an additive noise with probability density function (PDF) being the finite mixture model. A Bayesian framework is then formulated in which likelihood functions are given by the mixture model. Inspired by the expectation-maximization (EM) algorithm, we present two models with variational framework in this study. The superiority of the proposed models is that: the weighting functions can effectively detect the noise in the image; with the noise information, the proposed algorithm can automatically balance the regularity of the restored image and the fidelity term by updating the weighting functions and the control parameters. These two steps ensure that one can obtain a good restoration even though the degraded color image is contaminated by impulse noise with large ration (90% or more). In addition, the numerical implementation of this algorithm is very fast by using a split algorithm. Some numerical experimental results and comparisons with other methods are provided to show the significant effectiveness of our approach.     

Data race: tame the beast

Data races hamper parallel programming and threaten the reliability of future software. This paper proposes the data race prevention scheme View-Oriented Data race Prevention (VODAP), which can prevent data races in the View-Oriented Parallel Programming (VOPP) model. VOPP is a novel shared-memory data-centric parallel programming model, which uses views to bundle mutual exclusion with data access. We have implemented the data race prevention scheme with a memory protection mechanism. Experimental results show that the extra overhead of memory protection is trivial in our applications. The performance is evaluated and compared with modern programming models such as OpenMP and Cilk.     

基于MSP430的二线制高精度表头设计

针对传统的二线制表头在高温下测量精度差、温漂大的特点,提出了一种在高温下的高精度数显表头的设计方案。分别介绍了其软硬件的实现方法,即采用超低功耗微处理器MSP430F4250采集回路中的电流值,采用24位ADC转换器ADS1244进行模数转换,最后将经过运算的变送器输出信号值在LED数码管中加以显示。实测结果证明,该表头在高温下测量精度高、工作可靠、抗干扰性强、实用性强,势必会成为无源二线制仪表的发展方向。