A strategy-based process for effectively determining system requirements in eCRM development

Customer relationship management (CRM) is an important concept to maintain competitiveness at e-commerce. Thus, many organizations hastily implement eCRM and fail to achieve its goal. CRM concept consists of a number of compound components on product designs, marketing attributes, and consumer behaviors. This requires different approaches from traditional ones in developing eCRM. Requirements engineering is one of the important steps in software development. Without a well-defined requirements specification, developers do not know how to proceed with requirements analysis. This research proposes a strategy-based process for requirements elicitation. This framework contains three steps: define customer strategies, identify consumer and marketing characteristics, and determine system requirements. Prior literature lacks discussing the important role of customer strategies in eCRM development. Empirical findings reveal that this strategy-based view positively improves the performance of requirements elicitation.     

A green supplier selection model for high-tech industry

With growing worldwide awareness of environmental protection, green production has become an important issue for almost every manufacturer and will determine the sustainability of a manufacturer in the long term. A performance evaluation system for green suppliers thus is necessary to determine the suitability of suppliers to cooperate with the firm. While the works on the evaluation and/or selection of suppliers are abundant, those that concern environmental issues are rather limited. Therefore, in this study, a model for evaluating green suppliers is proposed. The Delphi method is applied first to differentiate the criteria for evaluating traditional suppliers and green suppliers. A hierarchy is constructed next to help evaluate the importance of the selected criteria and the performance of green suppliers. Since experts may not identify the importance of factors clearly, the results of questionnaires may be biased. To consider the vagueness of experts’ opinions, the fuzzy extended analytic hierarchy process is exploited. With the proposed model, manufacturers can have a better understanding of the capabilities that a green supplier must possess and can evaluate and select the most suitable green supplier for cooperation.     

Micro robot system with moving micro-car driven by electrostatic comb-drive actuators

This paper describes a silicon micro robot system (MRS) that is capable of driving micro-cars in different directions based on a ratchet mechanism and electrostatic comb-drive actuators. Lateral movement of the ratchet racks makes the micro-car move in the perpendicular direction with different velocities. Based on MEMS technology, the MRS described in this article was fabricated from a silicon on insulator wafer by using only one photo mask. In our experiments, various driving frequencies ranging from 1 to 20 Hz were used to accelerate the micro-car up to 200 μm/s. It was observed that the velocity of the micro-car was proportional to the driving frequency used in the experiments. This relation was also confirmed with our theoretical calculation. When combined with microscopes, this MRS can be applied in bio-medical analysis for transportation and classification of small samples.     

一种改进的耦合编码器的视频降噪方法

为了降低视频降噪算法的计算量,提出一种适用于H.264的分级非线性确定滤波因子的方案.该方法是对变换域时间方向滤波算法的改进,根据绝对误差和和运动适量选用相应的滤波因子后,通过调节DCT系数实现降噪.实验结果表明该方法简单、计算量小并有较好的降噪效果.     

Adaptive receiver-driven approach in P2P live streaming networks

Efficient delivery under changing network conditions is a major challenge in the design of live streaming systems. This study analyzes the key considerations and factors influencing live stream quality during system operations, and attempts to improve current P2P (peer-to-peer) live streaming systems by allowing users to enjoy high quality of service under the limitations of network resources. The proposed R-D (rate-distortion) optimized dynamic nodes join algorithm is based on multipath streaming concept and receiver-driven approach. This distributed algorithm enables the system to evaluate the current network status in order to optimize the end-to-end distortion of P2P networks. Experimental results of this study demonstrate the effectiveness of the proposed approach.     

Design and Analysis of Online Batching Systems

In this paper, we study the design and analysis of online batching systems, which can be used to model many popular IT systems such as the Video-On-Demand system and the Pull-based Data Dissemination system. We analyze how the start-up delay affects the performance of these systems and investigate the tradeoff relationship between the number of servers and the length of the start-up delay. We also study a simple online algorithm for scheduling online batching systems. By deriving close lower and upper bounds, we prove that our algorithm is near optimal.     

A path radiance estimation algorithm using reflectance measurements in radiometric control areas

A new algorithm of path radiance estimation based on measurements of surface reflectance at radiometric control areas (RCAs) is proposed. Path radiance estimates of the proposed RCA-based method were compared against estimates of other methods including the dark object subtraction (DOS) method, the multi-band regression (MBR) technique and the covariance matrix method (CMM). The RCA-based method is superior to other methods based on three qualitative assessment criteria and a quantitative assessment based on measurements of molecule and aerosol optical depths (AODs) available from the Aerosol Robotic Network (AERONET) and Moderate Resolution Imaging Spectroradiometer (MODIS) data archive. Asphalt-paved surface, which could be easily identified in most images, was also found to be a good choice for RCAs. The DOS method and the CMM tend to overestimate path radiances. Although in our study the MBR technique and the RCA-based method seem to perform equally well, estimates of the MBR technique may be less reliable.     

Black-Box Trace&Revoke Codes

We address the problem of designing an efficient broadcast encryption scheme which is also capable of tracing traitors. We introduce a code framework to formalize the problem. Then, we give a probabilistic construction of a code which supports both traceability and revocation. Given N users with at most r revoked users and at most t traitors, our code construction gives rise to a Trace&Revoke system with private keys of size O((r+t)logN) (which can also be reduced to constant size based on an additional computational assumption), ciphertexts of size O((r+t)logN), and O(1) decryption time. Our scheme can deal with certain classes of pirate decoders, which we believe are sufficiently powerful to capture practical pirate strategies. In particular, our code construction is based on a combinatorial object called (r,s)-disjunct matrix, which is designed to capture both the classic traceability notion of disjunct matrix and the new requirement of revocation capability. We then probabilistically construct (r,s)-disjunct matrices which help design efficient Black-Box Trace&Revoke systems. For dealing with “smart” pirates, we introduce a tracing technique called “shadow group testing” that uses (close to) legitimate broadcast signals for tracing. Along the way, we also proved several bounds on the number of queries needed for black-box tracing under different assumptions about the pirate’s strategies.     

Real-time capacity requirement planning for make-to-order manufacturing with variable time-window orders

In a make-to-stock (MTS) manufacturing environment using material requirement planning (MRP), checking the capacity feasibility of a master production schedule (MPS) requires capacity requirement planning (CRP) that can be easily calculated. The time window of an order is the time interval from its ready date to its due date. In a make-to-order (MTO) manufacturing environment, the CRP method checks whether a set of orders with different time windows can be scheduled for timely completion. This corporate-level CRP problem has long perplexed MTO contract manufacturers, such as those in the fashion industry. This study therefore develops an efficient and effective CRP approach that considers orders with variable time windows. Real-time capacity feasibility can be checked on both the corporate planning and detailed operational scheduling levels by applying the preemptive earliest due date (PEDD) rule to a single machine problem. This simple and efficient dispatching rule can assess the impact on capacity consumption each time an inquiry order is received or select a set of pre-prioritized orders that can be feasibly scheduled. The efficiency of a supply chain network is affected by its overall lead time, which includes time spent on order processing, manufacturing, and transportation. The proposed approach significantly reduces the order processing time and enhances supply chain efficiency.     

Accurate surface tension measurement of glass melts by the pendant drop method

A pendant drop tensiometer, coupled with image digitization technology and a best-fitting algorithm, was built to accurately measure the surface tension of glass melts at high temperatures. More than one thousand edge-coordinate points were obtained for a pendant glass drop. These edge points were fitted with the theoretical drop profiles derived from the Young-Laplace equation to determine the surface tension of glass melt. The uncertainty of the surface tension measurements was investigated. The measurement uncertainty (σ) could be related to a newly defined factor of drop profile completeness (Fc): the larger the Fc is, the smaller σ is. Experimental data showed that the uncertainty of the surface tension measurement when using this pendant drop tensiometer could be ±3 mN∕m for glass melts.