Personalized web feeds based on ontology technologies

The rapid development of the social Web has resulted in diverse Web 2.0 applications for accessing various Web feeds such as Weblogs, news headlines, business products, real time information and Podcasts. Due to the masses of Web feeds available on the Internet, a major challenge is how to access them efficiently. Conventional methods of manually finding and matching keyword for Web feeds are time-consuming and inaccurate. This study addresses this issue by defining a Personalized Web Feeds Framework (PWFF) for integrating ontology technologies into Web feeds and user profiles. The proposed PWFF is used to develop an Ontology-based Personalized Web Feed Platform (OPWFP) that provides customized Web feeds for personnel needs. To demonstrate the feasibility of OPWFP, the experimental results illustrate the efficiency and effectiveness of the proposed approach.     

Commodity or competitive advantage? Analysis of the ERP value paradox

A true e-business enabled firm needs the support from a well-tuned enterprise resource planning (ERP) system for providing real time data. However, many companies complain that after their huge investments in ERP systems, they found the ERP systems do not bring them new orders, new profits, or competitive advantage as ERP vendors claim. Academic studies also found mixed results regarding ERP’s payoff. In line with resource based view (RBV), the study proposes an integrated model to shed light on the ERP value paradox. We try to answer “With what organizational resources and by building what firm specific capabilities, the investment in ERP systems may bring firms competitive advantage”. Using a sample of 150 ERP and e-business adopters in the US, we found that (1) organizational resources such as managerial skills and organizational change management play a more important role than IT resources (ERP, e-Business technologies) in generating business integration capability. (2) However, neither IT resources nor organizational resources directly provide firms with competitive advantage. Instead, business integration capability built from the two resources plays a mediating role through which business achieves competitive advantage.     

Adaptive PI Hermite neural control for MIMO uncertain nonlinear systems

This paper presents an adaptive PI Hermite neural control (APIHNC) system for multi-input multi-output (MIMO) uncertain nonlinear systems. The proposed APIHNC system is composed of a neural controller and a robust compensator. The neural controller uses a three-layer Hermite neural network (HNN) to online mimic an ideal controller and the robust compensator is designed to eliminate the effect of the approximation error introduced by the neural controller upon the system stability in the Lyapunov sense. Moreover, a proportional–integral learning algorithm is derived to speed up the convergence of the tracking error. Finally, the proposed APIHNC system is applied to an inverted double pendulums and a two-link robotic manipulator. Simulation results verify that the proposed APIHNC system can achieve high-precision tracking performance. It should be emphasized that the proposed APIHNC system is clearly and easily used for real-time applications.     

Supervisory adaptive dynamic RBF-based neural-fuzzy control system design for unknown nonlinear systems

Many published papers show that a TSK-type fuzzy system provides more powerful representation than a Mamdani-type fuzzy system. Radial basis function (RBF) network has a similar feature to the fuzzy system. As this result, this article proposes a dynamic TSK-type RBF-based neural-fuzzy (DTRN) system, in which the learning algorithm not only online generates and prunes the fuzzy rules but also online adjusts the parameters. Then, a supervisory adaptive dynamic RBF-based neural-fuzzy control (SADRNC) system which is composed of a DTRN controller and a supervisory compensator is proposed. The DTRN controller is designed to online estimate an ideal controller based on the gradient descent method, and the supervisory compensator is designed to eliminate the effect of the approximation error introduced by the DTRN controller upon the system stability in the Lyapunov sense. Finally, the proposed SADRNC system is applied to control a chaotic system and an inverted pendulum to illustrate its effectiveness. The stability of the proposed SADRNC scheme is proved analytically and its effectiveness has been shown through some simulations.     

The two-equal-disjoint path cover problem of Matching Composition Network

Embedding of paths have attracted much attention in the parallel processing. Many-to-many communication is one of the most central issues in various interconnection networks. A graph G is globally two-equal-disjoint path coverable if for any two distinct pairs of vertices (u,v) and (w,x) of G, there exist two disjoint paths P and Q satisfied that (1) P (Q, respectively) joins u and v (w and x, respectively), (2) |P|=|Q|, and (3) V(PQ)=V(G). The Matching Composition Network (MCN) is a family of networks which two components are connected by a perfect matching. In this paper, we consider the globally two-equal-disjoint path cover property of MCN. Applying our result, the Crossed cube CQ_n, the Twisted cube TQ_n, and the Möbius cube MQ_n can all be proven to be globally two-equal-disjoint path coverable for n5.     

Coordinated ordering decisions for products with short lifecycle and variable selling price

The supplier–buyer coordination is an important policy in the supply chain management. The buyer in the two-echelon inventory system with regular selling season has to face the uncertainty of customer demand, supplier’s delivery time and variable price change. At the same time, the supplier has to consider the inventory holding and delay cost. The objective of this study is to develop an integrated supply chain strategy for products with short lifecycle and variable selling price to entice cooperation. The strategy must provide a win–win situation for both the supplier and the buyer. A numerical case example, sensitivity analysis and compensation mechanism are given to illustrate the model.     

Design of BOM configuration for reducing spare parts logistic costs

This paper proposes an approach to reduce the total operational cost of a spare part logistic system by appropriately designing the BOM (bill of material) configuration. A spare part may have several vendors. Parts supplied by different vendors may vary in failure rates and prices – the higher the failure rate, the lower the price. Selecting vendors for spare parts is therefore a trade-off decision. Consider a machine where the BOM is composed of s critical parts and each part has k vendors. The number of possible BOM configurations for the machine is then k^s. For each BOM configuration, we can use OPUS10 (proprietary software) to calculate an optimum inventory policy and its associated total logistic cost. Exhaustively searching the solution space by OPUS10 can yield an optimal BOM configuration; however, it may be formidably time-consuming. To remedy the time-consuming problem, this research proposes a GA-neural network approach to solve the BOM configuration design problem. A neural network is developed to efficiently emulate the function of OPUS10 and a GA (genetic algorithm) is developed to quickly find a near-optimal BOM configuration. Experiment results indicate that the approach can obtain an effective BOM configuration efficiently.     

A Fuzzy Ontological Knowledge Document Clustering Methodology

This correspondence presents a novel hierarchical clustering approach for knowledge document self-organization, particularly for patent analysis. Current keyword-based methodologies for document content management tend to be inconsistent and ineffective when partial meanings of the technical content are used for cluster analysis. Thus, a new methodology to automatically interpret and cluster knowledge documents using an ontology schema is presented. Moreover, a fuzzy logic control approach is used to match suitable document cluster(s) for given patents based on their derived ontological semantic webs. Finally, three case studies are used to test the approach. The first test case analyzed and clustered 100 patents for chemical and mechanical polishing retrieved from the World Intellectual Property Organization (WIPO). The second test case analyzed and clustered 100 patent news articles retrieved from online Web sites. The third case analyzed and clustered 100 patents for radio-frequency identification retrieved from WIPO. The results show that the fuzzy ontology-based document clustering approach outperforms the K-means approach in precision, recall, F-measure, and Shannon's entropy.     

NMR microscopy of single neurons at 500 MHZ

Previous NMR microimaging studies at 360 MHz have demonstrated a clear differentiation between the nucleus and cytoplasm in isolated single neurons. In particular, theT ₂ of the cell nucleus is 2.5 times larger than that of the cytoplasm. In order to determine the magnitude of possibleT ₂ ^* influences on these observations, images of single cells have been obtained at 500 MHz using spin-echo and line-narrowing sequences. Comparison of the images acquired by the two sequences, and of the spin-echo images at 360 and 500 MHz, imply that anyT ₂ ^* contributions are relatively small. Consequently, the measuredT ₂ differences in spin-echo imaging represent a true difference in theT ₂ relaxation in the two cellular compartments.