Spin-valve planar Hall sensor for single bead detection

The planar Hall effect (PHE) sensor with a junction size of 3 μm × 3 μm for a single micro-bead detection has been fabricated successfully using a typical spin-valve thin film Ta(5)/NiFe(16)/Cu(1.2)/NiFe(2)/IrMn(15)/Ta(5) nm. The PHE sensor exhibits a sensitivity of about 7.2 μV Oe^?1 in the magnetic field range of ±7 Oe approximately. We have performed an experiment to illustrated the possibility of single micro-bead detection by using a PHE sensor. A single micro-bead of 2.8 μm diameter size is secluded from 0.1% dilute solution of the Dynabeads^® M-280 dropped on the sensor surface and is located on the sensor junction by using a micro magnetic needle. The comparison of the PHE voltage profiles in the field range from 0 to 20 Oe in the absence and presence of a single micro-bead identifies a single Dynabeads^® M-280, the maximal signal change as large as ΔV ～ 1.1 μV can be obtained at the field ～6.6 Oe. The results are well described in terms of the reversal of a basic single domain structure.     

An improvement on the digital redesign method using fuzzy PWM controller

In this paper, a new digital redesign composed of pulse width modulator (PWM) is proposed. The proposed PWM combines fuzzy logic with genetic algorithm (GA) to tune the parameter of the proposed controller such that the output response of hybrid system closely matches the one of original continuous system. Finally, an illustrated example is proposed to show the proposed method is superior to the existing one.     

Combining GA and iterative searching DOA estimation for CDMA signals

This paper deals with direction-of-arrival (DOA) estimation based on iterative searching technique for code-division multiple access signals. It has been shown that the iterative searching technique is more likely to converge to a local maximum, causing errors in DOA estimation. In conjunction with a genetic algorithm for selecting initial search angle, we present an efficient approach to achieve the advantages of iterative DOA estimation with fast convergence and more accuracy estimate over existing conventional spectral searching methods. Finally, several computer simulation examples are provided for illustration and comparison.     

Electroplating of nickel films at ultra low electrolytic temperature

In this paper, we have demonstrated a successful electroplating process of nickel (Ni) in a sulfamate electrolyte bath at ultra low electrolytic temperatures of 273–278 K. The potentiostatic mode is essential for the electroplating process rather than galvanostatic mode. The reason is that diffusion-limited current can be easily obtained by applying a specific potential which is higher than reduction potential. On the contrary, galvanostatic mode can not identify the diffusion-limited current and the reduction will suspend while the setting current is higher than diffusion-limited current ranged in hundreds of μA. The microstructure, morphology and hardness of the Ni electrodeposits were characterized using grazing incidence x-ray diffractometer, atomic force microscopy and nano-indentation test were performed. The hardness of Ni film was much enhanced to around 6.37 GPa at 273 K to 6.18 GPa at 278 K compared with that around 4.11 GPa at 288 K to 4.01 GPa at 293 K. The normal hardness of pure nickel is about 4 GPa. The enhanced hardness of Ni at ultra low temperature is attributed to both mechanisms of reduced grain size strengthening and residual compressive stress hardening.     

Performance analysis of the IEEE 802.11 DCF in the presence of the hidden stations

In this paper, we present an analytical model to evaluate the hidden station effect on the performance of the IEEE 802.11 Distributed Coordination Function (DCF) in both non-saturation and saturation condition. DCF is a random channel-access scheme based on Carrier Sense Multiple Access with Collision Avoidance (CSMA/CA) method and the exponential backoff procedure. DCF is widely used and can support both wireless network with an access point and ad hoc wireless network because of its random channel-access method. On the other hand, this method unavoidably suffers the hidden station effect that causes significant performance degradation. As shown in this paper, hidden stations occur frequently in real-world settings, and the performance impact on the 802.11 DCF is a significant concern, but it has not been adequately studied. We study this problem through a spatial–temporal analysis and a Markov chain model. Our model generalizes the existing work on the performance modeling of 802.11 DCF for both non-saturation and saturation conditions. The scenario of no hidden station can be considered as a special case in our model. The performance of our model is evaluated by comparison with ns-2 simulations.     

Activity-based divergent supply chain planning for competitive advantage in the risky global environment: A DEMATEL-ANP fuzzy goal programming approach

Supply chain management allows modern enterprises to relax their own capacities and produce in a more flexible manner for diversified consumer demands. However, for an enterprise with divergent supply chain (DSC) and multiple product lines, to plan the production allocation for higher competitive advantage in the risky global market is a challenging problem. The existing literature still has not address this problem very well. This paper is aimed to treat this problem by using an integrated approach of activity based costing (ABC) and management, five forces analysis, risk and value-at-risk analysis, decision making trial and evaluation laboratory (DEMATEL), analytic network process (ANP), and fuzzy goal programming (FGP). The proposed model can effectively incorporate the key factors of precise costing, managerial constraints, competitive advantage analysis, and risk management into DSC forecasting and multi-objective production planning. A case study of a consumer-oriented cell phone DSC is also presented. The sensitivity analysis shows that identifying and relaxing crucial constraints can play an important role in DSC planning for higher competitive advantage and lower risk.     

An efficient fuzzy weighted average algorithm for the military UAV selecting under group decision-making

The fuzzy weighted average (FWA), which is a function of fuzzy numbers and is useful as an aggregation method in engineering or management science based on fuzzy sets theory. It provides a discrete approximate solution by α-cuts level representation of fuzzy sets and interval analysis. Since the FWA method has an exponential complexity, thus several researches have focused on reducing this complexity. This paper also presents an enhanced fuzzy weighted average approach to achieve the objective of reducing the complexity. This proposed approach is through an improved initial solution for original FWA algorithm, and a two-phase concept by extending and applying both the algorithms of Chang et al. [4] and Guu [14]. Although the complexity of the proposed FWA algorithm is O(n) the same as Guu [14] which is the best level achieved to date. But from the experimental results appear that the proposed algorithm is more efficient, which only needs a few evaluated numbers and spend much less overall CPU time than Guu [14] and other FWA algorithms. In order to demonstrate the usefulness of this study, a practical example for unmanned aerial vehicle (UAV) selecting under military requirement has illustrated. Additionally, a computer-based interface, which helps the decision maker make decisions more efficiently, has been developed.     

Optimal assembly plan generation: a simplifying approach

The main difficulty in the overall process of optimal assembly plan generation is the great number of different ways to assemble a product (typically thousands of solutions). This problem confines the application of most existing automated planning methods to products composed of only a limited number of components. The presented method of assembly plan generation belongs to the approach called “disassembly” and is founded on a new representation of the assembly process, with introduction of a new concept, the equivalence of binary trees. This representation allows to generate the minimal list of all non-redundant (really different) assembly plans. Plan generation is directed by assembly operation constraints and plan-level performance criteria. The method was tested for various assembly applications and compared to other generation approaches. Results show a great reduction in the combinatorial explosion of the number of plans. Therefore, this simplifying approach of assembly sequence modeling allows to handle more complex products with a large number of parts.     

A fuzzy GARCH model applied to stock market scenario using a genetic algorithm

In this paper, we derive a new application of fuzzy systems designed for a generalized autoregression conditional heteroscedasticity (GARCH) model. In general, stock market performance is time-varying and nonlinear, and exhibits properties of clustering. The latter means simply that certain large changes tend to follow other large changes, and in general small changes tend to follow other small changes. This paper shows results from using the method of functional fuzzy systems to analyze the clustering in the case of a GARCH model.The optimal parameters of the fuzzy membership functions and GARCH model are extracted using a genetic algorithm (GA). The GA method aims to achieve a global optimal solution with a fast convergence rate for this fuzzy GARCH model estimation problem. From the simulation results, we have determined that the performance is significantly improved if the leverage effect of clustering is considered in the GARCH model. The simulations use stock market data from the Taiwan weighted index (Taiwan) and the NASDAQ composite index (NASDAQ) to illustrate the performance of the proposed method.