Power Distribution Fault Cause Identification With Imbalanced Data Using the Data Mining-Based Fuzzy Classification E-Algorithm

Power distribution systems have been significantly affected by many outage-causing events. Good fault cause identification can help expedite the restoration procedure and improve the system reliability. However, the data imbalance issue in many real-world data sets often degrades the fault cause identification performance. In this paper, the E-algorithm, which is extended from the fuzzy classification algorithm by Ishibuchi to alleviate the effect of imbalanced data constitution, is applied to Duke Energy outage data for distribution fault cause identification. Three major outage causes (tree, animal, and lightning) are used as prototypes. The performance of E-algorithm on real-world imbalanced data is compared with artificial neural network. The results show that the E-algorithm can greatly improve the performance when the data are imbalanced     

A distributed adverse drug reaction detection system using intelligent agents with a fuzzy recognition‐primed decision model

Discovering unknown adverse drug reactions (ADRs) in postmarketing surveillance as early as possible is highly desirable. Nevertheless, current postmarketing surveillance methods largely rely on spontaneous reports that suffer from serious underreporting, latency, and inconsistent reporting. Thus these methods are not ideal for rapidly identifying rare ADRs. The multiagent systems paradigm is an emerging and effective approach to tackling distributed problems, especially when data sources and knowledge are geographically located in different places and coordination and collaboration are necessary for decision making. In this article, we propose an active, multiagent framework for early detection of ADRs by utilizing electronic patient data distributed across many different sources and locations. In this framework, intelligent agents assist a team of experts based on the well‐known human decision‐making model called Recognition‐Primed Decision (RPD). We generalize the RPD model to a fuzzy RPD model and utilize fuzzy logic technology to not only represent, interpret, and compute imprecise and subjective cues that are commonly encountered in the ADR problem but also to retrieve prior experiences by evaluating the extent of matching between the current situation and a past experience. We describe our preliminary multiagent system design and illustrate its potential benefits for assisting expert teams in early detection of previously unknown ADRs. © 2007 Wiley Periodicals, Inc. Int J Int Syst 22: 827–845, 2007.     

Neural networks and blood cell identification

The objective of this project is to propose a method of identifying cells found in human blood and to classify them based upon their morphological features using neural networks. The project focuses on three major blood cell types, namely, erythrocytes, leukocytes and platelets. The data are collected using peripheral blood smears from clinical patients. The image acquisition requires 100x magnification on all the blood smears, the preprocessing involves the use of median and edge enhance filters; the feature extraction is done by performing the wavelet transform on the images. Finally classification of the blood cell types is done using ALOPEX and Back Propagation trained neural networks. The efficacy of both networks is then compared by comparing their outputs and number of iterations required to reach the final result.     

The importance of electrochemistry-related etching in thegate-groove fabrication for InAlAs/InGaAs HFETs

For the first time, the surface metal on nonalloyed ohmic electrodes is found to significantly change the profiles of gate grooves, when resist openings are employed to monitor drain current during wet-chemical gate recess for sub-micron InAlAs/lnGaAs heterojunction field-effect transistors (HFETs). The surface metal of Ni enhances the etching rate in comparison with that in the absence of electrodes by a factor of 4 and 10, laterally and vertically, which is favorable to fabricate deep gate grooves with small side etching. The Pt surface metal, however, leads to preferential etching of InGaAs over InAlAs, which can be useful to realize large side etching. The existence of an electrochemistry-related etching component, which arises when the ohmic electrodes are present during recess etching, is considered to be responsible for these behaviors     

Leiomyomatosis peritonealis disseminata. Two case reports

AIM: To study the action of quercetin (Que) on inhibiting platelet aggregation. METHODS: Active oxygen free radicals produced by xanthine/xanthine oxidase (Xan/XO) reaction was used, platelet aggregation was determined by the turbidimetric method, and the Xan/XO oxyradicals generating reaction by luminol-dependent chemiluminescence (Che) method. RESULTS: Active oxygen free radicals enhanced the platelet aggregation induced by ADP 1.6 mumol.L-1. The rate of maximal aggregation increased from 29%-38% for ADP to 59%-70% for ADP + Xan/XO. The enhancement was abolished by the treatment of platelet-rich plasma (PRP) with Que 650 mumol.L-1 or hydrocortisone (Hyd) 900 mg.L-1. Both Que and Hyd scavenged the active oxyradicals in vitro. The Che was decreased by 75.7% (Que 4 mumol.L-1) and 79.0% (Hyd 900 mg.L-1) as compared with control. CONCLUSION: Active oxygen free radicals participated in the platelet aggregation, and scavenging oxyradicals by Que was one of mechanisms of inhibiting platelet aggregation.     

Analysis of a resonant-cavity enhanced GaAs/AlGaAs MSMphotodetector

The authors have developed a 2-D device simulator for heterostructure metal-semiconductor-metal (MSM) photodetectors. They have incorporated a model of multilayer optics into the simulator and used it to analyze the temporal response of a resonant-cavity enhanced heterostructure with a confining buffer layer and a distributed Bragg reflector (DBR). The authors show that through fine tuning the layer thicknesses, optical resonance enhancement of the light absorption can be obtained     

Performance analysis of the bidirectional associative memory and animproved model from the matched-filtering viewpoint

This paper discusses the bidirectional associative memory (BAM) model from the matched-filtering viewpoint and offers it a new interpretation. Our attention is focused on the problem of stability and attractivity of equilibrium states. Several sufficient and/or necessary conditions are presented. To improve the BAM performance, an exponential function is used to enhance the correlations between the binary vectors of the retrieval key and that of the stored pattern similar to the key. The modified model is shown to be asymptotically stable. Theoretical analysis and simulation results demonstrate that the modified model performs much better than the original BAM in terms of memory capacity and error correction capability.     

适用于啤酒行业能源管理的智能冷量积算仪

介绍了智能冷量积算仪的测量原理以及软硬件设计，该仪表适用于啤酒行业中冰水和乙二醇水溶液冷量计量，并得到成功应用，具有广阔的应用前景。     

Novel algorithms for shared segment protection

The major challenges in designing survivable schemes are how to allocate a minimal amount of spare resources (e.g., bandwidth) using fast (e.g., polynomial-time) algorithms, and, in case a failure occurs, to be able to recover quickly from it. All existing approaches invariably make tradeoffs. We propose novel shared segment protection algorithms which make little or no compromise . We develop an elegant integer linear programming (ILP) model to determine an optimal set of segments to protect a given active path. Although the ILP approach is useful for a medium-size network, it is too time consuming for large networks. Accordingly, we also design a fast heuristic algorithm based on dynamic programming to obtain a near-optimal set of segments. Although the heuristic algorithm has a polynomial time complexity, it can achieve a bandwidth efficiency as high as some best-performing shared path protection schemes and, at the same time, much faster recovery than these shared path protection schemes. The proposed scheme is also applicable to a wide range of networking technologies, including Internet Protocol and wavelength-division multiplexing networks under the generalized multiprotocol label switched framework.