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Arabidopsis inositol polyphosphate 6-/3-kinase gene (AtIpk2β) has previously been demonstrated to participate in inositol phosphate metabolism. However, overall little is known about its physiological functions in higher plants. Here, we report that AtIpk2β positively regulates axillary shoot branching in Arabidopsis. AtIpk2β overexpression plants displayed more axillary shoot branches and produced twice as many total branches than those of the wild-type. This phe notype was confirmed in ipk2β mutant transgenic lines. The expres sion pattern of AtIpk2β was similar to in vivo IAA distribution. Moreover, AtIpk2β can be induced by exogenous IAA. The overexpression plants exhibited IAA-related phenotypes and altered IAA responses. Our experiments showed that the transcription of some auxin-related genes was altered in AtIpk2β overexpression plants. Taken together, our data indicate that AtIpk2β plays a role in axillary shoot branching via auxin signaling in Arabidopsis. [ABSTRACT FROM AUTHOR]

Designing the approximate reasoning matching schemes and the corresponding algorithms with similarity relation ℚ instead of equivalence relation ℚ can reflect the nature of approximate reasoning and meet more application expectations. This paper bases on similarity relation ℚ and introduces the type V matching scheme and the corresponding approximate reasoning type V ℚ-algorithm with the given input A* and knowledge A → B. We also present type V completeness and type V perfection of knowledge base K in ℚ-logic ℂℚ in this paper. [ABSTRACT FROM AUTHOR]

This paper introduces and investigate the ℚ-knowledge mass, ℚ-knowledge universe, ℚ-knowledge base and ℚ-automatic reasoning system bases on the similarity logic ℂℚ. We also present and investigate the ℚ-true level k knowledge circle, extended ℚ- knowledge base, extended Qℚ-automatic reasoning system and the level (k,j) perfection of extended Qℚ- knowledge base $$ \mathbb{K}^V $$ in this paper. [ABSTRACT FROM AUTHOR]

Based on fuzzy logic theory, the information fusion technique at decision-making level is introduced for fault diagnosis system. A comprehensive fault diagnosis method based on fuzzy logic and D-S evidence theory is presented by making use of multi-sensor information fusion technique. In this method, the basic reliability distribution of evidence theory is obtained by using fuzzy membership function, which can significantly improve the accuracy of the fault diagnosis through taking full advantages of redundant and complementary fault information from all sensors. Finally the method is applied for fault diagnosis of ship diesel engine. Diagnostic results indicate that the technique is effective, greatly improving the efficiency of fault diagnosis. [ABSTRACT FROM AUTHOR]

Unreliable failure detectors have been an important abstraction to build dependable communication applications over iSCSI systems subject to faults. In this paper, we propose a new implementation of a failure detector. This implementation is a variant of the heartbeat failure detector which is adaptable and can support scalable applications. In this implementation we dissociate two aspects: a basic estimation of the expected arrival date to provide a short detection time, and an adaptation of the quality of service according to application needs. [ABSTRACT FROM AUTHOR]

Knowledge of bottleneck capacity of an Internet path is critical for efficient network design, management, and usage. With emerging high speed Internet links, most traditional estimation techniques are limited in providing fast and accurate capacity estimations. In this paper, we propose a new technique, called PBProbe, to estimate high speed links. PBProbe is based on CapProbe; however, instead of solely relying on packet pairs, PBProbe employs a "packet bulk" technique and adapts the bulk length in order to overcome the well known problem with packet pair based approaches, namely the lack of accurate timer resolution. As a result, PBProbe not only preserves the simplicity and speed of CapProbe, but it also correctly estimates link capacities within a much larger range. Using analysis, we evaluate PBProbe with various bulk lengths and network configurations. We then perform emulation and Internet experiments to verify the accuracy and speed of PBProbe on high speed links. The results show that PBProbe is consistently fast and accurate in the great majority of test cases. [ABSTRACT FROM AUTHOR]

A new strategy for modeling of chaotic systems is presented, which is based on the combination of the stationary wavelet transform and Recurrent Least Squares Support Vector Machines (RLS-SVM). The stationary wavelet transform provide a sensible decomposition of the data so that the underlying temporal structures of the original time series become more tractable. The similarity of dynamic invariants between the origin and generated time series shows that the proposed method can capture the dynamics of the chaotic time series effectively. [ABSTRACT FROM AUTHOR]

Falcon-ART is a fuzzy neural network that can be used as fuzzy controllers or applied to areas such as pattern recognition, forgery detection and data analysis. Our previously proposed Falcon-DIC has stronger noise tolerance capability compared to the original Falcon-ART by employing a new clustering technique called Discrete Incremental Clustering (DIC). In this paper, Falcon-DIC is applied to perform direct gray-scale minutiae extraction. Fingerprint features extraction, or minutiae extraction, is an essential part of fingerprint identification systems. Most existing minutiae extraction methods require image preprocessing, such as binarization and thinning. Since these image processing techniques results in the loss of valuable information, our proposed approach can extract minutia directly from gray-scale fingerprint images. Experimental results show that Falcon-DIC based minutiae extraction has invariant ability to rotation and good performance on true acceptance. [ABSTRACT FROM AUTHOR]

This paper presents the results of a comparative study of linear and kernel-based methods for face recognition. We focus mainly on the experimental comparison of classification methods, i.e. Nearest Neighbor, Linear Support Vector Machine, Kernel based Nearest Neighbor and Nonlinear Support Vector Machine. Some interesting conclusions can be obtained after all of these methods are performed on two well-known database, i.e. ORL, YALE Face Database, respectively. [ABSTRACT FROM AUTHOR]

Knowledge of link capacity is important for network design, management, and utilization. With the increasing popularity of asymmetric link technologies (such as DSL, 1xRTT, and satellite links), it is desirable to have a capacity estimation technique, which can simultaneously measure forward and backward direction link capacities on an Internet path. Moreover, this estimation must often be "sender only", because of receiver limitations or lack of standards. In this study, we propose a simple, fast and accurate technique, called AsymProbe, to estimate asymmetric link capacities. AsymProbe is a "sender only", round trip procedure. It achieves asymmetric link capacity estimation by strategically altering the ratio of probe and acknowledgement packet sizes. Using simulation and testbed experiments, we validate AsymProbe with a variety of network configurations. The results show that AsymProbe can correctly estimate the asymmetric link capacities as long as an appropriate packet size ratio can be employed. [ABSTRACT FROM AUTHOR]

A Mobile "Ad hoc" wireless NETwork (MANET) is a network established for a special, often extemporaneous service customized to applications. The ad hoc network is typically set up for a limited period of time, in an environment that may change from application to application. As a difference from the Internet where the TCP/IP protocol suite supports a vast range of applications, in the MANET the protocols are tuned to a specific customer and application (eg, send a video stream across the battlefield; find out if there is a fire in the forest; establish a videoconference among several teams engaged in a rescue effort, etc). The customers move and the environment may change dynamically and unpredictably. For the MANET to retain its efficiency, the ad hoc protocols at various layers may need to self-tune to adjust to environment, traffic and mission changes. From these properties emerges the vision of the MANET as an extremely flexible, malleable and yet robust and formidable network architecture. Indeed, an architecture that can be deployed to monitor the habits of birds in their natural habitat, and which, in other circumstances, can be organized to interconnect rescue crews after a Tsunami disaster, or yet can be structured to launch deadly attacks onto unsuspecting enemies. [ABSTRACT FROM AUTHOR]