Evaluating online trust using machine learning methods

Trust plays an important role in e-commerce, P2P networks, and information filtering. Current challenges in trust evaluations include: (1) fnding trustworthy recommenders, (2) aggregating heterogeneous trust recommendations of different trust standards based on correlated observations and different evaluation processes, and (3) managing efficiently large trust systems where users may be sparsely connected and have multiple local reputations. The purpose of this dissertation is to provide solutions to these three challenges by applying ordered depth-first search, neural network, and hidden Markov model techniques. It designs an opinion filtered recommendation trust model to derive personal trust from heterogeneous recommendations; develops a reputation model to evaluate recommenders\u27 trustworthiness and expertise; and constructs a distributed trust system and a global reputation model to achieve efficient trust computing and management. The experimental results show that the proposed three trust models are reliable. The contributions lie in: (1) novel application of neural networks in recommendation trust evaluation and distributed trust management; (2) adaptivity of the proposed neural network-based trust models to accommodate dynamic and multifacet properties of trust; (3) robustness of the neural network-based trust models to the noise in training data, such as deceptive recommendations; (4) efficiency and parallelism of computation and load balance in distributed trust evaluations; and (5) novel application of Hidden Markov Models in recommenders\u27 reputation evaluation

The dynamic simulation analysis of the coupling vibration of a maglev levitation frame and the levitation control system

To study the characteristics of the coupling vibration between the maglev vehicle and the track beam system, a new type of vibration test bench model was developed. Take the single maglev levitation frame as the study object, the structural characteristics of the maglev vehicle can be adequately considered in the research. Further more, the variable stiffness of the track beam makes the frequency conversion simulation possible. In addition, all types of real track irregularity excitations can be simulated through the test bench dynamics model. Based on the model, the influence of the track beam support stiffness, the track irregularity and the local support deficiency on the levitation control performance was determined using the dynamics simulation method, and the vibration resonance phenomenon of the vehicle/track system was reproduced by the dynamics simulation, too. The developed of the model can increase the research progress of the maglev dynamics research

Human Nav1.5 F1486 deletion associated with long-QT syndrome leads to deficiency in inactivation and reduces lidocaine sensitivity

Indiana University-Purdue University Indianapolis (IUPUI)The cardiac voltage-gated sodium channel α subunit Nav1.5 generates the cardiac sodium current, which is essential for the initiation and propagation of the cardiac action potentials. Mutations of SCN5A, the gene that encodes Nav1.5, have been well documented to cause long-QT syndrome (LQTs) by disrupting channel inactivation and increasing late sodium current. Previous studies have revealed the importance of the intracellular loop region between transmembrane domain III and IV of sodium channel α subunit in regulating the fast inactivation. A recent clinical case study reported an infant patient with LQTs carrying a phenylalanine (F) deletion at amino acid 1486 of the Nav1.5 channel. This study reported that the patient showed severe cardiac arrhythmia reflected as LQTs and subsequent ventricular tachycardia, which was refractory to antiarrhythmic drug lidocaine treatment. Therefore, it was hypothesized that the deletion of F1486 on Nav1.5 would substantially alter electrophysiological properties of the channel and reduce the potency of lidocaine on sodium channel. Using HEK293 cells and neonatal rat cardiomyocytes, the F1486del channel was functionally characterized by whole-cell patch clamp techniques. Studies revealed that the deletion of F1486 causes a combination of changes including a loss-of-function alteration reflected as a substantial reduction of peak current density and a number of gain-of-function alterations including reduced channel inactivation, substantial augmentation of late sodium current, and an increase in ramp current. In addition, lidocaine sensitivity was dramatically reduced. By contrast, the voltage for half maximal activation (V1/2) and the time constant for channel deactivation for the F1486del channel were identical to the wild type channels. Using neonatal rat cardiomyocytes, we were able to study the functional consequence of F1484del on action potential duration (APD). Cardiomyocytes expressing F1486del channel have substantial APD prolongation and prominent spontaneous early afterdepolarizations, which likely underlie the subsequent LQTs in the patient. Taken together, despite the reduction in peak current density, the substantial gain-of-function changes are sufficient to cause the APD prolongation, which is a prominent characteristic of LQTs. These findings provide knowledge for understanding the relationships between sodium channel structure, pharmacology and the physiological consequence of sodium channel mutations that underlie LQT3

A new target for differentiation therapy in AML

Despite major advances in understanding the genetics and epigenetics of acute myelogenous leukemia, there is still a great need to develop more specific and effective therapies. High throughput approaches involving either genetic approaches or small molecule inhibitor screens are beginning to identify promising new therapeutic targets

Fruit Tree Pollination Technology and Industrialization in China

This work investigates the bee pollination of fruit trees, especially apples and pears in the field. We first introduce research carried out into bee pollination of crops in China, and then our own pollination experiments with managed bees such as Apis mellifera in the field. We monitor the efficiency of bee pollination of fruit trees by regulating hive bees and tree arrangement. In addition, we develop some methods to attract bees to visit fruit trees. Our research shows that the number of beehives and the arrangement of trees greatly influence bee pollination. The results provide a comprehensive tutorial on the best practices of bee pollination of fruit trees

Improved English to Russian Translation by Neural Suffix Prediction

Neural machine translation (NMT) suffers a performance deficiency when a limited vocabulary fails to cover the source or target side adequately, which happens frequently when dealing with morphologically rich languages. To address this problem, previous work focused on adjusting translation granularity or expanding the vocabulary size. However, morphological information is relatively under-considered in NMT architectures, which may further improve translation quality. We propose a novel method, which can not only reduce data sparsity but also model morphology through a simple but effective mechanism. By predicting the stem and suffix separately during decoding, our system achieves an improvement of up to 1.98 BLEU compared with previous work on English to Russian translation. Our method is orthogonal to different NMT architectures and stably gains improvements on various domains.Comment: 8 pages, 3 figures, 5 table

Detection and recognition of illegally parked vehicles based on an adaptive gaussian mixture model and a seed fill algorithm.

In this paper, we present an algorithm for the detection of illegally parked vehicles based on a combination of some image processing algorithms. A digital camera is fixed in the illegal parking region to capture the video frames. An adaptive Gaussian mixture model (GMM) is used for background subtraction in a complex environment to identify the regions of moving objects in our test video. Stationary objects are detected by using the pixel-level features in time sequences. A stationary vehicle is detected by using the local features of the object, and thus, information about illegally parked vehicles is successfully obtained. An automatic alarm system can be utilized according to the different regulations of different illegal parking regions. The results of this study obtained using a test video sequence of a real-time traffic scene show that the proposed method is effective