996 resultados para predictive coding


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Connectivity mapping is the process of establishing connections between different biological states using gene-expression profiles or signatures. There are a number of applications but in toxicology the most pertinent is for understanding mechanisms of toxicity. In its essence the process involves comparing a query gene signature generated as a result of exposure of a biological system to a chemical to those in a database that have been previously derived. In the ideal situation the query gene-expression signature is characteristic of the event and will be matched to similar events in the database. Key criteria are therefore the means of choosing the signature to be matched and the means by which the match is made. In this article we explore these concepts with examples applicable to toxicology.

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In this letter, we propose a simple space-time code to simultaneously achieve both the space and time diversities over time dispersive channels by using two-dimensional lattice constellations and Alamouti codes. The proposed scheme still reserves full space diversity and double-real-symbols joint maximum likelihood decoding which has the similar computation complexity as the Alamouti code.

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A new domain-specific, reconfigurable system-on-a-chip (SoC) architecture is proposed for video motion estimation. This has been designed to cover most of the common block-based video coding standards, including MPEG-2, MPEG-4, H.264, WMV-9 and AVS. The architecture exhibits simple control, high throughput and relatively low hardware cost when compared with existing circuits. It can also easily handle flexible search ranges without any increase in silicon area and can be configured prior to the start of the motion estimation process for a specific standard. The computational rates achieved make the circuit suitable for high-end video processing applications, such as HDTV. Silicon design studies indicate that circuits based on this approach incur only a relatively small penalty in terms of power dissipation and silicon area when compared with implementations for specific standards. Indeed, the cost/performance achieved exceeds that of existing but specific solutions and greatly exceeds that of general purpose field programmable gate array (FPGA) designs.

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This paper presents a predictive current control strategy for doubly-fed induction generators (DFIG). The method predicts the DFIG’s rotor current variations in the synchronous reference frame fixed to the stator flux within a fixed sampling period. This is then used to directly calculate the required rotor voltage to eliminate the current errors at the end of the following sampling period. Space vector modulation is used to generate the required switching pulses within the fixed sampling period. The impact of sampling delay on the accuracy of the sampled rotor current is analyzed and detailed compensation methods are proposed to improve the current control accuracy and system stability. Experimental results for a 1.5 kW DFIG system illustrate the effectiveness and robustness of the proposed control strategy during rotor current steps and rotating speed variation. Tests during negative sequence current injection further demonstrate the excellent dynamic performance of the proposed PCC method.

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Based on an algorithm for pattern matching in character strings, we implement a pattern matching machine that searches for occurrences of patterns in multidimensional time series. Before the search process takes place, time series are encoded in user-designed alphabets. The patterns, on the other hand, are formulated as regular expressions that are composed of letters from these alphabets and operators. Furthermore, we develop a genetic algorithm to breed patterns that maximize a user-defined fitness function. In an application to financial data, we show that patterns bred to predict high exchange rates volatility in training samples retain statistically significant predictive power in validation samples.

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Research has focused on in vitro expansion of bone marrow stromal cells with the aim of developing cell-based therapies or tissue-engineered constructs. There is debate over whether there is a reduction in stem cells/osteoprogenitors in the bone marrow compartment with increasing age. The aim of this study was to investigate patient factors that affect the progenitor pool in bone marrow samples. Six milliliters of marrow aspirate was obtained from the femoral canal of 38 primary hip replacement patients (aged 28-91). Outcome measures were total nucleated cell count, colony-forming efficiency, alkaline phosphatase expression, and expression of stem cell markers. There was a nonsignificant negative correlation between age and both colony-forming efficiency and stem cell marker expression. However, body mass index showed a positive, significant correlation with colony area and number in men-accounting for up to 75% of the variation. In conclusion, body mass index, not age, was highly predictive of the number of progenitors found in bone marrow, and this relationship was sex specific. These results may inform the clinician's treatment choice when considering bone marrow-based therapies. Further, it highlights the need to widen research into patient factors that affect the adult stem cell population beyond age and reinforces the need to consider sexes separately.