Incentive mechanism for allocating total permitted pollution discharge capacity and evaluating the validity of free allocation

In this paper, the validity evaluation method of free allocation is studied under the background of allocating the total permitted pollution discharge capacity (TPPDC). First, the free allocation method’s localization and players’ strategic behaviors are analyzed. Second, an incentive mechanism for allocating TPPDC is proposed based on the uniform price auction of divisible goods, and an evaluation model to evaluate the validity for the free allocation of TPPDC is established, and the feasibility and reasonableness of this evaluation model are proved. Third, the evaluation criterion and the evaluation process are given. Finally, this evaluation model is applied to the environmental planning of Han River basin, and the validity evaluation result of free allocation is obtained by analyzing the statistical data of chemical oxygen demand (COD) in 14 counties and cities of Hubei Province, China. The results of our study will provide the government environmental management departments with theoretical basis and scientific methods to effectively implement the pollutant gross control system and design the related environmental policies.     

A robust motion estimation with center-biased diamond search and its parallel architecture for motion-compensated de-interlace

For motion compensated de-interlace, the accuracy and reliability of the motion vectors have a significant impact on the performance of the motion compensated interpolation. In order to improve the robustness of motion vector, a novel motion estimation algorithm with center-biased diamond search and its parallel VLSI architecture are proposed in this paper. Experiments show that it works better than conventional motion estimation algorithms in terms of motion compensation error and robustness, and its architecture overcomes the irregular data flow and achieves high efficiency. It also efficiently reuses data and reduces the control overhead. So, it is highly suitable for HDTV applications.     

Characterization and humidity sensing properties of Bi0.5Na0.5TiO3-Bi0.5K0.5TiO3 powder synthesized by metal-organic decomposition

Bi_0.5Na_0.5TiO₃-Bi_0.5K_0.5TiO₃ (BNT-BKT) powder is synthesized by a metal-organic decomposition method and characterized by field-emission scanning electron microscopy (FE-SEM), transmission electron microscopy (TEM), and X-ray diffraction (XRD). A humidity sensor, which is consisted of five pairs of Ag-Pd interdigitated electrodes and an Al₂O₃ ceramic substrate, is fabricated by spin-coating the BNT-BKT powder on the substrate. Good humidity sensing properties such as high response value, short response and recovery times, and small hysteresis are observed in the sensing measurement. The impedance changes more than four orders of magnitude within the whole humidity range from 11% to 95% relative humidity (RH) at 100 Hz. The response time and recovery time are about 20 and 60 s, respectively. The maximum hysteresis is around 4% RH. The results indicate that BNT-BKT powder is of potential applications for fabricating high performance humidity sensors.     

Plasmonic enhanced fluorescence spectroscopy using side-polished microstructured optical fiber

We report excitation of surface plasmon in a gold-coated side-polished D-shape microstructure optical fiber (MOF). As the leaky evanescent field from the fiber core becomes highly localized by the plasmon wave, its intensity also gets amplified significantly. Here we demonstrate an efficient use of this intensified field as excitation in fluorescence spectroscopy. The so-called plasmonic enhanced fluorescence emission from Rhodamine B has been investigated experimentally. First, plasmonic effect alone was found to provide an immediate fluorescence enhancement factor of two. Second, experimental results show a good agreement with theoretical modeling. Strong evanescent field generation and surface enhancement with simple metallic coating makes this fiber based device a good candidate for compact fluorescence spectroscopy.     

Video personalization in heterogeneous and resource-constrained environments

Access to multimedia data and multimedia services is becoming increasingly common in networked mobile environments. In such environments, both the mobile client devices and multimedia servers are typically resource constrained. Moreover, the mobile client population is often heterogeneous in terms of the clients’ preferences with regard to multimedia content, the clients’ quality of service requirements and system-level resource constraints. In order to provide a resource-constrained mobile client with its desired video content, it is often necessary to personalize the requested multimedia content in a manner that satisfies simultaneously the various client-specified content preferences and the system-level resource constraints. Also, in order to simultaneously reduce the client-experienced latency, provide optimal quality of service to the clients and ensure efficient utilization of server and network resources, it is necessary to perform client request aggregation on the server end. To this end, a video personalization strategy is proposed to provide mobile, resource-constrained clients with personalized video content that is most relevant to the clients’ requests while satisfying simultaneously multiple client-side system-level resource constraints. A client request aggregation strategy is also proposed to cluster client requests with similar video content preferences and similar client-side resource constraints such that the number of requests the server needs to process and service, and the client-experienced latency are both reduced simultaneously. The primary contributions of the paper are: (1) the formulation and implementation of a Multiple-choice Multi-dimensional Knapsack Problem (MMKP)-based video personalization strategy; and (2) the design and implementation of a client request aggregation strategy based on a multi-stage clustering algorithm. Experimental results comparing the proposed MMKP-based video personalization strategy to existing 0/1 Knapsack Problem (0/1KP)-based and the Fractional Knapsack Problem (FKP)-based video personalization strategies are presented. It is observed that: (1) the proposed MMKP-based personalization strategy includes more relevant video content in response to the client’s request compared to the existing 0/1KP-based and FKP-based personalization strategies; and (2) in contrast to the 0/1KP-based and FKP-based personalization strategies which can satisfy only a single client-side resource constraint at a time, the proposed MMKP-based personalization strategy is capable of satisfying multiple client-side resource constraints simultaneously. Experimental results comparing the client-experienced latency with and without the proposed server-side client request aggregation strategy are also presented. It is shown that the proposed client request aggregation strategy reduces the mean client-experienced latency without significant reduction in the average relevance of the delivered video content and without significant deviation in the client-side resources actually consumed by the delivered video content from the client-specified resource constraints.     

Accelerating the kernel-method-based feature extraction procedure from the viewpoint of numerical approximation

The kernel method suffers from the following problem: the computational efficiency of the feature extraction procedure is inversely proportional to the size of the training sample set. In this paper, from a novel viewpoint, we propose a very simple and mathematically tractable method to produce the computationally efficient kernel-method-based feature extraction procedure. We first address the issue that how to make the feature extraction result of the reformulated kernel method well approximate that of the naïve kernel method. We identify these training samples that statistically contribute much to the feature extraction results and exploit them to reformulate the kernel method to produce the computationally efficient kernel-method-based feature extraction procedure. Indeed, the proposed method has the following basic idea: when one training sample has little effect on the feature extraction result and statistically has the high correlation with regard to all the training samples, the feature extraction term associated with this training sample can be removed from the feature extraction procedure. The proposed method has the following advantages: First, it proposes, for the first time, to improve the kernel method through formal and reasonable evaluation on the feature extraction term. Second, the proposed method improves the kernel method at a low extra cost and thus has a much more computationally efficient training phase than most of the previous improvements to the kernel method. The experimental comparison shows that the proposed method performs well in classification problems. This paper also intuitively shows the geometrical relation between the identified training samples and other training samples.     

TPEMatcher: A tool for searching in parsed text corpora

Recently, due to the widespread on-line availability of syntactically annotated text corpora, some automated tools for searching in such text corpora have gained great attention. Generally, those conventional corpus search tools use a decomposition-matching-merging method based on relational predicates for matching a tree pattern query to the desired parts of text corpora. Thus, their query formulation and expressivity are often complicated due to poorly understood query formalisms, and their searching tasks may require a big computational overhead due to a large number of repeated trials of matching tree patterns. To overcome these difficulties, we present TPEMatcher, a tool for searching in parsed text corpora. TPEMatcher provides not only an efficient way of query formulation and searching but also a good query expressivity based on concise syntax and semantics of tree pattern query. We also demonstrate that TPEMatcher can be effectively used for a text mining in practice with its useful interface providing in-depth details of search results.     

一种求解Ramsey数的DNA计算机算法

Ramsey理论是组合数学中一个庞大而又丰富的领域,在集合论、逻辑学、分析以及代数学上具有极重要的应用.Ramsey数的求解是非常困难的,迄今为止只求出9个Ramsey数的准确值.探讨了DNA生物分子超级计算在求解这一困难数学问题的可能性.将Adleman-Lipton模型生物操作与粘贴模型解空间相结合的DNA计算模型...