Oil supply between OPEC and non-OPEC based on game theory

The competing strategies between OPEC (Organization of the Petroleum Exporting Countries) and non-OPEC producers make the oil supply market a complex system, and thus, it is very difficult to model and to make predictions. In this paper, we combine the macro-model based on game theory and micro-model to propose a new approach for forecasting oil supply. We take into account the microscopic behaviour in the clearing market and also use the game relationships to adjust oil supplies in our approach. For the supply model, we analyse and consider the different behaviour of non-OPEC and OPEC producers. According to our analysis, limiting the oil supply, and thus maintaining oil price, is the best strategy for OPEC in the low-price scenario, while the rising supply is the best strategy in the high-price scenario. No matter what the oil price is, the dominant strategy for non-OPEC producers is to increase their oil supply. In the high-price scenario, OPEC will try to deplete non-OPEC’s share in the oil supply market, which is to OPEC’s advantage.     

Making sky lanterns from polygonal meshes

Releasing sky lanterns is a popular way of celebrating festivals and ceremonies in the Asian countries. This paper presents a computer-aided approach to help novice users to design flyable sky lantern with desired shape. Given a closed up-right 3D model with a user-specified cutting on the bottom, our system optimizes the shape by regularizing the boundary, smoothing the geometry and improving the volume-to-area ratio to make it feasible for flying. The optimized shape is then approximated by a set of developable patches. Next, through a physical analysis step that tests the flying condition and determines the optimal size, the approximated shape is flattened into 2D patches, which can be printed out and glued together to form the airbag. Finally, the user can attach the airbag to a bamboo frame and assemble the fuel cell. We successfully apply our prototype system to design and construct real sky lanterns.     

射流流化床内流体力学行为的模拟研究

以流化床应用为代表的气固流动系统是许多化工过程中的重要组成部分 ,CFD( computational fluid dynamics)方法能够为其优化设计和放大提供所需要的信息 .本文采用双欧拉模型 ,与 Gidaspow等的实验结果进行了对比 ,模拟了二维射流流化床内气泡的形成规律 ,得到了带锥型分布器的流化床内瞬时空隙率和气固相速度分布等流体力学参数 .对锥型分布器流化床的实验结果表明 ,模拟得到的气泡的形状与实验现象相接近 .     

加压下二氧化碳在二甲基甲酰胺中的溶解度研究

本文报道了二氧化碳在二甲基甲酰胺中的溶解度,实验温度分别为15、20、25、30、35、40、45℃,实验压力为207.21—1684.02kPa.并且提出一个考虑了过量熵的、用溶度参数表示的活度系数方程.     

涤纶短纤维生产现状及发展趋势

对目前国内外涤纶短纤维生产的企业规模和工艺技术现状进行了分析比较，并论述了涤纶短纤维生产的经济规模和今后的发展趋势。     

Dynamic deviation reduction‐based concurrent dual‐band digital predistortion

This article introduces the concurrent dual‐band digital predistortion (DPD) architecture with only one upconvertion unit, which is suitable for the linearization of wideband power amplifiers (PAs) excited by concurrent dual‐band signals. By extending the conventional dynamic deviation reduction (DDR) model to the concurrent dual‐band mode, we propose two DDR‐based concurrent dual‐band models, the dual‐band DDR (DB‐DDR) model and the simplified dual‐band DDR (SDB‐DDR) model. The performance of these two models is experimentally assessed with two types of wideband PAs (a GaN Class F PA and a GaN Doherty PA) driven by the concurrent dual‐band signal, and compared with the prior two‐dimensional digital predistortion (2D‐DPD) model and the two‐dimensional modified memory polynomial (2D‐MMP) model. The results prove the good DPD performance and low computational complexity of the proposed models. © 2013 Wiley Periodicals, Inc. Int J RF and Microwave CAE 24:401–411, 2014.     

To accelerate shot boundary detection by reducing detection region and scope

Video Shot Boundary Detection (SBD) is the fundamental process towards video summarization and retrieval. A fast and efficient SBD algorithm is necessary for real-time video processing applications. Extensive work has focused on accurate shot boundary detection at the expense of demanding computational costs. In this paper, we propose a fast SBD approach that reduces the computation pixel-wise and frame-wise while still giving satisfactory accuracy. The proposed approach substantially speeds up the computation through reducing both detection region and scope. Color histogram and mutual information are used together to measure the difference between frames. Corner distribution of frames is utilized to exclude most of false boundaries. We conduct extensive experiments to evaluate the proposed approach, and the results show that our approach can not only speed up SBD, but also detect shot boundaries with high accuracy in both Cut (CUT) and Gradual Transition (GT) boundaries.     

Optimal entropy-constrained non-uniform scalar quantizer design for low bit-rate pixel domain DVC

In this paper, an optimal entropy-constrained non-uniform scalar quantizer is proposed for the pixel domain DVC. The uniform quantizer is efficient for the hybrid video coding since the residual signals conforming to a single-variance Laplacian distribution. However, the uniform quantizer is not optimal for pixel domain distributed video coding (DVC). This is because the uniform quantizer is not adaptive to the joint distribution of the source and the SI, especially for low level quantization. The signal distribution of pixel domain DVC conforms to the mixture model with multi-variance. The optimal non-uniform quantizer is designed according to the joint distribution, the error between the source and the SI can be decreased. As a result, the bit rate can be saved and the video quality won’t sacrifice too much. Accordingly, a better R-D trade-off can be achieved. First, the quantization level is fixed and the optimal RD trade-off is achieved by using a Lagrangian function J(Q). The rate and distortion components is designed based on P(Y|Q). The conditional probability density function of SI Y depend on quantization partitions Q, P(Y|Q), is approximated by a Guassian mixture model at encocder. Since the SI can not be accessed at encoder, an estimation of P(Y|Q) based on the distribution of the source is proposed. Next, J(Q) is optimized by an iterative Lloyd-Max algorithm with a novel quantization partition updating algorithm. To guarantee the convergence of J(Q), the monotonicity of the interval in which the endpoints of the quantizer lie must be satisfied. Then, a quantizer partition updating algorithm which considers the extreme points of the histogram of the source is proposed. Consequently, the entropy-constrained optimal non-uniform quantization partitions are derived and a better RD trade-off is achieved by applying them. Experiment results show that the proposed scheme can improve the performance by 0.5 dB averagely compared to the uniform scalar quantization.     

A comparative study of iterative and non-iterative feature selection techniques for software defect prediction

Two important problems which can affect the performance of classification models are high-dimensionality (an overabundance of independent features in the dataset) and imbalanced data (a skewed class distribution which creates at least one class with many fewer instances than other classes). To resolve these problems concurrently, we propose an iterative feature selection approach, which repeated applies data sampling (in order to address class imbalance) followed by feature selection (in order to address high-dimensionality), and finally we perform an aggregation step which combines the ranked feature lists from the separate iterations of sampling. This approach is designed to find a ranked feature list which is particularly effective on the more balanced dataset resulting from sampling while minimizing the risk of losing data through the sampling step and missing important features. To demonstrate this technique, we employ 18 different feature selection algorithms and Random Undersampling with two post-sampling class distributions. We also investigate the use of sampling and feature selection without the iterative step (e.g., using the ranked list from a single iteration, rather than combining the lists from multiple iterations), and compare these results from the version which uses iteration. Our study is carried out using three groups of datasets with different levels of class balance, all of which were collected from a real-world software system. All of our experiments use four different learners and one feature subset size. We find that our proposed iterative feature selection approach outperforms the non-iterative approach.     

A keyword retrieval system for historical Mongolian document images

In this paper, we propose a keyword retrieval system for locating words in historical Mongolian document images. Based on the word spotting technology, a collection of historical Mongolian document images is converted into a collection of word images by word segmentation, and a number of profile-based features are extracted to represent word images. For each word image, a fixed-length feature vector is formulated by obtaining the appropriate number of the complex coefficients of discrete Fourier transform on each profile feature. The system supports online image-to-image matching by calculating similarities between a query word image and each word image in the collection, and consequently, a ranked result is returned in descending order of the similarities. Therein, the query word image can be generated by synthesizing a sequence of glyphs when being retrieved. By experimental evaluations, the performance of the system is confirmed.