MACD与K线图技术在证券投机中的实证研究

利用MACD趋势指标与K线形态图进行相互验证技术,改进一般的基于MACD的证券买卖准则。实证结果表明,基于改进后的MACD买卖准则进行证券投机,几乎能使投机者捕捉到每一波段行情,从而获取较高收益。     

Mathematical model of deoxidization with post stirring in a combined blowing converter

Dissolved oxygen in the steel at the terminal of the converter smelting process is the main cause for the formation of oxide inclusions, and the high terminal oxygen content worsens the steel cleanness. However, post stirring in a combined blowing converter can promote the carbon-oxygen reaction in the liquid steel and reduce the dissolved oxygen content at the terminal of the converter smelting process. Thus, the mathematical model of deoxidization in the post stirring process was obtained, and the rationa...     

Degradability and biocompatibility of bioglass/poly(amino acid) composites with different surface bioactivity as bone repair materials

Bioglass (BG) possesses excellent bioactivity and has been widely used in the manufacture of biomaterials. In this study, a composite with different surface bioactivity was fabricated via in situ melting polymerization by incorporating BG and poly(amino acid) (PAA) at a suitable ratio. The structure of the composite was characterized by Fourier transform infrared spectroscopy and XRD. The compressive strength of the BG/PAA composites was 139 MPa (BG:PAA = 30:70). The BG/PAA composites were degradable, and higher BG in composite showed higher weight loss after 4 weeks of incubation in simulated body fluid. In addition, the BG/PAA composite maintained adequate residual compressive strength during the degradation period. The SEM results showed the differences in surface bioactivities of the composites directly, and 30BG/PAA composite showed thicker apatite layer and higher Ca/p than 15BG/PAA. in vitro MG-63 cell culture experiments showed that the composite was noncytotoxic and thus allows cells to adhere, proliferate, and differentiate. This indicates that the composite has good biocompatibility. The implantations in the bone defects of rabbits for 4 and 12 weeks were studied. The composites had good biocompatibility and were capable of guiding new bone formation without causing any inflammation. The composite may be successfully used in the development of bone implants.     

Extending 3D Lucas–Kanade tracking with adaptive templates for head pose estimation

The Lucas–Kanade tracker (LKT) is a commonly used method to track target objects over 2D images. The key principle behind the object tracking of an LKT is to warp the object appearance so as to minimize the difference between the warped object’s appearance and a pre-stored template. Accordingly, the 2D pose of the tracked object in terms of translation, rotation, and scaling can be recovered from the warping. To extend the LKT for 3D pose estimation, a model-based 3D LKT assumes a 3D geometric model for the target object in the 3D space and tries to infer the 3D object motion by minimizing the difference between the projected 2D image of the 3D object and the pre-stored 2D image template. In this paper, we propose an extended model-based 3D LKT for estimating 3D head poses by tracking human heads on video sequences. In contrast to the original model-based 3D LKT, which uses a template with each pixel represented by a single intensity value, the proposed model-based 3D LKT exploits an adaptive template with each template pixel modeled by a continuously updated Gaussian distribution during head tracking. This probabilistic template modeling improves the tracker’s ability to handle temporal fluctuation of pixels caused by continuous environmental changes such as varying illumination and dynamic backgrounds. Due to the new probabilistic template modeling, we reformulate the head pose estimation as a maximum likelihood estimation problem, rather than the original difference minimization procedure. Based on the new formulation, an algorithm to estimate the best head pose is derived. The experimental results show that the proposed extended model-based 3D LKT achieves higher accuracy and reliability than the conventional one does. Particularly, the proposed LKT is very effective in handling varying illumination, which cannot be well handled in the original LKT.     

Automatic detection of breast cancers in mammograms using structured support vector machines

Breast cancer is one of the most common cancers diagnosed in women. Large margin classifiers like the support vector machine (SVM) have been reported effective in computer-assisted diagnosis systems for breast cancers. However, since the separating hyperplane determination exclusively relies on support vectors, the SVM is essentially a local classifier and its performance can be further improved. In this work, we introduce a structured SVM model to determine if each mammographic region is normal or cancerous by considering the cluster structures in the training set. The optimization problem in this new model can be solved efficiently by being formulated as one second order cone programming problem. Experimental evaluation is performed on the Digital Database for Screening Mammography (DDSM) dataset. Various types of features, including curvilinear features, texture features, Gabor features, and multi-resolution features, are extracted from the sample images. We then select the salient features using the recursive feature elimination algorithm. The structured SVM achieves better detection performance compared with a well-tested SVM classifier in terms of the area under the ROC curve.     

Batch Nearest Neighbor Search for Video Retrieval

To retrieve similar videos to a query clip from a large database, each video is often represented by a sequence of high- dimensional feature vectors. Typically, given a query video containing m feature vectors, an independent nearest neighbor (NN) search for each feature vector is often first performed. After completing all the NN searches, an overall similarity is then computed, i.e., a single content-based video retrieval usually involves m individual NN searches. Since normally nearby feature vectors in a video are similar, a large number of expensive random disk accesses are expected to repeatedly occur, which crucially affects the overall query performance. Batch nearest neighbor (BNN) search is stated as a batch operation that performs a number of individual NN searches. This paper presents a novel approach towards efficient high-dimensional BNN search called dynamic query ordering (DQO) for advanced optimizations of both I/O and CPU costs. Observing the overlapped candidates (or search space) of a pervious query may help to further reduce the candidate sets of subsequent queries, DQO aims at progressively finding a query order such that the common candidates among queries are fully utilized to maximally reduce the total number of candidates. Modelling the candidate set relationship of queries by a candidate overlapping graph (COG), DQO iteratively selects the next query to be executed based on its estimated pruning power to the rest of queries with the dynamically updated COG. Extensive experiments are conducted on real video datasets and show the significance of our BNN query processing strategy.     

Three-dimensional reconstruction on PC-Windows platform for evaluation of living donor nephrectomy

Evaluation of renal vasculature was necessary for preoperative donor assessment in living donor kidney transplantation, and the ability to view the vascular imaging in three-dimensional (3D) space should be helpful undoubtedly. Considering the widespread use of personal computer (PC) systems, we aimed to find a handy way to display the anatomy of the renal arterial and venous systems of potential donors on PC-Windows platform. Ten living-related donors were included in this study. Serial computed tomography (CT) images were loaded into Amira 3.1 running on a PC with Windows XP. Following image crop, segmentation and 3D reconstruction, we got the 3D images and the video clips. According to the displays which were confirmed by latter intraoperative findings, eight donors had single renal vessels, one had a left accessory renal artery and one had a right accessory renal artery. This project offered a new approach to evaluate the renal vessel anatomy in living donor kidney transplantation, and it was favorable for accuracy and popularizing.     

珠江流域未来30 年洪水对气候变化的响应

从第5次耦合模式比较计划（CMIP5）的47个全球气候模式中,根据模式对珠江流域降水模拟的相似性,筛选出5个相对独立的模式,耦合大尺度水文模型（VIC模型）模拟了21个主要干支流控制站日流量过程。以洪峰流量和洪水总量为指标,评估了IPCC RCP4.5情景下未来30年洪水对气候变化的响应。结果表明：2011—2040年洪峰流量和洪水总量在西江和粤西桂南沿海诸河可能呈增加趋势;而在北江（洪水总量）和东江多半可能呈减少趋势。与1970—1999年相比,郁江、桂江、东江及粤西桂南沿海诸河特大洪水可能呈增加趋势,红水河和北江多半可能呈增加趋势;柳江则可能或多半可能呈减少趋势。西江洪水与红水河、郁江关系将更为密切,北江与西江及红水河与柳江洪水遭遇的情况多半可能增加。