View-Aware Image Object Compositing and Synthesis from Multiple Sources

Image compositing is widely used to combine visual elements from separate source images into a single image. Although recent image compositing techniques are capable of achieving smooth blending of the visual elements from different sources, most of them implicitly assume the source images are taken in the same viewpoint. In this paper, we present an approach to compositing novel image objects from multiple source images which have different viewpoints. Our key idea is to construct 3D proxies for meaningful components of the source image objects, and use these 3D component proxies to warp and seamlessly merge components together in the same viewpoint. To realize this idea, we introduce a coordinate-frame based single-view camera calibration algorithm to handle general types of image objects, a structure-aware cuboid optimization algorithm to get the cuboid proxies for image object components with correct structure relationship, and finally a 3D-proxy transformation guided image warping algorithm to stitch object components. We further describe a novel application based on this compositing approach to automatically synthesize a large number of image objects from a set of exemplars. Experimental results show that our compositing approach can be applied to a variety of image objects, such as chairs, cups, lamps, and robots, and the synthesis application can create novel image objects with significant shape and style variations from a small set of exemplars.     

Transferring Case Knowledge To Adaptation Knowledge: An Approach for Case-Base Maintenance

In this article we propose a case-base maintenance methodology based on the idea of transferring knowledge between knowledge containers in a case-based reasoning (CBR) system. A machine-learning technique, fuzzy decision-tree induction, is used to transform the case knowledge to adaptation knowledge. By learning the more sophisticated fuzzy adaptation knowledge, many of the redundant cases can be removed. This approach is particularly useful when the case base consists of a large number of redundant cases and the retrieval efficiency becomes a real concern of the user. The method of maintaining a case base from scratch, as proposed in this article, consists of four steps. First, an approach to learning feature weights automatically is used to evaluate the importance of different features in a given case base. Second, clustering of cases is carried out to identify different concepts in the case base using the acquired feature-weights knowledge. Third, adaptation rules are mined for each concept using fuzzy decision trees. Fourth, a selection strategy based on the concepts of case coverage and reachability is used to select representative cases. In order to demonstrate the effectiveness of this approach as well as to examine the relationship between compactness and performance of a CBR system, experimental testing is carried out using the Traveling and the Rice Taste data sets. The results show that the testing case bases can be reduced by 36 and 39 percent, respectively, if we complement the remaining cases by the adaptation rules discovered using our approach. The overall accuracies of the two smaller case bases are 94 and 90 percent, respectively, of the originals.     

Computation of madalines' sensitivity to input and weight perturbations

The sensitivity of a neural network's output to its input and weight perturbations is an important measure for evaluating the network's performance. In this letter, we propose an approach to quantify the sensitivity of Madalines. The sensitivity is defined as the probability of output deviation due to input and weight perturbations with respect to overall input patterns. Based on the structural characteristics of Madalines, a bottom-up strategy is followed, along which the sensitivity of single neurons, that is, Adalines, is considered first and then the sensitivity of the entire Madaline network. By means of probability theory, an analytical formula is derived for the calculation of Adalines' sensitivity, and an algorithm is designed for the computation of Madalines' sensitivity. Computer simulations are run to verify the effectiveness of the formula and algorithm. The simulation results are in good agreement with the theoretical results.     

聚四氟乙烯薄膜复合蒸呢包布及其应用性能

为了提高羊毛精纺面料的表面光泽及其耐久性,采用聚四氟乙烯（PTFE）微孔薄膜与传统包布复合研制新型复合蒸呢包布,测试采用新型复合包布罐蒸后毛织物的各项性能。结果表明;PTFE微孔薄膜的结构对复合包布的透湿量影响较小;采用复合包布经一次罐蒸的毛织物,其表面平整性、尺寸稳定性、力学性能、表面光泽都优于采用传统包布一次罐蒸的毛织物;采用复合包布经两次罐蒸的毛织物的表面平整性、尺寸稳定性、力学性能、表面光泽基本达到传统包布经罐蒸→电压→罐蒸的织物的效果。     

A separation theorem for single-source network coding

In this paper, we consider a point-to-point communication network of discrete memoryless channels. In the network, there are a source node and possibly more than one sink node. Information is generated at the source node and is multicast to each sink node. We allow a node to encode its received information before loading it onto an outgoing channel, where the channels are independent of each other. We also allow the nodes to pass along messages asynchronously. In this paper, we characterize the admissibility of single-source multi-sink communication networks. Our result can be regarded as a network generalization of Shannon's result that feedback does not increase the capacity of a discrete memoryless channels (DMCs), and it implies a separation theorem for network coding and channel coding in such a communication network.     

Electrokinetic Remediation of Cadmium-Contaminated Clay

Electrokinetic extraction has been demonstrated to be very effective in removing heavy metals from Georgia kaolinite. The relatively high removal efficiency depends on the extremely acidic soil environment generated by the electrokinetic process. However, the efficiency observed in Georgia kaolinite cannot be achieved in soils of high acid/base buffer capacity without enhancement. In this study, the effect of ethylenediaminetetraacetic acid (EDTA) to enhance electrokinetic extraction of cadmium from Milwhite kaolinite was examined. The influence of electro-osmotic flow direction on the migration of cadmium, EDTA, and their complexes were also investigated. It was observed that injection of EDTA from the cathode reservoir by a reverse electro-osmotic flow could mobilize the cadmium in the specimen effectively. A less significant mobilization of cadmium was observed when the electro-osmotic flow was directed toward the cathode. However, accumulation of cadmium near the anode was observed regardless of the electro-osmotic flow direction.     

Optimal power control system of a research nuclear reactor

The power control system is a key control system for a nuclear reactor, which directly concerns the safe operation of a nuclear reactor. Much attention is paid to the power control system performance of nuclear reactor in engineering. The designers put a high value upon design of an optimal power control system. In this paper, a design method is applied to the design of power control system. According to the optimal control theory, an objective function, quadratic performance index with weight factors is proposed. Then, the objective function is transformed into frequency domain form by use of Paserval's theorem. In frequency domain, an optimal transfer function can be obtained at the lowest value of objective function. The system with optimal transfer function has an optimal performance. The transfer function of the power control system is derived from a typical research nuclear reactor. Using the state feedback theory, the transfer function is synthesized to the optimal transfer function. The simulative results with the optimal controller and with a conventional controller show that the performance of the optimal power control system is largely improved on dynamic characters. The method applied here not only can be used for research nuclear reactor but also can be easily extended to pressurized water reactor power plant and other fields.     

Designing Efficient and Robust Caching Algorithms for Streaming-on-Demand Services on the Internet

Content Delivery Networks (CDN) have been used on the Internet to cache media content so as to reduce the load on the original media server, network congestion, and latency. Due to the large size of media content compared to normal web objects, current caching algorithms used in the Internet are no longer suitable. This paper presents a high-performance prefetch system that accommodates user time-varying behavior. A hybrid caching technique, which combines prefetch and replacement algorithms, is also introduced. The robustness of the cache system against imperfect user request information is evaluated using three request noise models. Two prefetch performance indices are also presented to help content administrators in deciding when to update the user request profile for caching algorithms.