In the paper we propose a general, abstract framework for Automatic Secret Generation and Sharing (ASGS) that should be independent of underlying Secret Sharing Scheme (SSS). ASGS allows to prevent the Dealer from knowing the secret. The Basic Property Conjecture (BPC) forms the base of the framework. Due to the level of abstraction, results are portable into the realm of quantum computing.

The objective of conformance testing is to determine whether an implementation under test (IUT) conforms to its specification. In distributed test architecture where there are multiple remote testers, the objective can be complicated by the fact that testers may encounter controllability and observability problems during the application of a test sequence. A certain amount of work has been done in the area of generating test sequence that is free from these problems. However, few researchers investigate them from the aspect of test execution. This work studies the test execution phase when test sequences are applied to the implementation and it is pointed out that controllability and observability problems can be resolved if and only if the test system implements some timing constraints. When determining these constraints, the dynamic time information during test is taken into account, which reduces the test execution time and improves test efficiency further.

The problem of continuously monitoring multiple K-nearest neighbor (K-NN) queries with dynamic object and query dataset is valuable for many location-based applications. A practical method is to partition the data space into grid cells, with both object and query table being indexed by this grid structure, while solving the problem by periodically joining cells of objects with queries having their influence regions intersecting the cells. In the worst case, all cells of objects will be accessed once. Object and query cache strategies are proposed to further reduce the I/O cost. With object cache strategy, queries remaining static in current processing cycle seldom need I/O cost, they can be returned quickly. The main I/O cost comes from moving queries, the query cache strategy is used to restrict their search-regions, which uses current results of queries in the main memory buffer. The queries can share not only the accessing of object pages, but also their influence regions. Theoretical analysis of the expected I/O cost is presented, with the I/O cost being about 40% that of the SEA-CNN method in the experiment results.

A new approach based on multiwavelets transformation and singular value decomposition (SVD) is proposed for the classification of image textures. Lower singular values are truncated based on its energy distribution to classify the textures in the presence of additive white Gaussian noise (AWGN). The proposed approach extracts features such as energy, entropy, local homogeneity and max-min ratio from the selected singular values of multiwavelets transformation coefficients of image textures. The classification was carried out using probabilistic neural network (PNN). Performance of the proposed approach was compared with conventional wavelet domain gray level co-occurrence matrix (GLCM) based features, discrete multiwavelets transformation energy based approach, and HMM based approach. Experimental results showed the superiority of the proposed algorithms when compared with existing algorithms.

In this paper, we propose a highly automatic approach for 3D photorealistic face reconstruction from a single frontal image. The key point of our work is the implementation of adaptive manifold learning approach. Beforehand, an active appearance model (AAM) is trained for automatic feature extraction and adaptive locally linear embedding (ALLE) algorithm is utilized to reduce the dimensionality of the 3D database. Then, given an input frontal face image, the corresponding weights between 3D samples and the image are synthesized adaptively according to the AAM selected facial features. Finally, geometry reconstruction is achieved by linear weighted combination of adaptively selected samples. Radial basis function (RBF) is adopted to map facial texture from the frontal image to the reconstructed face geometry. The texture of invisible regions between the face and the ears is interpolated by sampling from the frontal image. This approach has several advantages: (1) Only a single frontal face image is needed for highly automatic face reconstruction; (2) Compared with former works, our reconstruction approach provides higher accuracy; (3) Constraint based RBF texture mapping provides natural appearance for reconstructed face.

An objective performance measure for image fusion considering region information is proposed. The measure not only reflects how much the pixel level information that fused image takes from the source image, but also considers the region information between source images and fused image. The measure is meaningful and explicit. Several simulations were conducted to show that it accords well with the subjective evaluations.

An approach for generating interactive 3D graphical visualization of the genetic architectures of complex traits in multiple environments is described. 3D graphical visualization is utilized for making improvements on traditional plots in quantitative trait locus (QTL) mapping analysis. Interactive 3D graphical visualization for abstract expression of QTL, epistasis and their environmental interactions for experimental populations was developed in framework of user-friendly software QTLNetwork (http://ibi.zju.edu.cn/software/qtlnetwork). Novel definition of graphical meta system and computation of virtual coordinates are used to achieve explicit but meaningful visualization. Interactive 3D graphical visualization for QTL analysis provides geneticists and breeders a powerful and easy-to-use tool to analyze and publish their research results.

This paper proposes a learning-based method for text detection and text segmentation in natural scene images. First, the input image is decomposed into multiple connected-components (CCs) by Niblack clustering algorithm. Then all the CCs including text CCs and non-text CCs are verified on their text features by a 2-stage classification module, where most non-text CCs are discarded by an attentional cascade classifier and remaining CCs are further verified by an SVM. All the accepted CCs are output to result in text only binary image. Experiments with many images in different scenes showed satisfactory performance of our proposed method.

Segmenting a complex 3D surface model into some visually meaningful sub-parts is one of the fundamental problems in digital geometry processing. In this paper, a novel segmentation approach of point-sampled surfaces is proposed, which is based on the level set evolution scheme. To segment the model so as to align the patch boundaries with high curvature zones, the driven speed function for the zero level set inside narrow band is defined by the extended curvature field, which approaches zero speed as the propagating front approaches high curvature zone. The effectiveness of the proposed approach is demonstrated by our experimental results. Furthermore, two applications of model segmentation are illustrated, such as piecewise parameterization and local editing for point-sampled geometry.

Video object segmentation is important for video surveillance, object tracking, video object recognition and video editing. An adaptive video segmentation algorithm based on hidden conditional random fields (HCRFs) is proposed, which models spatio-temporal constraints of video sequence. In order to improve the segmentation quality, the weights of spatio-temporal constraints are adaptively updated by on-line learning for HCRFs. Shadows are the factors affecting segmentation quality. To separate foreground objects from the shadows they cast, linear transform for Gaussian distribution of the background is adopted to model the shadow. The experimental results demonstrated that the error ratio of our algorithm is reduced by 23% and 19% respectively, compared with the Gaussian mixture model (GMM) and spatio-temporal Markov random fields (MRFs).

We consider the class of parametric curves that can be represented by combination of control points and basis functions. A control point is let vary while the rest is held fixed. It’s shown that the locus of the moving control point that yields points of zero torsion is the osculating plane of the corresponding discriminant curve at its point of the same parameter value. The special case is studied when the basis functions sum to one.

SimWall is a user-friendly, stereo tiled display wall system composed of 18 commodity projectors operated by a Linux graphics cluster. Collaborating together, these projectors work as a single logical display capable of giving a high-resolution show, large-scale, and passive stereo scene. In order to avoid tedious system setup and maintenance, software-based automatic geometry and photometric calibration are used. The software calibration is integrated to the system seamlessly by an on-card transform method and is transparent to users. To end-users, SimWall works just as a common PC, but provides super computing, rendering and displaying ability. In addition, SimWall has stereoscopic function that gives users a semi-immersive experience in polarized passive way. This paper presents system architecture, implementation, and other technical issues such as hardware constraints, projectors alignment, geometry and photometric calibration, implementation of passive stereo, and development of overall software environment.

Multimedia streaming served through peer-to-peer (P2P) networks is booming nowadays. However, the end-to-end streaming quality is generally unstable due to the variability of the state of serve-peers. On the other hand, proxy caching is a bandwidth-efficient scheme for streaming over the Internet, whereas it is a substantially expensive method needing dedicated powerful proxy servers. In this paper, we present a P2P cooperative streaming architecture combined with the advantages of both P2P networks and multimedia proxy caching techniques to improve the streaming quality of participating clients. In this framework, a client will simultaneously retrieve contents from the server and other peers that have viewed and cached the same title before. In the meantime, the client will also selectively cache the aggregated video content so as to serve still future clients. The associate protocol to facilitate the multi-path streaming and a distributed utility-based partial caching scheme are detailedly discussed. We demonstrate the effectiveness of this proposed architecture through extensive simulation experiments on large, Internet-like topologies.

In real multiple-input multiple-output (MIMO) systems, the perfect channel state information (CSI) may be costly or impossible to acquire. But the channel statistical information can be considered relatively stationary during long-term transmission. The statistical information can be obtained at the receiver and fed back to the transmitter and do not require frequent update. By exploiting channel mean and covariance information at the transmitter simultaneously, this paper investigates the optimal transmission strategy for spatially correlated MIMO channels. An upper bound of ergodic capacity is derived and taken as the performance criterion. Simulation results are also given to show the performance improvement of the optimal transmission strategy.

In this paper, we propose a sparse overcomplete image approximation method based on the ideas of overcomplete log-Gabor wavelet, mean shift and energy concentration. The proposed approximation method selects the necessary wavelet coefficients with a mean shift based algorithm, and concentrates energy on the selected coefficients. It can sparsely approximate the original image, and converges faster than the existing local competition based method. Then, we propose a new compression scheme based on the above approximation method. The scheme has compression performance similar to JPEG 2000. The images decoded with the proposed compression scheme appear more pleasant to the human eyes than those with JPEG 2000.

RF power amplifiers (PAs) are usually considered as memoryless devices in most existing predistortion techniques. Nevertheless, in wideband communication systems, PA memory effects can no longer be ignored and memoryless predistortion cannot linearize PAs effectively. After analyzing PA memory effects, a novel predistortion method based on wavelet networks (WNs) is proposed to linearize wideband RF power amplifiers. A complex wavelet network with tapped delay lines is applied to construct the predistorter and then a complex backpropagation algorithm is developed to train the predistorter parameters. The simulation results show that compared with the previously published feed-forward neural network predistortion method, the proposed method provides faster convergence rate and better performance in reducing out-of-band spectral regrowth.

Floorplan, clock network and power plan are crucial steps in deep sub-micron system-on-chip design. A novel diagonal floorplan is integrated to enhance the data sharing between different cores in system-on-chip. Custom clock network containing hand-adjusted buffers and variable routing rules is constructed to realize balanced synchronization. Effective power plan considering both IR drop and electromigration achieves high utilization and maintains power integrity in our MediaSoC. Using such methods, deep sub-micron design challenges are managed under a fast prototyping methodology, which greatly shortens the design cycle.

Background knowledge is important for data mining, especially in complicated situation. Ontological engineering is the successor of knowledge engineering. The sharable knowledge bases built on ontology can be used to provide background knowledge to direct the process of data mining. This paper gives a common introduction to the method and presents a practical analysis example using SVM (support vector machine) as the classifier. Gene Ontology and the accompanying annotations compose a big knowledge base, on which many researches have been carried out. Microarray dataset is the output of DNA chip. With the help of Gene Ontology we present a more elaborate analysis on microarray data than former researchers. The method can also be used in other fields with similar scenario.

A vague-set-based fuzzy multi-objective decision making model is developed for evaluating bidding plans in a bidding purchase process. A group of decision-makers (DMs) first independently assess bidding plans according to their experience and preferences, and these assessments may be expressed as linguistic terms, which are then converted to fuzzy numbers. The resulting decision matrices are then transformed to objective membership grade matrices. The lower bound of satisfaction and upper bound of dissatisfaction are used to determine each bidding plan’s supporting, opposing, and neutral objective sets, which together determine the vague value of a bidding plan. Finally, a score function is employed to rank all bidding plans. A new score function based on vague sets is introduced in the model and a novel method is presented for calculating the lower bound of satisfaction and upper bound of dissatisfaction. In a vague-set-based fuzzy multi-objective decision making model, different valuations for upper and lower bounds of satisfaction usually lead to distinct ranking results. Therefore, it is crucial to effectively contain DMs’ arbitrariness and subjectivity when these values are determined.

Consider the positive d-dimensional lattice Z₊^d (d≥2) with partial ordering ≤, let {X_K; K∈Z₊^d be i.i.d. random variables taking values in a real separable Hilbert space (H, ||∙||) with mean zero and covariance operator ∑, and set partial sums S_N =∑_K≤NX_K, N∈Z₊^d. Under some moment conditions, we obtain the precise asymptotics of a kind of weighted infinite series for partial sums S_N as ε↘0 by using the truncation and approximation methods. The results are related to the convergence rates of the law of the logarithm in Hilbert space, and they also extend the results of (Gut and Spǎtaru, 2003).

This paper applies the EXP-function method to find exact solutions of various nonlinear equations. Tzitzeica-Dodd-Bullough (TDB) equation was selected to illustrate the effectiveness and convenience of the suggested method. More generalized solitonary solutions with free parameters were obtained by suitable choice of the free parameters, and also the obtained solitonary solutions can be converted into periodic solutions.

In arbitrary Riemannian 4-spaces, continuity equations are constructed which could be interpreted as conservation laws for the energy and momentum of the gravitational field. Special attention is given to general relativity to obtain, of natural manner, the pseudotensors of Einstein, Landau-Lifshitz, Möller, Goldberg and Stachel, and also the conservation equations of Komar, Trautman, DuPlessis and Moss.

Acoustic wave propagation in piezoelectric crystals of classes 4̄3m and 23 is studied. The crystals Tl₃VS₄ and Tl₃TaSe₄ (4̄3m) of the Chalcogenide family and the crystal Bi₁₂TiO₂₀ (23) possess strong piezoelectric effect. Because the surface Bleustein-Gulyaev waves cannot exist in piezoelectric cubic crystals, it was concluded that new solutions for shear-horizontal surface acoustic waves (SH-SAWs) are found in the monocrystals using different electrical boundary conditions such as electrically “short” and “open” free-surfaces for the unique [101] direction of wave propagation. For the crystal Tl₃TaSe₄ with coefficient of electromechanical coupling (CEMC) K_e²=e²/(C×g)~1/3, the phase velocity V_ph for the new SH-SAWs can be calculated with the following formula: V_ph=(V_a+V_t)/2, where V_t is the speed of bulk SH-wave, V_t=V_t4(1+K_e²)^1/2, V_a=a_KV_t4, a_K=2[K_e(1+K_e²)^1/2−K_e²]^1/2, and V_t4=(C₄₄/ρ)^1/2. It was found that the CEMC K² evaluation for Tl₃TaSe₄ gave the value of K²=2(V_f–V_m)/V_f~0.047 (~4.7%), where V_f~848 m/s and V_m~828 m/s are the new-SAW velocities for the free and metallized surfaces, respectively. This high value of K²(Tl₃TaSe₄) is significantly greater than K²(Tl₃VS₄)~3% and about five times that of K²(Bi₁₂TiO₂₀).