基于VSL的动态图示表的实现

复杂虚拟系统的交互界面,一般由二维的动态图示框架构成。但是用Virtools自带BB模块过于复杂和繁琐。本文提出一种基于VSL的混合模式的的解决方案,用简单、清晰的流程和更有效的方法,实现动态图示表。

图示表征在第二学段倍比问题中运用策略研究

"倍比"问题是具有典型意义的一类数学问题。在学习过程中发现,无论是三年级简单的倍数关系还是五六年级较为复杂的"和倍关系"、"差倍关系",学生解决此类问题的错误率高居不下。

An Incremental Algorithm for Non-Slicing Floorplan Based on Corner Block List Representation

We present a novel incremental algorithm for non-slicing floorplans based on the corner block list representation. The horizontal and vertical adjacency graphs are derived from the packing of the initial floorplanning results. Based on the critical path and the accumulated slack distances we define,we choose the best position for insertion and do a series of operations incrementally, such as deleting modules, adding modules, and resizing modules quickly. This incremental floorplanning algorithm has a very high speed less than 1μm,which is one of the most important measures in this research. The algorithm preserves the original good performances on area and wire length. It can also supply other tools with good physical estimates for area, wire length, and other performance guidelines.

Two-level Bregmanized method for image interpolation with graph regularized sparse coding

A two-level Bregmanized method with graph regularized sparse coding （TBGSC） is presented for image interpolation. The outer-level Bregman iterative procedure enforces the observation data constraints, while the inner-level Bregmanized method devotes to dictionary updating and sparse represention of small overlapping image patches. The introduced constraint of graph regularized sparse coding can capture local image features effectively, and consequently enables accurate reconstruction from highly undersampled partial data. Furthermore, modified sparse coding and simple dictionary updating applied in the inner minimization make the proposed algorithm converge within a relatively small number of iterations. Experimental results demonstrate that the proposed algorithm can effectively reconstruct images and it outperforms the current state-of-the-art approaches in terms of visual comparisons and quantitative measures.

Electronic Chart Display and Information System

This paper introduces the most advanced form of electronic chart display and information systems (ECDIS) which complies with the Performance Standards for ECDIS established by the International Maritime Organization (IMO) and the International Hydrographic Organization (IHO).It also describes the key features and the important functions of ECDIS.Then the future development of ECDIS in marine is discussed.

Navigation Map Data Representation and Parallel Display Algorithm in an Embedded Environment

Map data display is the basic information representation mode under embedded real-time navigation. After a navigation display data set （NDIS_SET） with several dimensions and corresponding mathematical description formula are designed, a series of rules and algorithms are advanced to optimize embedded navigation data and promote data index and input efficiency. A new parallel display algorithm with navigation data named N PDIS is then presented to adapt to limited embedded resources of computation and memory after a normal navigation data display algorithm named NDIS and related problems are analyzed, N_PDIS can synchronously create two preparative bitmapa by two parallel threads and switch one of them to screen automatically. Compared with NDIS, the results show that N_PDIS is more effective in improving display efficiency.

Traffic sign recognition algorithm based on shape signature and dual-tree complex wavelet transform

A novel traffic sign recognition system is presented in this work. Firstly, the color segmentation and shape classifier based on signature feature of region are used to detect traffic signs in input video sequences. Secondly, traffic sign color-image is preprocessed with gray scaling, and normalized to 64×64 size. Then, image features could be obtained by four levels DT-CWT images. Thirdly, 2DICA and nearest neighbor classifier are united to recognize traffic signs. The whole recognition algorithm is implemented for classification of 50 categories of traffic signs and its recognition accuracy reaches 90%. Comparing image representation DT-CWT with the well-established image representation like template, Gabor, and 2DICA with feature selection techniques such as PCA, LPP, 2DPCA at the same time, the results show that combination method of DT-CWT and 2DICA is useful in traffic signs recognition. Experimental results indicate that the proposed algorithm is robust, effective and accurate.

Which is better for presenting your data： table or graph？

This study aimed at investigating the characteristics of table and graph that people perceive and the data types which people consider the two displays are most appropriate for. Participants in this survey were 195 teachers and undergraduates from four universities in Beijing. The results showed people's different attitudes towards the two forms of display.

Knowledge Innovation of Great Tradition of Chinese Literary Anthropology

It is very innovative significance that Chinese Literary Anthropology invents the Great Tradition in the new century and puts forward series of theoretical propositions and academic points based on it. The new Great Tradition transforms the opposition between the Great and Little Tradition of American anthropology, and makes the new concepts gain the legitimacy of the cultural values transferred from the old terms. It dates the second coded significance of the written culture from the material narrative and the image narrative of the oral tradition, and highlights the generative and primary of the symbolic significance. It also questions the authenticity of the written representation, endows the truth and credibility to the material and image representation, and manifests the imaginative and expression of the early human culture. Though its theoretical innovation inverts the binary opposition structure, and it wants to jump out of knowledge limits of dual structure such as structure and destruction, objective and subjective, material and spiritual.

From Sex Objects to Heroines A Tough Road for Female Characters in Video Games

Female character in video games is the one of the most controversial topic in game studies and nowadays women＇s anthropology. From the beginning of role in games＇ plot to sexualized graphical representation, woman in virtual world were （and sometimes still are） a point of discussion about characters sexualisation and role of female sex in virtual industry. The main aim of this paper is to present analysis of female representation in video games and how in last 30 years it has changed. In other words, how female characters were ennobled from sex object to main protagonist status. In presented research, there were used mostly the examples of popular video games with extended plot and world which can be explored by protagonists. Video game historiography, textual analysis （which helped to treat video game character as a protagonist）, and thematic analysis of video games were used as a main research method. The main conclusion of this paper is that female characters can overcome all gender or sexual stereotypes and even eventually became an icon of popular culture

Analysis of Hydrological Simulation Models Using the Parameter Combinatorial Diagram

The aim of this paper is to present graphically the behaviour of a simulation model to the varying parameters and to establish the suitability of this representation as a valid tool for the analysis of the same parameters. In this paper, we define parameter combinatorial diagram as the joint graphical representation of all box plots related to the adjustment between real and simulated data, by setting and/or changing the parameters of the simulation model. To do this, we start with a box plot representing the values of an objective adjustment function, achieving these results when varying all the parameters of the simulation model, Then we draw the box plot when setting all the parameters of the model, for example, using the median or average. Later, we get all the box plots when carrying out simulations combining fixed or variable values of the model parameters. Finally, all box plots obtained are represented neatly in a single graph. It is intended that the new parameter combinatorial diagram is used to examine and analyze simulation models useful in practice. This paper presents combinatorial diagrams of different examples of application as in the case of hydrologic models of one, two, three, and five parameters.

Statistical Reasoning of High School Teachers in a Computer Environment of Dynamic Data Exploration

Results of a research about statistical reasoning that six high school teachers developed in a computer environment are presented in this article. A sequence of three activities with the support of software Fathom was presented to the teachers in a course to investigate about the reasoning that teachers develop about the data analysis, particularly about the distribution concept, that involves important concepts such as averages, variability and graphics representations. The design of the activities was planned so that the teachers analyzed quantitative variables separately first, and later made an analysis of a qualitative variable versus a quantitative variable with the objective of establishing comparisons between distributions and use concepts as averages, variability, shape and outliers. The instructions in each activity indicated to the teachers to use all the resources of the software that were necessary to make the complete analysis and respond to certain questions that pretended to capture the type of representations they used to answer. The results indicate that despite the abundance of representations provided by the software, teachers focu,; on the calculation of averages to describe and compare distributions, rather than on the important properties of data such as variability, ：shape and outliers. Many teachers were able to build interesting graphs reflecting important properties of the data, but cannot use them 1：o support data analysis. Hence, it is necessary to extend the teachers＇ understanding on data analysis so they can take advantage of the cognitive potential that computer tools to offer.

Heterogeneous graph construction and node representation learning method of Treatise on Febrile Diseases based on graph convolutional network

Objective To construct symptom-formula-herb heterogeneous graphs structured Treatise on Febrile Diseases(Shang Han Lun,《伤寒论》)dataset and explore an optimal learning method represented with node attributes based on graph convolutional network(GCN).Methods Clauses that contain symptoms,formulas,and herbs were abstracted from Treatise on Febrile Diseases to construct symptom-formula-herb heterogeneous graphs,which were used to propose a node representation learning method based on GCN−the Traditional Chinese Medicine Graph Convolution Network(TCM-GCN).The symptom-formula,symptom-herb,and formula-herb heterogeneous graphs were processed with the TCM-GCN to realize high-order propagating message passing and neighbor aggregation to obtain new node representation attributes,and thus acquiring the nodes’sum-aggregations of symptoms,formulas,and herbs to lay a foundation for the downstream tasks of the prediction models.Results Comparisons among the node representations with multi-hot encoding,non-fusion encoding,and fusion encoding showed that the Precision@10,Recall@10,and F1-score@10 of the fusion encoding were 9.77%,6.65%,and 8.30%,respectively,higher than those of the non-fusion encoding in the prediction studies of the model.Conclusion Node representations by fusion encoding achieved comparatively ideal results,indicating the TCM-GCN is effective in realizing node-level representations of heterogeneous graph structured Treatise on Febrile Diseases dataset and is able to elevate the performance of the downstream tasks of the diagnosis model.

Single Image Super-Resolution by Clustered Sparse Representation and Adaptive Patch Aggregation

A Single Image Super-Resolution (SISR) reconstruction method that uses clustered sparse representation and adaptive patch aggregation is proposed. First, we randomly extract image patch pairs from the training images, and divide these patch pairs into different groups by K-means clustering. Then, we learn an over-complete sub-dictionary pair offline from corresponding group patch pairs. For a given low-resolution patch, we adaptively select one sub-dictionary to reconstruct the high resolution patch online. In addition, non-local self-similarity and steering kernel regression constraints are integrated into patch aggregation to improve the quality of the recovered images. Experiments show that the proposed method is able to realize state-of-the-art performance in terms of both objective evaluation and visual perception.

Schematic interface of sound creation for computer animators

As an audiovisual medium, computer animations require superior image quality and professional soundtrack to lead audiences into their fascinating virtual world. Without sound, the impact of storytelling is reduced or the story is even not under- standable. Despite the importance of sound, most animators are unfamiliar with sound editing software. Limited budget projects such as independent or student works have difficulty hiring sound professionals to create tailor-made soundtrack. Therefore, we need a suitable sound tool to express their individual ideas. In this paper, we propose an approach using schematic for both computer animation and sound. Our approach provides (1) physical simulation on sound through animation parameters and (2) a new channel for animators to add aesthetic values in sound through their experience of using schematics in existing animation software. We demonstrate our idea through several examples, such as Doppler shift, obstacle effect, importance, energetic, and sputtering effect.

Two-Level Bregman Method for MRI Reconstruction with Graph Regularized Sparse Coding

In this paper, a two-level Bregman method is presented with graph regularized sparse coding for highly undersampled magnetic resonance image reconstruction. The graph regularized sparse coding is incorporated with the two-level Bregman iterative procedure which enforces the sampled data constraints in the outer level and updates dictionary and sparse representation in the inner level. Graph regularized sparse coding and simple dictionary updating applied in the inner minimization make the proposed algorithm converge with a relatively small number of iterations. Experimental results demonstrate that the proposed algorithm can consistently reconstruct both simulated MR images and real MR data efficiently, and outperforms the current state-of-the-art approaches in terms of visual comparisons and quantitative measures.

Unique Embeddings for Graphs on Orientable Surfaces Permitting Short Noncontractible Cycles

A fundamental result in topological graph theory by H.Whitney states that a 3-connected graph has at most one planar embedding. C.Thomassen generalized this to LEW-embeddings on higher surfaces. We establish several unique embedding results for 3-connected graphs on orientable surfaces which admit relatively large facial walks and rcpresentativity and hence generalize Thomassen's uniqueness theorem on LEW-embeddings.

A mass and energy estimation for the hydrogen utilization in the iron-making process

The possibility of using hydrogen to lower CO 2 emissions in the iron-making process was confirmed by the heat and mass balances in the blast furnace operation. The mass and heat balances for hydrogen utilization in the blast furnace were estimated by using the basic concept of RIST operating diagram. In this study, the RIST operating diagram was modified to be suitable for representing the operation with respect to hydrogen, where the RIST operating diagram is a graphical representation of heat and mass balance in blast furnace operation. RIST operating diagram was applied here to some individual parameters of interest such as H 2 injection in blast furnace process to reduce coke (carbon consumption). It was observed that the point W moved to the right in the RIST operating diagram under the condition of increasing hydrogen injection at tuyere, which originates from the contribution of gas composition (O/H 2 ) equilibrated with Fe/FeO at a certain temperature. Point P also moved downward due to heat requirement with respect to hydrogen utilization, by which the new RIST operating diagram for hydrogen utilization was able to be constructed. Under the condition of hydrogen injection, the expected overall carbon consumption in the blast furnace decreased due to the contribution of hydrogen.

On region crossing change and incidence matrix

In a recent work of Ayaka Shimizu, she studied an operation named region crossing change on link diagrams, which was proposed by Kishimoto, and showed that a region crossing change is an unknotting operation for knot diagrams. In this paper, we prove that the region crossing change on a 2-component link diagram is an unknotting operation if and only if the linking number of the diagram is even. Besides, we define an incidence matrix of a link diagram via its signed planar graph and its dual graph. By studying the relation between region crossing change and incidence matrix, we prove that a signed planar graph represents an n-component link diagram if and only if the rank of the associated incidence matrix equals c n + 1, where c denotes the size of the graph.

Aversive and non-reward learning in the fire-bellied toad using familiar and unfamiliar prey stimuli

The present study investigated how snapping behavior toward familiar and unfamiliar prey is modified by reward omission and aversive conditioning in the f^re-bellied toad Bombina orientalis. Toads were trained to snap at cricket images by rewarding them with live crickets. The task was learned, and the learning criterion （10 snapping responses within 2 minutes） was reached in all individuals investigated. Subsequent reward omission did not alter the frequency of snapping to the familiar cricket stimulus. Snapping decreased only in some individuals, when a mild foot shock was applied at snapping. However, at presenta- tion of images of hitherto unfamiliar meal worms and foot-shock application at snapping to the stimulus, the majority of toads diminished snapping significantly. Snapping responses decreased more rapidly, when snapping at meal worms was not rewarded or a footshock was applied uncorrelated to the presentation of or snapping at meal worms. These results demonstrate that in toads familiarity and unfamiliarity of prey stimuli are important factors in aversive learning, because well-trained responses to familiar stimuli become immune against reward omission. Furthermore, at presentation of unfamiliar stimuli, omission of reward and un- correlated footshock had a stronger aversive effect than correlated footshock [Current Zoology 57 （6）： 709-716, 2011 ].