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The performance of modern processors is often limited by execution stalls resulting from long memory access latencies. Compile-time optimizations, deep cache hierarchies and prefetching mechanisms already provide significant performance gains, by performing memory accesses in parallel with computation. However, they are reaching a throughput improvement limit. Hence, new solutions that effectively exploit the memory access patterns to improve processing throughput are required. To achieve this objective, a new compiler-assisted data streaming method is proposed. It leverages static analysis and code transformations with an on-chip data streaming support as a viable alternative to prefetching mechanisms for regular code structures. Static analysis is used to identify and encode memory accesses with a dedicated representation. Then, a code transformation algorithm detaches data indexation and address calculation from computation, allowing for a significant code reduction. An on-chip data stream controller, attached to the L1 data cache, is used to autonomously generate memory accesses from the pattern representation and reorganize the data transfers in streams, with the aid of stream buffers. When compared with state-of-the-art prefetchers, the proposed solution provides up to 26 percent of code reduction, an IPC improvement of 2.4x, and an average performance improvement of 40 percent. [ABSTRACT FROM AUTHOR]

A decision support system is used by decision makers for a long time. But, in some cases, the originally designed multidimensional schema does not cover the entire needs of decision makers, which can change over time. One such unfulfilled need, is using facts to describe dimension members. In this article, we propose a methodology to transform the constellation schema of a data warehouse by integrating factual data into a dimension. The proposed methodology and algorithms enrich a constellation multidimensional schema with new analytical possibilities for decision makers. This enrichment has repercussions for the entire multidimensional schema that are managed by multidimensional modeling, hierarchy calculation and the hierarchy version. In this article, we present a theoretical view of the proposed methodology supported by a case study, an implemented prototype and a complete evaluation based on a standard benchmark. [ABSTRACT FROM AUTHOR]

Tactile sensing is a key sensor modality for robots interacting with their surroundings. These sensors provide a rich and diverse set of data signals that contain detailed information collected from contacts between the robot and its environment. The data are however not limited to individual contacts and can be used to extract a wide range of information about the objects in the environment as well as the actions of the robot during the interactions. In this article, we provide an overview of tactile information and its applications in robotics. We present a hierarchy consisting of raw, contact, object, and action levels to structure the tactile information, with higher-level information often building upon lower-level information. We discuss different types of information that can be extracted at each level of the hierarchy. The article also includes an overview of different types of robot applications and the types of tactile information that they employ. Finally we end the article with a discussion for future tactile applications which are still beyond the current capabilities of robots. [ABSTRACT FROM AUTHOR]

In this article, we propose a parallel hierarchy convolutional neural network (PHCNN) combining a Long Short-Term Memory (LSTM) network structure to quantitatively assess the grading of facial nerve paralysis (FNP) by considering the region-based asymmetric facial features and temporal variation of the image sequences. FNP, such as Bell’s palsy, is the most common facial symptom of neuromotor dysfunctions. It causes the weakness of facial muscles for the normal emotional expression and movements. The subjective judgement by clinicians completely depends on individual experience, which may not lead to a uniform evaluation. Existing computer-aided methods mainly rely on some complicated imaging equipment, which is complicated and expensive for facial functional rehabilitation. Compared with the subjective judgment and complex imaging processing, the objective and intelligent measurement can potentially avoid this issue. Considering dynamic variation in both global and regional facial areas, the proposed hierarchical network with LSTM structure can effectively improve the diagnostic accuracy and extract paralysis detail from the low-level shape, contour to sematic level features. By segmenting the facial area into two palsy regions, the proposed method can discriminate FNP from normal face accurately and significantly reduce the effect caused by age wrinkles and unrepresentative organs with shape and position variations on feature learning. Experiment on the YouTube Facial Palsy Database and Extended CohnKanade Database shows that the proposed method is superior to the state of the art deep learning methods. [ABSTRACT FROM AUTHOR]

Organizing multivariate data spaces by their dimensions or attributes can be a rather difficult task. Most of the work in this area focuses on the statistical aspects such as correlation clustering, dimension reduction, and the like. These methods typically produce hierarchies in which the leaf nodes are labeled by the attribute names while the inner nodes are often represented by just a statistical measure and criterion, such as a threshold. This makes them difficult to understand for mainstream users. Taxonomies in science, biology, engineering, etc. on the other hand, are easy to comprehend since they provide meaningful labels at the inner nodes as well. Labeling inner nodes of taxonomies automatically requires the identification of hypernyms. Our proposed framework, called Taxonomizer, takes a visual analytics approach to meet this challenge. It appeals to the wisdom of humans to liaise with state of the art data analytics, neural word embeddings, and lexical databases. It consists of a set of visual tools that starts out with an automatically computed hierarchy where the leaf nodes are the original data attributes, and it then allows users to sculpt high-quality taxonomies for any multivariate dataset. [ABSTRACT FROM AUTHOR]

The formation of social groups is defined by the interactions among the group members. Studying this group formation process can be useful in understanding the status of members, decision-making behaviors, spread of knowledge and diseases, and much more. A defining characteristic of these groups is the pecking order or hierarchy the members form which help groups work towards their goals. One area of social science deals with understanding the formation and maintenance of these hierarchies, and in our work we provide social scientists with a visual analytics tool - PeckVis - to aid this process. While online social groups or social networks have been studied deeply and lead to a variety of analyses and visualization tools, the study of smaller groups in the field of social science lacks the support of suitable tools. Domain experts believe that visualizing their data can save them time as well as reveal findings they may have failed to observe. We worked alongside domain experts to build an interactive visual analytics system to investigate social hierarchies. Our system can discover patterns and relationships between the members of a group as well as compare different groups. The results are presented to the user in the form of an interactive visual analytics dashboard. We demonstrate that domain experts were able to effectively use our tool to analyze animal behavior data. [ABSTRACT FROM AUTHOR]

Most recommender systems (RSs), especially group RSs, focus on methods and accuracy but lack explanations, hence users find them difficult to trust. We present a hierarchy visualization method for group recommender (HVGR) systems to provide visual presentation and intuitive explanation. We first use a hierarchy graph to organize all the entities using nodes (e.g., neighbor nodes and recommendation nodes) and illustrate the overall recommender process using edges. Second, a pie chart is attached to every entity node in which each slice represents a single member, which makes it easy to track the influence of each member on a specific entity. HVGR can be extended to adapt different pseudouser modeling methods by resizing group member nodes and pseudouser nodes. It can also be easily extended to individual RSs through the use of a single member group. An implementation has been developed and feasibility is tested using a real data set. [ABSTRACT FROM AUTHOR]

This paper introduces a routability-driven macro placement algorithm for mixed-size circuits and pays special attention to the effect of regular placement of macros. Once macros are placed with regularity, powerplanning will become easier and better routability can be obtained. Our methodology consists of two stages. First, placement prototyping stage distributes cells and macros over a placement region while keeping those macros and cells with a strong connection and in similar hierarchies tied together. This is facilitated by clustering macros and cells properly in advance. In the second stage, a deterministic macro legalization algorithm is proposed to arrange macros without deteriorating the result obtained in the previous stage. Although several macro legalization algorithms have been proposed in recent years, most of these works adopt the simulated annealing algorithm which usually takes longer runtime. Moreover, they either cannot handle preplaced macros or require preplaced macros to be abutted to chip boundaries. Unlike these approaches, our method iteratively places a macro by extracting available space for it. Experimental results demonstrate the efficiency and effectiveness of our method according to real industry circuits. [ABSTRACT FROM AUTHOR]

Region-based hierarchical image representation is crucial in many computer vision applications. However, in practice, an image hierarchy is usually dense, and contains many less informative branches. It is expected that a hierarchy should be accurate and simplified, which is not only desirable for different applications, but also saves considerable computational load for the further analysis. To achieve this target, this paper proposes a novel approach for unsupervised simplification of region-based image hierarchies, which employs the global and local evolution analyses of a hierarchy. First, we introduce a global evolution analysis in the scale-sets framework, which provides clues for eliminating less informative branches. Moreover, a hybrid unsupervised simplification method is designed, utilizing the information from global and local evolution functions. A number of experiments on various images have shown that the proposed approach is effective and efficient in removing less informative nodes (averagely about 90% of the whole nodes), while preserving salient image details and retaining the accuracy. [ABSTRACT FROM PUBLISHER]

In this paper we examine how the Minimum Description Length (MDL) principle can be used to efficiently select aggregated views of hierarchical datasets that feature a good balance between clutter and information. We present MDL formulae for generating uneven tree cuts tailored to treemap and sunburst diagrams, taking into account the available display space and information content of the data. We present the results of a proof-of-concept implementation. In addition, we demonstrate how such tree cuts can be used to enhance drill-down interaction in hierarchical visualizations by implementing our approach in an existing visualization tool. Validation is done with the feature congestion measure of clutter in views of a subset of the current DMOZ web directory, which contains nearly half million categories. The results show that MDL views achieve near constant clutter level across display resolutions. We also present the results of a crowdsourced user study where participants were asked to find targets in views of DMOZ generated by our approach and a set of baseline aggregation methods. The results suggest that, in some conditions, participants are able to locate targets (in particular, outliers) faster using the proposed approach. [ABSTRACT FROM AUTHOR]

Information hierarchies are difficult to express when real-world space or time constraints force traversing the hierarchy in linear presentations, such as in educational books and classroom courses. We present booc.io, which allows linear and non-linear presentation and navigation of educational concepts and material. To support a breadth of material for each concept, booc.io is Web based, which allows adding material such as lecture slides, book chapters, videos, and LTIs. A visual interface assists the creation of the needed hierarchical structures. The goals of our system were formed in expert interviews, and we explain how our design meets these goals. We adapt a real-world course into booc.io, and perform introductory qualitative evaluation with students. [ABSTRACT FROM AUTHOR]

Graphs are used to model relations between objects, where these objects can be grouped hierarchically based on their connectivity. In many applications, the relations change over time and so does the hierarchical group structure. We developed a visualization technique that supports the analysis of the topology and the hierarchical group structure of a dynamic graph and the tracking of changes over time. Each graph of a sequence is visualized by an adjacency matrix, where the hierarchical group structure is encoded within the matrix using indentation and nested contours, complemented by icicle plots attached to the matrices. The density within and between subgroups of the hierarchy is represented within the matrices using a gray scale. To visualize changes, transitions and dissimilarities between the hierarchically structured graphs are shown using a flow metaphor and color coding. The design of our visualization technique allows us to show more than one hierarchical group structure of the same graph by stacking the sequences, where hierarchy comparison is supported not only within but also between sequences. To improve the readability, we minimize the number of crossing curves within and between sequences based on a sorting algorithm that sweeps through the sequences of hierarchies. [ABSTRACT FROM AUTHOR]

Evidence resolution has been studied previously for crisp hierarchies and here we develop approaches for fuzzy concept hierarchies. Since fuzzy hierarchies are characterized by decompositions of their domains as opposed to partitions, properties and measures of decompositions are developed. Fuzzy complete and partial evidence resolution is defined and related to the valuation of evidence. Finally a for-and-against analysis is developed for the selection of which concept to choose in the generalization. [ABSTRACT FROM AUTHOR]

Morphological operators may be taken up from the two entries of dilation and of connection. This tutorial focuses on the second entry, and leads to optimum partitionings of the images under study. Five notions, which derive from each other, are successively explored. The “set connection,” which generalizes the usual connectivities, opens the series, and yields the “connective segmentation,” which associates connection with maximum partition. Then the “connected operators” allow to construct “hierarchies of partitions” whose the laws of “optimal cuts” are given. [ABSTRACT FROM PUBLISHER]

Abstract-Efficient multiresolution representations for isosurfaces and interval volumes are becoming increasingly important as the gap between volume data sizes and processing speed continues to widen. Our multiresolution scalar field model is a hierarchy of tetrahedral clusters generated by longest edge bisection that we call a hierarchy of diamonds. We propose two multiresolution models for representing isosurfaces, or interval volumes, extracted from a hierarchy of diamonds which exploit its regular structure. These models are defined by subsets of diamonds in the hierarchy that we call isodiamonds, which are enhanced with geometric and topological information for encoding the relation between the isosurface, or interval volume, and the diamond itself. The first multiresolution model, called a relevant isodiamond hierarchy, encodes the isodiamonds intersected by the isosurface, or interval volume, as well as their nonintersected ancestors, while the second model, called a minimal isodiamond hierarchy, encodes only the intersected isodiamonds. Since both models operate directly on the extracted isosurface or interval volume, they require significantly less memory and support faster selective refinement queries than the original multiresolution scalar field, but do not support dynamic isovalue modifications. Moreover, since a minimal isodiamond hierarchy only encodes intersected isodiamonds, its extracted meshes require significantly less memory than those extracted from a relevant isodiamond hierarchy. We demonstrate the compactness of isodiamond hierarchies by comparing them to an indexed representation of the mesh at full resolution. [ABSTRACT FROM AUTHOR]

The perceptual computer (Per-C) is an architecture that makes subjective judgments by computing with words (CWWs). This paper applies the Per-C to hierarchical decision making, which means decision making based on comparing the performance of competing alternatives, where each alternative is first evaluated based on hierarchical criteria and subcriteria, and then, these alternatives are compared to arrive at either a single winner or a subset of winners. What can make this challenging is that the inputs to the subcriteria and criteria can be numbers, intervals, type-1 fuzzy sets, or even words modeled by interval type-2 fuzzy sets. Novel weighted averages are proposed in this paper as a CWW engine in the Per-C to aggregate these diverse inputs. A missile-evaluation problem is used to illustrate it. The main advantages of our approaches are that diverse inputs can be aggregated, and uncertainties associated with these inputs can be preserved and are propagated into the final evaluation. [ABSTRACT FROM AUTHOR]

We present a model for building, visualizing, and interacting with multiscale representations of information visualization techniques using hierarchical aggregation. The motivation for this work is to make visual representations more visually scalable and less cluttered. The model allows for augmenting existing techniques with multiscale functionality, as well as for designing new visualization and interaction techniques that conform to this new class of visual representations. We give some examples of how to use the model for standard information visualization techniques such as scatterplots, parallel coordinates, and node-link diagrams, and discuss existing techniques that are based on hierarchical aggregation. This yields a set of design guidelines for aggregated visualizations. We also present a basic vocabulary of interaction techniques suitable for navigating these multiscale visualizations. [ABSTRACT FROM AUTHOR]

We explore the effects of selecting alternative layouts in hierarchical displays that show multiple aspects of large multivariate datasets, including spatial and temporal characteristics. Hierarchical displays of this type condition a dataset by multiple discrete variable values, creating nested graphical summaries of the resulting subsets in which size, shape and colour can be used to show subset properties. These 'small multiples' are ordered by the conditioning variable values and are laid out hierarchically using dimensional stacking. Crucially, we consider the use of different layouts at different hierarchical levels, so that the coordinates of the plane can be used more effectively to draw attention to trends and anomalies in the data. We argue that these layouts should be informed by the type of conditioning variable and by the research question being explored. We focus on space-filling rectangular layouts that provide data-dense and rich overviews of data to address research questions posed in our exploratory analysis of spatial and temporal aspects of property sales in London. We develop a notation ('HIVE') that describes visualisation and layout states and provides reconfiguration operators, demonstrate its use for reconfiguring layouts to pursue research questions and provide guidelines for this process. We demonstrate how layouts can be related through animated transitions to reduce the cognitive load associated with their reconfiguration whilst supporting the exploratory process. [ABSTRACT FROM AUTHOR]

This paper presents the sizing rules method for basic building blocks in analog CMOS and bipolar circuit design. It consists of the development of a hierarchical library of transistor-pair groups as basic building blocks for analog CMOS and bipolar circuits, the derivation of a hierarchical generic list of constraints that must be satisfied to guarantee the function and robustness of each block, and the development of a reliable automatic recognition procedure of building blocks in a circuit schematic. Sizing rules efficiently capture design knowledge on the technology-specific level of transistor-pair groups. This reduces the effort and improves the resulting quality for analog circuit synthesis. Results of applications like circuit sizing, design centering, response surface modeling, or analog placement show the benefits of the sizing rules method. [ABSTRACT FROM AUTHOR]

Recently, √5-refinement hierarchical sampling has been studied and √5-refinement has been used for surface subdivision. Compared with other refinements, such as the dyadic or quincunx refinement, √5-refinement has a special property that the nodes in a refined lattice form groups of five nodes with these five nodes having different x and y coordinates. This special property has been shown to be very useful to represent adaptively and render complex and procedural geometry. When √5-refinement is used for multiresolution data processing, √5-refinement filter banks and wavelets are required. While the construction of 2-D nonseparable (bi)orthogonal wavelets with the dyadic or quincunx refinement has been studied by many researchers, the construction of (bi)orthogonal wavelets with √5-refinement has not been investigated. The main goal of this paper is to construct compactly supported orthogonal and biorthogonal wavelets with √5-refinement. In this paper, we obtain block structures of orthogonal and biorthogonal √5-refinement FIR filter banks with 4-fold rotational symmetry. We construct compactly supported orthogonal and biorthogonal wavelets based on these block structures. [ABSTRACT FROM AUTHOR]

The nature of an information visualization can be considered to lie in the visual metaphors it uses to structure information. The process of understanding a visualization therefore involves an interaction between these external visual metaphors and the user's internal knowledge representations. To investigate this claim, we conducted an experiment to test the effects of visual and verbal metaphor on the understanding of tree visualizations. Participants answered simple data comprehension questions while viewing either a tree-map or a node-link diagram. Questions were worded to reflect a verbal metaphor that was either compatible or incompatible with the visualization a participant was using. The results (based on correctness and response time) suggest that the visual metaphor indeed affects how a user derives information from a visualization. Additionally, we found that the degree to which a user is affected by the metaphor is strongly correlated with the user's ability to answer task questions correctly. These findings are a first step towards illuminating how visual metaphors shape user understanding and have significant implications for the evaluation, application, and theory of visualization. [ABSTRACT FROM AUTHOR]

Point placement strategies aim at mapping data points represented in higher dimensions to bi-dimensional spaces and are frequently used to visualize relationships amongst data instances. They have been valuable tools for analysis and exploration of data sets of various kinds. Many conventional techniques, however, do not behave well when the number of dimensions is high, such as in the case of documents collections. Later approaches handle that shortcoming, but may cause too much clutter to allow flexible exploration to take place. In this work we present a novel hierarchical point placement technique that is capable of dealing with these problems. While good grouping and separation of data with high similarity is maintained without increasing computation cost, its hierarchical structure lends itself both to exploration in various levels of detail and to handling data in subsets, improving analysis capability and also allowing manipulation of larger data sets. [ABSTRACT FROM AUTHOR]

The treemap is one of the most popular methods for visualizing hierarchical data. When a treemap contains a large number of items, inspecting or comparing a few selected items in a greater level of detail becomes very challenging. In this paper, we present a seamless multi-focus and context technique, called Balloon Focus, that allows the user to smoothly enlarge multiple treemap items served as the foci, while maintaining a stable treemap layout as the context. Our method has several desirable features. First, this method is quite general and can be used with different treemap layout algorithms. Second, as the foci are enlarged, the relative positions among all items are preserved. Third, the foci are placed in a way that the remaining space is evenly distributed back to the non-focus treemap items. When Balloon Focus enlarges the focus items to a maximum degree, the above features ensure that the treemap will maintain a consistent appearance and avoid any abrupt layout changes. In our algorithm, a DAG (Directed Acyclic Graph) is used to maintain the positional constraints, and an elastic model is employed to govern the placement of the treemap items. We demonstrate a treemap visualization system that integrates data query, manual focus selection, and our novel multi-focus+context technique, Balloon Focus, together. A user study was conducted. Results show that with Balloon Focus, users can better perform the tasks of comparing the values and the distribution of the foci. [ABSTRACT FROM AUTHOR]

E-commerce applications generate and consume a tremendous amount of online information, which is typically available as textual documents. Conceivably, organizations and individuals generally use category sets or hierarchies to organize, archive, and access their documents. Meanwhile, organizations and individuals constantly acquire relevant documents from various Internet sources, each of which may organize its documents in a category set or hierarchy different from that used by the acquiring organization or individual. Consequently, the integration of source documents organized in a category hierarchy into an existing category hierarchy deployed by the acquiring organization or individual becomes an important issue in the e-commerce era. Existing category-integration techniques are mainly designed to integrate document catalogs, each of which is organized nonhierarchically (i.e., in a flat set). In this paper, we propose a clustering-based category-hierarchy integration (CHI) technique, which is an extension of the clustering-based category- integration (CCI) technique. Our empirical evaluation results show that the proposed CHI technique appears to improve the effectiveness of category-hierarchy integration compared with that attained by nonhierarchical category-integration techniques, particularly in homogeneous and comparable scenarios. [ABSTRACT FROM AUTHOR]

Similarity searching often reduces to finding the κ nearest neighbors to a query object. Finding the κ nearest neighbors is achieved by applying either a depth-first or a best-first algorithm to the search hierarchy containing the data. These algorithms are generally applicable to any index based on hierarchical clustering. The idea is that the data is partitioned into clusters that are aggregated to form other clusters, with the total aggregation being represented as a tree. These algorithms have traditionally used a lower bound corresponding to the minimum distance at which a nearest neighbor can be found (termed MINDIST) to prune the search process by avoiding the processing of some of the clusters, as well as individual objects when they can be shown lobe farther from the query object q than all of the current κ nearest neighbors of q. An alternative pruning technique that uses an upper bound corresponding to the maximum possible distance at which a nearest neighbor is guaranteed to be found (termed MAXNEARESTDIST) is described. The MAXNEARESTDIST upper bound is adapted to enable its use for finding the κ nearest neighbors instead of just the nearest neighbor (that is, κ = 1) as in its previous uses. Both the depth-first and best-first κ-nearest neighbor algorithms are modified to use MAXNEARESTDIST, which is shown to enhance both algorithms by overcoming their shortcomings. In particular, for the depth-first algorithm, the number of clusters in the search hierarchy that must be examined is not increased thereby potentially lowering its execution time, while for the best-first algorithm, the number of clusters in the search hierarchy that must be retained in the priority queue used to control the ordering of processing of the clusters is also not increased, thereby potentially lowering its storage requirements. [ABSTRACT FROM AUTHOR]

Table-driven routing algorithms in flat networks have the scalability problem due to the need for global topology updates. To reduce update cost, networks are hierarchically organized. Clustering algorithms organize flat networks into hierarchical networks. One important problem, which has not been adequately addressed so far, is to evaluate how good a clustering algorithm is. In other words, it is useful to know what the desired properties of hierarchical networks are. In this paper, we address this issue by considering the routing update cost, which can be measured by the total routing table size and the variance of cluster size distribution. We provide a set of desired properties of clustering algorithms. Applying these properties to the cluster structure generated by an algorithm, we can determine how good a clustering algorithm is. Specifically, we discuss how to choose appropriate number of hierarchy levels, number of clusters, and cluster size distribution, such that the topology update cost is minimized. The desired properties obtained from the analysis can be used as guidelines in the design of clustering algorithms for table-driven hierarchical networks. We apply the idea developed in this paper to evaluate three routing algorithms, namely the lowest ID algorithm, the maximum degree algorithm, and the variable degree clustering algorithm. We show how the variable degree clustering algorithm, which takes into account these desired properties, improves routing performance. [ABSTRACT FROM AUTHOR]

We present VisLink, a method by which visualizations and the relationships between them can be interactively explored. VisLink readily generalizes to support multiple visualizations, empowers inter-representational queries, and enables the reuse of the spatial variables, thus supporting efficient information encoding and providing for powerful visualization bridging. Our approach uses multiple 2D layouts, drawing each one in its own plane. These planes can then be placed and re-positioned in 3D space: side by side, in parallel, or in chosen placements that provide favoured views. Relationships, connections, and patterns between visualizations can be revealed and explored using a variety of interaction techniques including spreading activation and search filters. [ABSTRACT FROM AUTHOR]

A recurrent neural network for the optimal control of a group of interconnected dynamic systems is presented in this paper. On the basis of decomposition and coordination strategy for interconnected dynamic systems, the proposed neural network has a two-level hierarchical structure: several local optimization subnetworks at the lower level and one coordination subnetwork at the upper level. A goal-coordination method is used to coordinate the interactions between the subsystems. By nesting the dynamic equations of the subsystems into their corresponding local optimization subnetworks, the number of dimensions of the neural network can be reduced significantly. Furthermore, the subnetworks at both the lower and upper levels can work concurrently. Therefore, the computation efficiency, in comparison with the consecutive executions of numerical algorithms on digital computers, is increased dramatically. The proposed method is extended to the case where the control inputs of the subsystems are bounded. The stability analysis shows that the proposed neural network is asymptotically stable. Finally, an example is presented which demonstrates the satisfactory performance of the neural network. [ABSTRACT FROM AUTHOR]

Temporal sequence learning is one of the most critical components for human intelligence. In this paper, a novel hierarchical structure for complex temporal sequence learning is proposed. Hierarchical organization, a prediction mechanism, and one-shot learning characterize the model. In the lowest level of the hierarchy, we use a modified Hebbian learning mechanism for pattern recognition. Our model employs both active 0 and active 1 sensory inputs. A winner-take-all (WTA) mechanism is used to select active neurons that become the input for sequence learning at higher hierarchical levels. Prediction is an essential element of our temporal sequence learning model. By correct prediction, the machine indicates it knows the current sequence and does not require additional learning. When the prediction is incorrect, one-shot learning is executed and the machine learns the new input sequence as soon as the sequence is completed. A four-level hierarchical structure that isolates letters, words, sentences, and strophes is used in this paper to illustrate the model. [ABSTRACT FROM AUTHOR]

We introduce the notion of the medial scaffold, a hierarchical organization of the medial axis of a 3D shape in the form of a graph constructed from special medial curves connecting special medial points. A key advantage of the scaffold is that it captures the qualitative aspects of shape in a hierarchical and tightly condensed representation. We propose an efficient and exact method for computing the medial scaffold based on a notion of propagation along the scaffold itself, starting from initial sources of the flow and constructing the scaffold during the propagation. We examine this method specifically in the context of an unorganized cloud of points in 3D, e.g., as obtained from laser range finders, which typically involve hundreds of thousands of points, but the ideas are generalizable to data arising from geometrically described surface patches. The computational bottleneck in the propagation-based scheme is in finding the initial sources of the flow. We thus present several ideas to avoid the unnecessary consideration of pairs of points which cannot possibly form a medial point source, such as the "visibility" of a point from another given a third point and the interaction of clusters of points. An application of using the medial scaffold for the representation of point samplings of real-life objects is also illustrated. [ABSTRACT FROM AUTHOR]

Obtaining ground truth for classification of remotely sensed data is time consuming and expensive, resulting in poorly represented signatures over large areas. In addition, the spectral signatures of a given class vary with location and/or time. Therefore, successful adaptation of a classifier designed from the available labeled data to classify new hyperspectral images acquired over other geographic locations or subsequent times is difficult, if minimal additional labeled data are available. In this paper, the binary hierarchical classifier is used to propose a knowledge transfer framework that leverages the information extracted from the existing labeled data to classify spatially separate and multitemporal test data. Experimental results show that in the absence of any labeled data in the new area, the approach is better than a direct application of the original classifier on the new data. Moreover, when small amounts of the labeled data are available from the new area, the framework offers further improvements through semisupervised learning mechanisms and compares favorably with previously proposed methods. [ABSTRACT FROM AUTHOR]

A compound graph is a frequently encountered type of data set. Relations are given between items, and a hierarchy is defined on the items as well. We present a new method for visualizing such compound graphs. Our approach is based on visually bundling the adjacency edges, i.e., non-hierarchical edges, together. We realize this as follows. We assume that the hierarchy is shown via a standard tree visualization method. Next, we bend each adjacency edge, modeled as a B-spline curve, toward the polyline defined by the path via the inclusion edges from one node to another. This hierarchical bundling reduces visual clutter and also visualizes implicit adjacency edges between parent nodes that are the result of explicit adjacency edges between their respective child nodes. Furthermore, hierarchical edge bundling is a generic method which can be used in conjunction with existing tree visualization techniques. We illustrate our technique by providing example visualizations and discuss the results based on an informal evaluation provided by potential users of such visualizations. [ABSTRACT FROM AUTHOR]

The article examines the emerging designs for hierarchical Web sites. Hierarchies are considered to be a natural way of organizing, presenting, or navigating online information. Often times, users feel frustrated when they are not satisfied with the result of their information-seeking process. On the other hand, designers have developed variants and designs for users to get the desired information quickly. According to the author, hierarchical Web sites should include three features such as flexible navigation orders, ability to expose and explore dependencies, and support for procedural tasks.

The real-time display of huge geometry and imagery databases involves view-dependent approximations, typically through the use of precomputed hierarchies that are selectively refined at runtime. A classic motivating problem is terrain visualization in which planetary databases involving billions of elevation and color values are displayed on PC graphics hardware at high frame rates. This paper introduces a new diamond data structure for the basic selective-refinement processing, which is a streamlined method of representing the well-known hierarchies of right triangles that have enjoyed much success in real-time, view-dependent terrain display. Regular-grid tiles are proposed as the payload data per diamond for both geometry and texture. The use of 4–8 grid refinement and coarsening schemes allows level-of-detail transitions that are twice as gradual as traditional quadtree-based hierarchies, as well as very high-quality low-pass filtering compared to subsampling-based hierarchies. An out-of-core storage organization is introduced based on Sierpinski indices per diamond, along with a tile preprocessing framework based on fine-to-coarse, same-level, and coarse- to-fine gathering operations. To attain optimal frame-to-frame coherence and processing-order priorities, dual split and merge queues are developed similar to the Realtime Optimally Adapting Meshes (ROAM) Algorithm, as well as an adaptation of the ROAM frustum culling technique. Example applications of lake-detection and procedural terrain generation demonstrate the flexibility of the tile processing framework. [ABSTRACT FROM AUTHOR]

Along Petri nets' history, numerous approaches have been proposed that try to manage model size through the introduction of structuring mechanisms allowing hierarchical representations and model composability. This paper proposes a classification system for Petri nets' structuring mechanisms and discusses each one of them. These include node fusion, node vectors, high-level nets, and object-oriented inspired Petri nets extensions, among others. One running example is used emphasizing the application of the presented mechanisms to specific areas, namely to automation systems modeling, and software engineering, where object-oriented modeling plays a major role. [ABSTRACT FROM PUBLISHER]

Describes an approach based on evolutionary algorithms, hierarchical decision rules (HIDER), for learning rules in continuous and discrete domains. Pseudocode of HIDER; Parameters of HIDER; Number of databases for which the method improves HIDER.

Presents information on a study which determined the weight hierarchies of some product codes. Methodology of the study; Results and discussion on the study.

Presents a hierarchical color clustering obtained by a color feature for image processing. Description of a set of filtering methods; Information on the similarity measurement with color features; Comparison of image retrieval with different color quantization schemes.

Presents an analytical model for designing memory hierarchies. Previous work on memory hierarchies; Performance comparisons for the processor-cache hierarchy; Cost and speed of available technologies; Simulation of storage hierarchy.

The content community, which arises from the Internet's unique communication characteristics, contrasts in significant ways with territorial communities. [ABSTRACT FROM PUBLISHER]

Space-filling layout techniques for tree representations are frequently used when the available screen space is small or the data set is large. In this paper, we propose an efficient approach to space-filling tree representations that uses mechanisms from the point-based rendering paradigm. We present helpful interaction techniques and visual cues that tie in with our layout. Additionally, we relate this new layout approach to common layout mechanisms and evaluate the new layout along the lines of a numerical evaluation using the measures of the Ink-Paper Ratio and overplotted%, and in a preliminary user study. The flexibility of the general approach is illustrated by several enhancements of the basic layout, as well as its usage within the context of two software frameworks from different application fields. [ABSTRACT FROM AUTHOR]