ppxscal/embedding_network huggingface dataset:
Visual analysis of documents with semantic graphs
Authors: Delia Rusu, Blaž Fortuna, Dunja Mladenić, Marko Grobelnik, Ruben Sipoš
Venue: Proceedings of the ACM SIGKDD Workshop on Visual Analytics and Knowledge Discovery: Integrating Automated Analysis with Interactive Exploration (2009)

In this paper, we present a technique for visual analysis of documents based on the semantic representation of text in the form of a directed graph, referred to as semantic graph. This approach can aid data mining tasks, such as exploratory data analysis, data description and summarization. In order to derive the semantic graph, we take advantage of natural language processing, and carry out a series of operations comprising a pipeline, as follows. Firstly, named entities are identified and co-reference resolution is performed; moreover, pronominal anaphors are resolved for a subset of pronouns. Secondly, subject -- predicate -- object triplets are automatically extracted from the Penn Treebank parse tree obtained for each sentence in the document. The triplets are further enhanced by linking them to their corresponding co-referenced named entity, as well as attaching the associated WordNet synset, where available. Thus we obtain a semantic directed graph composed of connected triplets. The document's semantic graph is a starting point for automatically generating the document summary. The model for summary generation is obtained by machine learning, where the features are extracted from the semantic graph structure and content. The summary also has an associated semantic representation. The size of the semantic graph, as well as the summary length can be manually adjusted for an enhanced visual analysis. We also show how to employ the proposed technique for the Visual Analytics challenge.
What's on Users' Minds? Toward a Usable Smart Phone Security Model
Authors: Alessandra Toninelli, Rebecca Montanari, Ora Lassila, Deepali Khushraj
Venue: IEEE Pervasive Computing (2009)

Smart phones pose new challenges to usable security. Current means of specifying security policies or preferences for resource sharing are either woefully inadequate or too hard to use. This article presents a policy model approach toward usable security for smart phones. In particular, the approach adopts a semantic-based policy representation to help users' understanding of security policies and to better reflect what users really want. Furthermore, given the special nature of smart phones' usage, social awareness plays an important role. In this regard, the authors present propose a socially-aware policy reasoning model based on the results of a user study.
Enhancing photographs using content-specific image priors
Authors: David J. Kriegman
Venue:  (2008)

The digital imaging revolution has made the camera ubiquitous; however, image quality has not improved at the same rate as the increase in camera availability. Increasingly more cameras are small, with inexpensive lenses, no flash, and lightweight bodies that are difficult to hold steady, and this results in images with blur, noise, and poor color-balance. Consequently, there is a strong need for simple, automatic, and accurate methods for image correction. This dissertation, presents work that uses "content-specific" image models and priors for image enhancement.Image enhancement is a challenge problem&mdash;corrections such as deblurring, denoising, and color-correction are ill-posed, where the number of unknown values outweighs the number of observations. As a result, it is necessary to add additional information as constraints. Previous work has focused on using generic image priors that are applicable to a large number of images. In this work, we develop constraints that are tuned to the specific content of an image.First, we discuss a fast, accurate blur estimation method that models all edges in a sharp image as step-edges. The method predicts the "sharp" version of a blurry input image and uses the two images together to solve for a PSF. Second, we discuss a framework for image deblurring and denoising that uses local color statistics to produce sharp, low-noise results. Even when the blur function is known, deblurring an image is still quite difficult due to information loss during blurring and due to the presence of noise. In our work, we investigate using local-color statistics of an image in a joint framework for deblurring and denoising of images.Lastly, we discuss work in methods that use "identity-specific" priors to perform corrections for images containing faces. These priors provide the guidance needed to perform high-quality corrections needed for known, familiar faces. Deblurring, super-resolution, color-balancing, and exposure correction operate independently, so that a user can correct selected image properties, while still retaining certain desired qualities of the original photo. We have also developed a prototype application for performing these corrections.
An analysis of social support exchanges in online HIV/AIDS self-help groups
Authors: Constantinos K. Coursaris, Ming Liu
Venue: Computers in Human Behavior (2009)

Hundreds of thousands of people sharing concerns about HIV/AIDS have taken advantage of online self-help groups to exchange resources and support. Little research so far has focused on the nature and content of actual messages exchanged by group members. To provide an in-depth understanding of social support exchanges in online HIV/AIDS self-help groups, this study identifies and analyzes the dimensions and corresponding frequencies of exchanged social support as well as the group interactions facilitating those exchanges. A total of 5000 postings created within a 1year period were randomly selected from a selected online HIV/AIDS forum. Content analysis was then conducted to assess the types and proportions of exchanged social support. A thematic analysis of the postings that could not be categorized with the adopted coding system was performed to find further patterns of positive group interactions. The results show that information support (41.6%) and emotional support (16.0%) were exchanged most frequently, followed by network support (6.8%) and esteem support exchanges (6.4%), whereas tangible assistance was quite rare (0.8%). The authors also suggest that three types of group interactions including sharing personal experience, expression of gratitude, and offering congratulations can facilitate social support exchanges among group members.
Asynchronous view maintenance for VLSD databases
Authors: Parag Agrawal, Adam Silberstein, Brian F. Cooper, Utkarsh Srivastava, Raghu Ramakrishnan
Venue: Proceedings of the 35th SIGMOD international conference on Management of data (2009)

The query models of the recent generation of very large scale distributed (VLSD) shared-nothing data storage systems, including our own PNUTS and others (e.g. BigTable, Dynamo, Cassandra, etc.) are intentionally simple, focusing on simple lookups and scans and trading query expressiveness for massive scale. Indexes and views can expand the query expressiveness of such systems by materializing more complex access paths and query results. In this paper, we examine mechanisms to implement indexes and views in a massive scale distributed database. For web applications, minimizing update latencies is critical, so we advocate deferring the work of maintaining views and indexes as much as possible. We examine the design space, and conclude that two types of view implementations, called remote view tables (RVTs) and local view tables (LVTs), provide good tradeoff between system throughput and minimizing view staleness. We describe how to construct and maintain such view tables, and how they can be used to implement indexes, group-by-aggregate views, equijoin views and selection views. We also introduce and analyze a consistency model that makes it easier for application developers to cope with the impact of deferred view maintenance. An empirical evaluation quantifies the maintenance costs of our views, and shows that they can significantly improve the cost of evaluating complex queries.
Virtualization of virtual measurement machines as component of distributed artificial intelligence system
Authors: Andrey Angelov Elenkov
Venue: Proceedings of the 8th WSEAS international conference on Artificial intelligence, knowledge engineering and data bases (2009)

The focus of Distributed Artificial Intelligence (DAI) is on the development of systems that emulate the intellectual abilities of a society of human beings. The approach in this paper corresponds to this focus - master, slave, hierarchy, centralized management. A low cost solution for High Availability and Disaster Recovery with hot site recovery strategy in SAN-oriented Virtual Measurement Systems, which are components of DAI System, is presented. It is based on cooperation and interaction between the intelligent agents (IAs). The agency is hierarchic and centralized, separated in branches formed of the IAs. Some of the branches are responsible for the measurements. The Virtual Measurement Machine (VM) is component of the IA. The IAs work as team. Each IA has a role but in case of disaster can play the role of the damaged IA because of implementation of VM live migration as virtualization technology.
Object Categorization Based on Kernel Principal Component Analysis of Visual Words
Authors: Kazuhiro Hotta
Venue: Proceedings of the 2008 IEEE Workshop on Applications of Computer Vision (2008)

In recent years, many researchers are studying object categorization problem. It is reported that bag of keypoints approach which is based on local features without topological information is effective for object categorization. Conventional bag of keypoints approach selects the visual words by clustering and uses the similarity with each visual word as the features for classification. In this paper, we model the ensemble of visual words, and the similarities with ensemble of visual words not each visual word are used for classification. Kernel Principal Component Analysis (KPCA) is used to model them and extract the information specialized for each category. The projection length in subspace is used as features for Support Vector Machine (SVM). There are two reasons why we use KPCA to model the ensemble of visual words. The first reason is to model the non-linear variations induced by various kinds of visual words. The second reason is that KPCA of local features is robust to pose variations. The proposed method is evaluated using Caltech 101 database. We confirm that the proposed method is comparable with the state of the art methods without absolute position information.
Unmanned Aerial Vehicle Localization Based on Monocular Vision and Online Mosaicking
Authors: Fernando Caballero, Luis Merino, Joaquín Ferruz, Aníbal Ollero
Venue: Journal of Intelligent and Robotic Systems (2009)

This paper presents a new approach for vision-based UAV localization, using mosaics as environment representations. Inter-image motions are used to estimate the motion of the UAV. Online mosaicking is applied to reduce the impact of the accumulative errors in UAV position estimation. A new method to build an stochastic mosaic given the image-to-image homographies is detailed. The mosaic consists of a network of inter-image relations, and is used to create a consistent view of the environment of the UAV and hence, to detect the drift in position estimation by using the mosaic as a resource. The technique could be called simultaneous localization and mosaicking. This technique is specially suitable for monitoring and surveillance tasks in which the UAV will repeatedly cover the same area. The paper also shows experimental results with real UAVs where the benefits of the proposed method are evident.
A series solution of the foam drainage equation
Authors: M. T. Darvishi, F. Khani
Venue: Computers Mathematics with Applications (2009)

Foaming occurs in many distillation and absorption processes. The drainage of liquid foams involves the interplay of gravity, surface tension, and viscous forces. In this paper, we apply an analytic technique, namely the homotopy analysis method (HAM) to handle the foam drainage equation. The powerful homotopy analysis method computes the solution in a rapidly convergent infinite series. We also compare the numerical results obtained by HPM or ADM and the same results obtained by using the analytic solutions obtained by HAM.
Evaluating hybrid constraint tightening for scheduling agents
Authors: James C. Boerkoel,  Jr., Edmund H. Durfee
Venue: Proceedings of The 8th International Conference on Autonomous Agents and Multiagent Systems - Volume 1 (2009)

Hybrid Scheduling Problems (HSPs) combine temporal and finite-domain variables via hybrid constraints that dictate that specific bounds on temporal constraints rely on assignments to finite-domain variables. Hybrid constraint tightening (HCT) reformulates hybrid constraints to apply the tightest consistent temporal bound possible, assisting in search space pruning. The contribution of this paper is to empirically evaluate the HCT approach using a state-of-the-art Satisfiability Modulo Theory solver on realistic, interesting problems related to developing scheduling agents to assist people with cognitive impairments. We demonstrate that HCT leads to orders of magnitude reduction of search complexity. The success of HCT is enhanced as we apply HCT to hybrid constraints involving increasing numbers of finite-domain variables and finite-domains with increasing size, as well as hybrid constraints expressing increasing temporal precision. We show that while HCT reduces search complexity for all but the simplest problems, the relative effectiveness is dampened on problems with partially conditional temporal constraints and hybrid constraints with increasing temporal disjunctions. Finally, we present our preliminary investigations that indicate that HCT can assist in increasing communication efficacy in a multiagent setting.
Multiple planes based registration using 3D Projective Space for Augmented Reality
Authors: Yuko Uematsu, Hideo Saito
Venue: Image and Vision Computing (2009)

We propose a vision-based registration method for Augmented Reality (AR) that uses real scenes containing multiple planar structures. Our method provides users with an enhanced view of a real scene by overlaying computer-generated virtual objects onto images captured with a movable camera. The virtual objects are associated with a 3D planar structure and appeared to move with that structure. To align the coordinates of the virtual objects with the coordinates of the images captured with the camera, the camera's motion should be estimated for every frame by tracking and integrating the multiple planes. In contrast with related work, the proposed method does not require a priori knowledge about the geometrical relationships among the multiple planes because the geometrical relationship is automatically estimated by ''Projective Space''. This space is 3D and is defined by projective reconstruction of two reference images. Automatic estimation using the Projective Space can eliminate the time-consuming task of measuring the planes and the constraints of plane arrangement, e.g. only vertical or co-planar. Therefore, the proposed method can be applied even to complicated multi-planar scenes.
Interdependency Analysis of Infrastructures
Authors: Zijun Mao, Liu Hong, Qi Fei, Ming Ouyang
Venue: Proceedings of the 6th International Symposium on Neural Networks: Advances in Neural Networks - Part III (2009)

Electric power, potable water, telecommunications, natural gas, and transportation are examples of critical infrastructures, the intrinsic feature of which are suitable for network analysis. This paper proposes a method framework based on the complex network to explore the interdependency of these infrastructures. We describe the topological characterization of two interdependent small-sized real networks, based on which the interdependent model is devised. We define the interdependent factor to characterize the direct interdependency of two infrastructures, and also its fluctuation in the situations of random removal and targeted removal on the electric and water infrastructures is studied. Furthermore we propose a matrix M to reflect all direct and indirect interactions among infrastructures, which also makes contributions to the understanding of infrastructures catastrophes.
The graphlet spectrum
Authors: Risi Kondor, Nino Shervashidze, Karsten M. Borgwardt
Venue: Proceedings of the 26th Annual International Conference on Machine Learning (2009)

Current graph kernels suffer from two limitations: graph kernels based on counting particular types of subgraphs ignore the relative position of these subgraphs to each other, while graph kernels based on algebraic methods are limited to graphs without node labels. In this paper we present the graphlet spectrum, a system of graph invariants derived by means of group representation theory that capture information about the number as well as the position of labeled subgraphs in a given graph. In our experimental evaluation the graphlet spectrum outperforms state-of-the-art graph kernels.
Increasing children's social competence through games, an exploratory study
Authors: Koen Hendrix, Robert van Herk, Janneke Verhaegh, Panos Markopoulos
Venue: Proceedings of the 8th International Conference on Interaction Design and Children (2009)

We describe the design and evaluation of Playground Architect, a multi-player game designed to help shy children gain social confidence. The game is played by a small group of children around an interactive tabletop surface using a tangible user interface. The game was evaluated with 32 children (mean age 9.5). All players enjoyed the game. Shy children enjoyed being in charge and were quite talkative during play. Interviews with teachers show that some shy children behaved notably more outgoing. These results illustrate the potential of socially educational games.
Robust stability of uncertain discrete impulsive switching systems
Authors: Zhigang Zhang, Xinzhi Liu
Venue: Computers Mathematics with Applications (2009)

This paper studies discrete impulsive switching systems and uncertain linear discrete switching systems. It establishes some stability and robust stability criteria for such systems by using the method of Lyapunov functions and linear matrix inequalities (LMI). These criteria are verifiable by using the LMI toolbox of MATLAB.
A Method of Software Structure Designing Based on Graph Planning
Authors: Mingzhi Mao, Yunfei Jiang, Xiaolong Chai
Venue: Proceeding of the 2007 conference on New Trends in Software Methodologies, Tools and Techniques: Proceedings of the sixth SoMeT_07 (2007)

With the rapid growth in the development of sophisticated modern software, the complexity of the software has increased enormously, posing an urgent need for the automation of the more time-consuming structure designing. In this paper, we proposed SDGP which is an automatic generating method of software structure designing based on the graph planning technique. The method has properties of self-adaptation, finite terminating and complete.
Measuring information volatility in a health care information supply chain
Authors: Monica Chiarini Tremblay, Donald J. Berndt, Alan R. Hevner
Venue: Proceedings of the 4th International Conference on Design Science Research in Information Systems and Technology (2009)

We propose a measure of reliability called information volatility (IV) to complement Business Intelligence tools when considering aggregated data or when observing trends. Two types of information volatility are defined: intra-cell and inter-cell. For each, two types of distributions are considered: normal and lognormal, which is often the case for time series data. The IV measures are based on similar measures found in the finance literature, since there are similarities in the types of data. In order to understand the information volatility metrics, the notion of benchmarking is introduced with three propositions: numerical benchmarking, graphical benchmarking and categorical benchmarking. The IV metric is designed and evaluated using the design science research paradigm: first, the metric is developed and then it is evaluated through the use of focus groups (including several cycles for refinement of the design). The paper concludes with our research contributions and future research directions.
Group-based interface for content-based image retrieval
Authors: Munehiro Nakazato, Ljubomir Manola, Thomas S. Huang
Venue: Proceedings of the working conference on Advanced visual interfaces (2002)

In Content-based Image Retrieval (CBIR) systems, the Query-by-Example (QBE) approach is commonly used. However, because of inevitable "semantic gaps" between visual features and the user's concepts, trial-and-error query is essential for successful retrieval. Unfortunately, traditional user interfaces are not suitable for trying different combinations of query examples. This is because in these systems, query specification and result display are done on the same workspace. Once the user removes an image from the query examples, the image may disappear from the user interface. In addition, it is difficult to combine the result of different queries. In this paper, we propose a new interface for Content-based image retrieval. In our system, the users can interactively compare different combinations of query examples by dragging and grouping images on the workspace (Query-by-Group.) Because the query results are displayed on another pane, the user can quickly review the results. Combining different queries is also easy. Furthermore, the concept of "image groups" is also applied to annotating and organizing a large number of images. Because the gestural operations of our system is similar to file operations of modern window-based operation systems, users can easily learn to use the system.