ppxscal/embedding_network huggingface dataset:
Design of a braille writing tutor to combat illiteracy
Authors: N. Kalra, T. Lauwers, D. Dewey, T. Stepleton, M. B. Dias
Venue: Information Systems Frontiers (2009)

Less than 3% of the 145 million blind people living in developing countries are literate (Helander, Prejudice and dignity: An introduction to community-based rehabilitation. New York: UNDP 1998). This low literacy rate is partly due to the lack of trained teachers and the challenges associated with learning to write braille on a traditional slate and stylus. These challenges include writing from right to left, writing mirrored images of letters, and receiving significantly delayed feedback. Extensive conversations with the Mathru Educational Trust for the Blind near Bangalore, India, revealed the need for a robust, low-power, low-cost braille writing tutor. We present an iterative and participatory process resulting in the creation and refinement of a prototype braille writing tutor system. This system uses a novel input device to capture a student's activity on a slate using a stylus and uses a range of techniques to teach braille writing skills to both beginner and advanced students. We report on lessons learned from the implementation of this project and from a 6-week pilot study at Mathru, and outline future directions for improvement.
Measuring non-linear dependence for two random variables distributed along a curve
Authors: Pedro Delicado, Marcelo Smrekar
Venue: Statistics and Computing (2009)

We propose new dependence measures for two real random variables not necessarily linearly related. Covariance and linear correlation are expressed in terms of principal components and are generalized for variables distributed along a curve. Properties of these measures are discussed. The new measures are estimated using principal curves and are computed for simulated and real data sets. Finally, we present several statistical applications for the new dependence measures.
Predictive models for emission of hydrogen powered car using various artificial intelligent tools
Authors: Vishy Karri, Tien Nhut Ho
Venue: Neural Computing and Applications (2009)

This paper investigates the use of artificial intelligent models as virtual sensors to predict relevant emissions such as carbon dioxide, carbon monoxide, unburnt hydrocarbons and oxides of nitrogen for a hydrogen powered car. The virtual sensors are developed by means of application of various Artificial Intelligent (AI) models namely; AI software built at the University of Tasmania, back-propagation neural networks with Levenberg&#x2013;Marquardt algorithm, and adaptive neuro-fuzzy inference systems. These predictions are based on the study of qualitative and quantitative effects of engine process parameters such as mass airflow, engine speed, air-to-fuel ratio, exhaust gas temperature and engine power on the harmful exhaust gas emissions. All AI models show good predictive capability in estimating the emissions. However, excellent accuracy is achieved when using back-propagation neural networks with Levenberg&#x2013;Marquardt algorithm in estimating emissions for various hydrogen engine operating conditions with the predicted values less than 6% of percentage average root mean square error.
Theory and Implementation on Automatic Adaptive Metadata Generation for Image Retrieval
Authors: Hideyasu Sasaki, Yasushi Kiyoki
Venue: Proceeding of the 2006 conference on Information Modelling and Knowledge Bases XVII (2006)

In this paper, we present the detailed theory and implementation on an automatic adaptive metadata generation system using content analysis of sample images with a variety of experimental results. Instead of costly human-created metadata, our method ranks sample images by distance computation on their structural similarity to query images, and automatically generates metadata as textual labels that represent geometric structural properties of the most similar sample images to the query images. First, our system screens out improper query images for metadata generation by using CBIR that computes structural similarity between sample images and query images. We have realized automatic selection of proper threshold-values in the screening module. Second, the system generates metadata by selecting sample indexes attached to the sample images that are structurally similar to query images. Third, the system detects improper metadata and re-generates proper metadata by identifying wrongly selected metadata. Our system has improved metadata generation by 23.5% on recall ratio and 37% on fallout ratio rather than just using the results of content analysis even with more practical experimental figures. Our system has its extensibility to the various types of specific object domains with inclusion of computer vision techniques.
Experimental study of large-scale computing on virtualized resources
Authors: Juan C. Martinez, Lixi Wang, Ming Zhao, S. Masoud Sadjadi
Venue: Proceedings of the 3rd international workshop on Virtualization technologies in distributed computing (2009)

Parallel applications have a pressing need for the utilization of more and more resources to meet user's performance expectations. Unfortunately, these resources are not necessarily available within one single domain. Grid computing provides a solution to scaling out from a single domain; however, it also brings another problem for some applications: resource heterogeneity. Since some applications require having homogeneous resources for their execution, virtualizing the resources is a noble and viable solution. In this paper, we present two parallel applications, namely WRF and mpiBLAST and report the results of different runs scaling them out from 2 to 128 virtual nodes. Later, we analyze the effects of scaling out based on the application's communication behavior.
Autonomic virtual resource management for service hosting platforms
Authors: Hien Nguyen Van, Frederic Dang Tran, Jean-Marc Menaud
Venue: Proceedings of the 2009 ICSE Workshop on Software Engineering Challenges of Cloud Computing (2009)

Cloud platforms host several independent applications on a shared resource pool with the ability to allocate computing power to applications on a per-demand basis. The use of server virtualization techniques for such platforms provide great flexibility with the ability to consolidate several virtual machines on the same physical server, to resize a virtual machine capacity and to migrate virtual machine across physical servers. A key challenge for cloud providers is to automate the management of virtual servers while taking into account both high-level QoS requirements of hosted applications and resource management costs. This paper proposes an autonomic resource manager to control the virtualized environment which decouples the provisioning of resources from the dynamic placement of virtual machines. This manager aims to optimize a global utility function which integrates both the degree of SLA fulfillment and the operating costs. We resort to a Constraint Programming approach to formulate and solve the optimization problem. Results obtained through simulations validate our approach.
Large-scale communication network behavior analysis and feature extraction using multiple motif pattern association rule mining
Authors: Weisong He, Guangmin Hu, Xingmiao Yao
Venue: WSEAS TRANSACTIONS on COMMUNICATIONS (2009)

Minimize false positive and false negative is one of the difficult problems of network behavior analysis. This paper propose a large-scale communications network behavior feature analysis method using multiple motif pattern association rule mining, analyze multiple behavior feature time series as a whole, produce valid association rules of abnormal network behavior feature, characterize the entire communication network security situation accurately. Experiment with Abilene network data verifies this method.
Applying Semantic Social Graphs to Disambiguate Identity References
Authors: Matthew Rowe
Venue: Proceedings of the 6th European Semantic Web Conference on The Semantic Web: Research and Applications (2009)

Person disambiguation monitors web appearances of a person by disambiguating information belonging to different people sharing the same name. In this paper we extend person disambiguation to incorporate the abstract notion of identity. This extension utilises semantic web technologies to represent the identity of the person to be found and the web resources to be disambiguated as semantic graphs. Our approach extracts a complete semantic social graph from distributed Web 2.0 services. Web resources containing possible person references are converted into semantic graphs describing available identity features. We disambiguate these web resources to identify correct identity references by performing random walks through the graph space, measuring the distances between the social graph and web resource graphs, and clustering similar web resources. We present a new distance measure called "Optimum Transitions" and evaluate the accuracy of our approach using the information retrieval measure f-measure. The ACM Portal is published by the Association for Computing Machinery. Copyright © 2010 ACM, Inc. Terms of Usage Privacy Policy Code of Ethics Contact Us Useful downloads: Adobe Acrobat QuickTime Windows Media Player Real Player
New proofs of (new) direct product theorems
Authors: Russell Impagliazzo
Venue:  (2008)

In this Dissertation we give an alternate proof of the well known Direct Product Theorem which in contrast to the previous proofs, achieves optimal values for the related parameters. We also obtain a stronger version of the Direct Product Theorem which is motivated by some interesting applications in Cryptography.Direct Product Theorems are formal statements of the intuition: "if solving one instance of a problem is hard, then solving multiple instances is even harder". For example, a Direct Product Theorem with respect to bounded size circuits computing a function is a statement of the form: "if a function f is hard to compute on average for small size circuits, then fk(x1, ..., x k) =def f(x1), ..., f(xk) is even harder on average for certain smaller size circuits". The proof of the such a statement is by contradiction, that is, we start with a circuit which computes fk on some non-negligible fraction of the inputs and then use this circuit to construct another circuit which computes f on almost all inputs. By viewing such a constructive proof as decoding certain error-correcting code, it was independently observed by Trevisan [Tre03] and Impagliazzo [Imp02] that constructing a single circuit is not possible in general. Instead, we can only hope to construct a list of circuits such that one of them computes f on almost all inputs. This makes the list size an important parameter of the Theorem which can be minimized. In a sequence of results [IJK06] and [IJKW08], we achieve optimal value of the list size which is a substantial improvement compared to previous proofs of the Theorem. In particular, this new version can be applied to uniform models of computation (e.g. randomized algorithms) whereas all previous versions applied only to nonuniform models (e.g. circuits). This proof is presented in Chapter III. Consider the following stronger and a more general version of the previous Direct Product Theorem statement: "if a problem is hard to solve on average, then solving more than the expected fraction of problem instances from a pool of multiple independently chosen instances becomes even harder". Such statements are useful in cryptographic settings where the goal is to amplify the gap between the ability of legitimate users to solve a type of problem and that of attackers. We call such statements "Chernoff-type Direct Product Theorems" and prove such a statement for a very general setting in [IJK07]. This is presented in Chapter V.
e-Collaboration Platform for Metal Forming Enterprises based on the Semantic Web Technologies
Authors: Łukasz Rauch, Maciej Pietrzyk
Venue: Proceeding of the 2006 conference on Leading the Web in Concurrent Engineering: Next Generation Concurrent Engineering (2006)

Structured communication between trading partners is crucial in everyday business life. A lot of solutions of this problem exist, allowing application to application (A2A), human to application (H2A) and human to human (H2H) communication. Such formalized exchange of information is, in most cases, based on the XML language structures, standardized by different organizations e.g. OASIS, RosettaNet. However, the content of these structures should also be recognized properly, thus it has to originate from specific ontology. Unfortunately, the lack of ontologies dedicated for various business activities often impede creation of efficient trading communication. Idea of the e-Collaboration platform, which combines various innovative technologies, allowing business processes description and ontology-based exchange of information, is presented in this paper. The proposed solution is dedicated for companies trading in Metal Forming branch. The example of such trading activities, based on material tests and determination of material rheological properties, is described in the following sections as well.
Survivability approaches using p-cycles in WDM mesh networks under static traffic
Authors: Abdelhamid E. Eshoul, Hussein T. Mouftah
Venue: IEEE/ACM Transactions on Networking (TON) (2009)

The major challenge in survivable mesh networks is the design of resource allocation algorithms that allocate network resources efficiently while at the same time are able to recover from a failure quickly. This issue is particularly more challenging in optical networks operating under wavelength continuity constraint, where the same wavelength must be assigned on all links in the selected path. This paper proposes two approaches to solve the survivable routing and wavelength assignment RWA problem under static traffic using p-cycles techniques. The first is a nonjointly approach, where the minimum backup capacity against any single span failure is set up first. Then the working lightpaths problem is solved by first generating the most likely candidate routes for each source and destination s-d pair. These candidate routes are then used to formulate the overall problem as an ILP problem. Alternatively, for a more optimum solution, the problem can be solved jointly, where the working routes and the backup p-cycles are jointly formulated as an ILP problem to minimize the total capacity required. Furthermore, only a subset of high merit cycles that are most likely able to protect the proposed working paths is used in the formulation. Reducing the number of candidate cycles in the final formulation plays a significant role in reducing the number of variables required to solve the problem. To reduce the number of candidate cycles in the formulation, a new metric called Route Sensitive Efficiency (RSE)--has been introduced to pre-select a reduced number of high merit cycle candidates. The RSE ranks each cycle based on the number of links of the primary candidate routes that it can protect. The two approaches were tested and their performances were compared.
Semantic mining of networks with scale free structure
Authors: Ameera Jaradat
Venue:  (2008)

Meaning is often derived from context, or an entity's relationship with its neighbors. Extracting meaning from large amounts of data, often, involves identifying groups of entities with certain shared characteristics. From these groupings, the meaning (semantics) of the data is interpreted. In this work, contextual relationships among data are represented as a graph. The entities in the data, i.e. terms in a document, individuals in social groups, or routers on a network, are the vertices of a graph, and the relationships are edges. Then, the connectivity properties of the graph representation of the data are exploited to organize the data into meaningful groups. Specifically, transitivity (a local structural property that measures the cliquishness of the graph in the neighborhood of a specific node) is used to partition the data into groups. The key characteristic is that a vertex with high transitivity tends to belong to the same group as its neighbors, and whereas one with low transitivity tends to bridge groups. The method capitalizes on the scale-free or small world character of complex, real-life systems, in which highly connected individuals provide communication pathways leading to the small-world effect (related to "six degrees of separation"). Moreover, using a binary decision tree, the partitioning is accomplished efficiently, automatically, and without supervision. The method developed here was compared to similar techniques on a variety of data, and was found to produce similar results. The ACM Portal is published by the Association for Computing Machinery. Copyright © 2010 ACM, Inc. Terms of Usage Privacy Policy Code of Ethics Contact Us Useful downloads: Adobe Acrobat QuickTime Windows Media Player Real Player
A Truthful Two-Stage Mechanism for Eliciting Probabilistic Estimates with Unknown Costs
Authors: Athanasios Papakonstantinou, Alex Rogers, Enrico H. Gerding, Nicholas R. Jennings
Venue: Proceeding of the 2008 conference on ECAI 2008: 18th European Conference on Artificial Intelligence (2008)

This paper reports on the design of a novel two-stage mechanism, based on strictly proper scoring rules, that motivates selfish rational agents to make a costly probabilistic estimate or forecast of a specified precision and report it truthfully to a centre. Our mechanism is applied in a setting where the centre is faced with multiple agents, and has no knowledge about their costs. Thus, in the first stage of the mechanism, the centre uses a reverse second price auction to allocate the estimation task to the agent who reveals the lowest cost. While, in the second stage, the centre issues a payment based on a strictly proper scoring rule. When taken together, the two stages motivate agents to reveal their true costs, and then to truthfully reveal their estimate. We prove that this mechanism is incentive compatible and individually rational, and then present empirical results comparing the performance of the well known quadratic, spherical and logarithmic scoring rules. We show that the quadratic and the logarithmic rules result in the centre making the highest and the lowest expected payment to agents respectively. At the same time, however, the payments of the latter rule are unbounded, and thus the spherical rule proves to be the best candidate in this setting.
Object Oriented Simulation: A Modeling and Programming Perspective, 1st edition
Authors: Jos M. Garrido
Venue:  (2009)

Object Oriented Simulation Jos Garrido About this textbook: Object Oriented Simulation will qualify as a valuable resource to students and accomplished professionals and researchers alike, as it provides an extensive, yet comprehensible introduction to the basic principles of object-oriented modeling, design and implementation of simulation models. Key features include an introduction to modern commercial graphical simulation and animation software, accessible breakdown of OOSimL language constructs through various programming principles, and extensive tutorial materials ideal for undergraduate classroom use. Presents a comprehensive introduction to the basic principles of object-oriented modeling, design, and implementation of simulation models. Encourages a stronger foundation with objects and classes using an "objects early" approach. Emphasizes model implementation with minimal treatment of statistics. Accommodates a smooth transition to object-oriented modeling and a gradual introduction to object-oriented simulation for professionals. Provides complete case studies fully explained with corresponding case study in OOSimL. Includes summaries, examples, and problems in every chapter. Simulation software presented in material is available on the books web site. Introduces graphical simulation and animation software Arena and Flexsim. Models described with UML and/or extended simulation diagrams.
Blog categorization exploiting domain dictionary and dynamically estimated domains of unknown words
Authors: Chikara Hashimoto, Sadao Kurohashi
Venue: Proceedings of the 46th Annual Meeting of the Association for Computational Linguistics on Human Language Technologies: Short Papers (2008)

This paper presents an approach to text categorization that i) uses no machine learning and ii) reacts on-the-fly to unknown words. These features are important for categorizing Blog articles, which are updated on a daily basis and filled with newly coined words. We categorize 600 Blog articles into 12 domains. As a result, our categorization method achieved an accuracy of 94.0% (564/600).
What Wearable Augmented Reality Can Do for You
Authors: Bruce H. Thomas, Christian Sandor
Venue: IEEE Pervasive Computing (2009)

This paper focuses on the present and near-future possibilities and technologies for wearable augmented reality. The paper provides an overview of the concept of wearable augmented reality and describes a current state-of-the-art system Tinmith. A number of benefits are presented, such as in situ information presentation, hands-free operation, ability to multitask, and navigation aids. The following five major application domains are examined as a means of highlighting the effectiveness of this technology: consumer help, entertainment, manufacturing, medicine, and navigation. The article provides some insights into technological hurdles yet to be overcome.
Joint degrees in e-learning environments
Authors: Julio R. Ribón, Tomás P. de Miguel, J. Hamiltón Ortíz
Venue: Proceedings of the 2009 Euro American Conference on Telematics and Information Systems: New Opportunities to increase Digital Citizenship (2009)

Information and communication technologies offer a great opportunity for the development of joint degrees between organizations. In these spaces of cooperative knowledge, each organization contributes with their partners providing learning resources that they offer to students and teachers. Each organization manages their resources and students. However, there is a problem. The Learning Management Systems (LMS) that gives support to the development of the joint degrees have not been conceived to allow multiple spaces of cooperation, which is generating technological isolation. One of the reasons is the lack of knowledge of the joint degrees framework in e-learning environments. The purpose of this document is, first to contribute to the solution of the problem, describing a conceptual model that allows understanding of these cooperative spaces. Second, being useful during the design and development of cooperative e-learning activities and finally to serve as a reference for the design of the new LMS and the adaptation of the present ones.
A MAX-SAT Algorithm Portfolio
Authors: Paulo Matos, Jordi Planes, Florian Letombe, João Marques-Silva
Venue: Proceeding of the 2008 conference on ECAI 2008: 18th European Conference on Artificial Intelligence (2008)

The results of the last MaxSAT Evaluations suggest there is no universal best algorithm for solving MaxSAT, as the fastest solver often depends on the type of instance. Having an oracle able to predict the most suitable MaxSAT solver for a given instance would result in the most robust solver. Inspired by the success of SATzilla for SAT, this paper describes the first approach for a portfolio of algorithms for MaxSAT. Compared to existing solvers, the resulting portfolio can achieve significant performance improvements on a representative set of instances.