ppxscal/embedding_network huggingface dataset:
Automated Assessment of Aggregate Query Imprecision in Dynamic Environments
Authors: Vasanth Rajamani, Christine Julien, Jamie Payton
Venue: Proceedings of the 9th IFIP WG 6.1 International Conference on Distributed Applications and Interoperable Systems (2009)

Queries are widely used for acquiring data distributed in opportunistically formed mobile networks. However, when queries are executed in such dynamic settings, the returned result may not be consistent, i.e., it may not accurately reflect the state of the environment. It can thus be difficult to reason about the meaning of a query's result. Reasoning about imperfections in the result becomes even more complex when in-network aggregation is employed, since only a single aggregate value is returned. We define the semantics of aggregate queries in terms of a qualitative description of consistency and a quantitative measure of imprecision. We provide a protocol that performs in-network aggregation while simultaneously generating quality assessments for the query result. The protocol enables intuitive interpretations of the semantics associated with an aggregate query's execution in a dynamic environment.
On the evaluation of recommender systems with recorded interactions
Authors: Romain Robbes
Venue: Proceedings of the 2009 ICSE Workshop on Search-Driven Development-Users, Infrastructure, Tools and Evaluation (2009)

Recommender systems are Integrated Development Environment (IDE) extensions which assist developers in the task of coding. However, since they assist specific aspects of the general activity of programming, their impact is hard to assess. In previous work, we used with success an evaluation strategy using automated benchmarks to automatically and precisely evaluate several recommender systems, based on recording and replaying developer interactions. In this paper, we highlight the challenges we expect to encounter while applying this approach to other recommender systems.
Learning Algorithm of Neural Network using Orthogonal Decomposition Method
Authors: Shigenobu Yamawaki, Lakhmi Jain
Venue: Proceeding of the 2005 conference on Advances in Logic Based Intelligent Systems: Selected Papers of LAPTEC 2005 (2005)

In this paper, we present a new learning algorithm of neural network based on the orthogonal decomposition method (ORT). The main scheme of this algorithm is using the ORT to obtain specially structured subspaces defined by the input-output data. This structure is then exploited in the calculation of the parameter estimation of the neural network. Therefore, the method to obtain the comparatively accurate estimate is introduced without iteration calculations. We show that this algorithm can be applied to successfully identify the nonlinear system in the presence of comparatively loud noise. Results from several simulation studies have been included to the effectiveness of this method.
Series-Parallel Automata and Short Regular Expressions
Authors: Nelma Moreira, Rogério Reis
Venue: Fundamenta Informaticae (2009)

Computing short regular expressions equivalent to a given finite automaton is a hard task. In this work we present a class of acyclic automata for which it is possible to obtain in time O(n$^{2}$ log n) an equivalent regular expression of size O(n). A characterisation of this class is made using properties of the underlying digraphs that correspond to the series-parallel digraphs class. Using this characterisation we present an algorithm for the generation of automata of this class and an enumerative formula for the underlying digraphs with a given number of vertices.
Probabilistic IP prefix authentication (PIPA) for prefix hijacking
Authors: Akmal Khan, Ted "Taekyoung" Kwon, Hyunchul Kim
Venue: Proceedings of the 4th International Conference on Future Internet Technologies (2009)

BGP is the most important component of Internet routing and yet it is vulnerable to many threats such as IP prefix hijacking, which has created significant problems over the decade. There have been two approaches to address the IP prefix hijacking issue: anomaly detection-based approach and cryptography-based one. Due to complexity and deployment concern of the latter, there are a lot of solutions that take the former approach. We propose a probabilistic IP prefix authentication (PIPA) scheme that leverages the existing BGP anomaly detection-based solutions as well as public internet registry information. That is, PIPA determines the authenticity of the pair (IP prefix, AS path) in BGP messages by using historical stability of the BGP information and internet registry data. We also discuss how to recover the hijacked IP prefixes in PIPA.
Active sample selection for named entity transliteration
Authors: Dan Goldwasser, Dan Roth
Venue: Proceedings of the 46th Annual Meeting of the Association for Computational Linguistics on Human Language Technologies: Short Papers (2008)

This paper introduces a new method for identifying named-entity (NE) transliterations within bilingual corpora. Current state-of-the-art approaches usually require annotated data and relevant linguistic knowledge which may not be available for all languages. We show how to effectively train an accurate transliteration classifier using very little data, obtained automatically. To perform this task, we introduce a new active sampling paradigm for guiding and adapting the sample selection process. We also investigate how to improve the classifier by identifying repeated patterns in the training data. We evaluated our approach using English, Russian and Hebrew corpora.
High-Level Concept Detection in Video Using a Region Thesaurus
Authors: Evaggelos Spyrou, Yannis Avrithis
Venue: Proceeding of the 2007 conference on Emerging Artificial Intelligence Applications in Computer Engineering: Real Word AI Systems with Applications in eHealth, HCI, Information Retrieval and Pervasive Technologies (2007)

This work presents an approach on high-level semantic feature detection in video sequences. Keyframes are selected to represent the visual content of the shots. Then, low-level feature extraction is performed on the keyframes and a feature vector including color and texture features is formed. A region thesaurus that contains all the high-level features is constructed using a subtractive clustering method where each feature results as the centroid of a cluster. Then, a model vector that contains the distances from each region type is formed and a SVM detector is trained for each semantic concept. The presented approach is also extended using Latent Semantic Analysis as a further step to exploit co-occurrences of the regiontypes. High-level concepts detected are desert, vegetation, mountain, road, sky and snow within TV news bulletins. Experiments were performed with TRECVID 2005 development data.
Artificial Neural Network and Hidden Space SVM for Fault Detection in Power System
Authors: Qian Wang
Venue: Proceedings of the 6th International Symposium on Neural Networks: Advances in Neural Networks - Part II (2009)

This paper presents an artificial neural network(ANN) and hidden space support vector machines (HSSVMs) approach for locating faults in radial distribution systems. Different from the traditional Fault Section Estimation methods, the proposed approach uses measurements available at the substation, circuit breaker and relay statuses. The data is analyzed using the principal component analysis (PCA) technique and the faults are classified according to the reactances of their path using a combination of HSSVMs classifiers and feedforward neural networks (FFNNs). The extensive numerical experiments performed for location of different kinds of faults of the transmission line have proved very good accuracy of fault location algorithm. The average error of fault location is about 4%. The result proved its effectiveness. 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
Cartesio: A Software Tool for Pre-implant Stent Analyses
Authors: Ciro Indolfi, Mario Cannataro, Pierangelo Veltri, Giuseppe Tradigo
Venue: Proceedings of the 9th International Conference on Computational Science: Part I (2009)

Quantitative angiography has becoming largely used in interventional cardiology thanks to positive outcomes in terms of patients survival indexes and life quality. This technique is based on positioning a medical stent in a laparoscopic intervention to cure coronary stenoses. Patients gain an immediate benefit from such a procedure by avoiding an open-heart surgery procedure. Stent positioning is guided by using contrast liquid and angiographic X-Rays images, which are used to define stent dimensions. Physicians may have difficulties in optimally estimating the stenosis size in order to choose the most appropriate stent mainly because there is no absolute reference on the angiographer screens. In this paper we present an innovative software tool able to assist the physician pre-implant analysis and thus supporting an optimal stent choice. 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 Concurrent Dynamic Logic of Knowledge, Belief and Certainty for Multi-agent Systems
Authors: Lijun Wu, Jinshu Su, Xiangyu Luo, Zhihua Yang, Qingliang Chen
Venue: Proceedings of the 22nd Canadian Conference on Artificial Intelligence: Advances in Artificial Intelligence (2009)

This paper extends the logic of Knowledge, Belief and Certainty from one agent to multi-agent systems, and gives a good combination between logic of knowledge, belief, certainty in multi-agent systems and actions that have concurrent and dynamic properties. Based on it, we present a concurrent dynamic logic of knowledge, belief and certainty for MAS, which is called CDKBC logic. Furthermore, a CDKBC model is given for interpreting this logic. We construct a CDKBC proof system for the logic and show the proof system is sound and complete, and prove the validity problem for the system is EXPTIME-complete.
Analysis of shortest path routing for large multi-hop wireless networks
Authors: Sungoh Kwon, Ness B. Shroff
Venue: IEEE/ACM Transactions on Networking (TON) (2009)

In this paper, we analyze the impact of straight line routing in large homogeneous multi-hop wireless networks. We estimate the nodal load, which is defined as the number of packets served at a node, induced by straight line routing. For a given total offered load on the network, our analysis shows that the nodal load at each node is a function of the node's Voronoi cell, the node's location in the network, and the traffic pattern specified by the source and destination randomness and straight line routing. In the asymptotic regime, we show that each node's probability that the node serves a packet arriving to the network approaches the products of half the length of the Voronoi cell perimeter and the load density function that a packet goes through the node's location. The density function depends on the traffic pattern generated by straight line routing, and determines where the hot spot is created in the network. Hence, contrary to conventional wisdom, straight line routing can balance the load over the network, depending on the traffic patterns.
The Design, Deployment and Evaluation of the AnimalWatch Intelligent Tutoring System
Authors: Paul R. Cohen, Carole R. Beal, Niall M. Adams
Venue: Proceeding of the 2008 conference on ECAI 2008: 18th European Conference on Artificial Intelligence (2008)

Europe and the U.S. both face the challenges of urban schools with low-achieving adolescent learners, many of whom are not proficient in the language of instruction. This paper describes the deployment and evaluation of the AnimalWatch intelligent tutoring system for mathematics in challenging classrooms. Previous studies demonstrated that AnimalWatch benefits 12--14 year-old students in relatively controlled conditions. The current study indicates that the system can help older, very low-achieving students in challenging secondary schools that serve diverse student populations.
An analysis of salmonid rna sequences and implications for salmonid evolution
Authors: Gordon David Brown
Venue:  (2008)

This work addresses two areas of computational biology: automation of sequence processing and an assessment of the evidence for a hypothesized salmonid genome based on an analysis of a set of expressed sequence tags. Three problem areas in sequence processing are addressed in the first half of the work. Chapter 3 describes an accurate technique for trimming of vector, adapter and poly(A) sequence. Chapter 4 suggests methods for verifying the accuracy of assembled mRNA transcripts despite a large number of chimeras in the cDNA clone libraries. Chapter 5 is concerned with the problem of estimating the number of transcripts in a tissue or cDNA library, concluding that computational and statistical techniques are inadequate to estimate the quantity accurately. The hypothesized salmonid genome duplication has been widely accepted since 1984. If it occurred, it should have left evidence in the form of many paralogous pairs of genes, all at approximately the same degree of sequence divergence. To assess this question, several hundred thousand ESTs were assembled into transcripts, compared to each other to find homologs, and the evolutionary distances of the homologs represented as a histogram. Evidence of a single evolutionary event was not seen. The same procedure was applied to Xenopus laevis, which has a well-established recent genome duplication, and Danio rerio, which is known not to have had one. In those cases, the evidence for or against a genome duplication appeared exactly as predicted. The conclusion is that if the salmonid genome duplication occurred, some force altered its evolutionary development subsequently to mask the duplication, but also that a genome duplication is not necessary to explain the observed pattern of homolog distances. 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 low power CMOS voltage reference circuit with sub threshold MOSFETs
Authors: S. Ramasamy, B. Venkataramani, P. Meenatchisundaram
Venue: International Journal of Information and Communication Technology (2009)

In this paper, a novel approach is proposed for the design of low power CMOS band gap reference circuit. In the literature, an inversion technique is proposed to make the voltage reference to be independent of temperature by using parasitic bipolar transistors. In the above technique, this paper proposes the use of MOSFETs operating in sub threshold region for generating a voltage with negative temperature coefficient. The performance of the proposed scheme is studied by implementing the band gap reference circuit for 1.2 V in TSMC035 CMOS process. Studies through Mentorgraphics IC station and Eldo simulator demonstrate that the proposed scheme has a voltage reference with temperature coefficient of less than 50 ppm&#47;&deg;C over the temperature range of &minus;10&deg;C to 120&deg;C. The proposed scheme results in 18 times lesser area and dissipates ten times lower power compared with that using parasitic bipolar transistors. The circuit technique has been validated using both NMOS and PMOS diode connected sub threshold MOSFETs for generating voltages with negative temperature coefficient.
Jxta-Overlay: An interface for efficient peer selection in P2P JXTA-based systems
Authors: Fatos Xhafa, Leonard Barolli, Thanasis Daradoumis, Raúl Fernández, Santi Caballé
Venue: Computer Standards Interfaces (2009)

In this paper we address the problem of the efficient peer selection in P2P distributed platforms. To this end, we have developed a P2P distributed platform using Sun's JXTA technology, which is endowed with resource brokerage strategies to efficiently select peers using four selection models: (a) economic scheduling model; (b) priced-based model; (c) peer-priority selection model; and, (d) random selection model. Next, we have deployed the P2P platform in a real network using nodes of the PlanetLab and have experimentally evaluated the performance of the peer selection models. The P2P platform offers a user-friendly interface for efficient peer selection and configuration of the P2P platform.
Automated analysis of images in documents for intelligent document search
Authors: Xiaonan Lu, Saurabh Kataria, William J. Brouwer, James Z. Wang, Prasenjit Mitra, C. Lee Giles
Venue: International Journal on Document Analysis and Recognition (2009)

Authors use images to present a wide variety of important information in documents. For example, two-dimensional (2-D) plots display important data in scientific publications. Often, end-users seek to extract this data and convert it into a machine-processible form so that the data can be analyzed automatically or compared with other existing data. Existing document data extraction tools are semi-automatic and require users to provide metadata and interactively extract the data. In this paper, we describe a system that extracts data from documents fully automatically, completely eliminating the need for human intervention. The system uses a supervised learning-based algorithm to classify figures in digital documents into five classes: photographs, 2-D plots, 3-D plots, diagrams, and others. Then, an integrated algorithm is used to extract numerical data from data points and lines in the 2-D plot images along with the axes and their labels, the data symbols in the figure&#x2019;s legend and their associated labels. We demonstrate that the proposed system and its component algorithms are effective via an empirical evaluation. Our data extraction system has the potential to be a vital component in high volume digital libraries.
Know-how for motivated BDI agents
Authors: Matthias Thimm, Patrick Krümpelmann
Venue: Proceedings of The 8th International Conference on Autonomous Agents and Multiagent Systems - Volume 2 (2009)

The BDI model is well accepted as an architecture for representing and realizing rational agents. The beliefs in this model are focused on the representation of beliefs about the world and other agents and are widely independent from the agents intentions. We argue that also the representation of know-how, which captures the beliefs about actions and procedures, has to be taken into account when modeling rational agents. Using the notion of know-how as introduced by Singh we formalize and implement a concrete and usable agent architecture that supports and benefits from this representation of procedural beliefs in multiple ways. It also supports the representation of motivations that influence the agent's behavior. We thus enable the agent to reason about its planning capabilities in the same way as it can reason about any other of its beliefs by extending a BDI-based agent architecture to allow the representation of procedural beliefs explicitly as part of the agent's logical beliefs which again influences and enhances the agent's behavior.
Intelligent controllers in HVDC system based on PSO algorithm
Authors: Zhengqiang Song, Ping Zhang, Xiaofa Zhou
Venue: Proceedings of the 9th WSEAS international conference on Robotics, control and manufacturing technology (2009)

In this paper, particle swarm optimization (PSO) algorithm is improved and employed in designing HVDC system's proportional- integral (PI) controller. Feasible region of kp and ki is derived from scanning the kp - ki plane under amplitude and phase margin constraints, and then the search area of PSO algorithm can be identified. Simulation results are implemented on the CIGRE HVDC Benchmark Model as a contrast to the proposed method, which show that the PI controller designed by using the proposed algorithm can satisfy the requirements of stability and dynamic response performance indexes of HVDC transmission system.
Designing a multi-modal affective knowledge-based user interface: combining empirical studies
Authors: Maria Virvou, George Tsihrintzis, Efthymios Alepis, Ioanna-Ourania Stathopoulou
Venue: Proceeding of the 2008 conference on Knowledge-Based Software Engineering: Proceedings of the Eighth Joint Conference on Knowledge-Based Software Engineering (2008)

In this paper, we present and discuss three empirical studies that we have conducted involving human subjects and human observers concerning the recognition of emotions from audio-lingual visual-facial and keyboard-evidence modalities. Many researchers agree that these modalities are complementary to each other and that their combination can improve the accuracy in affective user models. However, there is a shortage of research in empirical work concerning the strengths and weaknesses of each modality so that more accurate recognizers can be built. In our research, we have investigated the recognition of emotions with respect to 6 basic emotional states, namely happiness, sadness, surprise, anger and disgust as well as the emotionless state which we refer to as neutral. We have concluded that, in cases where a single modality may be deficient in providing emotion recognition evidence, the recognition process can be supported and complemented by the other modalities.
Establishing and maintaining traceability between large aerospace process standards
Authors: Ove Armbrust, Alexis Ocampo, Jurgen Munch, Masafumi Katahira, Yumi Koishi, Yuko Miyamoto
Venue: Proceedings of the 2009 ICSE Workshop on Traceability in Emerging Forms of Software Engineering (2009)

The aerospace domain is known for its emphasis on product quality, since hardware or software failures may have potentially catastrophic consequences. Therefore, numerous standards govern space software development. In this paper, we present an approach for systematically establishing and maintaining traceability between software development standards. It augments the standards' word processing files with additional meta-information, thereby making them accessible and understandable for programs, so that a database can be used for advanced analyses. Additionally, we present experience collected during application of the approach at the European Space Agency (ESA) and the Japan Aerospace Exploration Agency (JAXA).
Mathematical application for departure model
Authors: Jan Krcal, Ivan Nagy, Michal Jerabek
Venue: Proceedings of the 2009 Euro American Conference on Telematics and Information Systems: New Opportunities to increase Digital Citizenship (2009)

In the light of today's high traffic volume, it is crucial to anticipate the traffic flow on traffic lights controlled intersections. Without this knowledge, it would be impossible to control the traffic in complicated hubs, such as, for instance, those in Prague. One of the characteristics, through which we can describe dynamics of vehicle movement on traffic lights controlled intersections, is the interval between departure of a vehicle from the space in front of the stop line and the arrival to the actual stop line. This is called a departure model. Our aim is, first, to create an appropriate mathematical application, which would take into account individual variables influencing departure of individual vehicles and determine the dependence among these variables. Second to create such a departure model, which would, on one hand, correspond as much as possible to the contemporary traffic situations, but on the other hand, be more exact for specific intersections.