ppxscal/embedding_network huggingface dataset:
CORA: Collaborative Opportunistic Recovery Algorithm for loss controlled, delay bounded ad hoc multicast
Authors: Yunjung Yi, Jiejun Kong, Mario Gerla, Joon-Sang Park
Venue: Computer Communications (2008)

In this paper, we present Collaborative Opportunistic Recovery Algorithm (CORA) designed for multicast multimedia applications with low loss as well as latency constraints in ad hoc networks. CORA is an independent service that can run atop any ad hoc multicast routing protocol. The main features of CORA are localized recovery process, deterministic (as opposed to probabilistic) peer-to-peer recovery, and ability to trade off recovery with latency. A key component of CORA is the Cached Packet Distance Vector (CPDV) protocol for local peer-to-peer loss recovery. CPDV finds and retrieves the nearest copy of the missing packet while providing other useful NACK aggregation features. We use simulation experiments to demonstrate the effectiveness of CORA and explore the tradeoffs of CPDV localized recovery benefits versus memory and processor overhead. In a typical simulation experiment with mobile nodes CORA yields up to 99% delivery ratio as compared to 91% delivery ratio by Gossip. This improvement is achieved with negligible overhead.
Luminance Correction in Stereo Correspondence Based Structure from Motion
Authors: Colin Estermann, Walter Stechele, Robert Kutka, Andreas Hutter
Venue: Proceedings of the 2008 Ninth International Workshop on Image Analysis for Multimedia Interactive Services (2008)

This paper addresses disparity estimation from image pairs by error minimization. When taken from a monocular camera pan sequence, those images often suffer from luminance variations, caused by the spatially and temporally separated camera positions. Therefore, here we discuss and analyze an existing correction approach for the block matching algorithm. From the observations made we derive a new approach for illumination correction of local error minimization in disparity space. With its simplicity, this multiple disparity space prescaling not only provides the high speed needed for mobile devices, but also decreases the number of false matches by an a priori restriction of correction values.
Pruning Relations for Substructure Discovery of Multi-relational Databases
Authors: Hongyu Guo, Herna L. Viktor, Eric Paquet
Venue: Proceedings of the 11th European conference on Principles and Practice of Knowledge Discovery in Databases (2007)

Multirelational data mining methods discover patterns across multiple interlinked tables (relations) in a relational database. In many large organizations, such a multi-relational database spans numerous departments and/or subdivisions, which are involved in different aspects of the enterprise such as customer profiling, fraud detection, inventory management, financial management, and so on. When considering multirelational classification, it follows that these subdivisions will express different interests in the data, leading to the need to explore various subsets of relevant relations with high utility with respect to the target class. The paper presents a novel approach for pruning the uninteresting relations of a relational database where relations come from such different parties and spans many classification tasks. We aim to create a pruned structure and thus minimize predictive performance loss on the final classification model. Our method identifies a set of strongly uncorrelated subgraphs to use for training and discards all others. The experiments performed demonstrate that our strategy is able to significantly reduce the size of the relational schema without sacrificing predictive accuracy.
Virtual Institutions: Normative Environments Facilitating Imitation Learning in Virtual Agents
Authors: Anton Bogdanovych, Simeon Simoff, Marc Esteva
Venue: Proceedings of the 8th international conference on Intelligent Virtual Agents (2008)

The most popular two methods of extending the intelligence of virtual agents are explicit programming of the agents' decision making apparatus and learning agent behaviors from humans or other agents. The major obstacles of the existing approaches are making the agent understand the environment it is situated in and interpreting the actions and goals of other participants. Instead of trying to solve these problems we propose to formalize the environment in a way that these problems are minimized. The proposed solution, called Virtual Institutions, facilitates formalization of participants' interactions inside Virtual Worlds, helping the agent to interpret the actions of other participants, understand its options and determine the goals of the principal that is conducting the training of the agent. Such formalization creates facilities to express the principal's goals during training, as well as establishes a way to communicate desires of the human to the agent once the training is completed.
Application of E-commerce Risk Assessment Research with Weight Unknown TOPSIS Method
Authors: Peide Liu, Zhengwei Du
Venue: Proceedings of the 2008 International Symposiums on Information Processing (2008)

E-commerce risk assessment is a research subject which comes from the integration of e-commerce and the enterprise competition study. This paper proposed a new E-commerce risk assessment method based on the weight unknown TOPSIS method. By selecting the object of risk assessment, establishing the risk assessment indicator system and quantifying each indicator’s weight, this method can assess the extent of the pros and cons of each project accurately. Also, it does not have the subjectivity and can provide strong support to risk decision-making.
Optimization of application QoS protocols for 3G/4G mobile networks
Authors: Gordana Gardaševic, Milojko Jevtovic, Philip Constantinou
Venue: Proceedings of the 7th WSEAS International Conference on Application of Electrical Engineering (2008)

The importance of Quality of Service (QoS) provisioning has become one of the central issues of 3G/4G mobile network design and analysis. Mobile multimedia applications have high demands in terms of available network resources, equipment design and QoS performances. The challenging task for research activities is the creation of adaptive application QoS protocol suit in order to obtain optimal QoS performance. In this paper we identify key adaptation issues and propose the architectural framework for application level QoS adaptation.
Query-Answering CG Knowledge Bases
Authors: Michel Leclère, Nicolas Moreau
Venue: Proceedings of the 16th international conference on Conceptual Structures: Knowledge Visualization and Reasoning (2008)

Conceptual graphs are a good choice for constructing and exploiting a knowledge base. In several of our projects (semantic portal for e-tourism, exploitation of digital object corpus, etc.), we have to query such bases. So it is natural to consider queries and bases as simple graphs and to compute the set of all projections from a query to a base. However, there is a problem of the return of this set of projections to the user. More generally, the main issue is about the definition of the notion of answers in an query-answering system made of knowledge bases formalized by graphs (Conceptual Graphs, RDF (Resource Description Framework) , Topic Maps, etc.). In this paper, we study several notions of answers and some of their characterizations. We distinguish between notions of answers by subgraphs of the base and answers by creation of result graphs. For the last type of answers, we define completeness, non-redundancy and minimality criteria of the answer sets and propose several notions of answers w.r.t these criteria.
Application of the Unusual Motion Detection Using CHLAC to the Video Surveillance
Authors: Kenji Iwata, Yutaka Satoh, Takumi Kobayashi, Ikushi Yoda, Nobuyuki Otsu
Venue: Neural Information Processing: 14th International Conference, ICONIP 2007, Kitakyushu, Japan, November 13-16, 2007, Revised Selected Papers, Part II (2008)

Cubic Higher-Order Local Auto-Correlation (CHLAC) is feature vector that simultaneously represent motion and shape. The system learns a sample set of "usual motion" to create a "usual subspace" with PCA. Feature vectors are then similarly extracted from unknown input data, and accurate detection of "unusual motion" is achieved by measuring the deviation from the usual subspace. Therefore, by defining unusual motion as "motion that is outside the usual motion," this method can detect unusual motion without an actual model of unusual motion, which differs depending on the situation, and furthermore, is difficult to define. This paper reports on the fast CHLAC that we have developed, so that these capabilities of CHLAC can be put to practical use as an unusual motion detection system that operates in real time. This paper also demonstrated the effectiveness of this method through example tests, conducted using real images both indoors and outdoors.
Deciding Effectively Propositional Logic Using DPLL and Substitution Sets
Authors: Leonardo Moura, Nikolaj Bjørner
Venue: Proceedings of the 4th international joint conference on Automated Reasoning (2008)

We introduce a DPLL calculus that is a decision procedure for the Bernays-Schönfinkel class, also known as EPR. Our calculus allows combining techniques for efficient propositional search with data-structures, such as Binary Decision Diagrams, that can efficiently and succinctly encode finite sets of substitutions and operations on these. In the calculus, clauses comprise of a sequence of literals together with a finite set of substitutions; truth assignments are also represented using substitution sets. The calculus works directly at the level of sets, and admits performing simultaneous constraint propagation and decisions, resulting in potentially exponential speedups over existing approaches.
Founders at Work: Stories of Startups' Early Days, 1 edition
Authors: Jessica Livingston
Venue:  (2008)

For wouldbe entrepreneurs, innovation managers or just anyone fascinated by the special chemistry and drive that created some of the best technology companies in the world, this book offers both wisdom and engaging insightsstraight from the source. Chris Anderson, editorinchief of Wired Magazine, and author of The Long TailAll the best things that I did at Apple came from (a) not having money and (b) not having done it before, ever. Steve Wozniak, Apple Now available in paperbackwith a new preface and interview with Jessica Livingston about Y Combinator! Founders at Work: Stories of Startups Early Days is a collection of interviews with founders of famous technology companies about what happened in the very earliest days. These people are celebrities now. What was it like when they were just a couple friends with an idea? Founders like Steve Wozniak (Apple), Caterina Fake (Flickr), Mitch Kapor (Lotus), Max Levchin (PayPal), and Sabeer Bhatia (Hotmail) tell you in their own words about their surprising and often very funny discoveries as they learned how to build a company. Where did they get the ideas that made them rich? How did they convince investors to back them? What went wrong, and how did they recover?Nearly all technical people have thought of one day starting or working for a startup. For them, this book is the closest you can come to being a fly on the wall at a successful startup, to learn how it's done.But ultimately these interviews are required reading for anyone who wants to understand business, because startups are business reduced to its essence. The reason their founders become rich is that startups do what businessesdocreate valuemore intensively than almost any other part of the economy. How? What are the secrets that make successful startups so insanely productive? Read this book, and let the founders themselves tell you.
Research of Frequency Band Derangement of Wavelet Packet and Application
Authors: Yongjun Chen, Xiaojing Chen, Di Wu, Yong He
Venue: Proceedings of the 2008 Congress on Image and Signal Processing, Vol. 4 - Volume 04 (2008)

The reason of frequency band derangement and the rule of frequency band division of wavelet packet transform were analyzed. The correct frequency band sequence of wavelet packet transform (WPT) was found. Then in this study, because of the texture feature information is on the middle frequency band, according to the conclusion, we select the correct frequency band sequence of WPT to classify tea categories, the images of tea were captured by multi-spectral imager (3CCD). Firstly, image was transformed by WPT, the decomposed lever was 3, so 8 nodes were obtained, and the 8 nodes were rearranged. The node (2,3) and node (2,7) were selected as the input texture feature set of training and prediction using by least squares-support vector machine (LS-SVM). The nodes which were selected by the correct frequency band is satisfactory as evident from the experiments; up to 100% accuracy is obtained using LS-SVM
Communication and query privacy: intrusion-resilient secure channels and private database queries
Authors: Gene Itkis
Venue:  (2008)

This dissertation consists of two parts. The first part considers the problem of two-party communication in the presence of a passive eavesdropper. We describe a new communication primitive called an Intrusion-Resilient Secure Channel (IRC) that offers improved confidentiality over traditional secure channels against passive but mobile, highly adaptive adversaries. IRCs limit the loss of confidentiality resulting from the exposure of parties' secret keys by utilizing key-evolution and proactive security techniques similar to those employed in intrusion-resilient signature schemes. We show how to construct an IRC using existing chosen-ciphertext-secure public-key cryptosystems in a black-box manner. We also show how to use IRCs to improve two-party protocol security. As a concrete example, we prove an IRC-augmented version of the Itkis-Reyzin intrusion-resilient signature scheme secure against highly adaptive adversaries capable of exposing even expired secrets. The second part of this dissertation considers the privacy of a user's queries to a server-hosted database. User privacy means the server learns nothing about the user's query or its result. Server privacy means the user learns nothing about the server's database beyond the correct query answer. We describe an interactive binary search protocol with both user and server privacy that improves upon an existing user-private only protocol. We use our search protocol to construct user- and server-private protocols for predecessor, successor, and simple range queries on one-dimensional data. We also describe a user- and server-private protocol for multi-way search, a generalization of binary search, and how to modify the other protocols to utilize it. All of these protocols are secure in the standard model without setup assumptions against semi-honest parties who correctly follow the protocol but attempt to break its privacy. To facilitate the efficient retrieval of range query results, we also provide a communication-optimized user- and server-private protocol for retrieving a contiguous range of elements of known size by position. This protocol generalizes existing notions of block oblivious transfer and is secure against semi-honest servers and malicious users who deviate arbitrarily from the protocol.
The 2007 IEEE CEC simulated car racing competition
Authors: Julian Togelius, Simon Lucas, Ho Duc Thang, Jonathan M. Garibaldi, Tomoharu Nakashima, Chin Hiong Tan, Itamar Elhanany, Shay Berant, Philip Hingston, Robert M. Maccallum, Thomas Haferlach, Aravind Gowrisankar, Pete Burrow
Venue: Genetic Programming and Evolvable Machines (2008)

This paper describes the simulated car racing competition that was arranged as part of the 2007 IEEE Congress on Evolutionary Computation. Both the game that was used as the domain for the competition, the controllers submitted as entries to the competition and its results are presented. With this paper, we hope to provide some insight into the efficacy of various computational intelligence methods on a well-defined game task, as well as an example of one way of running a competition. In the process, we provide a set of reference results for those who wish to use the simplerace game to benchmark their own algorithms. The paper is co-authored by the organizers and participants of the competition.
Estimation of Nitrogen Removal Effect in Groundwater Using Artificial Neural Network
Authors: Jinlong Zuo
Venue: Proceedings of the 5th international symposium on Neural Networks: Advances in Neural Networks, Part II (2008)

Groundwater contamination by nitrate is a globally growing problem. Biological denitrification is a simple and cost effective method. However, this process is non-linear, complex and multivariable. This paper presents the application of artificial neural network (ANN) in denitrification process in ground water. Experimental results showed that the ANN was able to predict the output water quality parameters--including nitrate as well as nitrite and COD. Most of relative error of NO3 ¿-N and COD were in the range of ±10% and ±5% respectively. The ANN model of nitrate removal in ground water prediction results produced good agreement with experimental data.
Towards a Two Layered Verification Approach for Compiled Graph Transformation
Authors: Ákos Horváth
Venue: Proceedings of the 4th international conference on Graph Transformations (2008)

As model driven software development (MDSD) is being applied more and more in the safety critical (SC) and dependable system development processes there is an increasing need for verified model transformations to guarantee certain semantic properties to hold after their execution. For instance, when transforming UML models into Petri nets, the results of a formal analysis can be invalidated by erroneous model transformationswhen the system developer cannot easily distinguish whether an error is in the design or in the transformation.In this paper we introduce our vision for verifying property preservation of graph transformation systems with a two layered approach.
Focused local cluster formation for multidimensional microarray data
Authors: Keon Myung Lee, Kyung Mi Lee, Chan Hee Lee, Jee-Hyong Lee
Venue: Proceedings of the 7th WSEAS International Conference on Application of Electrical Engineering (2008)

It is a challenging task to find meaningful clusters in a high dimensional data set due to the curse of dimensionality. Microarray gene expression data is a typical high dimensional one of which dimension goes up to tens of thousands. Subspace clustering is a promising approach to handling such high dimensional data. In microarray data analysis, the analysts sometimes pay special attention to specific subspace clusters rather than overall picture. This paper presents a method to find an interesting subspace cluster in an interactive way. The proposed method makes use of a hierarchical clustering result to select an interest region. The selected interest region plays role of a seed from which a subspace cluster grows up. The proposed method has been implemented as a graphical analysis tool and evaluated very helpful in the microarray data analysis.
Orbital degeneracy and magnetic properties of potassium clusters incorporated into nanoporous crystals of zeolite A
Authors: Takehito Nakano, Yasuo Nozue
Venue: Journal of Computational Methods in Sciences and Engineering (2007)

Potassium nanoclusters in aluminosilicate zeolite A shows ferromagnetic properties, although bulk metal of K is nonmagnetic. K clusters are prepared by adsorbing guest K atoms into the supercages (&alpha; cages) of dehydrated zeolite A, where supercages with the inside diameter of &sim; 11 &Aring; are arrayed in a simple cubic structure. By the loading of guest K atoms, s-electrons are provided for clusters, and successively occupy 1s- and 1p-like quantum states of cluster. The average number of guest K atoms in a cluster, n, is widely controlled up to 7.2. This material shows ferromagnetism at n > 2 at low temperatures, where s-electrons in the 1p state of clusters are responsible for the ferromagnetism. We have found a fine step at n=2 in magnetization and g value. The g values of ferromagnetic samples with 2 < n < 6 obviously decrease from 2 at low temperatures, indicating that an enhancement of the spin-orbit interaction (SOI) occurs due to the orbital degeneracy of the 1p state. An enhancement mechanism is proposed based on the Schmidt orthogonalized wave function. In the ferromagnetic sample, an anomalously large magnetization is observed at higher magnetic fields up to 52 T at low temperatures. The level crossing of LS multiplet terms in the degenerate 1p orbital of cluster is proposed as the possible origin of the anomalous increase in magnetization at higher fields. The ferromagnetism coexists with antiferromagnetic coupling between magnetic moments of clusters. The origin of the spontaneous magnetization of the ferromagnetism is interpreted in terms of spin-canting mechanism where the Dzyaloshinsky-Moriya interaction is strongly enhanced by the degenerate 1p orbital of K cluster. Possible structures of K cluster in the supercage are also discussed for the orbital degeneracy of 1p state
AMOEBA-RT: Run-Time Verification of Adaptive Software
Authors: Heather J. Goldsby, Betty H. Cheng, Ji Zhang
Venue: Models in Software Engineering: Workshops and Symposia at MoDELS 2007, Nashville, TN, USA, September 30 - October 5, 2007, Reports and Revised Selected Papers (2008)

Increasingly, software must dynamically adapt its behavior in response to changes in the supporting computing, communication infrastructure, and in the surrounding physical environment. Assurance that the adaptive software correctly satisfies its requirements is crucial if the software is to be used in high assurance systems, such as command and control or critical infrastructure protection systems. Adaptive software development for these systems must be grounded upon formalism and rigorous software engineering methodology to gain assurance. In this paper, we briefly describe AMOebA-RT, a run-time monitoring and verification technique that provides assurance that dynamically adaptive software satisfies its requirements.
GPX: Ad-Hoc Queries and Automated Link Discovery in the Wikipedia
Authors: Shlomo Geva
Venue: Focused Access to XML Documents: 6th International Workshop of the Initiative for the Evaluation of XML Retrieval, INEX 2007 Dagstuhl Castle, Germany, December 17-19, 2007. Selected Papers (2008)

The INEX 2007 evaluation was based on the Wikipedia collection. In this paper we describe some modifications to the GPX search engine and the approach taken in the Ad-hoc and the Link-the-Wiki tracks. In earlier version of GPX scores were recursively propagated from text containing nodes, through ancestors, all the way to the document root of the XML tree. In this paper we describe a simplification whereby the score of each node is computed directly, doing away with the score propagation mechanism. Results indicate slightly improved performance. The GPX search engine was used in the Link-the-Wiki track to identify prospective incoming links to new Wikipedia pages. We also describe a simple and efficient approach to the identification of prospective outgoing links in new Wikipedia pages. We present and discuss evaluation results.