ppxscal/embedding_network huggingface dataset:
Analysis, Modeling And Simulation Of Network Traces For Video Transmission Over IP Networks
Authors: Ming Yang, Nikolaos Bourbakis
Venue: Journal of Integrated Design Process Science (2009)

In the best-effort IP network, quality of service (QoS) cannot be guaranteed, and thus packets could possibly be delayed or lost. Packet delay/loss will inevitably degrade the perceptual quality of real-time multimedia-over-IP service, such as Voice-over-IP (VoIP), Video-on-Demand (VoD), etc. In general, packet loss/delay exhibits temporal dependence. In order to efficiently conduct error recovery/concealment and improve the perceptual quality of the transmitted multimedia contents, packet loss/delay has to be precisely modeled. Different mathematical models, such as Bernoulli Model, Gilbert Model, Extended Gilbert Model, have been proposed to model network trace. However, none of them is able to precisely model the networked multimedia trace like the General Markov Model (GMM), which has rarely been applied in practice due to massive computational resource requirements. With the developments of modern computing hardware and parallel processing algorithms, GMM is becoming computationally feasible. In this paper, in order to obtain network traces for real-time VoD transmission, different connections have been setup to simulate a real VoD system. Data packets have been transmitted between the server and clients under RTP/UDP/IP protocol stack. Different models have been applied to analyze and model the obtained video transmission network traces. Specifically, a 6-state GMM has been applied to analyze the network trace, and the parameterized model has been obtained for further error recover/concealment. Compared to the other models, GMM offers the best modeling precision, in terms of loss-run distribution (LSD) and Forward Error Correction (FEC) performance prediction. The parameterized GMM is very useful to model and analyze network traces and further improve the QoS in multimedia-over-IP based on the modeling and analysis.
Human Action Recognition Using LBP-TOP as Sparse Spatio-Temporal Feature Descriptor
Authors: Riccardo Mattivi, Ling Shao
Venue: Proceedings of the 13th International Conference on Computer Analysis of Images and Patterns (2009)

In this paper we apply the Local Binary Pattern on Three Orthogonal Planes (LBP-TOP) descriptor to the field of human action recognition. A video sequence is described as a collection of spatial-temporal words after the detection of space-time interest points and the description of the area around them. Our contribution has been in the description part, showing LBP-TOP to be a promising descriptor for human action classification purposes. We have also developed several extensions to the descriptor to enhance its performance in human action recognition, showing the method to be computationally efficient.
Elliptic Curve Scalar Multiplication Combining Yao's Algorithm and Double Bases
Authors: Nicolas Méloni, M. Anwar Hasan
Venue: Proceedings of the 11th International Workshop on Cryptographic Hardware and Embedded Systems (2009)

In this paper we propose to take one step back in the use of double base number systems for elliptic curve point scalar multiplication. Using a modified version of Yao's algorithm, we go back from the popular double base chain representation to a more general double base system. Instead of representing an integer k as $\sum^n_{i=1}2^{b_i}3^{t_i}$ where (b i ) and (t i ) are two decreasing sequences, we only set a maximum value for both of them. Then, we analyze the efficiency of our new method using different bases and optimal parameters. In particular, we propose for the first time a binary/Zeckendorf representation for integers, providing interesting results. Finally, we provide a comprehensive comparison to state-of-the-art methods, including a large variety of curve shapes and latest point addition formulae speed-ups.
Interval-Valued Fuzzy Formal Concept Analysis
Authors: Yassine Djouadi, Henri Prade
Venue: Proceedings of the 18th International Symposium on Foundations of Intelligent Systems (2009)

Fuzzy formal concept analysis is concerned with formal contexts expressing scalar-valued fuzzy relationships between objects and their properties. Existing fuzzy approaches assume that the relationship between a given object and a given property is a matter of degree in a scale L (generally [0,1]). However, the extent to which "object o has property a" may be sometimes hard to assess precisely. Then it is convenient to use a sub-interval from the scale L rather than a precise value. Such formal contexts naturally lead to interval-valued formal concepts. The aim of the paper is twofold. We provide a sound minimal set of requirements for interval-valued implications in order to fulfill the fuzzy closure properties of the resulting Galois connection. Secondly, a new approach based on a generalization of Gödel implication is proposed for building the complete lattice of all interval-valued formal concepts.
Implementing Affect Parameters in Personalized Web-Based Design
Authors: Zacharias Lekkas, Nikos Tsianos, Panagiotis Germanakos, Constantinos Mourlas, George Samaras
Venue: Proceedings of the 13th International Conference on Human-Computer Interaction. Part III: Ubiquitous and Intelligent Interaction (2009)

Researchers used to believe that emotional processes are beyond the scope of a scientific study. Recent advances in cognitive science and artificial intelligence, however, suggest that there is nothing mystical about emotional processes. Affective neuroscience and psychology have reported that human affect and emotional experience play a significant, and useful, role in human learning and decision making. Emotions are considered to play a central role in guiding and regulating learning, performance, behaviour and decision making, by modulating numerous cognitive and physiological activities. Our purpose is to improve learning performance and, most importantly, to personalize web-content to users' needs and preferences, eradicating known difficulties that occur in traditional approaches. Affect parameters are implemented, by constructing a theory that addresses emotion and is feasible in Web-learning environments.
The Application of Group-Person Model (GPM) on the University Learning Climate Construction
Authors: Zhong Ping, Liu Yong, Qin Tang
Venue: Proceedings of the 2009 WASE International Conference on Information Engineering - Volume 02 (2009)

University learning climate construction is an essential guarantee of higher education quality. Learning climate in university is dependent on each student, while individual is influenced by the whole group. This paper offers a Group-Person Model(GPM) to analyze students' academic goals and the influential mechanism of group on individuals. This paper aims to instruct university learning climate construction and provide "how to improve" suggestions, by using GPM to simulate the state of students in various activities, such as academic activities, social practices and etc..
Approximation Algorithms for Buy-at-Bulk Geometric Network Design
Authors: Artur Czumaj, Jurek Czyzowicz, Leszek Gąsieniec, Jesper Jansson, Andrzej Lingas, Pawel Zylinski
Venue: Proceedings of the 11th International Symposium on Algorithms and Data Structures (2009)

The buy-at-bulk network design problem has been extensively studied in the general graph model. In this paper we consider the geometric version of the problem, where all points in a Euclidean space are candidates for network nodes. We present the first general approach for geometric versions of basic variants of the buy-at-bulk network design problem. It enables us to obtain quasi-polynomial-time approximation schemes for basic variants of the buy-at-bulk geometric network design problem with polynomial total demand. Then, for instances with few sinks and low capacity links, we design very fast polynomial-time low-constant approximations algorithms.
Domain-independent shallow sentence ordering
Authors: Thade Nahnsen
Venue: Proceedings of Human Language Technologies: The 2009 Annual Conference of the North American Chapter of the Association for Computational Linguistics, Companion Volume: Student Research Workshop and Doctoral Consortium (2009)

We present a shallow approach to the sentence ordering problem. The employed features are based on discourse entities, shallow syntactic analysis, and temporal precedence relations retrieved from VerbOcean. We show that these relatively simple features perform well in a machine learning algorithm on datasets containing sequences of events, and that the resulting models achieve optimal performance with small amounts of training data. The model does not yet perform well on datasets describing the consequences of events, such as the destructions after an earthquake.
Sketch recognition based on manifold learning
Authors: Heeyoul Choi, Tracy Hammond
Venue: Proceedings of the 23rd national conference on Artificial intelligence - Volume 3 (2008)

Current feature-based methods for sketch recognition systems rely on human-selected features. Certain machine learning techniques have been found to be good nonhnear features extractors. In this paper, we apply a manifold learning method, kernel Isomap, with a new algorithm for multi-stroke sketch recognition, which significantly outperforms the standard feature-based techniques.
Reliable and Energy-Efficient Routing for Static Wireless Ad Hoc Networks with Unreliable Links
Authors: Xiang-Yang Li, Yu Wang, Haiming Chen, Xiaowen Chu, Yanwei Wu, Yong Qi
Venue: IEEE Transactions on Parallel and Distributed Systems (2009)

Energy efficient routing and power control techniques in wireless ad hoc networks have drawn considerable research interests recently. In this paper, we address the problem of energy efficient reliable routing for wireless ad hoc networks in the presence of unreliable communication links or devices or lossy wireless link layers by integrating the power control techniques into the energy efficient routing. We consider both the case when the link layer implements a perfect reliability and the case when the reliability is implemented through the transport layer, e.g., TCP. We study the energy efficient unicast and multicast when the links are unreliable. Subsequently, we study how to perform power control (thus, controlling the reliability of each communication link) such that the unicast routings use the least power when the communication links are unreliable, while the power used by multicast is close to optimum. Extensive simulations have been conducted to study the power consumption, the end-to-end delay, and the network throughput of our proposed protocols compared with existing protocols.
Coding with skew polynomial rings
Authors: Delphine Boucher, Felix Ulmer
Venue: Journal of Symbolic Computation (2009)

In analogy to cyclic codes, we study linear codes over finite fields obtained from left ideals in a quotient ring of a (non-commutative) skew polynomial ring. The paper shows how existence and properties of such codes are linked to arithmetic properties of skew polynomials. This class of codes is a generalization of the @q-cyclic codes discussed in [Boucher, D., Geiselmann, W., Ulmer, F., 2007. Skew cyclic codes. Applied Algebra in Engineering, Communication and Computing 18, 379-389]. However @q-cyclic codes are powerful representatives of this family and we show that the dual of a @q-cyclic code is still @q-cyclic. Using Groebner bases, we compute all Euclidean and Hermitian self-dual @q-cyclic codes over F"4 of length less than 40, including a [36,18,11] Euclidean self-dual @q-cyclic code which improves the previously best known self-dual code of length 36 over F"4.
Study on the Fault Arc On-line Detecting Based on Wavelet Singularity Detection Principle
Authors: Yang Yi, Yu Qiongfang, Dong Aihua, Zheng Dezhong
Venue: Proceedings of the 2009 WASE International Conference on Information Engineering - Volume 02 (2009)

For the current value of fault arc can not make protection devices action, the fault arc can not be found easily and cut off timely when the arc is come into being in power supply line. Therefore, it is very necessary to research the reliable and effective method for detecting fault arc. Through the simulation experiments to the fault arc, found an important characteristic of fault arc, that is the arc would present cyclical singular paints when it is burning smoothly. According to this characteristic of fault arc, applying the singularity detection principle of the wavelet transform, studied the detecting method of fault arc in power supply line. Through the imitation and comparison of the test data, the fault arc’s detecting method based on wavelet singularity detection principle shows remarkable effect to improve the reliability of fault arc detection.
Meta Galaxy: A Flexible and Efficient Cube Model for Data Retrieval in OLAP
Authors: Jie Zuo, Changjie Tang, Lei Duan, Yue Wang, Liang Tang, Tianqing Zhang, Jun Zhu
Venue: Advances in Web and Network Technologies, and Information Management: APWeb/WAIM 2009 International Workshops: WCMT 2009, RTBI 2009, DBIR-ENQOIR 2009, PAIS 2009, Suzhou, China, April 2-4, 2009, Revised Selected Papers (2009)

OLAP is widely used in data analysis. The existing design models, such as star schema and snowflake schema, are not flexible when the data model is changed. For example, the task for inserting a dimension may involve complex operations over model and application implementation. To deal with this problem, a new cube model, called Meta Galaxy, is proposed. The main contributions of this work include: (1) analyzing the shortcoming of traditional design method, (2) proposing a new cube model which is flexible for dimension changes, and (3) designing an index structure and an algorithm to accelerate the cube query. The time complexity of query algorithm is linear. The extensive experiments on the real application and synthetic dataset show that Meta Galaxy is effective and efficient for cube query. Specifically, our method decreases the storage size by 95.12%, decreases the query time by 89.89% in average compared with SQL Server 2005, and has good scalability on data size.
A behavioral-based multi-agent optimization algorithm for system level radio design
Authors: Delia Rodríguez De Llera González, Ana Rusu, Mohammed Ismail
Venue: Analog Integrated Circuits and Signal Processing (2009)

This paper introduces a multi-agent behavioral-based optimization algorithm for system level radio design. Making multi-standard wireless communication receivers that meet their specs while keeping the requirements of the individual blocks as relaxed as possible is the goal of this algorithm. In order to achieve this goal a "divide and conquer" approach is proposed. Different agents focus on different objectives that are pursued in parallel. Agents adopt different behaviors depending on the status of the environment and their interaction with other agents. Agents are cooperative by default as they try to meet their spec without making changes that affect other agents. However, more aggressive behaviors that lead to global changes can be adopted when needed. The interaction between these simple entities yields an emergent behavior able to deal smoothly with the complexity of the problem at hand.
Demo abstract: Laser-based trace-gas chemical sensors for distributed wireless sensor networks
Authors: Stephen So, Ardalan Amiri Sani, Lin Zhong, Frank Tittel, Gerard Wysocki
Venue: Proceedings of the 2009 International Conference on Information Processing in Sensor Networks (2009)

We demonstrate low-power, integrated laser-based tracegas chemical sensor systems which directly interface to the Telos wireless sensor networking (WSN) modules. We will demonstrate a prototype sensor which measures atmospheric oxygen concentration configured as a battery powered, handheld unit with power consumption ≪0.3W, sensitivity of 0.07%, high specificity, and the robustness required for long term environmental sensing applications.
Two-Dimensional Distributed Inverted Files
Authors: Esteban Feuerstein, Mauricio Marin, Michel Mizrahi, Veronica Gil-Costa, Ricardo Baeza-Yates
Venue: Proceedings of the 16th International Symposium on String Processing and Information Retrieval (2009)

Term-partitioned indexes are generally inefficient for the evaluation of conjunctive queries, as they require the communication of long posting lists. On the other side, document-partitioned indexes incur in excessive overheads as the evaluation of every query involves the participation of all the processors, therefore their scalability is not adequate for real systems. We propose to arrange a set of processors in a two-dimensional array, applying term-partitioning at row level and document-partitioning at column level. Choosing the adequate number of rows and columns given the available number of processors, together with the selection of the proper ways of partitioning the index over that topology is the subject of this paper.
A Feature Selection and Extraction Method for Uyghur Handwriting-Based Writer identification
Authors: Kurban Ubul, Dilmurat Tursun, Askar Hamdulla, Alim Aysa
Venue: Proceedings of the 2009 International Conference on Computational Intelligence and Natural Computing - Volume 02 (2009)

This paper proposes a method for texture feature extraction by integrating Gabor filters and independent component analysis (ICA) for Uyghur handwriting based writer identification. That is, the texture image is firstly filtered by a given bank of Gabor filters, and then higher dimensional feature vectors are constructed from the filtered texture images. Next, the dimensionality of these vectors is reduced by means of principal component analysis (PCA). Finally, the independent components in the resulting vectors with dimensionality reduced are analyzed and extracted by us. Experiments were performed using KNN-5 classifier to Uyghur handwriting samples from 55 different people and promising results of 92.5% correct identification rate were achieved.
Nonmonotonic modes of inference
Authors: Victor Jauregui
Venue: Proceedings of the 23rd national conference on Artificial intelligence - Volume 1 (2008)

In this paper we investigate nonmonotonic 'modes of inference'. Our approach uses modal (conditional) logic to establish a uniform framework in which to study nonmonotonic consequence. We consider a particular mode of inference which employs a majority-based account of default reasoning--one which differs from the more familiar preferential accounts--and show how modal logic supplies a framework which facilitates analysis of, and comparison with more traditional formulations of nonmonotonic consequence.
ANTON: Composing Logic and Logic Composing
Authors: Georg Boenn, Martin Brain, Marina Vos, John Ffitch
Venue: Proceedings of the 10th International Conference on Logic Programming and Nonmonotonic Reasoning (2009)

In most styles of music, composition is governed by a set of rules. We demonstrate that approaching the automation and analysis of composition declaratively, by expressing these rules in a suitable logical language, powerful and expressive intelligent composition tools can easily be built. This paper describes the use of answer set programming to construct an automated system, named Anton, that can compose both melodic and harmonic music, diagnose errors in human compositions and serve as a computer-aided composition tool.
Site-Wide Wrapper Induction for Life Science Deep Web Databases
Authors: Saqib Mir, Steffen Staab, Isabel Rojas
Venue: Proceedings of the 6th International Workshop on Data Integration in the Life Sciences (2009)

We present a novel approach to automatic information extraction from Deep Web Life Science databases using wrapper induction. Traditional wrapper induction techniques focus on learning wrappers based on examples from one class of Web pages, i.e. from Web pages that are all similar in structure and content. Thereby, traditional wrapper induction targets the understanding of Web pages generated from a database using the same generation template as observed in the example set. However, Life Science Web sites typically contain structurally diverse web pages from multiple classes making the problem more challenging. Furthermore, we observed that such Life Science Web sites do not just provide mere data, but they also tend to provide schema information in terms of data labels --- giving further cues for solving the Web site wrapping task. Our solution to this novel challenge of Site-Wide wrapper induction consists of a sequence of steps: 1. classification of similar Web pages into classes, 2. discovery of these classes and 3. wrapper induction for each class. Our approach thus allows us to perform unsupervised information retrieval from across an entire Web site. We test our algorithm against three real-world biochemical deep Web sources and report our preliminary results, which are very promising.
Niche Genetic Algorithm and Minimum Spanning Tree for Substation Planning
Authors: Peng Wen, Liu Wenxia
Venue: Proceedings of the 2009 WRI Global Congress on Intelligent Systems - Volume 03 (2009)

This paper presents a method based on Niche Genetic Algorithm (NGA) and Minimum Spanning Tree (MST) for substation planning. The problem of substation planning is divided into two parts: one is the capacity-determining and another is location-determining. The customer loads are represented a tree built by MST. Through clustering the loads, the capacity of every substation is calculated, and then the least square method is used to determine the location of substation with the objective function of minimal cost. NGA is employed to optimize the above process. Large amount of experiments show the effectiveness of our algorithm comparing with the other methods.
Meet-in-the-Middle Attacks on SHA-3 Candidates
Authors: Dmitry Khovratovich, Ivica Nikolić, Ralf-Philipp Weinmann
Venue: Fast Software Encryption: 16th International Workshop, FSE 2009 Leuven, Belgium, February 22-25, 2009 Revised Selected Papers (2009)

We present preimage attacks on the SHA-3 candidates Boole, EnRUPT, Edon-R, and Sarmal, which are found to be vulnerable against a meet-in-the-middle attack. The idea is to invert (or partially invert) the compression function and to exploit its non-randomness. To launch an attack on a large internal state we manipulate the message blocks to be injected in order to fix some part of the internal state and to reduce the complexity of the attack. To lower the memory complexity of the attack we use the memoryless meet-in-the-middle approach proposed by Morita-Ohta-Miyaguchi.
A multi-path architecture for machine translation of English text into American Sign Language animation
Authors: Matt Huenerfauth
Venue: Proceedings of the Student Research Workshop at HLT-NAACL 2004 on XX (2004)

The translation of English text into American Sign Language (ASL) animation tests the limits of traditional MT architectural designs. A new semantic representation is proposed that uses virtual reality 3D scene modeling software to produce spatially complex ASL phenomena called "classifier predicates." The model acts as an interlingua within a new multi-pathway MT architecture design that also incorporates transfer and direct approaches into a single system.