ppxscal/embedding_network huggingface dataset:
Subquadratic Space Complexity Multiplication over Binary Fields with Dickson Polynomial Representation
Authors: M. Anwar Hasan, Christophe Negre
Venue: Proceedings of the 2nd international workshop on Arithmetic of Finite Fields (2008)

We study Dickson bases for binary field representation. Such a representation seems interesting when no optimal normal basis exists for the field. We express the product of two elements as Toeplitz or Hankel matrix vector product. This provides a parallel multiplier which is subquadratic in space and logarithmic in time.
Developing Data Warehouse for Simulation Experiments
Authors: Janusz Sosnowski, Przemysław Zygulski, Piotr Gawkowski
Venue: Proceedings of the international conference on Rough Sets and Intelligent Systems Paradigms (2007)

The paper deals with the problem of creating a specialized data warehouse for collecting and analyzing experimental results, which relate to system dependability evaluation using fault injections into running programs. The developed data warehouse with embedded data mining capabilities facilitates to identify factors influencing fault susceptibility of analyzed applications. The paper presents the developed system, and illustrates its usefulness with a sample of experimental results.
Daily Routine Classification from Mobile Phone Data
Authors: Katayoun Farrahi, Daniel Gatica-Perez
Venue: Proceedings of the 5th international workshop on Machine Learning for Multimodal Interaction (2008)

The automatic analysis of real-life, long-term behavior and dynamics of individuals and groups from mobile sensor data constitutes an emerging and challenging domain. We present a framework to classify people's daily routines (defined by day type, and by group affiliation type) from real-life data collected with mobile phones, which include physical location information (derived from cell tower connectivity), and social context (given by person proximity information derived from Bluetooth). We propose and compare single- and multi-modal routine representations at multiple time scales, each capable of highlighting different features from the data, to determine which best characterized the underlying structure of the daily routines. Using a massive data set of 87000+ hours spanning four months of the life of 30 university students, we show that the integration of location and social context and the use of multiple time-scales used in our method is effective, producing accuracies of over 80% for the two daily routine classification tasks investigated, with significant performance differences with respect to the single-modal cues.
Finding Synchronization-Free Parallelism Represented with Trees of Dependent Operations
Authors: Wlodzimierz Bielecki, Anna Beletska, Marek Palkowski, Pierluigi San Pietro
Venue: Proceedings of the 8th international conference on Algorithms and Architectures for Parallel Processing (2008)

Algorithms are presented for extracting synchronization-free parallelism available in arbitrarily nested parameterized loops. The parallelism is represented with synchronization-free trees of dependent operations. Sets representing trees can be described with non-linear expressions. The main idea is to firstly extract sources of synchronization-free trees and next to generate parallel code based on a while loop. Experimental results are presented exposing speed-up and efficiency of parallel programs written in the OpenMP standard on the basis of code generated by the algorithms proposed.
An Agent-Based Model That Relates Investment in Education to Economic Prosperity
Authors: Yuqing Tang, Simon Parsons, Elizabeth Sklar
Venue: Multi-Agent-Based Simulation VIII: International Workshop, MABS 2007, Honolulu, HI, USA, May 15, 2007, Revised and Invited Papers (2008)

This paper describes some experiments with an agent-based model designed to capture the relationship between the investment that a society makes in education in one generation, and the outcome in terms of the health of the society's economy in ensuing generations. The model we use is a multiagent simulation derived from an equation-based model in the economics literature. The equation-based model is used to establish parameterized sets of agent behaviors and environmental characteristics. Agents are divided into three chronological categories: students, adults and pensioners; and each responds to and affects the environment in different ways, in terms of both human and physical capital. We explore the effects of different parameter settings on the education investment of a society and the resulting economic growth.
Innovative Interfaces in MonAMI: The Reminder
Authors: Jonas Beskow, Jens Edlund, Björn Granström, Joakim Gustafson, Gabriel Skantze
Venue: Proceedings of the 4th IEEE tutorial and research workshop on Perception and Interactive Technologies for Speech-Based Systems: Perception in Multimodal Dialogue Systems (2008)

This demo paper presents the first version of the Reminder, a prototype ECA developed in the European project MonAMI, which aims at "mainstreaming accessibility in consumer goods and services, using advanced technologies to ensure equal access, independent living and participation for all". The Reminder helps users to plan activities and to remember what to do. The prototype merges ECA technology with other, existing technologies: Google Calendar and a digital pen and paper. This innovative combination of modalities allows users to continue using a paper calendar in the manner they are used to, whilst the ECA provides verbal notifications on what has been written in the calendar. Users may also ask questions such as "When was I supposed to meet Sara?" or "What's on my schedule today?"
Memory-Aware Dynamic Voltage and Frequency Prediction for Portable Devices
Authors: Wen-Yew Liang, Shih-Chang Chen, Yang-Lang Chang, Jyh-Perng Fang
Venue: Proceedings of the 2008 14th IEEE International Conference on Embedded and Real-Time Computing Systems and Applications (2008)

In recent years, dynamic voltage and frequency scaling (DVFS) has been considered as one of the most efficient techniques to decrease energy consumption, especially for battery-powered portable devices. However, many DVFS algorithms discuss the issue from the perspective of the processors only. Some researches have started to study the effects of memories in the DVFS algorithms. In this paper, an approximation equation (called MAR-CSE) based on the correlation of the memory access rate and the critical speed for the minimum energy consumption is conducted for frequency and voltage prediction. The memory access information is obtained from the performance monitor-ing unit (PMU) provided on an Intel XScale platform which we used in this study. With MAR-CSE, an MA-DVFS (Memory-aware DVFS) algorithm is proposed. The algorithm has been realized in the Linux kernel. Experiment results show that the energy consumption of the memory bound benchmarks can be reduced from 50% to 65%, much better than the result of 19% to 53% energy saving for the On-demand mechanism which is already supported by the Linux Kernel.
An Agent Framework Based on Signal Concepts for Highlighting the Image Semantic Content
Authors: Mohammed Belkhatir
Venue: Proceedings of the 19th international conference on Database and Expert Systems Applications (2008)

This paper addresses the image semantic gap (i.e. the difficulty to automatically characterize the image semantic content through extracted low-level signal features) by investigating the formation of semantic concepts (such as mountains, sky, grass...) in a population of image agents:abstract structures representing the image visual entities. Through the development of processes mapping extracted low-level features to concept-based visual information, our contribution is twofold. First, we propose a learning framework mapping signal (color, texture) and semantic concepts to highlight the image agents. Contrary to traditional architectures considering high-dimensional spaces of low-level extracted signal features, this framework addresses the curse of dimensionality. Then, at the image agent population level, the agents communicate about the perceived semantic concepts with no access to global information or to the representations of other agents, they only exchange conceptual information. While doing so they adapt their internal representations to be more successful at conveying the perceived semantic information in future interactions. The image content is therefore soundly inferred through these concept-based linguistic interactions.The SIR Agent prototype implements our theoretical framework and its architecture revolves around functional modules enabling the characterization of concept-based linguistic structures, highlighting the image agents and enforcing interactions and coordination between them.
Web Design Requirements for Improved Web Accessibility for the Blind
Authors: Rehema Baguma, Jude T. Lubega
Venue: Proceedings of the 1st international conference on Hybrid Learning and Education (2008)

Considerable research has been done on how to make e-learning systems accessible. But Learners in electronic and hybrid learning environments utilize many Web based systems beyond what the instructor and institution provides and can control such as search engines, news portals and research databases. This paper presents Web design requirements that can improve the accessibility of such websites for PWDs particularly the blind. The requirements were derived from both theoretical and quantitative data gathered from both literature and a case study. It was observed that graphical user interfaces, non-linear navigation, forms, tables, images, lack of key board support, non-standard document formats and acronyms and abbreviations hinder Web accessibility for the blind. Therefore in order to improve Web accessibility for the blind, the following requirements were suggested; a text only version of the website or a combination of design considerations namely: text alternatives for visual elements, meaningful content structure in the source code, skip navigation link(s), orientation during navigation, ensure (tables, frames and forms) are accessible if any is used, test the website with keyboard only access, use or convert documents into standard formats and expand abbreviations and acronyms the first time they appear on a page. Meeting the given requirements in the Web development process improves Web accessibility for all blind Web users including those engaged in hybrid learning.
A Generative Model for Statistical Determination of Information Content from Conversation Threads
Authors: Yingjie Zhou, Malik Magdon-Ismail, William A. Wallace, Mark Goldberg
Venue: Proceedings of the IEEE ISI 2008 PAISI, PACCF, and SOCO international workshops on Intelligence and Security Informatics (2008)

We present a generative model for determining the information content of a message without analyzing the message content. Such a tool is useful for automated analysis of the vast contents of online communication which are extensively contaminated by uninformative content, spam, and broadcast. Content analysis is not feasible in such a setting. We propose a purely statistical methodology to determine the information value of a message, which we denote the Information Content Factor (ICF). Underlying our methodology is the definition of information in a message as the message's ability to generate conversation. The generative nature of our model allows us to estimate the ICF of a message without prior information on the participants. We test our approach by applying it to separating spam/broadcast messages from non-spam/non-broadcast. Our algorithms achieve 94% accuracy when tested against a human classifier which analyzed content.
Image Guidance and Surgery Simulation Using Inverse Nonlinear Finite Element Methods
Authors: Philip Pratt
Venue: Proceedings of the 4th international symposium on Biomedical Simulation (2008)

Nonlinear finite element methods are described in which cyclic organ motion is implied from 4D scan data. The equations of motion corresponding to an explicit integration of the total Lagrangian formulation are reversed, such that the sequence of node forces which produces known changes in displacement is recovered. The forces are resolved from the global coordinate system into systems local to each element, and at every simulation time step are expressed as weighted sums of edge vectors. In the presence of large deformations and rotations, this facilitates the combination of external forces, such as tool-tissue interactions, and also positional constraints. Applications in the areas of surgery simulation and minimally invasive robotic interventions are proposed, and the methods are illustrated using CT images of a pneumatically-operated beating heart phantom.
Extraction of Ambiguous Sequential Patterns with Least Minimum Generalization from Mismatch Clusters
Authors: Kotaro Araki, Keiichi Tamura, Tomoyuki Kato, Yasuma Mori, Hajime Kitakami
Venue: Proceedings of the 2007 Third International IEEE Conference on Signal-Image Technologies and Internet-Based System (2007)

An ambiguous query in sequence databases returns a set of similar subsequences, called a mismatch cluster, to the user. The inherent problem is that it is difficult for users to identify the characteristics of very large similar subsequences in a mismatch cluster. In order to support user comprehension of mismatch clusters, it is important to extract a set of ambiguous sequence patterns with the least minimum generalization in the mismatch cluster. The extraction of the ambiguous sequential pattern set requires an enormous amount of computational time, since we have to discover generalized patterns with minimum covers for the mismatch cluster from candidate generalized patterns. The present paper is a proposal for an iterative refinement method to extract ambiguous sequence patterns with minimum cover for mismatch clusters selected from a sequence database. It includes a proposal to use the method with a domain segmentation method to achieve an efficient pattern extraction. Moreover, a prototype implementing the two proposed methods has been applied to three datasets included in PROSITE in order to evaluate their usefulness. The proposed methods resulted in a high capability to extract ambiguous sequential patterns from mismatch clusters that are provided by an ambiguous query in the sequence database.
VAST Improvements to Diagrammatic Scheduling Using Representational Epistemic Interface Design
Authors: David Ranson, Peter C. Cheng
Venue: Proceedings of the 5th international conference on Diagrammatic Representation and Inference (2008)

REpresentational EPistemic Interface Design (REEP-ID) advocates exploiting the abstract structure of a target domain as the foundation for building cohesive diagrammatic representations. Previous research explored the application of this approach to the display and optimisation of solutions to complex, data rich, real world problems with promising results. This paper demonstrates the application of these principles to generate interactive visualisations for solving complex combinatorial optimisation problems, in this case the University Exam Timetabling Problem (ETP). Using the ETP as an example the principles of REEP-ID are applied, illustrating the design process and advantages of this methodology. This led to the implementation of the VAST (Visual Analysis and Scheduling for Timetables) application, enabling individuals to solve complete instances of the ETP using interactive visualisations. Rather than using automated heuristics or algorithms, VAST relies entirely on the user's problem solving abilities, applying their knowledge and perceptiveness to the interactive visualisations maintained by the computer. Results from an evaluation of VAST support the use of the REEP-ID methodology and the case for further research. In the closing discussion these findings are summarised together with implications for future designers.
Probabilistic Head Pose Tracking Evaluation in Single and Multiple Camera Setups
Authors: Sileye O. Ba, Jean-Marc Odobez
Venue: Multimodal Technologies for Perception of Humans: International Evaluation Workshops CLEAR 2007 and RT 2007, Baltimore, MD, USA, May 8-11, 2007, Revised Selected Papers (2008)

This paper presents our participation in the CLEAR 07 evaluation workshop head pose estimation tasks where two head pose estimation tasks were to be addressed.The first task estimates head poses with respect to (w.r.t.) a single camera capturing people seated in a meeting room scenario. The second task consisted of estimating the head pose of people moving in a room from four cameras w.r.t. a global room coordinate.To solve the first task, we used a probabilistic exemplar-based head pose tracking method using a mixed state particle filter based on a represention in a joint state space of head localization and pose variable. This state space representation allows the combined search for both the optimal head location and pose. To solve the second task, we first applied the same head tracking framework to estimate the head pose w.r.t each of the four camera. Then, using the camera calibration parameters, the head poses w.r.t. individual cameras were transformed into head poses w.r.t to the global room coordinates, and the measures obtained from the four cameras were fused using reliability measures based on skin detection. Good head pose tracking performances were obtained for both tasks.
Approximation algorithms for constraint satisfaction problems
Authors: Yury Makarychev
Venue:  (2008)

Constraint satisfaction problems (CSP) are very basic and natural combinatorial optimization problems. Given a set of variables and constraints on them, our goal is to satisfy as many constraints as possible. In this dissertation, we study two constraint satisfaction problems, the Unique Games Problem and MAX 2CSP Problem. Both problems behave very differently depending on what fraction of all constraints (as a function of other parameters) is satisfiable. Thus we design different algorithms for different ranges of parameters. In the first part of the thesis, we study approximation algorithms for Unique Games. Our algorithms satisfy (roughly) k-3/2-3 ,1-O3log n,and 1-O3lognlog k fraction of all constraints if a 1&minus;&egr; fraction of all constraints is satisfiable (where n is the number of variables, k is the domain size). The first two algorithms are near optimal assuming the Unique Games Conjecture. Our algorithms have better approximation guarantees than the previously best known algorithms in all ranges of parameters. In the second part of the thesis, we present approximation algorithms for MAX 2CSP that satisfy 1&minus;O( 3 ) and 1&minus;O( 3logn ) fraction of all constraints if a 1&minus;&egr; fraction of all constraints is satisfiable. Our first algorithm is near optimal assuming the Unique Games Conjecture.
Classifying Assumptions Made during Requirements Verification of Embedded Systems
Authors: Jelena Marinčić, Angelika Mader, Roel Wieringa
Venue: Proceedings of the 14th international conference on Requirements Engineering: Foundation for Software Quality (2008)

We are investigating ways to improve the process of modelling of embedded systems for formal verification. In the modelling process, we make a mathematical model of the system software and its environment (the plant), and we prove that the requirement holds for the model. But we also want to have an argument that increases our confidence that the model represents the system correctly (with respect to the requirement). Therefore, we document some of the modelling decisions in form of a list of the system assumptions made while modelling. Identifying the assumptions and deciding which ones are relevant is a difficult task and it cannot be formalized. To support this process, we give a classification of assumptions. We show our approach on an example.
Learning in Cooperating Agents Environment as a Method of Solving Transport Problems and Limiting the Effects of Crisis Situations
Authors: Jaroslaw Koźlak
Venue: Proceedings of the 7th international conference on Computational Science, Part II (2007)

The realising of transport requests plays an important role for companies regarding cost. For this reason the construction of an optimal and effective transport planning and scheduling, offering the best use of transport means is hugely important. One of the researched transport problems at present is PDPTW. In this work, the PDPTW problem will be extended by adding changeable and uncertain travel times between given locations, which will then be examined and learnt by the dispatching company system. The changeable travel times are the results of traffic jams forming and propagating. The applied multi-agent approach allows us to consider the problem on the level of a whole company and on the local level analysed by a particular vehicle. The other aspects which are taken into consideration are traffic patterns, whose goal it is to facilitate the optimal routes for the given traffic patterns. These patterns contain the information about the dependencies between the traffic state on the particular routes.
Analysis on Bidirectional Associative Memories with Multiplicative Weight Noise
Authors: Chi Sing Leung, Pui Fai Sum, Tien-Tsin Wong
Venue: Neural Information Processing: 14th International Conference, ICONIP 2007, Kitakyushu, Japan, November 13-16, 2007, Revised Selected Papers, Part I (2007)

In neural networks, network faults can be exhibited in different forms, such as node fault and weight fault. One kind of weight faults is due to the hardware or software precision. This kind of weight faults can be modelled as multiplicative weight noise. This paper analyzes the capacity of a bidirectional associative memory (BAM) affected by multiplicative weight noise. Assuming that weights are corrupted by multiplicative noise, we study how many number of pattern pairs can be stored as fixed points. Since capacity is not meaningful without considering the error correction capability, we also present the capacity of a BAM with multiplicative noise when there are some errors in the input pattern. Simulation results have been carried out to confirm our derivations.
Designing HMM-Based Part-of-Speech Tagger for Lithuanian Language
Authors: Giedrė Pajarskaitė, Vilma Griciūtė, Gailius Raškinis, Jan Kuper
Venue: Informatica (2004)

This paper describes a preliminary experiment in designing a Hidden Markov Model (HMM)-based part-of-speech tagger for the Lithuanian language. Part-of-speech tagging is the problem of assigning to each word of a text the proper tag in its context of appearance. It is accomplished in two basic steps: morphological analysis and disambiguation. In this paper, we focus on the problem of disambiguation, i.e., on the problem of choosing the correct tag for each word in the context of a set of possible tags. We constructed a stochastic disambiguation algorithm, based on supervised learning techniques, to learn hidden Markov model's parameters from hand-annotated corpora. The Viterbi algorithm is used to assign the most probable tag to each word in the text.