ppxscal/embedding_network huggingface dataset:
Consideration of Multiple Components of Emotions in Human-Technology Interaction
Authors: Sascha Mahlke, Michael Minge
Venue: Affect and Emotion in Human-Computer Interaction: From Theory to Applications (2008)

The study of users' emotional behavior as an important aspect of the user experience has been receiving increasing attention for the past few years. In this paper we discuss the multi-component character of emotions and its consideration in the area of human-technology interaction. Based on the approach proposed by Scherer [1], various aspects of emotions were investigated in an interactive context: subjective feelings, physiological activation, motor expression, cognitive appraisals, and behavioral tendencies. In an experiment emotion-related changes were detected for a number of emo tional components by using a variety of methods: rating scales for sub jec tive feelings, electromyography of facial muscles, heart rate, electrodermal activity, perfor mance data and questionnaires on cognitive appraisals. Results are discussed with respect to the correlation between the components and their associated methods. We suggest that a combination of methods provides a comprehensive basis for analyzing emotions as an aspect of the user experience.
Handwritten Digit Classification Based on Alpha-Beta Associative Model
Authors: Luis Octavio López-Leyva, Cornelio Yáñez-Márquez, Rolando Flores-Carapia, Oscar Camacho-Nieto
Venue: Proceedings of the 13th Iberoamerican congress on Pattern Recognition: Progress in Pattern Recognition, Image Analysis and Applications (2008)

In this paper we present a new model appropriate for pattern recognition tasks. This new model, called ¿β Associative Model, arises when taking theoretical elements from the ¿β associative memories, and they are merged with several new mathematical transforms. When applied to handwritten digits recognition, namely in the MNIST database, the ¿β Associative Model exhibits competitive results against some of the most widely known algorithms currently available in scientific literature.
Locating and Segmenting 3D Deformable Objects by Using Clusters of Contour Fragments
Authors: Manuel J. Marín-Jiménez, Nicolás Pérez Blanca, José I. Gómez
Venue: Proceedings of the 3rd Iberian conference on Pattern Recognition and Image Analysis, Part I (2007)

This paper presents a new approach to the problem of simultaneous location and segmentation of object in images. The main emphasis is done on the information provided by the contour fragments present in the image. Clusters of contour fragments are created in order to represent the labels defining the different parts of the object. An unordered probabilistic graph is used to model the objects, where a greedy approach (using dynamic programming) is used to fit the graph model to the labels.
Simulation of Fire Evacuation by Real-Coded Cellular Automata (RCA)
Authors: Kazuhiro Yamamoto, Satoshi Kokubo, Hiroshi Yamashita, Katsuhiro Nishinari
Venue: Proceedings of the 8th international conference on Cellular Automata for Reseach and Industry (2008)

We present simulation of fire evacuation by real-coded Cellular Automata (RCA), which is a new approach for pedestrian dynamics. Here, we consider the evacuation from a relatively large room with one or two exits. To describe the flame spread in fire, a percolation model is applied, where the flame position is determined stochastically. In the simulation, we focus on several parameters including the number of people in room, the distance from the flame, and the location and size of the exit.
Multimodal Comprehension of Graphics with Textual Annotations: The Role of Graphical Means Relating Annotations and Graph Lines
Authors: Cengiz Acarturk, Christopher Habel, Kursat Cagiltay
Venue: Proceedings of the 5th international conference on Diagrammatic Representation and Inference (2008)

Graphs are often accompanied by text, i.e. linguistically coded information, augmenting the information presented diagrammatically. Thus, graph comprehension by humans often constitutes comprehension and integration of information provided by different representational modalities, namely graphical elements and verbal constituents. In this study we focus on textual annotations to line graphs providing information about events, processes and their temporal properties as well as temporal relations about the events and processes in question. We present results of an experimental investigation on parameters which influence subject's interpretations concerning the temporal properties of the annotated events and on eye movement behavior. In particular, we discuss the role of graph shape and the role of graphical means for relating textual annotations and determined parts of the graph line.
Categorization of Digital Ink Elements Using Spectral Features
Authors: José A. Rodríguez, Gemma Sánchez, Josep Lladós
Venue: Graphics Recognition. Recent Advances and New Opportunities: 7th International Workshop, GREC 2007, Curitiba, Brazil, September 20-21, 2007. Selected Papers (2008)

In sketch-based interfaces, the separation of text and graphic elements can be essential when a system has to react to different kinds of input. Even if the interaction with the interface consists in drawing graphic elements, text input may be considered for some purposes, such as annotation, labelling, or input of recognizable text. This work deals with the detection of textual patterns in a set of digital ink elements. The main idea is that text needs a special hand behaviour to be produced, different from the behaviour employed to draw symbols or other graphic elements. Inspired by the models that describe handwriting as a system of coupled oscillations, we believe that the frequencies of these oscillations contain some information about the symbol nature. Therefore, we employ a descriptor that works in the Fourier space. Results show that this representation leads to distinguished patterns for text and graphic elements. The performance of our system is close to the performance one would obtain by using a handwriting recognition engine tuned for this task, while being much faster. Some benefits are also present when both approaches - the proposed and the engine - are combined.
Incrementally Refined Acquaintance Model for Consortia Composition
Authors: Jan Doubek, Jiří Vokřínek, Michal Pěchouček, Martin Rehák
Venue: Proceedings of the 12th international workshop on Cooperative Information Agents XII (2008)

This paper presents a specific contracting algorithm that contributes to the process of distributed planning and resource allocation in competitive, semi-trusted environments. The presented contraction algorithm is based on incrementally refined acquaintance models (IRAM) of the actor that provide the right set of approximate knowledge needed for appropriate task decomposition and delegation. This paper reports on empirical evaluation of the IRAM algorithm deployment in consortia formation domain.
Plenary lecture VII: probability measures of fuzzy events and linguistic fuzzy modelling - forms expressing randomness and imprecision
Authors: Anna Walaszek-Babiszewska
Venue: Proceedings of the 7th WSEAS International Conference on Software Engineering, Parallel and Distributed Systems (2008)

Statistical methods have a long history of applications to data analysis and modelling in many fields of human activities, as financial markets, business, optimal control. Zadeh's theory of fuzzy systems, soft computing and computing with words gave possibilities of utilising many approaches to modelling, taking into account different types of uncertainties, especially, human knowledge and perception expressed imprecisely in linguistic categories. The sets of numerical data, collected in many real systems, and expert's experiences would be very useful to modelling both randomness and imprecision. Starting with the reminding the basic notions of probability of fuzzy events, we define probability distributions of a linguistic variable and a linguistic vector as well as a mean fuzzy value (a mean fuzzy set) of the linguistic variable. We formulate also a stochastic process with fuzzy states. The next, we try to modelling randomness and imprecision, using linguistic fuzzy models with weights of rules. A structure of the fuzzy model is predefined at the beginning of the task. Probability of fuzzy events has been used to formulate probabilities of the occurrence linguistic values of input and output variables in a product-space. Marginal probabilities of linguistic values of input variables are the weights of file rules. Conditional probabilities of linguistic values of the output variable are the weights in the consequence of elementary rules. The inference procedures are proposed and exemplary calculations are presented.
Uniqueness Filtering for Local Feature Descriptors in Urban Building Recognition
Authors: Giang Phuong Nguyen, Hans Jørgen Andersen
Venue: Proceedings of the 3rd international conference on Image and Signal Processing (2008)

Existing local feature detectors such as Scale Invariant Feature Transform (SIFT) usually produce a large number of features per image. This is a major disadvantage in terms of the speed of search and recognition in a run-time application. Besides, not all detected features are equally important in the search. It is therefore essential to select informative descriptors. In this paper, we propose a new approach to selecting a subset of local feature descriptors. Uniqueness is used as a filtering criterion in selecting informative features. We formalize the notion of uniqueness and show how it can be used for selection purposes. To evaluate our approach, we carried out experiments in urban building recognition domains with different datasets. The results show a significant improvement not only in recognition speed, as a result of using fewer features, but also in the performance of the system with selected features.
Tool Integration for Reasoned Programming
Authors: Andrew Ireland
Venue: Verified Software: Theories, Tools, Experiments: First IFIP TC 2/WG 2.3 Conference, VSTTE 2005, Zurich, Switzerland, October 10-13, 2005, Revised Selected Papers and Discussions (2005)

We argue for the importance of tool integration in achieving the Program Verifier Grand Challenge. In particular, we argue for what we call strong integration, i.e. a co-operative style of interaction between tools. We propose the use of an existing planning technique, called proof planning, as a possible basis for achieving strong integration.
Representative Views and Paths for Volume Models
Authors: Pere-Pau Vázquez, Eva Monclús, Isabel Navazo
Venue: Proceedings of the 9th international symposium on Smart Graphics (2008)

Volume data models are becoming larger and larger as the capture technology improves. Thus, their visualization requires high computational power. The automatic presentation of volume models through representative images and/or exploration paths becomes more and more useful. Representative views are also useful for document illustration, fast data quality evaluation, or model libraries documentation. Exploration paths are also useful for video demonstrations and previsualization of captured data. In this paper we present a fast, adaptive method for the selection of representative views and the automatic generation of exploration paths for volume models. Our algorithm is based on multi-scale entropy and algorithmic complexity. These views and paths reveal informative parts of a model given a certain transfer function. We show that our method is simple and easy to incorporate in medical visualization tools.
New Algorithm for Determining Object Attitude Based on Trapezoid Feature
Authors: Lijuan Qin, Yulan Hu, Yingzi Wei, Hong Wang, Yue Zhou
Venue: Proceedings of the 4th international conference on Intelligent Computing: Advanced Intelligent Computing Theories and Applications - with Aspects of Theoretical and Methodological Issues (2008)

Trapezoid is one feature which is widely presented in natural environments. In this paper, we propose a new pose estimation method based on trapezoid. The algorithm is simple to solve. It has good real-time characteristic. Furthermore, there exists unique solution for object pose from rectangle to locate. Thus, it has good practical value in application. At last, simulation results show this method is reasonable and has good real-time characteristic.
Brief paper: Local stability analysis using simulations and sum-of-squares programming
Authors: Ufuk Topcu, Andrew Packard, Peter Seiler
Venue: Automatica (Journal of IFAC) (2008)

The problem of computing bounds on the region-of-attraction for systems with polynomial vector fields is considered. Invariant subsets of the region-of-attraction are characterized as sublevel sets of Lyapunov functions. Finite-dimensional polynomial parametrizations for Lyapunov functions are used. A methodology utilizing information from simulations to generate Lyapunov function candidates satisfying necessary conditions for bilinear constraints is proposed. The suitability of Lyapunov function candidates is assessed solving linear sum-of-squares optimization problems. Qualified candidates are used to compute invariant subsets of the region-of-attraction and to initialize various bilinear search strategies for further optimization. We illustrate the method on small examples from the literature and several control oriented systems.
Self-Coordinating Localized Fair Queueing in Wireless Ad Hoc Networks
Authors: Haiyun Luo, Jerry Cheng, Songwu Lu
Venue: IEEE Transactions on Mobile Computing (2004)

Distributed fair queueing in a multihop, wireless ad hoc network is challenging for several reasons. First, the wireless channel is shared among multiple contending nodes in a spatial locality. Location-dependent channel contention complicates the fairness notion. Second, the sender of a flow does not have explicit information regarding the contending flows originated from other nodes. Fair queueing over ad hoc networks is a distributed scheduling problem by nature. Finally, the wireless channel capacity is a scarce resource. Spatial channel reuse, i.e., simultaneous transmissions of flows that do not interfere with each other, should be encouraged whenever possible. In this paper, we reexamine the fairness notion in an ad hoc network using a graph-theoretic formulation and extract the fairness requirements that an ad hoc fair queueing algorithm should possess. To meet these requirements, we propose Maximize-Local-Minimum Fair Queueing (MLM-FQ), a novel distributed packet scheduling algorithm where local schedulers self-coordinate their scheduling decisions and collectively achieve fair bandwidth sharing. We then propose Enhanced MLM-FQ (EMLM-FQ) to further improve the spatial channel reuse and limit the impact of inaccurate scheduling information resulted from collisions. EMLM-FQ achieves statistical short-term throughput and delay bounds over the shared wireless channel. Analysis and extensive simulations confirm the effectiveness and efficiency of our self-coordinating localized design in providing global fair channel access in wireless ad hoc networks.
Wraplet: Wrapping Your Web Contents with a Lightweight Language
Authors: Natsumi Sawa, Atsuyuki Morishima, Shigeo Sugimoto, Hiroyuki Kitagawa
Venue: Proceedings of the 2007 Third International IEEE Conference on Signal-Image Technologies and Internet-Based System (2007)

Wrapping of Web sources is known to be one of the key tasks in information integration problems. This paper proposes Wraplet, a wrapping language for extracting structured data from Web contents written in HTML. Unlike existing solutions, Wraplet is designed as a lightweight language in which users can write scripts for wrapping easily with text editors. Its simple syntax and the library of useful patterns help the user write wrapping descriptions by hand. We explain the motivation of its development and the language design and then shows the result of a preliminary experiment about applicability of the language to real Web sources. We conducted a statistical analysis and obtained the result that the applicability of Wraplet is more than 90% at the 95% confidence level in the experimental setting.
Developing Competence Assessment Procedure for Spinal Anaesthesia
Authors: Dajie Zhang, Dietrich Albert, Cord Hockemeyer, Dorothy Breen, Zsuzsanna Kulcsár, George Shorten, Annette Aboulafia, Erik Lövquist
Venue: Proceedings of the 2008 21st IEEE International Symposium on Computer-Based Medical Systems (2008)

Traditional approaches of assessment in the medical domain are insufficient for evaluating trainees' technical skills. Currently, many European medical training bodies are attempting to introduce competence-based training programmes for technical skills as well as other domains (e.g., communication, professional behaviour, clinical cognition). These efforts are limited due to the absence of appropriate assessment tools. Based on Competence-based Knowledge Space Theory (CbKST), a collaborative project MedCAP intends to develop a valid and reliable competence assessment procedure for one important medical skill, spinal anaesthesia. The paper briefly overviews the current states of training and assessment for medical procedural skills, describes the core ideas of CbKST, and introduces the ongoing project that will transfer the innovative approach of CbKST in personalized learning and competence assessment to the medical domain.
Automated Reasoning in Kleene Algebra
Authors: Peter Höfner, Georg Struth
Venue: Proceedings of the 21st international conference on Automated Deduction: Automated Deduction (2007)

It has often been claimed that model checking, special purpose automated deduction or interactive theorem proving are needed for formal program development. We demonstrate that off-the-shelf automated proof and counterexample search is an interesting alternative if combined with the right domain model. We implement variants of Kleene algebras axiomatically in Prover9/Mace4 and perform proof experiments about Hoare, dynamic, temporal logics, concurrency control and termination analysis. They confirm that a simple automated analysis of some important program properties is possible. Particular benefits of this approach include "soft" model checking in a first-order setting, cross-theory reasoning between standard formalisms and full automation of some (co)inductive arguments. Kleene algebras might therefore provide light-weight formal methods with heavy-weight automation.
Foundations of Onto-Relational Learning
Authors: Francesca A. Lisi, Floriana Esposito
Venue: Proceedings of the 18th international conference on Inductive Logic Programming (2008)

ILP is a major approach to Relational Learning that exploits previous results in concept learning and is characterized by the use of prior conceptual knowledge. An increasing amount of conceptual knowledge is being made available in the form of ontologies, mainly formalized with Description Logics (DLs). In this paper we consider the problem of learning rules from observations that combine relational data and ontologies, and identify the ingredients of an ILP solution to it. Our proposal relies on the expressive and deductive power of the KR framework $\mathcal{DL}$+log that allows for the tight integration of DLs and disjunctive Datalog with negation. More precisely we adopt an instantiation of this framework which integrates the DL $\mathcal{SHIQ}$ and positive Datalog. We claim that this proposal lays the foundations of an extension of Relational Learning, called Onto-Relational Learning, to account for ontologies.
Analysis of Adaptive Bandwidth Allocation in Wireless Networks with Multilevel Degradable Quality of Service
Authors: Chun-Ting Chou Kang G. Shin
Venue: IEEE Transactions on Mobile Computing (2004)

A wireless/mobile network supporting multilevel Quality of Service (QoS) is considered. In such a network, users or applications can tolerate a certain degree of QoS degradation. Bandwidth allocation to users can, therefore, be adjusted dynamically according to the underlying network condition so as to increase bandwidth utilization and service provider's revenue. However, arbitrary QoS degradation may be unsatisfactory or unacceptable to the users, hence resulting in their subsequent defection. Instead of only focusing on bandwidth utilization or blocking/dropping probability, two new user-perceived QoS metrics, degradation ratio and upgrade/degrade frequency, are proposed. A Markov model is then provided to derive these QoS metrics. Using this model, we evaluate the effects of adaptive bandwidth allocation on user-perceived QoS and show the existence of trade offs between system performance and user-perceived QoS. We also show how to exploit adaptive bandwidth allocation to increase system utilization (for the system administrator) with controlled QoS degradation (for the users). By considering various mobility patterns, the simulation results are shown to match our analytical results, demonstrating the applicability of our analytical model to more general cases.
A New BP Network Based on Improved PSO Algorithm and Its Application on Fault Diagnosis of Gas Turbine
Authors: Wei Hu, Jingtao Hu
Venue: Proceedings of the 4th international symposium on Neural Networks: Advances in Neural Networks, Part III (2007)

Aiming at improving the convergence performance of conventional BP neural network, this paper presents an improved PSO algorithm instead of gradient descent method to optimize the weights and thresholds of BP network. The strategy of the algorithm is that in each iteration loop, on every dimension d of particle swarm containing n particles, choose the particle whose velocity decreases most quickly to mutate its velocity according to some probability. Simulation results show that the new algorithm is very effective. It is successful to apply the algorithm to gas turbine fault diagnosis.
Locating dependence structures using search-based slicing
Authors: Tao Jiang, Nicolas Gold, Mark Harman, Zheng Li
Venue: Information and Software Technology (2008)

This paper introduces an approach to locating dependence structures in a program by searching the space of the powerset of the set of all possible program slices. The paper formulates this problem as a search-based software engineering problem. To evaluate the approach, the paper introduces an instance of a search-based slicing problem concerned with locating sets of slices that decompose a program into a set of covering slices that minimize inter-slice overlap. The paper reports the result of an empirical study of algorithm performance and result-similarity for Hill Climbing, Genetic, Random Search and Greedy Algorithms applied to a set of 12 C programs.
Roll your own city
Authors: Graham Whelan, George Kelly, Hugh McCabe
Venue: Proceedings of the 3rd international conference on Digital Interactive Media in Entertainment and Arts (2008)

The creation of detailed virtual urban environments is an increasingly common task being faced by both the film and games industries. It is a time-consuming and expensive process that requires artists to model vast amounts of geometric detail, including terrain, roads, buildings and other associated features. We demonstrate a system that allows an artist to rapidly generate 3D cityscapes of arbitrary size, complexity and layout. This is achieved by means of an interactive interface that enables close control over key parameters while the system procedurally generates the required detail in real time. The results can be viewed and edited or exported in a format suitable for use in 3D modelling packages and game engines.