ppxscal/embedding_network huggingface dataset:
Relationships between the Learning Strategies, Mental Models of Learning and Learning Orientations of Post-secondary Students in Hong Kong
Authors: Dennis C. Law, Jan H. Meyer
Venue: Proceedings of the 1st international conference on Hybrid Learning and Education (2008)

The present study is based on analyses of data resulting from an administration of a Chinese translation of the Inventory of Learning Styles (ILS) to a large sample of post-secondary students in Hong Kong. The ILS is a research instrument developed by Vermunt to capture variation in contrasting forms of learning strategies, mental models of learning, and learning orientations. In what are believed to be the first analyses of ILS data obtained in a Chinese response-context, empirical support is found for the theoretical model that underpins the ILS. Findings also confirm the posited central explanatory role of regulation strategies. In particular, students' processing strategies are found to be most directly influenced by their regulation strategies, while the influence of students' mental models of learning and students' learning orientations on their processing strategies is mostly indirect, via students' regulation strategies.
Reasoning with Conditional Preferences Across Attributes
Authors: Shaoju Chen, Scott Buffett, Michael W. Fleming
Venue: Proceedings of the 20th conference of the Canadian Society for Computational Studies of Intelligence on Advances in Artificial Intelligence (2007)

Before an autonomous agent can perform automated negotiation on behalf of a user in an electronic commerce transaction, the user's preferences over the set of outcomes must be learned as accurately as possible. This paper presents a structure, a Conditional Outcome Preference Network (COP-network), for modeling preferences directly elicited from a user. The COP-network then expands to indicate all preferences that can be inferred as a result. The network can be easily checked for consistency and redundancy, and can be used to determine quickly whether one outcome is preferred over another. An important feature of the COP-network is that conditional preferences, where a user's preference over outcomes depends on whether particular attribute values are included, can be modeled and inferred as well. If the agent also knows the user's utilities for some of the possible outcomes, then these can be considered in the COP-network as well. Three techniques for estimating utilities based on the specified preferences and utilities are described. One such technique, which works by first estimating utilities for long chains of outcomes for which preferences are known, is shown to be the most effective.
Business performance forecasting of convenience store based on enhanced fuzzy neural network
Authors: S. G. Li, Z. M. Wu
Venue: Neural Computing and Applications (2008)

Reliable business performance forecasting of convenience store (CVS) can not only help in making the correct local selection decision but also in decreasing the store cost and thereby enlarging the profit significantly. Therefore, the main aim of this paper is to design an enhanced fuzzy neural network (EFNN)-based predictor to forecast the business performance of CVS. Without considering relevant domain knowledge, traditional fuzzy neural networks suffer from the problem of low accuracy of forecasting unseen examples. Moreover, traditional fuzzy neural networks have to turn weights with a kind of time-consuming gradient steepest descent training algorithm. Considering the relationship between the evaluation factors globally, we devise the EFNN which assigns connection weights based on the expert domain knowledge without painstakingly and repeatedly turning them. Furthermore, by generating and refining the activation function based on genetic algorithm, our EFNN can provide comprehensive and accurate activation functions and fit a wider range of nonlinear models. By experimenting our methods with several benchmark methods, the proposed methods are found to have an optimal accuracy in forecasting the business performance of CVS with a permanent good performance.
Diverse Evolutionary Neural Networks Based on Information Theory
Authors: Kyung-Joong Kim, Sung-Bae Cho
Venue: Neural Information Processing: 14th International Conference, ICONIP 2007, Kitakyushu, Japan, November 13-16, 2007, Revised Selected Papers, Part II (2008)

There is no consensus on measuring distances between two different neural network architectures. Two folds of methods are used for that purpose: Structural and behavioral distance measures. In this paper, we focus on the later one that compares differences based on output responses given the same input. Usually neural network output can be interpreted as a probabilistic function given the input signals if it is normalized to 1. Information theoretic distance measures are widely used to measure distances between two probabilistic distributions. In the framework of evolving diverse neural networks, we adopted information-theoretic distance measures to improve its performance. Experimental results on UCI benchmark dataset show the promising possibility of the approach.
Non-equilibrium Thermodynamics, Thermomechanics, Geodynamics
Authors: Klaus Regenauer-Lieb, Bruce Hobbs, Alison Ord, Dave A. Yuen
Venue: Proceedings of the 7th international conference on Computational Science, Part I: ICCS 2007 (2007)

The subject of non-equilibrium thermodynamics is now quite old, dating back to Prigogine, Biot and Truesdell in the 1950's and 1960's. It has had a resurgence in the physical sciences in the past five years largely due to a consolidation of ideas on thermodynamics as a whole and to advances in computer speeds. Non-equilibrium thermodynamics has now advanced to a stage where it forms an umbrella approach to understanding and modelling coupled phenomena in Earth Sciences. Currently, approaches are pioneered independently in geodynamics, seismology, material sciences (solid mechanics), atmospheric and marine sciences (fluid dynamics) and the chemical sciences. We present a first attempt at consolidating some ideas and show a simple example with potential significance for geodynamics, structural geology and seismology.
A New Ear Recognition Approach for Personal Identification
Authors: Sepehr Attarchi, Masoud S. Nosrati, Karim Faez
Venue: Proceedings of the 4th international conference on Intelligent Computing: Advanced Intelligent Computing Theories and Applications - with Aspects of Theoretical and Methodological Issues (2008)

Personal identification based on the ear structure is a new biometrics. In this paper, a new ear recognition method is proposed. For the purpose of segmentation, we apply the Canny edge detector to the ear image. Then the longest path in the edge image is extracted and selected as the outer boundary of the ear. By selecting the top, bottom, and left point of the detected boundary, we form a triangle with the selected points as its vertices. Further we calculate the barycenter of the triangle and select it as a reference point in all images. Then the ear region is extracted from the entire image using a predefined window centered at the reference point. For the recognition approach, we improve a previous method based on PCA by using 2D wavelet in three different directions and extracting three different coefficient matrices. Experimental results show the effectiveness of our proposed method.
The MIT magnetic-core memory
Authors: William N. Papian
Venue: Papers and discussions presented at the Dec. 8-10, 1953, eastern joint AIEE-IRE computer conference: information processing systems---reliability and requirements (1953)

One recent development which is significantly raising the reliability of today's high-speed automatic digital computer is the multicoordinate magnetic-core memory. Two banks of 32 by 32 by 17 magnetic-core memory have been in full-time operation in the Whirlwind I Computer for some months. A description of the units and of the tests and operational data available on them will be preceded by a short review of operating principles of this type of memory.
Fuzzy Spatial Position between Objects in Image Retrieval
Authors: Hui Liu, Cai-ming Zhang
Venue: Proceedings of the 2008 International Symposiums on Information Processing (2008)

As we all know, ambiguity of spatial position between objects is still a difficult problem for image classification and retrieval. In this paper, a fuzzy spatial position definition method between objects based on Markov Random Field (MRF) is presented. This framework is a kind of fuzzy pattern-matching approach, which consists of comparing an object to a fuzzy set and representing the degree of position satisfaction to a reference object, moreover, the intricate relationships can be represented by Fuzzy Attributed Relational Graphs (FARGs) in this method. Finally, by comparing the performance of this approach with conventional techniques, effectiveness of this method to content-based image retrieval is illuminated.
PRT simulation in an immersive virtual world
Authors: Cristina V. Lopes, Anton Popov, Lorraine Kan, Ricardo Morla
Venue: Proceedings of the 1st international conference on Simulation tools and techniques for communications, networks and systems & workshops (2008)

Immersive virtual world environments, such as Second Life&trade; (SL), have the potential to dramatically improve the process of analyzing usability within technically correct system simulations, long before the system is built. We report our findings with the SL simulation of a Personal Rapid Transit (PRT) system. The SL model and simulation were done according to the original technical specifications. In interacting with this simulation, the system designers were able to identify several usability issues that would have gone unnoticed in a non-immersive simulation environment. Namely: (1) a problem with the design of the offramp to the station; (2) further requirements for the design of the top of the vehicles, so that the suspended track is out of direct sight of the people inside; (3) further safety requirements for dealing with unexpected obstacles along the path. While all of these issues would have been identified upon deployment of the physical prototype, the contribution of our work is to show how usability issues like these can now be identified much earlier, using simulations in a virtual world.
The Effect of Behavior Change on Honesty Checking in Peer-to-Peer Systems
Authors: Farag Azzedin, Ahmad Ridha
Venue: Proceedings of the 2008 Sixth Annual Conference on Privacy, Security and Trust (2008)

Reputation systems aim to reduce the risk of loss due to untrustworthy peers. This loss is aggravated by dishonest recommenders trying to pollute the recommendation network. The objective of an honesty checking mechanism is to detect dishonest recommenders. Existing honesty checking mechanisms assume that contradicting recommendations are due to the dishonesty of the recommenders. However, such difference may be also due to the behavior change of the target peer. This paper shows the effect of such behavior change on the performance of existing honesty checking mechanisms. To the best of our knowledge, this is the first attempt at linking the behavior change to honesty checking.
Weighting Individual Opinions in Group Decision Making
Authors: José Luis García-Lapresta
Venue: Proceedings of the 4th international conference on Modeling Decisions for Artificial Intelligence (2007)

In this paper we introduce a multi-stage decision making procedure where decision makers sort the alternatives by means of a fixed set of linguistic categories, each one has associated a numerical score. First we average the scores obtained by each alternative and we consider the associated collective preference. Then, we obtain a distance between each individual preference and the collective one through the Euclidean distance among the individual and collective scoring vectors. Taking into account these distances, we measure the agreement in each subset of decision makers, and a weight is assigned to each decision maker: his/her overall contribution to the agreement. Those decision makers whose overall contribution to the agreement are not positive are expelled and we re-initiate the decision procedure with only the opinions of the decision makers which positively contribute to the agreement. The sequential process is repeated until it determines a final subset of decision makers where all of them positively contribute to the agreement. Then, we apply a weighted procedure where the scores each decision maker indirectly assigns to the alternatives are multiplied by the weight of the corresponding decision maker, and we obtain the final ranking of the alternatives.
Theoretical aspects related to the design of a mechatronic system for recovery of the disabled persons
Authors: Petre Lucian Seiciu, Ioan Dan Filipoiu, Tiberiu Laurian
Venue: Proceedings of the 9th WSEAS International Conference on International Conference on Automation and Information (2008)

Human walking is theoretically explained by two prevailing, but contradictory theories. The first theory called "The Six Determinants Of Gait" (SDG) aims to minimize the energetic cost of locomotion by reducing the vertical displacement of the body center of mass (COM). The second theory called "The Inverted Pendulum Analogy" (IPA) suggests that walking is a movement combination of two pendulums: the inverted pendulum for the stance leg and a direct pendulum for the swing leg. Therefore, results that COM describes a quasi-sinusoid curve. The main evidence against SDG theory is that a flattened COM trajectory increases muscle work and force requirements. The IPA theory analysis shows that it predicts no work or force requirements. These shortcomings may be resolved through a new theory: "The Dynamic Walking Theory" DWT. These theories describe more or less appropriate walking of healthy persons. The paper presents some theoretical aspects to be considered at the design of a mechatronic system for the locomotory disabled persons.
2nd International Workshop on Dynamic Software Product Lines DSPL 2008
Authors: Svein Hallsteinsen, Mike Hinchey, Sooyong Park, Klaus Schmid
Venue: Proceedings of the 2008 12th International Software Product Line Conference (2008)

In emerging domains such as ubiquitous computing, service robotics, unmanned space and water exploration, and medical and life-support devices, software is becoming increasingly complex with extensive variation in both requirements and resource constraints. Developers face growing pressure to deliver high-quality software with additional functionality, on tight deadlines, and more economically.
A One Class Classifier for Signal Identification: A Biological Case Study
Authors: Vito Gesù, Giosuè Bosco, Luca Pinello
Venue: Proceedings of the 12th international conference on Knowledge-Based Intelligent Information and Engineering Systems, Part III (2008)

The paper describes an application of a one-class KNN to identify different signal patterns embedded in a noise structured background. The problem become harder whenever only one pattern is well represented in the signal, in such cases one class classifier techniques are more indicated. The classification phase is applied after a preprocessing phase based on a Multi Layer Model (MLM) that provides a preliminary signal segmentation in an interval feature space. The one-class KNN has been tested on synthetic data that simulate microarray data for the identification of nucleosomes and linker regions across DNA. Results have shown a good recognition rate on synthetic data for nucleosome and linker regions.
A Hardware-Assisted Realtime Attack on A5/2 Without Precomputations
Authors: Andrey Bogdanov, Thomas Eisenbarth, Andy Rupp
Venue: Proceedings of the 9th international workshop on Cryptographic Hardware and Embedded Systems (2007)

A5/2 is a synchronous stream cipher that is used for protecting GSM communication. Recently, some powerful attacks [2,5] on A5/2 have been proposed. In this contribution we enhance the ciphertext-only attack [2] by Barkan, Biham, and Keller by designing special-purpose hardware for generating and solving the required systems of linear equations. For realizing the LSE solver component, we use an approach recently introduced in [5,6] describing a parallelized hardware implementation of the Gauss-Jordan algorithm. Our hardware-only attacker immediately recovers the initial secret state of A5/2 - which is sufficient for decrypting all frames of a session - using a few ciphertext frames without any precomputations and memory. More precisely, in contrast to [2] our hardware architecture directly attacks the GSM speech channel (TCH/FS and TCH/EFS). It requires 16 ciphertext frames and completes the attack in about 1 second. With minor changes also input from other GSM channels (e.g., SDCCH/8) can be used to mount the attack.
Adaptive explicit decision functions for probabilistic design and optimization using support vector machines
Authors: Anirban Basudhar, Samy Missoum
Venue: Computers and Structures (2008)

This article presents a methodology to generate explicit decision functions using support vector machines (SVM). A decision function is defined as the boundary between two regions of a design space (e.g., an optimization constraint or a limit-state function in reliability). The SVM-based decision function, which is initially constructed based on a design of experiments, depends on the amount and quality of the training data used. For this reason, an adaptive sampling scheme that updates the decision function is proposed. An accurate approximated explicit decision functions is obtained with a reduced number of function evaluations. Three problems are presented to demonstrate the efficiency of the update scheme to explicitly reconstruct known analytical decision functions. The chosen functions are the boundaries of disjoint regions of the design space. A convergence criterion and error measure are proposed. The scheme is also applied to the definition of an explicit failure region boundary in the case of the buckling of a geometrically nonlinear arch.
Intelligent Agents Living in Social Virtual Environments --- Bringing Max into Second Life
Authors: Erik Weitnauer, Nick M. Thomas, Felix Rabe, Stefan Kopp
Venue: Proceedings of the 8th international conference on Intelligent Virtual Agents (2008)

When developing cognitive agents capable of interacting with humans, it is often challenging to provide a suitable environment in which agent and user are cosituated. This paper presents a straightforward approach to use Second Life (SL) [1] as a persistent, "near natural", and socially rich environment for research on autonomous agents in complex surroundings, learning social skills, and how they are perceived by humans.
An approach to enterprise process dynamic modeling supporting enterprise process evolution
Authors: Lida Xu, Wenan Tan, Hongyuan Zhen, Weiming Shen
Venue: Information Systems Frontiers (2008)

This study presents an evolutionary approach to support dynamic enterprise modeling for enterprise process cooperative scheduling and management. In this paper, an evolutionary dynamic enterprise process modeling method was proposed from the concepts of enterprise process evolution to zero-time enterprise modeling and layered complex enterprise modeling. Based on an autonomous agent development platform, an agent-based enterprise collaborative modeling environment has been implemented by integrating several software resource agents that wrap main function modules of EPMS. Scheduling strategies, algorithms, and process-driven cooperative scheduling mechanism are also discussed.
Mathematical Morphology in the HSI Colour Space
Authors: M. C. Tobar, C. Platero, P. M. González, G. Asensio
Venue: Proceedings of the 3rd Iberian conference on Pattern Recognition and Image Analysis, Part II (2007)

Mathematical Morphology is a powerful non-linear image analysis techniques based on lattice theory. The definitions of morphological operators need an ordered lattice algebraic structure. In order to apply these operators to the colour images it is required, on one hand the choice of a suitable colour space representation and on the other hand, to establish an order in the colour space providing an ordered lattice algebraic structure. The HSI space represents the colour in terms of physical attributes that separate the achromatic component from the chromatic one and it yields a more intuitive description of the colour properties than the RGB space. The suggested order weighs the hue and the intensity according to the saturation level: it has a lexicographical order in which the intensity has priority if the saturation is high, and the hue has priority if the saturation is low.
A case study of online project-based mobile learning: Beer King
Authors: Yi-Hui Liu, Shi-Jer Lou, Rong-Jyue Fang, Chung-Ping Lee, Yuan-Chang Guo, Hua-Lin Tsai
Venue: Proceedings of the 8th WSEAS International Conference on Multimedia systems and signal processing (2008)

The purpose of this study is to discover the elementary school students' online project-based mobile learning results of "Beer King". Nine sixth-grade pupils of an elementary school in Pingtung City were targeted, and they participated a whole semester's online project-based mobile learning as teamwork. The content analysis adopted in this study revealed their learning performance, and the conclusions are as the following: 1. The highest percentage of the students' chosen topics was online project discoveries and constructions followed by project marketing and investigation, and topic-based visits and feedback. 2. The websites designed and finished by the students contain the introduction of beer, key features, beer manufacturer visit, marketing, learning and sharing. 3. The construction of topic-based websites not only improves people's IT knowledge but also generates more browsers to the website which enhances the effectiveness and advantages of online mobile learning.
Sketch recognition in interspersed drawings using time-based graphical models
Authors: T. M. Sezgin, R. Davis
Venue: Computers and Graphics (2008)

Sketching is a natural mode of interaction used in a variety of settings. With the increasing availability of pen-based computers, sketch recognition has gained attention as an enabling technology for natural pen-based interfaces. Previous work in sketch recognition has shown that in certain domains the stroke orderings used when drawing objects contain temporal patterns that can aid recognition. So far, systems that use temporal information for recognition have assumed that objects are drawn one at a time. This paper shows how this assumption can be relaxed to permit temporal interspersing of strokes from different objects. We describe a statistical framework based on dynamic Bayesian networks that explicitly models the fact that objects can be drawn interspersed. We present recognition results for hand-drawn electronic circuit diagrams, showing that handling interspersed drawing provides a significant increase in accuracy.
A Tactic Language for Hiproofs
Authors: David Aspinall, Ewen Denney, Christoph Lüth
Venue: Proceedings of the 9th AISC international conference, the 15th Calculemas symposium, and the 7th international MKM conference on Intelligent Computer Mathematics (2008)

We introduce and study a tactic language, Hitac, for constructing hierarchical proofs, known as hiproofs. The idea of hiproofs is to superimpose a labelled hierarchical nesting on an ordinary proof tree. The labels and nesting are used to describe the organisation of the proof, typically relating to its construction process. This can be useful for understanding and navigating the proof. Tactics in our language construct hiproof structure together with an underlying proof tree. We provide both a big-step and a small-step operational semantics for evaluating tactic expressions. The big-step semantics captures the intended meaning, whereas the small-step semantics hints at possible implementations and provides a unified notion of proof state. We prove that these notions are equivalent and construct valid proofs.