ppxscal/embedding_network huggingface dataset:
Fractal Dimension of Trajectory as Invariant of Genetic Algorithms
Authors: Stefan Kotowski, Witold Kosiński, Zbigniew Michalewicz, Jakub Nowicki, Bartosz Przepiórkiewicz
Venue: Proceedings of the 9th international conference on Artificial Intelligence and Soft Computing (2006)

Convergence properties of genetic algorithms are investigated. For them some measures are introduced. A classification procedure is proposed for genetic algorithms based on a conjecture: the entropy and the fractal dimension of trajectories produced by them are quantities that characterize the classes of the algorithms. The role of these quantities as invariants of the algorithm classes is presented. The present approach can form a new method in construction and adaptation of genetic algorithms and their optimization based on dynamical systems theory.
Suboptimal Nonlinear Predictive Control with MIMO Neural Hammerstein Models
Authors: Maciej Ławryńczuk
Venue: Proceedings of the 21st international conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems: New Frontiers in Applied Artificial Intelligence (2008)

This paper describes a computationally efficient (suboptimal) nonlinear Model Predictive Control (MPC) algorithm with neural Hammerstein models. The Multi-Input Multi-Output (MIMO) dynamic model contains a steady-state nonlinear part realised by a set of neural networks in series with a linear dynamic part. The model is linearised on-line, as a result the MPC algorithm solves a quadratic programming problem. The algorithm gives control performance similar to that obtained in nonlinear MPC, which hinges on non-convex optimisation.
Evolving Committees of Support Vector Machines
Authors: D. Valincius, A. Verikas, M. Bacauskiene, A. Gelzinis
Venue: Proceedings of the 5th international conference on Machine Learning and Data Mining in Pattern Recognition (2007)

The main emphasis of the technique developed in this work for evolving committees of support vector machines (SVM) is on a two phase procedure to select salient features. In the first phase, clearly redundant features are eliminated based on the paired t-test comparing the SVM output sensitivity-based saliency of the candidate and the noise feature. In the second phase, the genetic search integrating the steps of training, aggregation of committee members, and hyper-parameter as well as feature selection into the same learning process is employed. A small number of genetic iterations needed to find a solution is the characteristic feature of the genetic search procedure developed. The experimental tests performed on five real world problems have shown that significant improvements in correct classification rate can be obtained in a small number of iterations if compared to the case of using all the features available.
Fractal Fitting Research on Stock Prices
Authors: Lin Yong, Tong Xin
Venue: Proceedings of the 2008 Congress on Image and Signal Processing, Vol. 4 - Volume 04 (2008)

In this paper, we mainly study the law of stock price changes and the fitting method of it. After introducing the key point of fractal and Genetic Algorithm, we focus on explaining the inverse problems of piecewise fractal interpolation theoretically first. Then, based on the theory, we analyze a large amount of stock price data, calculate all the values of parameters in the model, and finally get an image of the attractor. The result is comparatively satisfying, so that this algorithm is very effective.
Quotients over Minimal Type Theory
Authors: Maria Emilia Maietti
Venue: Proceedings of the 3rd conference on Computability in Europe: Computation and Logic in the Real World (2007)

We consider an extensional version, called qmTT, of the intensional Minimal Type Theory mTT, introduced in a previous paper with G. Sambin, enriched with proof-irrelevance of propositions and effective quotient sets. Then, by using the construction of total setoid à la Bishop we build a model of qmTT over mTT.The design of an extensional type theory with quotients and its interpretation in mTT is a key technical step in order to build a two level system to serve as a minimal foundation for constructive mathematics as advocated in the mentioned paper about mTT.
Situated Cognition in the Semantic Web Era
Authors: Paul Compton, Byeong Ho Kang, Rodrigo Martinez-Bejar, Mamatha Rudrapatna, Arcot Sowmya
Venue: Proceedings of the 16th international conference on Knowledge Engineering: Practice and Patterns (2008)

The challenge of situated cognition mounted by Clancey and others 20 years ago seems to have had little impact on the technical development of AI systems. However, the hopes for the Semantic Web also seem far from being realised in much the same way as too much was expected of expert systems, and again this seems to be because of the situated nature of knowledge. In this paper we claim that a possible way forward is to always ground the use of concepts in real data in particular contexts. We base this claim on experience with Ripple-Down Rule systems.
Statistical Deformation Models of Breast Compressions from Biomechanical Simulations
Authors: C. Tanner, J. H. Hipwell, D. J. Hawkes
Venue: Proceedings of the 9th international workshop on Digital Mammography (2008)

This paper describes the construction of 3D statistical deformation models (SDMs) from biomechanical simulations. The method was used to capture the average breast motion and its variability due to compressing it between two plates as performed for X-ray mammography. One SDM described the motion from the compressed to the undeformed state. Another SDM captured the deformation difference due to variations in patient positioning and compression magnitude. Such models could prove useful for guiding the development of algorithms to register serial X-ray mammograms. The SDMs are based on simulating plausible breast compressions for a population of 20 patients via finite element models created from segmented 3D MR breast images. Tissue properties and boundary conditions were varied according to reported values. Three compression configurations (called current, prior1, prior2) were simulated per breast. The associated displacement fields were mapped into a common space and SDMs were generated using principle component analysis. Leave-one-patient-out tests showed that these models can reduce the mean error of unseen deformations on average by 87% (19.35 mm to 2.49 mm for current-to-undeformed, 13.49 mm to 1.70 mm for current-to-prior) when using the first 16 modes of variation.
Problems, Workarounds and Possible Solutions Implementing the Singleton Pattern with C++ and OpenMP
Authors: Michael Suess, Claudia Leopold
Venue: Proceedings of the 3rd international workshop on OpenMP: A Practical Programming Model for the Multi-Core Era (2007)

Programs written in C++ and OpenMP are still relatively rare. This paper shows some problems with the current state of the OpenMP specification regarding C++. We illustrate the problems with various implementations of the singleton pattern, measure their performance and describe workarounds and possible changes to the specification. The singletons are available in the AthenaMP open-source project.
Towards Semantic Social Networks
Authors: Jason J. Jung, Jérôme Euzenat
Venue: Proceedings of the 4th European conference on The Semantic Web: Research and Applications (2007)

Computer manipulated social networks are usually built from the explicit assertion by users that they have some relation with other users or by the implicit evidence of such relations (e.g., co-authoring). However, since the goal of social network analysis is to help users to take advantage of these networks, it would be convenient to take more information into account. We introduce a three-layered model which involves the network between people (social network), the network between the ontologies they use (ontology network) and a network between concepts occurring in these ontologies. We explain how relationships in one network can be extracted from relationships in another one based on analysis techniques relying on this network specificity. For instance, similarity in the ontology network can be extracted from a similarity measure on the concept network. We illustrate the use of these tools for the emergence of consensus ontologies in the context of semantic peer-to-peer systems.
The Effect of Training Sample Size on Performance of Mass Detection
Authors: Michiel Kallenberg, Nico Karssemeijer
Venue: Proceedings of the 9th international workshop on Digital Mammography (2008)

In the development of a computer-aided detection (CAD) system a large database containing training samples is of major importance. However, as obtaining training samples may be costly, it is useful to evaluate the effect of training sample size on performance of mass detection and classification. In this paper we investigate the effect of the number of masses as well as the number of normals in the training database. In particular we are interested in the performance of the CAD system operating at high specificity. We use a combination of databases comprising over 5000 cases. Each mammogram is classified multiple times, using neural networks trained with a different number of training samples. To measure performance free-response operator characteristic (FROC)-curves are computed. The mean sensitivity in the interval between 0.05 and 0.5 false positive (FP) marks/image is taken as a performance measure. It was found that performance steadily increases with adding masses to the training database. Even with 555 mass cases a plateau was not yet reached. For normal cases, however, we found that a large number of normals was not needed. The maximal performance was reached with around 700 cases. These results show that optimal training requires a lot of malignant cases, whereas the influence of the number of normal cases is less.
Normative Consequence: The Problem of Keeping It Whilst Giving It up
Authors: Audun Stolpe
Venue: Proceedings of the 9th international conference on Deontic Logic in Computer Science (2008)

The problem of deriving implicit norms from explicitly given ones is at the heart of normative reasoning. In abstracto the problem is that of formalizing a plausible consequence relation taking norms to norms. I argue that any such relation should allow norms to be chained, even when the consequent of one is strictly stronger than the antecedent of another--i. e. even if logical inference is required to complete the chain. However, since it is commonly agreed that the set of items classically entailed by an obligatory proposition are not in general obligatory, we are left with the following problem: How do reserve the right to reason classically for the purpose of chaining, whilst not committing to the view that all items entailed by a norm are obligatory in the same sense. I shall argue that the problem can be given a natural solution with reference to different uses of a norm in a normative system.
Autonomous Forex Trading Agents
Authors: Rui Pedro Barbosa, Orlando Belo
Venue: Proceedings of the 8th industrial conference on Advances in Data Mining: Medical Applications, E-Commerce, Marketing, and Theoretical Aspects (2008)

In this paper we describe an infrastructure for implementing hybrid intelligent agents with the ability to trade in the Forex Market without requiring human supervision. This infrastructure is composed of three modules. The "Intuition Module", implemented using an Ensemble Model, is responsible for performing pattern recognition and predicting the direction of the exchange rate. The "A Posteriori Knowledge Module", implemented using a Case-Based Reasoning System, enables the agents to learn from empirical experience and is responsible for suggesting how much to invest in each trade. The "A Priori Knowledge Module", implemented using a Rule-Based Expert System, enables the agents to incorporate non-experiential knowledge in their trading decisions. This infrastructure was used to develop an agent capable of trading the USD/JPY currency pair with a 6 hours timeframe. The agent's simulated and live trading results lead us to believe our infrastructure can be of practical interest to the traditional trading community.
Distributed Collaborative Filtering for Robust Recommendations Against Shilling Attacks
Authors: Ae-Ttie Ji, Cheol Yeon, Heung-Nam Kim, Geun-Sik Jo
Venue: Proceedings of the 20th conference of the Canadian Society for Computational Studies of Intelligence on Advances in Artificial Intelligence (2007)

Recommender systems enable a user to decide which information is interesting and valuable in our world of information overload. Collaborative Filtering (CF), one of the most successful technologies in recommender systems suffers from improper use of personal information and the incredibility of recommendations. To deal with these issues, we have been focusing on the trust relationships between individuals, i.e. web of trust, especially for protecting the recommender system against profile injection attack. Based on trust propagation scheme, we proposed TCFMA architecture which is added agent-based scheme obtaining attack resistance property as well as improving the efficiency of distributed computing. In web of trust, users' personal agents find a unique migration path made up of latent neighborhoods and reduce search scope to a reasonable level for mobile agents by using the Advogato algorithm. The experimental evaluation on Epinions.com datasets shows that the proposed method brings significant advantages in terms of dealing with profile injection attack without any loss of prediction quality.
On a Hybrid Symbolic-Connectionist Approach for Modeling the Kinematic Robot Map - and Benchmarks for Computer Algebra
Authors: Jochen Pfalzgraf
Venue: Proceedings of the 9th AISC international conference, the 15th Calculemas symposium, and the 7th international MKM conference on Intelligent Computer Mathematics (2008)

The kinematics model of a robot arm (we are considering open kinematic chains) is described by a corresponding robot map having the configuration space as its domain and the workspace as codomain. In other words, the robot map assigns to every configuration of the joint parameters a unique point of the workspace of the robot arm. We briefly discuss the general introduction of the robot map where the parameters of a translational joint are represented by points of the real line and the parameters of a rotational joint by points of the unit circle in the real plane, respectively. Thus, in general, a concrete joint configuration (point of the configuration space) is an element of an abelian Lie group being a direct product of some copies of the real line and the unit circle. The position and orientation of the endeffector of a robot arm is represented by an element of the euclidean motion group of real 3-space. The standard problems like the direct kinematics problem, the inverse kinematics problem and the singularity problem can easily be defined.
Speech Enhancement in Noisy Environments for Video Retrieval
Authors: Huiyu Zhou, Abdul Sadka, Richard M. Jiang
Venue: Proceedings of the 2008 Ninth International Workshop on Image Analysis for Multimedia Interactive Services (2008)

In this paper, we propose a novel spectral subtraction approach for speech enhancement via maximum likelihood estimate (MLE). This scheme attempts to simulate the probability distribution of useful speech signals and hence maximally reduce the noise. To evaluate the quality of speech enhancement, we extract cepstral features from the enhanced signals, and then apply them to a dynamic time warping framework for similarity check between the clean and filtered signals. The performance of the proposed enhancement method is compared to that of other classical techniques. The entire framework does not assume any model for the background noise and does not require any noise training data.
Backhoe, a Packet Trace and Log Browser
Authors: Sergey Bratus, Axel Hansen, Fabio Pellacini, Anna Shubina
Venue: Proceedings of the 5th international workshop on Visualization for Computer Security (2008)

We present Backhoe, a tool for browsing packet trace or other event logs that makes it easy to spot "statistical novelties" in the traffic, i.e. changes in the character of frequency distributions of feature values and in mutual relationships between pairs of features. Our visualization uses feature entropy and mutual information displays as either the top-level summary of the dataset or alongside the data. Our tool makes it easy to switch between absolute and conditional metrics, and observe their variations at a glance. We successfully used Backhoe for analysis of proprietary protocols.
On the design of 2-DOF robot grippers
Authors: Ion Simionescu, Ion Ion
Venue: Proceedings of the 9th WSEAS International Conference on International Conference on Automation and Information (2008)

The gripper constitutes the end of the kinematic chain of an industrial robot and makes possible the interactions with the work environment. Although universal grippers with wide clamping ranges can be used for varied object shapes, in many cases they must be adapted to specific work-pieces shapes. The mechanical two-finger grippers with a single degree of freedom are the most usual device used in industry today. The fingers have symmetrical motions with respect to the gripper axis. In some applications, the position of the work piece with respect to the gripper frame may not be very precisely. It is the case of the unmachined or semi-finished parts in the interoperations transfer. A particular category of grippers for industrial robots has two degrees of freedom and a single driving motor. The relative positions of the component elements depend on the frictional coefficients between work piece and fingers and on the initial position of the work piece with respect to the gripper's frame. The paper presents some considerations on the design of the 2-DOF robot grippers.
A Cache Management Method for the Mobile Music Delivery System: JAMS
Authors: Hiroaki Shibata, Satoshi Tomisawa, Hiroki Endo, Yuka Kato
Venue: Proceedings of the 19th international conference on Database and Expert Systems Applications (2008)

The authors have proposed a music delivery system JAMS (JAMais vu System), which uses ad-hoc networks with mobile devices for the localization services. In this paper, they focus on a cache management scheme for JAMS to deliver music files efficiently. The proposed scheme makes it possible to manage cache files robustly by using adaptive cache delivery according to each node request. In addition, the authors conduct a simulation experiment and obtain access failure ratio of music files under various system conditions. The simulation results indicate that the proposed scheme is suitable for the system using localization services.
Engineering Autonomic Electronic Institutions
Authors: Josep Lluís Arcos, Juan A. Rodríguez-Aguilar, Bruno Rosell
Venue: Engineering Environment-Mediated Multi-Agent Systems: International Workshop, EEMMAS 2007, Dresden, Germany, October 5, 2007. Selected Revised and Invited Papers (2008)

There is a growing interest in the study and development of self-* systems motivated by the need for information systems capable of self-management in distributed, open, and dynamic scenarios. Unfortunately,there is a lack of frameworks that support the intricate task of developing self-* systems. We try to make headway along this direction by introducing a framework, EIDE-*, to support the engineering of a particular type of self-* systems, namely autonomic electronic institutions: regulated environments capable of adapting their norms to comply with institutional goals despite the varying behaviours of their participating agents.
What Is Commitment? Physical, Organizational, and Social (Revised)
Authors: Carl Hewitt
Venue: Coordination, Organizations, Institutions, and Norms in Agent Systems II: AAMAS 2006 and ECAI 2006 International Workshops, COIN 2006 Hakodate, Japan, May 9, 2006 Riva del Garda, Italy, August 28, 2006. Revised Selected Papers (2007)

This paper uses Participatory Semantics to explicate commitment. Information expresses the fact that a system is in a certain configuration that is correlated to the configuration of another system. Any physical system may contain information about another physical system.For the purposes of this paper, physical commitment is defined to be information pledgedabout physical systems (situated at a particular place and time). This use of the term physical commitment is currently nonstandard.Note that commitment is defined for whole physical system; not just a participant or process.Organizational and social commitments can be analyzed in terms of physical commitments. For example systems that behave as scientific communities can have commitments for monotonicity, concurrency, commutativity, pluralism, skepticism, and provenance.Speech Act Theory has attempted to formalize the semantics of some kinds of expressions for commitments. Participatory Semantics for commitment can overcome some of the lack of expressiveness and generality in Speech Act Theory.
An Embedded SoC System IP to Trace Object and Distance
Authors: Eun-Tack Oh, Kwang-Sung Jung, Sung-Min Lee, Cheol-Hong Moon
Venue: Proceedings of the 4th international conference on Intelligent Computing: Advanced Intelligent Computing Theories and Applications - with Aspects of Theoretical and Methodological Issues (2008)

This study created an An Embedded SoC System IP to Trace Object and Distance. The moving object tracing system uses video input, image separation of moving objects and block-matching. The distance detection system receives stereo video input through 2 CCD cameras. Using a decoder, the image is changed to the YCbCr4:2:2 for- mat and only the Y signal is saved in the 4*256*8bit shift register of the Dual-Port SRAM. When the fourth line of the axis (256 pixels per line) data of each video is saved in the shift register, each standard block and block-matching are set and stereo-matching is carried out. The matching range is set to the 100 pixels to the right of the standard block coordi- nates. As a result of the matching procedure, the Depth value, which is the distance information, is saved in SRAM, and the Depth Map is made and output to the TFT-LCD screen.abstract SoC system.
Exploring the Acceptability of Delayed Reciprocity in Peer-to-Peer Networks
Authors: Jenneke Fokker, Huib Ridder, Piet Westendorp, Johan Pouwelse
Venue: Proceedings of the 3rd international conference on Persuasive Technology (2008)

Using Peer-to-Peer (P2P) technology for distributing Television programs to many viewers simultaneously can only be successful if users cooperate voluntarily and massively. The current BitTorrent protocol only enforces instantaneous bandwidth exchange within the context of one video file. We explore ways to induce user cooperation flexible over time and over type of resources. Essential resources for a P2P system are: bandwidth, injections, moderations, and appreciations. Social exchange theory is taken as a background for addressing the inducement of cooperation in a P2P-TV system called Tribler. This theory helps to explain how the acceptability of delayed reciprocity can be influenced by the specificity of the exchangeable resources and by the relationship types between individuals. This paper presents the results from a study among 36 participants about the acceptability of delayed reciprocity in a P2P-TV system, under varying relationship types and specificity of exchangeable resources.