ppxscal/embedding_network huggingface dataset:
Heuristics for Planning with Action Costs Revisited
Authors: Emil Keyder, Héctor Geffner
Venue: Proceeding of the 2008 conference on ECAI 2008: 18th European Conference on Artificial Intelligence (2008)

We introduce a simple variation of the additive heuristic used in the HSP planner that combines the benefits of the original additive heuristic, namely its mathematical formulation and its ability to handle non-uniform action costs, with the benefits of the relaxed planning graph heuristic used in FF, namely its compatibility with the highly effective enforced hill climbing search along with its ability to identify helpful actions. We implement a planner similar to FF except that it uses relaxed plans obtained from the additive heuristic rather than those obtained from the relaxed planning graph. We then evaluate the resulting planner in problems where action costs are not uniform and plans with smaller overall cost (as opposed to length) are preferred, where it is shown to compare well with cost-sensitive planners such as SGPlan, Sapa, and LPG. We also consider a further variation of the additive heuristic, where symbolic labels representing action sets are propagated rather than numbers, and show that this scheme can be further developed to construct heuristics that can take delete-information into account.
Online Signature Verification and Recognition: An Approach Based on Symbolic Representation
Authors: D. S. Guru, H. N. Prakash
Venue: IEEE Transactions on Pattern Analysis and Machine Intelligence (2009)

In this paper, we propose a new method of representing on-line signatures by interval valued symbolic features. Global features of on-line signatures are used to form an interval valued feature vectors. Methods for signature verification and recognition based on the symbolic representation are also proposed. We exploit the notions of writer dependent threshold and introduce the concept of feature dependent threshold to achieve a significant reduction in equal error rate. Several experiments are conducted to demonstrate the ability of the proposed scheme in discriminating the genuine signatures from the forgeries. We investigate the feasibility of the proposed representation scheme for signature verification and also signature recognition using all 16500 signatures from 330 individuals of the MCYT bimodal biometric database. Further, extensive experimentations are conducted to evaluate the performance of the proposed methods by projecting features onto Eigenspace and Fisherspace. Unlike other existing signature verification methods, the proposed method is simple and efficient. The results of the experimentations reveal that the proposed scheme outperforms several other existing verification methods including the state-of-the-art method for signature verification.
The mathematicsmodule of the eMax system
Authors: Istvan Vajda, Anna Gyorgy
Venue: Proceedings of the 2nd conference on European computing conference (2008)

This paper is about the most important features of the mathematics module of the eMax exam-system. It shows the motivation for such a software, the covered chapters of mathematics and the provided question types, then summarizes the usage and the evaluation method. Finally it reviews the results of a test exam.
Autonomous inter-task transfer in reinforcement learning domains
Authors: Peter Stone
Venue:  (2008)

Reinforcement learning (RL) methods have become popular in recent years because of their ability to solve complex tasks with minimal feedback. While these methods have had experimental successes and have been shown to exhibit some desirable properties in theory, the basic learning algorithms have often been found slow in practice. Therefore, much of the current RL research focuses on speeding up learning by taking advantage of domain knowledge, or by better utilizing agents' experience. The ambitious goal of transfer learning, when applied to RL tasks, is to accelerate learning on some target task after training on a different, but related, source task. This dissertation demonstrates that transfer learning methods can successfully improve learning in RL tasks via experience from previously learned tasks. Transfer learning can increase RL's applicability to difficult tasks by allowing agents to generalize their experience across learning problems. This dissertation presents inter-task mappings, the first transfer mechanism in this area to successfully enable transfer between tasks with different state variables and actions. Inter-task mappings have subsequently been used by a number of transfer researchers. A set of six transfer learning algorithms are then introduced. While these transfer methods differ in terms of what base RL algorithms they are compatible with, what type of knowledge they transfer, and what their strengths are, all utilize the same inter-task mapping mechanism. These transfer methods can all successfully use mappings constructed by a human from domain knowledge, but there may be situations in which domain knowledge is unavailable, or insufficient, to describe how two given tasks are related. We therefore also study how inter-task mappings can be learned autonomously by leveraging existing machine learning algorithms. Our methods use classification and regression techniques to successfully discover similarities between data gathered in pairs of tasks, culminating in what is currently one of the most robust mapping-learning algorithms for RL transfer. Combining transfer methods with these similarity-learning algorithms allows us to empirically demonstrate the plausibility of autonomous transfer. We fully implement these methods in four domains (each with different salient characteristics), show that transfer can significantly improve an agent's ability to learn in each domain, and explore the limits of transfer's applicability.
Fuzzy Logic in Action: Applications in Epidemiology and Beyond, 1st edition
Authors: Eduardo Massad, Neli R.S. Ortega, Lacio C. Barros, Cludio J. Struchiner
Venue: Studies In Fuzziness And Soft Computing (2009)

Fuzzy Logic in Action: Applications in Epidemiology and Beyond, co-authored by Eduardo Massad, Neli Ortega, Lacio Barros, and Cludio Struchiner is a remarkable achievement. The book brings a major paradigm shift to medical sciences exploring the use of fuzzy sets in epidemiology and medical diagnosis arena. The volume addresses the most significant topics in the broad areas of epidemiology, mathematical modeling and uncertainty, embodying them within the framework of fuzzy set and dynamic systems theory. Written by leading contributors to the area of epidemiology, medical informatics and mathematics, the book combines a very lucid and authoritative exposition of the fundamentals of fuzzy sets with an insightful use of the fundamentals in the area of epidemiology and diagnosis. The content is clearly illustrated by numerous illustrative examples and several real world applications. Based on their profound knowledge of epidemiology and mathematical modeling, and on their keen understanding of the role played by uncertainty and fuzzy sets, the authors provide insights into the connections between biological phenomena and dynamic systems as a mean to predict, diagnose, and prescribe actions. An example is the use of Bellman-Zadeh fuzzy decision making approach to develop a vaccination strategy to manage measles epidemics in So Paulo. The book offers a comprehensive, systematic, fully updated and self- contained treatise of fuzzy sets in epidemiology and diagnosis. Its content covers material of vital interest to students, researchers and practitioners and is suitable both as a textbook and as a reference. The authors present new results of their own in most of the chapters. In doing so, they reflect the trend to view fuzzy sets, probability theory and statistics as an association of complementary and synergetic modeling methodologies.
Parameter estimation of Poisson mixture with automated model selection through BYY harmony learning
Authors: Jinwen Ma, Jianfeng Liu, Zhijie Ren
Venue: Pattern Recognition (2009)

Finite mixture is widely used in the fields of information processing and data analysis. However, its model selection, i.e., the selection of components in the mixture for a given sample data set, has been still a rather difficult task. Recently, the Bayesian Ying-Yang (BYY) harmony learning has provided a new approach to the Gaussian mixture modeling with a favorite feature that model selection can be made automatically during parameter learning. In this paper, based on the same BYY harmony learning framework for finite mixture, we propose an adaptive gradient BYY learning algorithm for Poisson mixture with automated model selection. It is demonstrated well by the simulation experiments that this adaptive gradient BYY learning algorithm can automatically determine the number of actual Poisson components for a sample data set, with a good estimation of the parameters in the original or true mixture where the components are separated in a certain degree. Moreover, the adaptive gradient BYY learning algorithm is successfully applied to texture classification.
Exponential Separation of Quantum and Classical Online Space Complexity
Authors: Fran&#x00e7;ois Le&#x00a0;Gall
Venue: Theory of Computing Systems (2009)

Although quantum algorithms realizing an exponential time speed-up over the best known classical algorithms exist, no quantum algorithm is known performing computation using less space resources than classical algorithms. In this paper, we study, for the first time explicitly, space-bounded quantum algorithms for computational problems where the input is given not as a whole, but bit by bit. We show that there exist such problems that a quantum computer can solve using exponentially less work space than a classical computer. More precisely, we introduce a very natural and simple model of a space-bounded quantum online machine and prove an exponential separation of classical and quantum online space complexity, in the bounded-error setting and for a total language. The language we consider is inspired by a communication problem (the disjointness function) that Buhrman, Cleve and Wigderson used to show an almost quadratic separation of quantum and classical bounded-error communication complexity. We prove that, in the framework of online space complexity, the separation becomes exponential.
Compact solution for a robotomechanism of a bimobile orientation with decoupled moves
Authors: Nicolae Bercan, Daniel Manolea, Radu Bercan
Venue: Proceedings of the 10th WSEAS international conference on Mathematical and computational methods in science and engineering (2008)

In this paper is presented a new kind of robotomechanism of a bimobile orientation, operated through wires, with decoupled moves, proposed by the authors. In comparison with other robotomechanisms for orientation, built out from other decoupling mechanisms with planetary units [1, 2, 3, 4, 5], the nominated variant is distinguished through an operating with wires and friction wheels, through compactness, and implicit, through reduced gauge. The solution proposed in contributes to the improving of the base of structural schemes of mechanisms for orientation activated through wires, and the kinematical relations obtained in the paper are useful in the organizing projection and command programming on the computer.
A Method for Extracting Unexpected Scenarios of Embedded Systems
Authors: Toshiro Mise, Yasufumi Shinyashiki, Takako Nakatani, Naoyasu Ubayashi, Keiichi Katamine, Masaaki Hashimoto
Venue: Proceeding of the 2006 conference on Knowledge-Based Software Engineering: Proceedings of the Seventh Joint Conference on Knowledge-Based Software Engineering (2006)

Systems embedded in household electric appliances are used for long periods of time by various kinds of people. These environments sometimes cause unexpected failures. To save users from the appliances failures, every product is required to retain a high standard of quality and safety until their terminal period. We have developed a method named ESIM (Embedded System Improving Method) to extract the causes of failures and lead failure scenarios to make design specifications secure prior to development. The scope of the method covers hardware deterioration, partial failure, environmental exception, as well as illegal operations. In this article, we present a practical method to evaluate comprehensive failure scenarios derived from this method.
Altruism and agents: an argumentation based approach to designing agent decision mechanisms
Authors: Trevor Bench-Capon, Katie Atkinson, Peter McBurney
Venue: Proceedings of The 8th International Conference on Autonomous Agents and Multiagent Systems - Volume 2 (2009)

We present an argument-based qualitative decision-making frame-work in which the social values promoted or demoted by alternative action-options are explicitly represented. We show how this framework may be used to explain the results of experimental economic studies in which human subjects play the Ultimatum Game, an interaction between two participants in which one player divides a sum of money between them, and the other player may accept or reject the offer. The results of these experiments are not explained by a decision-model assuming the participants are purely self-interested utility-maximizers. Some studies further suggest that differences in choices made in different cultures may reflect their day to day behaviour, which can in turn be related to the values of the subjects, and how they order their values. The decision-framework we propose will aid software engineers designing decision-making mechanisms for autonomous agents, particularly for situations requiring agent adaptability, for example, where agents may prefer different outcome states in transactions involving different types of counter-parties.
Requirements and Design of a Web-Based Tool for Supporting Blended Learning of Software Project Development
Authors: Y. T. Yu, M. Choy, E. Y. K. Chan, Y. T. Lo
Venue: Proceeding of the 2007 conference on Supporting Learning Flow through Integrative Technologies (2007)

: Software development courses invariably require students to work on non-trivial software projects and demand ample supervised practice of students. In a conventional face-to-face classroom environment, time and resource limitations often severely constrain the scope of experiences that students gain and the supervision they receive. To alleviate these difficulties, we are working towards a blended learning approach for improving the teaching, learning and assessment activities in software development courses. This paper describes the requirements and design of TREASURE, a tool custom built to support blended learning of software project development, and the use of the tool in such courses.
Relation between static and dynamic optimization in computer network routing
Authors: Milan Tuba
Venue: Proceedings of the 8th WSEAS international conference on Artificial intelligence, knowledge engineering and data bases (2009)

Computer network routing is a very important and interesting optimization problem. Many different routing algorithms have been used over the years on the Internet, often with unexpected problems. Dynamic systems, i.e. systems that change over time, can be optimized statically with a fixed solution that corresponds to some average system state, or dynamically where the solution tries to follow the system change over time. It is a normal expectation that dynamic optimization has to give better results than a static one. Dynamic optimization is more complex, requires more computation, more advanced methods, but is superior to static optimization because it can always be transformed to the static case simply by neglecting change of the system in time and selecting a single state as a representative. However, that expectation that dynamic optimization gives better results than static one applies only to the perfect dynamic optimization, which is impossible in practice. It takes some time to collect information about the system current state, and optimization is always done with that obsolete information. This situation is examined on computer network routing. By complete mathematical analysis of a simple network, we show that dynamic routing gives better results than static, as expected, but that the margin is much smaller then intuitively expected. Further analysis shows that that minor advantage can easily be lost if there is even a small error in the dynamic routing tables, and actually dynamic routing can easily become worse than static. It takes time to collect information about network traffic. By the time routing tables are calculated, they are already obsolete; they are about some previous condition on the network, not the current one. Quantitative analysis shows that delays in building routing tables can affect dynamic routing performance unexpectedly strongly. This leads to the qualitative recommendation: "Trying to optimize too hard will make things worse. Dynamic routing should not try to adapt to traffic changes very fast." This hypothesis is accepted today and implemented in routing algorithms.
Statistical Characterization of Steady-State Visual Evoked Potentials and Their Use in Brain---Computer Interfaces
Authors: Miguel A. Lopez, Francisco Pelayo, Eduardo Madrid, Alberto Prieto
Venue: Neural Processing Letters (2009)

Steady-state visual evoked potential (SSVEP)-based brain---computer interfaces (BCIs) use the spectral power of the potentials for classification as they can be voluntarily enhanced or diminished by the subject by means of selective attention. The features traditionally extracted from the EEG and used for BCIs have been characterized as a normal distribution, although some studies have shown recently that this normal distribution is not the most appropriate for SSVEPs. In this paper we attempt to characterize the power of SSVEPs as a random variable that follows Rayleigh and exponential distributions when the stimulus is attended and ignored, respectively. BCIs based on SSVEPs can improve the transfer-bit and successful-classification rates if this new model is used instead of the traditional one based on the normal distribution.
Multidimensional visual aid enhances haptic training simulations
Authors: Osama Halabi, Norishige Chiba
Venue: Proceedings of the World Haptics 2009 - Third Joint EuroHaptics conference and Symposium on Haptic Interfaces for Virtual Environment and Teleoperator Systems (2009)

This paper explores the use of hypotrochoid curves as visual aids for haptic training systems that are used to teach motor skills that require recall of forces and positions at specific locations to replicate the expert touch. The visual aid presented is a multidimensional feedback tool that can provide information on force, position, and velocity simultaneously. The extent of learning is measured by the accuracy of the force recall. A breast haptic simulation was used to test the presented visual aid. Results suggest that multidimensional feedback is an effective way to promote learning of forces. In addition, the presented visual aid made learning an enjoyable process.
On ACO-Based Fuzzy Clustering for Image Segmentation
Authors: Zhiding Yu, Weiyu Yu, Ruobing Zou, Simin Yu
Venue: Proceedings of the 6th International Symposium on Neural Networks: Advances in Neural Networks - Part II (2009)

Ant Colony Optimization (ACO) is a newly proposed intelligent algorithm for solving discrete optimization problems such as the Travelling Salesman Problem (TSP). In this paper we introduce a novel ACO-based clustering algorithm and exploit its application in image segmentation. Unlike traditional ACO which is mainly based on probabilistic and hard path choosing, the proposed method utilizes a soft and fuzzy scheme. In detail, every pixel in the image is viewed as an ant and the calculation of membership function is based on heuristic and pheromone information on each cluster center. In addition, memberships are modified to include spatial information which can further improve the algorithm performance for image segmentation. Experiments are taken to examine the performance of ACO-based fuzzy clustering algorithm and segmentation results indicate that the proposed approach has the potential of becoming an established clustering method for image segmentation.
Cardiac Imaging and Modeling for Guidance of Minimally Invasive Beating Heart Interventions
Authors: Terry M. Peters, Cristian A. Linte, John Moore, Andrew Wiles, Jennifer Lo, Danielle Pace, Chris Wedlake, Daniel Bainbridge, Douglas L. Jones, Gerard M. Guiraudon
Venue: Proceedings of the 5th International Conference on Functional Imaging and Modeling of the Heart (2009)

Minimally invasive beating heart intracardiac surgery is an area of research with many unique challenges. Surgical targets are in constant motion in a blood-filled environment that prevents direct line-of-sight guidance. The restrictive workspace requires compact, yet robust tools for proper therapy delivery. Our novel method for approaching multiple targets inside the beating heart allows their identification and access under augmented reality-assisted image guidance. The surgical platform integrates real-time ultrasound imaging with virtual models of the surgical instruments, along with virtual cardiac anatomy acquired from pre-operative images. Extensive in vitro studies were performed to assess the operator's ability to "deliver therapy" to dynamic intracardiac targets via both transmural and transluminal access, and demonstrated significantly more accurate targeting under augmented reality guidance compared to ultrasound image guidance alone, accompanied by a reduction of procedure time by half. Moreover, preliminary in vivo acute studies on porcine models showed successful prosthesis positioning for beating-heart septal defect repair and mitral valve implantation via direct surgical access. While still in its infancy, this work emphasizes the promise of ultrasound-enhanced model-guided environments for minimally-invasive cardiac therapy, whether delivered via a catheter introduced into the vascular system or a cannula inserted through the heart wall.
RFID Design Principles
Authors: Harvey Lehpamer
Venue: Artech House Microwave Library (2007)

This cutting-edge book serves as a comprehensive introduction to RFID, offering you a detailed understanding of design essentials and applications, and providing a thorough overview of management issues. By comparing RFID with WLAN and Bluetooth, this practical resource shows you how RFID technology can help you overcome many design challenges and limitations in the field. The book explains the design of electronic circuits, antennas, interfaces, data encoding schemes, and complete RFID systems. Starting with the basics of RF and microwave propagation, you learn about major system components including tags and readers. This hands-on reference distills the latest RFID standards, and examines RFID at work in supply chain management, intelligent buildings, intelligent transportation systems, and tracking animals. RFID is controversial among privacy and consumer advocates, and this book looks at every angle concerning security, ethics, and protecting consumer data. From design details... to applications... to socio-cultural implications, this authoritative volume offers the knowledge you need to create an optimal RFID system and maximize its performance.