ppxscal/embedding_network huggingface dataset:
Neural-Memory Based Control of Micro Air Vehicles (MAVs) with Flapping Wings
Authors: Liguo Weng, Wenchuan Cai, M. J. Zhang, X. H. Liao, David Y. Song
Venue: Proceedings of the 4th international symposium on Neural Networks: Advances in Neural Networks (2007)

This paper addresses the problem of wing motion control of flapping wing Micro Air Vehicles (MAVs). Inspired by hummingbird's wing structure as well as the construction of its skeletal and muscular components, a dynamic model for flapping wing is developed. As the model is highly nonlinear and coupled with unmeasurable disturbances and uncertainties, traditional strategies are not applicable for flapping wing motion control. A new approach called neural-memory based control is proposed in this work. It is shown that this method is able to learn from past control experience and current/past system behavior to improve its performance during system operation. Furthermore, much less information about the system dynamics is needed in construction such a control scheme as compared with traditional NN based methods. Both theoretical analysis and computer simulation verify its effectiveness.
Pieceswise linear lattice based associative memories
Authors: Paul D. Gader
Venue:  (2007)

Research into associative memories using linear correlation matrices began with the introduction of the Hopfield model in the 1980's. These networks have a limited capacity in terms of the number of pattern pairs that they can store. During the 1990's Ritter, et al. introduced a new family of associative memories based on lattice algebra instead of linear algebra. These memories provide unlimited storage capacity and, though they have been well discussed in the literature, research in this area is still active. It is possible to generalize the existing lattice based memories into a family of memories using order statistic operators for encoding and decoding. A novel method for encoding memories using all order statistic operators is examined. This new method provides a level of robustness to outliers in the initial data set that is not present in current lattice based models. In addition, this approach treats the lattice based associative memory as a piecewise linear dynamical system. This piecewise linear viewpoint imparts a new set of tools for analyzing the behavior of the canonical lattice based associative memories. Improvement in the retrieval of noisy patterns in the presence of outliers in the initial data is demonstrated using a widely available computer science data set. Using this piecewise linear framework, another class of memories using what are referred to as "near min-max" encoding and decoding operators is introduced. These memories, along with the order statistics memories, are a subset of novel set of memories created using Ordered Weighted Averages (OWAs), a process which is also introduced here. This experiment sheds light on an important property of the canonical lattice based associative memories, herein referred to as being "well behaved in the min-max sense." (Full text of this dissertation may be available via the University of Florida Libraries web site. Please check http://www.uflib.ufl.edu/etd.html)
An Estimating Traffic Scheme Based on Adaline
Authors: Fengjun Shang
Venue: Proceedings of the 5th international symposium on Neural Networks: Advances in Neural Networks, Part II (2008)

In order to manage the whole network, a novel estimating traffic scheme is proposed, called the Adaline model. In this model, there are two parts of works. Firstly, an Adaline network is proposed and implemented for estimating traffic. By using the Adaline network, we are able to overcome the challenge of ill-posed nature of the problem. Secondly, in order to optimize solutions, a prior knowledge is introduced. By using prior, the error is reduced markedly. Numeral result shows our model achieves better performance than the existing representative methods.
Inside looking out camera pose estimation for virtual studio
Authors: Kambiz Rahbar, Hamid Reza Pourreza
Venue: Graphical Models (2008)

This paper studies the inside looking out camera pose estimation for the virtual studio. The camera pose estimation process, the process of estimating a camera's extrinsic parameters, is based on closed-form geometrical approaches which use the benefit of simple corner detection of 3D cubic-like virtual studio landmarks. We first look at the effective parameters of the camera pose estimation process for the virtual studio. Our studies include all characteristic landmark parameters like landmark lengths, landmark corner angles and their installation position errors and some camera parameters like lens focal length and CCD resolution. Through computer simulation we investigate and analyze all these parameters' efficiency in camera extrinsic parameters, including camera rotation and position matrixes. Based on this work, we found that the camera translation vector is affected more than other camera extrinsic parameters because of the noise of effective camera pose estimation parameters. Therefore, we present a novel iterative geometrical noise cancellation method for the closed-form camera pose estimation process. This is based on the collinearity theory that reduces the estimation error of the camera translation vector, which plays a major role in camera extrinsic parameters estimation errors. To validate our method, we test it in a complete virtual studio simulation. Our simulation results show that they are in the same order as those of some commercial systems, such as the BBC and InterSense IS-1200 VisTracker.
Non-rigid 2D-3D Registration Based on Support Vector Regression Estimated Similarity Metric
Authors: Wenyuan Qi, Lixu Gu, Jianrong Xu
Venue: Proceedings of the 4th international workshop on Medical Imaging and Augmented Reality (2008)

In this paper, we proposed a novel non-rigid 2D-3D registration framework, which is based on Support Vector Regression (SVR) to compensate the disadvantages of generating large amounts of Digitally Rendered Radiographs (DRRs) in the stage of intra-operation for radiotherapy. It is successfully used to estimate similarity metric distribution from prior sparse target metric values against different featured transforming parameters of non-rigid registration. Through applying the appropriate selected features and kernel of SVR solution to our registration framework, experiments provide a precise registration result efficiently in order to assist radiologists locating the accurate positions of radiation surgery. Meanwhile, a medical diagnosis database is also built up to reduce the therapy cost and accelerate the procedure of radiotherapy in the case of future scheduling of multiple treatments.
Wiretapping Based on Node Corruption over Secure Network Coding: Analysis and Optimization
Authors: Mohammad Ravanbakhsh, Mehdi M. Hassanzadeh, Dag Haugland
Venue: Proceedings of the 2nd international Castle meeting on Coding Theory and Applications (2008)

A new type of attack on secure network coding is introduced in this paper. In this model, network nodes, which handle the traffic from the source node to sink nodes are potentially viewed to be corruptible. We study the maximum security capacity for this problem for a single- source single-sink scenario, and we generalize our study for multicast with network coding. Based on our study, two optimization problems are introduced to increase the security against the attacks under study. We have shown by simulation results that our proposed optimization method has increased the security against node corruption considerably, and at the same time, the cost per level of security is lower compared to optimization methods without constraints on node corruption.
Optimization of Two-Level Topological Structure of Distributed Intrusion Detection System
Authors: Adam Grzech
Venue: Proceedings of the 2008 19th International Conference on Systems Engineering (2008)

The paper is devoted to discuss selected issues of distributed intrusion detection system composed of two complementary parts: distributed monitoring system and distributed decision making system. The aim of the paper is to formulate and investigate various aspects of distributed monitoring system optimization. The discussed optimization tasks are motivated by assumption that quality of decision making are strongly depends on quality of monitoring services delivered to decision making system by distributed monitoring system. It is further assumed that the quality of monitoring services is measured by index combining amount of delivered data and delay introduced for transferred the monitoring data by co-shared distributed communication system. Distributed monitoring system for layered distributed intrusion detection system optimization tasks are discussed.
A Constraint Programming Approach for Allocation and Scheduling on the CELL Broadband Engine
Authors: Luca Benini, Michele Lombardi, Michela Milano, Martino Ruggiero
Venue: Proceedings of the 14th international conference on Principles and Practice of Constraint Programming (2008)

The Cell BE processor provides both scalable computation power and flexibility, and it is already being adopted for many computational intensive applications like aerospace, defense, medical imaging and gaming. Despite of its merits, it also presents many challenges, as it is now widely known that is very difficult to program the Cell BE in an efficient manner. Hence, the creation of an efficient software development framework is becoming the key challenge for this computational platform.We have developed a novel software toolkit, called Cellflow, which enables developers to quickly build multi-task applications for Cell-based platform. We support programmers from the initial stage of their work, through a development-time software infrastructure, to the final stage of the application development, proposing a safe and easy-to-use explicit parallel programming model.A fundamental component of the software toolkit is the off-line allocator and scheduler that manages hardware resources while optimizing performance metrics such as execution time, allocation costs, power. The optimization engine receives as input a task graph representing an application, the hardware resources and produces an optimal allocation and scheduling. We have developed various approaches, either based on decomposition [5] or based on pure Constraint Programming, this latter being the core of this paper. We have identified instance features that guide toward the choice of the best solver for the instance at hand.Experimental result show that Constraint Programming (possibly combined with Integer Programming) is a proper tool for dealing with this kind of applications achieving very good performance.
Ancestral Reconstruction by Asymmetric Wagner Parsimony over Continuous Characters and Squared Parsimony over Distributions
Authors: Miklós Csűrös
Venue: Proceedings of the international workshop on Comparative Genomics (2008)

Contemporary inferences about evolution occasionally involve analyzing infinitely large feature spaces, requiring specific algorithmic techniques. We consider parsimony analysis over numerical characters, where knowing the feature values at terminal taxa allows one to infer ancestral features, namely, by minimizing the total number of changes on the edges using continuous-valued distance measures. In particular, we show that ancestral reconstruction is possible in linear time for both an asymmetric linear distance measure (Wagner parsimony) over continuous-valued characters, and a quadratic distance measure over finite distributions. The former can be used to analyze gene content evolution with asymmetric gain and loss penalties, and the latter to reconstruct ancestral diversity of regulatory sequence motifs and multi-allele loci. As an example of employing asymmetric Wagner parsimony, we examine gene content evolution within Archaea.
A New Application of CAS to $\mbox{\LaTeX}$ Plottings
Authors: Masayoshi Sekiguchi, Masataka Kaneko, Yuuki Tadokoro, Satoshi Yamashita, Setsuo Takato
Venue: Proceedings of the 7th international conference on Computational Science, Part II (2007)

We have found a new application of Computer Algebra System (CAS), KETpic which has been developed as a macro package for a CAS. One of aspects in its philosophy is CAS-aided visualization in $\mbox{\LaTeX}$ documents. We aim to extend KETpic to other CASs, and derive necessary conditions from the basic idea for CASs to accept it, i.e., I/O functions with external files and manipulating numerical or string data. Finally, we describe KETpic for Maple as a successful example. By using KETpic we can draw fine pictures in $\mbox{\LaTeX}$ documents.
Lindig's Algorithm for Concept Lattices over Graded Attributes
Authors: Radim Belohlavek, Bernard Baets, Jan Outrata, Vilem Vychodil
Venue: Proceedings of the 4th international conference on Modeling Decisions for Artificial Intelligence (2007)

Formal concept analysis (FCA) is a method of exploratory data analysis. The data is in the form of a table describing relationship between objects (rows) and attributes (columns), where table entries are grades representing degrees to which objects have attributes. The main output of FCA is a hierarchical structure (so-called concept lattice) of conceptual clusters (so-called formal concepts) present in the data. This paper focuses on algorithmic aspects of FCA of data with graded attributes. Namely, we focus on the problem of generating efficiently all clusters present in the data together with their subconcept-superconcept hierarchy. We present theoretical foundations, the algorithm, analysis of its efficiency, and comparison with other algorithms.
Heap Assumptions on Demand
Authors: Andreas Podelski, Andrey Rybalchenko, Thomas Wies
Venue: Proceedings of the 20th international conference on Computer Aided Verification (2008)

Termination of a heap-manipulating program generally depends on preconditions that express heap assumptions (i.e., assertions describing reachability, aliasing, separation and sharing in the heap). We present an algorithm for the inference of such preconditions. The algorithm exploits a unique interplay between counterexample-producing abstract termination checker and shape analysis. The shape analysis produces heap assumptions on demand to eliminate counterexamples, i.e., non-terminating abstract computations. The experiments with our prototype implementation indicate its practical potential.
A model constructed based on multi-criteria decision making with incomplete linguistic preference relations
Authors: Tien-Chin Wang, Shu-Chen Hsu
Venue: Proceedings of the 7th WSEAS International Conference on Artificial intelligence, knowledge engineering and data bases (2008)

This study uses three types of pairwise comparisons algorithm which are horizontal vertical and oblique to construct Multi-Criteria Decision Making with Incomplete Linguistic Preference Relations Model. The use of pairwise comparisons will not produce the problem of inconsistency, which even allows every decision expert to choose an explicit criterion or alternative for index unrestrictedly. When there are n th criteria, only n-1 times of pairwise comparisons need to be carried out, then one can rest on Incomplete Linguistic Preference Relations Theory to obtain the complete matrix so as to obtain the priority value of alternative for the decision maker's reference. The decision making assessment model that construct by this study can be extensively applied to every field of decision science and served as the reference basis for the follow-up scholars.
Spanners of Additively Weighted Point Sets
Authors: Prosenjit Bose, Paz Carmi, Mathieu Couture
Venue: Proceedings of the 11th Scandinavian workshop on Algorithm Theory (2008)

We study the problem of computing geometric spanners for (additively) weighted point sets. A weighted point set is a set of pairs (p,r) where p is a point in the plane and r is a real number. The distance between two points (p i ,r i ) and (p j ,r j ) is defined as |p i p j | ¿ r i ¿ r j . We show that in the case where all r i are positive numbers and |p i p j | ¿ r i + r j for all i,j (in which case the points can be seen as non-intersecting disks in the plane), a variant of the Yao graph is a (1 + ¿)-spanner that has a linear number of edges. We also show that the Additively Weighted Delaunay graph (the face-dual of the Additively Weighted Voronoi diagram) has constant spanning ratio. The straight line embedding of the Additively Weighted Delaunay graph may not be a plane graph. Given the Additively Weighted Delaunay graph, we show how to compute a plane embedding with a constant spanning ratio in O(nlogn) time.
Cost-Based Domain Filtering for Stochastic Constraint Programming
Authors: Roberto Rossi, S. Armagan Tarim, Brahim Hnich, Steven Prestwich
Venue: Proceedings of the 14th international conference on Principles and Practice of Constraint Programming (2008)

Cost-based filtering is a novel approach that combines techniques from Operations Research and Constraint Programming to filter from decision variable domains values that do not lead to better solutions [7]. Stochastic Constraint Programming is a framework for modeling combinatorial optimization problems that involve uncertainty [9]. In this work, we show how to perform cost-based filtering for certain classes of stochastic constraint programs. Our approach is based on a set of known inequalities borrowed from Stochastic Programming -- a branch of OR concerned with modeling and solving problems involving uncertainty. We discuss bound generation and cost-based domain filtering procedures for a well-known problem in the Stochastic Programming literature, the static stochastic knapsack problem. We also apply our technique to a stochastic sequencing problem. Our results clearly show the value of the proposed approach over a pure scenario-based Stochastic Constraint Programming formulation both in terms of explored nodes and run times.
Constraints in the design of CMOS MVL circuits
Authors: Avinash D. Gawande, S. A. Ladhake
Venue: Proceedings of the 7th WSEAS International Conference on Instrumentation, Measurement, Circuits and Systems (2008)

Current mode CMOS circuits are receiving increasing attention. Current mode CMOS multiple-valued circuits are interesting and may have applications in digital signal processing and computing. In this paper we review developments and potential of multiple-valued signals and logic in the relevant context of binary and two valued signals. Various constraints in the design of CMOS multiple-valued signals are presented.
SIMCAN: a SIMulator framework for computer architectures and storage networks
Authors: Alberto Núñez, Javier Fernández, Jose D. Garcia, Laura Prada, Jesús Carretero
Venue: Proceedings of the 1st international conference on Simulation tools and techniques for communications, networks and systems & workshops (2008)

This paper presents an OMNeT-based Framework to simulate large complex storage networks, with its corresponding underlying subsystems (I/O, Networking, etc.). With this Framework, custom environments can be configured and deployed on a flexible and easy way. The most interesting features of this Framework are its flexibility and scalability, so the simulation of distributed storage environments can be performed with the required detail level. Thus, we will able to study the behaviour of complex distributed environments to several purposes, like detecting system bottlenecks, calculating the scalability degree of the system or testing the performance of developed algorithms, without using a real system.
Representation of factual and temporal unawareness in electronic patient records
Authors: Panagiotis Chountas, Ilias Petrounias, Elia El-Darzi, Vassilis Kodogiannis
Venue: Journal of Computational Methods in Sciences and Engineering (2005)

In this paper we are concerned with the problem of designing of a conceptual framework for the construction of a flexible data warehouse that is adequate for accommodating multi-source data and selecting useful answers to queries, posted to a conflicting community of Patient-Record sources. We put forward a proposal to provide representations with that kind of functionality through flexible reasoning mechanisms for handling perception based descriptions and retrieving intentional answers. We start by positioning conceptual schema, data-warehouses with regard to this problem.
Classifying Chemical Compounds Using Contrast and Common Patterns
Authors: Andrzej Dominik, Zbigniew Walczak, Jacek Wojciechowski
Venue: Proceedings of the 8th international conference on Adaptive and Natural Computing Algorithms, Part I (2007)

The problem of classifying chemical compounds is studied in this paper. An approach based on minimal contrast and common topological patterns discovered from compounds dataset is presented. The algorithm is strongly associated with the classical emerging patterns techniques known from decision tables. We tested the proposed algorithm on real classification problems. Results show that it provides better classification accuracy than other existing algorithms. Another advantage of the introduced classifier is that it has a simple, understandable structure and can be easily extended by the expert knowledge.
A System for Ontology-Based Annotation of Biomedical Data
Authors: Clement Jonquet, Mark A. Musen, Nigam Shah
Venue: Proceedings of the 5th international workshop on Data Integration in the Life Sciences (2008)

We present a system for ontology based annotation and indexing of biomedical data; the key functionality of this system is to provide a service that enables users to locate biomedical data resources related to particular ontology concepts. The system's indexing workflow processes the text metadata of diverse resource elements such as gene expression data sets, descriptions of radiology images, clinical-trial reports, and PubMed article abstracts to annotate and index them with concepts from appropriate ontologies. The system enables researchers to search biomedical data sources using ontology concepts. What distinguishes this work from other biomedical search tools is:(i) the use of ontology semantics to expand the initial set of annotations automatically generated by a concept recognition tool; (ii) the unique ability to use almost all publicly available biomedical ontologies in the indexing workflow; (iii) the ability to provide the user with integrated results from different biomedical resource in one place. We discuss the system architecture as well as our experiences during its prototype implementation (http://www.bioontology.org/tools.html).
Endowing Emotional Agents with Coping Strategies: From Emotions to Emotional Behaviour
Authors: Carole Adam, Dominique Longin
Venue: Proceedings of the 7th international conference on Intelligent Virtual Agents (2007)

Emotion takes an increasingly important place in the design of intelligent virtual agents. Designers of emotional agents build on theories from cognitive psychology, that describe the cognitive functioning of emotions with two indivisible processes [1,2]: the appraisal process triggers emotions, in particular intense negative emotions to point out threatening stimuli, and the coping process modifies the behaviour to manage these stimuli. Nevertheless, among the existing emotional agents, a lot express emotions triggered by an appraisal process [3] but few have a coping process allowing their emotions to impact their behaviour [4,5,6]. In previous work [7] we provided a formalization of Ortony et al.'s appraisal process [8] in a BDI logic, et al.'s a logic of mental attitudes. The next step is to formalize the coping process in the same framework. Our aim here is to provide the theoretical basis of an agent architecture rather than an implementation. We only give here an overview of our framework (cf. [9,10] for more details).