ppxscal/embedding_network huggingface dataset:
A framework for compositional design and analysis of systems
Authors: Thomas A. Henzinger, George C. Necula
Venue:  (2007)

Complex system design today calls for compositional design and implementation. However each component is designed with certain assumptions about the environment it is meant to operate in, and delivering certain guarantees if those assumptions are satisfied; numerous inter-component interaction errors are introduced in the manual and error-prone integration process as there is little support in design environments for machine-readably representing these assumptions and guarantees and automatically checking consistency during integration. Based on Interface Automata [54] we propose a framework for compositional design and analysis of systems: a set of domain-specific automata-theoretic type systems for compositional system specification and analysis by behavioral specification of open systems. We focus on three different domains: component-based hardware systems communicating on bidirectional wires, concurrent distributed recursive message-passing software systems, and embedded software system components operating in resource-constrained environments. For these domains we present approaches to formally represent the assumptions and conditional guarantees between interacting open system components. Composition of such components produces new components with the appropriate assumptions and guarantees. We check satisfaction of temporal logic specifications by such components, and the substitutability of one component with another in an arbitrary context. Using this framework one can analyze large systems incrementally without needing extensive summary information to close the system at each stage. Furthermore, we focus only on the inter-component interaction behavior without dealing with the full implementation details of each component. Many of the merits of automata-theoretic model-checking are combined with the compositionality afforded by type-system based techniques. We also present an integer-based extension of the conventional boolean verification framework motivated by our interface formalism for embedded software components. Our algorithms for checking the behavioral compatibility of component interfaces are available in our tool Chic [1], which can be used as a plug-in for the Java IDE JBuilder [2] and the heterogenous modeling and design environment Ptolemy II [3]. Finally, we address the complementary problem of partitioning a large system into meaningful coherent components by analyzing the interaction patterns between its basic elements. We demonstrate the usefulness of our partitioning approach by evaluating its efficacy in improving unit-test branch coverage for a large software system implemented in C.
Virtual Prototypes in Developing Mobile Software Applications and Devices
Authors: Kari Liukkunen, Matti Eteläperä, Markku Oivo, Juha-Pekka Soininen, Mika Pellikka
Venue: Proceedings of the 9th international conference on Product-Focused Software Process Improvement (2008)

The goal of this paper is to study how software based virtual prototypes and hardware simulation tools can be combined. By combining these tools and techniques we can shorten the time to market with parallel concurrent design and more importantly, we can provide a real-time simulation environment for virtual prototypes. Application designers get access to a simulated realistic real-time mobile device well before the first prototypes are available from the device manufacturer. The research work was done in two cases. In the first case the virtual prototypes were used to illustrate and help to select new mobile application concepts and to test new applications usability. In the second case the virtual prototypes were used for modelling the product platforms, e.g. the computer system and the simulation of the complete system including both hardware and software. Our approach facilitates early simulation and testing of the final user experience and system behaviour in cases where they are heavily dependent on the characteristics and performance of the underlying computer platform.
An Experimental Analysis of Robinson-Foulds Distance Matrix Algorithms
Authors: Seung-Jin Sul, Tiffani L. Williams
Venue: Proceedings of the 16th annual European symposium on Algorithms (2008)

In this paper, we study two fast algorithms--HashRF and PGM-Hashed--for computing the Robinson-Foulds (RF) distance matrix between a collection of evolutionary trees. The RF distance matrix represents a tremendous data-mining opportunity for helping biologists understand the evolutionary relationships depicted among their trees. The novelty of our work results from using a variety of different architecture- and implementation-independent measures (i.e., percentage of bipartition sharing, number of bipartition comparisons, and memory usage) in addition to CPU time to explore practical algorithmic performance. Overall, our study concludes that HashRF performs better across the various performance measures than its competitor, PGM-Hashed. Thus, the HashRF algorithm provides scientists with a fast approach for understanding the evolutionary relationships among a set of trees.
Efficient determination of the sequence of attributes of an N-attributed database for obtaining an optimal tree representation
Authors: Ranjeet Kumar, Preetham Kumar, V. S. Ananthanarayana
Venue: Proceedings of the 7th WSEAS International Conference on Artificial intelligence, knowledge engineering and data bases (2008)

For an N-attributed database i.e. database storing the non-binary values of N number of attributes, a great deal of saving in space can be achieved while representing the database on the lines similar to PC-Tree, by determining the sequence of attributes (sorting order) to be considered constructing the tree. In order to avoid the ordinary and highly inefficient approach of constructing the tree by trying all the N! ( Factorial N ) combinations one by one, and accepting the combination that gives minimal number of nodes in the tree, we construct a mesh (abstraction), called RON's mesh, which gives an idea of how strongly the elements of an attribute are linked with the elements of other attributes, in terms of the number of nodes (elements) under each attribute and the number of links existing between the elements of attributes in the mesh. Finally, using the information from the mesh in an N*N matrix, we can find a sequence of attributes that gives the minimal number of nodes in the tree.
A Hybrid Orthogonal Genetic Algorithm for Global Numerical Optimization
Authors: Peter A. Stubberud, Matthew E. Jackson
Venue: Proceedings of the 2008 19th International Conference on Systems Engineering (2008)

In this paper, a hybrid orthogonal genetic algorithm (HOGA) is presented to solve global numerical optimization problems of continuous variables. Based on traditional genetic algorithms, the HOGA has been augmented with a robust selection operator and an intelligent crossover operator. These augmentations reduce statistical bias while improving convergence times and relative accuracy of the solutions. Examples show that HOGA can effectively solve a number of multimodal problems which are widely accepted as optimization benchmarks.
Automated Implicit Computational Complexity Analysis (System Description)
Authors: Martin Avanzini, Georg Moser, Andreas Schnabl
Venue: Proceedings of the 4th international joint conference on Automated Reasoning (2008)

Recent studies have provided many characterisations of the class of polynomial time computable functions through term rewriting techniques. In this paper we describe a (fully automatic and command-line based) system that implements the majority of these techniques and present experimental findings to simplify comparisons.
A Genetic Algorithm Based on Eigen Fuzzy Sets for Image Reconstruction
Authors: Ferdinando Martino, Salvatore Sessa
Venue: Proceedings of the 7th international workshop on Fuzzy Logic and Applications: Applications of Fuzzy Sets Theory (2007)

By normalizing the values of its pixels, any image is interpreted as a fuzzy relation whose the greatest eigen fuzzy set with respect to the max ¿ min composition and the smallest eigen fuzzy set with respect to the min ¿ max composition are used in a genetic algorithm for image reconstruction scopes. Image-chromosomes form the population and a fitness function based on the above eigen fuzzy sets of each image-chromosome and of the related original image is used for performing the selection operator. The reconstructed image is the image-chromosome with the highest value of fitness.
On the theoretical calculation of the static dipole polarizabilities of Li$_n$, Cu$_n$ (n &le; 8) and Li$_n$Cu$_m$ (n, m &le; 4)
Authors: Patricio Fuentealba, Luis Padilla-Campos, Orfa Reyes
Venue: Journal of Computational Methods in Sciences and Engineering (2004)

The static dipole polarizabilities of three series of clusters have been calculated and compared. They are the bare lithium clusters, the copper clusters and the mixed lithium - copper clusters. The calculations have been done solving the Kohn - Sham equations with an hybrid exchange - correlation functional. Some discrepancies with the experimental values for lithium clusters have been discussed. It has been found that the dipole polarizabilities of the copper cluters are smaller than the ones of lithium clusters, and the mixed ones follow close the values found for the copper clusters.
Fifty Years of Computer Music: Ideas of the Past Speak to the Future
Authors: John Chowning
Venue: Computer Music Modeling and Retrieval. Sense of Sounds: 4th International Symposium, CMMR 2007, Copenhagen, Denmark, August 27-31, 2007. Revised Papers (2008)

The use of the computer to analyze and synthesize sound in two early forms, additive and FM synthesis, led to new thoughts about synthesizing sound spectra, tuning and pitch. Detached from their traditional association with the timbre of acoustic instruments, spectra become structured and associated with pitch in ways that are unique to the medium of computer music. The ACM Portal is published by the Association for Computing Machinery. Copyright © 2010 ACM, Inc. Terms of Usage Privacy Policy Code of Ethics Contact Us Useful downloads: Adobe Acrobat QuickTime Windows Media Player Real Player
Overview of the ImageCLEFmed 2007 Medical Retrieval and Medical Annotation Tasks
Authors: Henning Müller, Thomas Deselaers, Thomas M. Deserno, Jayashree Kalpathy---Cramer, Eugene Kim, William Hersh
Venue: Advances in Multilingual and Multimodal Information Retrieval: 8th Workshop of the Cross-Language Evaluation Forum, CLEF 2007, Budapest, Hungary, September 19-21, 2007, Revised Selected Papers (2008)

This paper describes the medical image retrieval and medical image annotation tasks of ImageCLEF 2007. Separate sections describe each of the two tasks, with the participation and an evaluation of major findings from the results of each given. A total of 13 groups participated in the medical retrieval task and 10 in the medical annotation task.The medical retrieval task added two new data sets for a total of over 66'000 images. Topics were derived from a log file of the Pubmed biomedical literature search system, creating realistic information needs with a clear user model.The medical annotation task was in 2007 organized in a new format as a hierarchical classification had to be performed and classification could be stopped at any hierarchy level. This required algorithms to change significantly and to integrate a confidence level into their decisions to be able to judge where to stop classification to avoid making mistakes in the hierarchy. Scoring took into account errors and unclassified parts.
Pitch Synchronous Based Feature Extraction for Noise-Robust Speaker Verification
Authors: Wei-Guo Gong, Li-Ping Yang, Di Chen
Venue: Proceedings of the 2008 Congress on Image and Signal Processing, Vol. 5 - Volume 05 (2008)

This paper proposes a pitch synchronous based feature extraction method for speaker verification under noisy conditions. Before feature extraction, a pitch synchronous analysis procedure is employed. Each speech frame of the input utterance is divided into a periodic part and a non-periodic part by pitch synchronous analysis. Because that the nonperiodic part causes harmonic leakage of the speech frame, only the periodic part is preserved for concatenating feature extraction. Two dominant spectral and cepstral analysis methods, MFCC and LPCC, are employed to represent the features of each frame. Speaker verification experiments under noisy conditions are conducted on NTT speech database. The performances of pitch synchronous based MFCC (p-syn MFCC), pitch synchronous based LPCC (psyn LPCC), MFCC and LPCC are compared with each other. Experiments results indicate that the proposed pitch synchronous based feature extraction method is efficient for speaker verification under noisy conditions.
Wavelet-Based Synthesis of a Multifractional Process
Authors: Zhao-rui Wang, Shan-wei Lü, Taketsune Nakamura
Venue: Proceedings of the 2008 Congress on Image and Signal Processing, Vol. 4 - Volume 04 (2008)

The multifractional process is introduced as a natural extension of traditional monofractional process. The selling point of multifractional process is that its Hölder regularity is allowed to vary from point to point, such that makes it a promising model for those stochastic processes whose regularity evolves in time. A new wavelet-based algorithm to synthesize a realization of multifractional process is proposed, and the validity is verified by numerical experiments and real-world data.
Shrinkage Estimator for Bayesian Network Parameters
Authors: John Burge, Terran Lane
Venue: Proceedings of the 18th European conference on Machine Learning (2007)

Maximum likelihood estimates (MLEs) are commonly used to parameterize Bayesian networks. Unfortunately, these estimates frequently have unacceptably high variance and often overfit the training data. Laplacian correction can be used to smooth the MLEs towards a uniform distribution. However, the uniform distribution may represent an unrealistic relationships in the domain being modeled and can add an unreasonable bias. We present a shrinkage estimator for domains with hierarchically related random variables that smoothes MLEs towards other distributions found in the training data. Our methods are quick enough to be performed during Bayesian network structure searches. On both a simulated and a real-world neuroimaging domain, we empirically demonstrate that our estimator yields superior parameters in the presence of noise and greater likelihoods on left-out data.
The Tactics Analysis about Early Phase Ends of the Partial Distortion Search
Authors: Wenguang Song, Qiongqin Jiang, Min Li, Youfu Du, Lin Chen
Venue: Proceedings of the 2008 Second International Conference on Genetic and Evolutionary Computing (2008)

The article analyzes the advantage and disadvantage of part lacking fidelity searching algorithm, based on early ending technology thought. Given the disadvantage of the partial distortion search (PDS) algorithm, it brings up one kind of improved method which is similar to it. The improved algorithm also calculates sum of absolute difference (SAD) once within a row and add it to the block pixel SAD, but the two disadvantages of part lacking fidelity searching algorithm has been improved. The results of related experiment show that the early termination of fine granularity adaptive threshold and search points in the levels of early termination of the introduction of adaptive strategies used in the paper improves the speed moving estimation. This will promote the transmission quality of network video frequency to a new higher grade.
Causal set topology
Authors: Sumati Surya
Venue: Theoretical Computer Science (2008)

The Causal Set Theory (CST) approach to quantum gravity is motivated by the observation that, associated with any causal spacetime (M,g) is a poset (M,@?), with the order relation @? corresponding to the spacetime causal relation. Spacetime in CST is assumed to have a fundamental atomicity or discreteness, and is replaced by a locally finite poset, the causal set. In order to obtain a well defined continuum approximation, the causal set must possess the requisite intrinsic topological and geometric properties that characterise a continuum spacetime in the large. The study of causal set topology is thus dictated by the nature of the continuum approximation. We review the status of causal set topology and present some new results relating poset and spacetime topologies. The hope is that in the process, some of the ideas and questions arising from CST will be made accessible to the larger community of computer scientists and mathematicians working on posets.
An Improved Extremum Seeking Algorithm Based on the Chaotic Annealing Recurrent Neural Network and Its Application
Authors: Yun-An Hu, Bin Zuo, Jing Li
Venue: Proceedings of the 4th international symposium on Neural Networks: Part II--Advances in Neural Networks (2007)

The application of sinusoidal periodic search signals into the general extremum seeking algorithm(ESA) results in the "chatter" problem of the output and the switching of the control law and incapability of escaping from the local minima. An improved chaotic annealing recurrent neural network (CARNN) is proposed for ESA to solve those problems in the general ESA and improve the global searching capability. The paper converts ESA into seeking the global extreme point where the slope of Cost Function is zero, and applies a CARNN to finding the global point and stabilizing the plant at that point. ESA combined with CARNN doesn't make use of search signals such as sinusoidal periodic signals, which solves those problems in previous ESA and improves the dynamic performance of the controlled system greatly. During the process of optimization, chaotic annealing is realized by decaying the amplitude of the chaos noise and the probability of accepting continuously. The process of optimization was divided into two phases: the coarse search based on chaos and the elaborate search based on ARNN. At last, CARNN will stabilize the system to the global extreme point. At the same time, it can be simplified by the proposed method to analyze the stability of ESA. The simulation results of a simplified UAV tight formation flight model and a typical Schaffer function validate the advantages mentioned above.
Does Knowledge Sharing Mediate the Relationship between Trust and Firm Performance?
Authors: Wang Cheng, Lan Hailin, Xie Hongming
Venue: Proceedings of the 2008 International Symposiums on Information Processing (2008)

Knowledge sharing is crucial for success of companies operating in turbulent and uncertain environments. Knowledge sharing need to be introduced at a rapid pace while at the same time companies have to absorb market information and integrate knowledge during information technology application. Hence, the purpose of this paper is to develop a general model on the critical antecedents and outcome of knowledge sharing. Using structural equations modeling with data collected 208 Chinese firms, the result show that knowledge sharing plays a perfect mediating role between trust and firm performance. Managerial implications are explored and future research directions are also identified.
Online Manifold Regularization: A New Learning Setting and Empirical Study
Authors: Andrew B. Goldberg, Ming Li, Xiaojin Zhu
Venue: Proceedings of the 2008 European Conference on Machine Learning and Knowledge Discovery in Databases - Part I (2008)

We consider a novel "online semi-supervised learning" setting where (mostly unlabeled) data arrives sequentially in large volume, and it is impractical to store it all before learning. We propose an online manifold regularization algorithm. It differs from standard online learning in that it learns even when the input point is unlabeled. Our algorithm is based on convex programming in kernel space with stochastic gradient descent, and inherits the theoretical guarantees of standard online algorithms. However, naïve implementation of our algorithm does not scale well. This paper focuses on efficient, practical approximations; we discuss two sparse approximations using buffering and online random projection trees. Experiments show our algorithm achieves risk and generalization accuracy comparable to standard batch manifold regularization, while each step runs quickly. Our online semi-supervised learning setting is an interesting direction for further theoretical development, paving the way for semi-supervised learning to work on real-world life-long learning tasks.
A Fast and Exact Algorithm for the Median of Three Problem--A Graph Decomposition Approach
Authors: Andrew Wei Xu
Venue: Proceedings of the international workshop on Comparative Genomics (2008)

In a previous paper, we have shown that adequate subgraphs can be used to decompose multiple breakpoint graphs, achieving a dramatic speedup in solving the median problem. In this paper, focusing on the median of three problem, we prove more important properties about adequate subgraphs with rank 3 and discuss the algorithms inventorying simple adequate subgraphs. After finding simple adequate subgraphs of small sizes, we incorporate them into ASMedian, an algorithm to solve the median of three problem. Results on simulated data show dramatic speedup so that many instances can be solved very quickly, even ones containing hundreds or thousands of genes.
DL-FOIL Concept Learning in Description Logics
Authors: Nicola Fanizzi, Claudia D'Amato, Floriana Esposito
Venue: Proceedings of the 18th international conference on Inductive Logic Programming (2008)

In this paper we focus on learning concept descriptions expressed in Description Logics. After stating the learning problem in this context, a FOIL-like algorithm is presented that can be applied to general DL languages, discussing related theoretical aspects of learning with the inherent incompleteness underlying the semantics of this representation. Subsequently we present an experimental evaluation of the implementation of this algorithm performed on some real ontologies in order to empirically assess its performance.
Unusual Event Recognition for Mobile Alarm System
Authors: Sooyeong Kwak, Guntae Bae, Kilcheon Kim, Hyeran Byun
Venue: Proceedings of the 7th international conference on Computational Science, Part IV: ICCS 2007 (2007)

This paper proposes an unusual event recognition algorithm, which is a part of a mobile alarm system. Our systems focus on unusual event. When the system detects the unusual event, the photos of emergency situation are passed to the user's portable devices such as mobile phone or PDA along with event description to help the user's final decision. The system combines the foreground segmentation, object tracking and unusual event recognition to detect the Drop off, Abandon and Steal bag event. The event recognition module constructs the Bayesian network of each event and uses inference algorithm to detect the unusual event. The proposed system tested in PETS2006 and CAVIAR dataset. The proposed algorithm showed good results on the real world environment and also worked at real time speed.
Schema-Based Design and the AKIRA Schema Language: An Overview
Authors: Giovanni Pezzulo, Gianguglielmo Calvi
Venue: Anticipatory Behavior in Adaptive Learning Systems: From Brains to Individual and Social Behavior (2007)

We present a theoretical analysis of schema-based design (SBD), a methodology for designing autonomous agent architectures. We also provide an overview of the AKIRA Schema Language (AKSL), which permits to design schema-based architectures for anticipatory behavior experiments and simulations. Several simulations using AKSL are reviewed, highlighting the relations between pragmatic and epistemic aspects of behavior. Anticipation is crucial in realizing several functionalities with AKSL, such as selecting actions, orienting attention, categorizing and grounding declarative knowledge.