ppxscal/embedding_network huggingface dataset:
Shape matching by curve modelling and alignment
Authors: Cecilia Di Ruberto, Marco Gaviano, Andrea Morgera
Venue: WSEAS Transactions on Information Science and Applications (2009)

Automatic information retrieval in the field of shape recognition has been widely covered by many research fields. Various techniques have been developed using different approaches such as intensity-based, model-based and shape-based methods. Whichever is the way to represent the objects in images, a recognition method should be robust in the presence of scale change, translation and rotation. In this paper we present a new recognition method based on a curve alignment technique, for planar image contours. The method consists of various phases including extracting outlines of images, detecting significant points and aligning curves. The dominant points can be manually or automatically detected. The matching phase uses the idea of calculating the overlapping indices between shapes as similarity measures. To evaluate the effectiveness of the algorithm, two databases of 216 and 99 images have been used. A performance analysis and comparison is provided by precision-recall curves.
Automation of pattern recognition and fractal-geometry-based pattern quantification, exemplified by mineral-phase distribution patterns in igneous rocks
Authors: Mark Peternell, Jörn H. Kruhl
Venue: Computers Geosciences (2009)

This study analyses the possibility of accurate quantification of automatically digitized mineral-phase distribution patterns in igneous rocks. Based on their colour contrast, different minerals were manually and automatically digitized on micro to macro scales. Depending on the digitized mineral phase, the accuracy of the automated digitizing procedure varies. Quantification of mineral distribution patterns was performed by box-counting. The results do not depend greatly on the pattern's pixel density and are similar to each other, even if automatic recording is performed at reduced precision in comparison to manual recording. Consequently, box-counting measurement of automatically recorded mineral distribution patterns (i) leads to fast and accurate pattern quantification, (ii) allows analysis of various phase distribution patterns from micro to macro scales, and (iii) forms an excellent basis for receiving information on pattern-forming processes, which is not available otherwise.
A Multiagent System for Scheduling Activities Onboard a Space System
Authors: Francesco Amigoni, Simone Farè, Michèle Lavagna, Guido Sangiovanni
Venue: Proceeding of the 2006 conference on ECAI 2006: 17th European Conference on Artificial Intelligence August 29 -- September 1, 2006, Riva del Garda, Italy (2006)

The possible advantages of employing multiple agents to manage activities on a single space system are largely unexplored. This paper presents the experimental validation of a multiagent scheduler for a low Earth orbit satellite.
Cross-document entity co-reference resolution in noisy environments
Authors: James Pustejovsky
Venue:  (2008)

Cross-document entity co-reference resolution task is part of and largely based on many Natural Language Processing (NLP) innovations that have been developed in the past several decades and are still evolving. At the core of the task is determining whether two or more pieces of information, each mentioned locally in various documents, refer to the same global entity. The complexity of the task increases when the documents represent a variety of sources including unstructured text, speech, and foreign languages. This dissertation presents a complete end-to-end solution to the problem of cross-document entity co-reference. The research divides the task into two major components: Name Matching and Entity Disambiguation. The two components have been designed for scalability, extensibility, and incremental processing. The Name Matching component consists of more than a dozen algorithms and produces equivalences between corpus names. The algorithms use a variety of information sources which fall into four categories: World Knowledge, Web Knowledge, String Similarity, and Statistical Extraction. The produced alternatives represent various name forms: misspellings, aliases, abbreviations, alternative spellings, short and long versions, nicknames, etc. The Entity Disambiguation component implements a 3-stage agglomerative clustering algorithm to resolve local entities to global clusters. Each of the algorithm stages uses combinations of various features to adjust discriminative levels in cluster comparisons. The features are retrieved from document metadata, information extraction, unsupervised topicality, and more. The system has been evaluated in several ways. The Name Matching component has been tested on a corpus consisting of more than half a million documents from various genres. The performance of the Entity Disambiguation component has been measured against human-annotated collections of English and Arabic documents mentioning ambiguous person and organization names. The truth data were produced using a cross-document annotation tool designed specifically for this research.**Copyright 2008 by BBN Technologies Corp. All Rights Reserved. Distribution Statement A (Approved for Public Release; Distribution Unlimited).
A patrol grid protocol for mobile wireless sensor network
Authors: Dongliang Xie, Mingxing Chen, Chen Canfeng, Jian Ma
Venue: Proceedings of the 4th Annual International Conference on Wireless Internet (2008)

Nowadays more requirements for wireless sensor networks are utilized to military, science and our daily life gradually, however the sink mobility is still bottleneck problem in a number of WSN application scenarios. In some fields like environmental monitoring, the solution is an especially urgent request. In this paper we propose Patrol Grid Protocol (PGP), a sink mobility supported route protocol for environmental monitoring which builds on a previously developed routing protocol called TWO-Tier Data Dissemination (TTDD). We prove that PGP can be more suitable for urgent events and query-driven mode than TTDD. The description of mechanisms and simulation are presented firstly, then we evaluate the performance of the new protocol and analyze the overhead and delay. PGP is a more applicable protocol for environmental monitoring.
Composite boolean separators for data analysis with applications in computed tomography and gene expression microarray data
Authors: Peter L. Hammer, Alexander Kogan
Venue:  (2007)

An important topic in machine-learning/data-mining is that of analyzing binary datasets. A binary dataset consists of a subset of n-vectors (observations) with binary components, each of which has an associated binary outcome (the class of the observation). Clearly, the set of n-vectors and their outcomes represent a partially defined Boolean function. The central problem of machine-learning/data-mining, the so-called classification problem, consists in finding an &ldquo;extension&rdquo; of the partially defined Boolean function closely approximating a hidden (&ldquo;target&rdquo;) function. Various methods have been developed to solve this and related problems, such as identifying misclassified observations, revealing irrelevant and/or redundant variables, etc.In this thesis, we propose a new approach to analyzing different problems in machine-learning/data-mining. First, we define a simple procedure for generating artificial Boolean variables, called Composite Boolean Features, and describe an iterative algorithm for generating Boolean functions which agree with the outcomes in a large proportion of the observations in the dataset. We call these functions Composite Boolean Separators ( CBSes for short). We then use the idea of CBSes in several ways. In particular, (1) we demonstrate the usefulness of these concepts by showing how the introduction of CBSes can enhance the accuracy of classification systems; (2) we employ CBSes for identifying misclassified observations and examine how deletion of such observations and reversal of their class influence the classification accuracy; (3) we apply the new variables to the attribute selection problem, i.e., to the problem of finding &ldquo;good&rdquo; (informative) subsets of the original attributes, or equivalently, identifying &ldquo;bad&rdquo; (irrelevant and/or redundant) attributes in the given datasets. All the results have been tested on eight publicly available datasets and validated by five well-known machine-learning/data-mining techniques. Also, we applied CBSes, along with other techniques, to the analysis of two real-life medical datasets: computed tomography data and breast cancer gene expression microarray data. The results presented in this thesis demonstrate that for many real-life datasets, the application of CBSes increases the classification accuracy significantly. CBSes also prove useful in the missclassification and attribute selection problems.
Applying fuzzy engineering economics to evaluate project investment feasibility of wind generation
Authors: J. N. Sheen
Venue: WSEAS TRANSACTIONS on SYSTEMS (2009)

In this paper, a fuzzy engineering economic decision model is derived to evaluate the investment feasibility of wind generation project. A straightforward vertex parameters' fuzzy mathematics operation using the function principle is derived as an alternative to the traditional extension principle, and is applied to evaluate a number of different economic decision indexes. Compared to the extension principle, the function principle is simple to implement and is conceptually straightforward. Using Mellin transform, the geometric moments of the fuzzy economic indexes are established in order to determine their relative ranking as part of a decision-making process. The performance of the proposed fuzzy economic model is verified by considering their application to a practical wind generation project in Taiwan. These investigations not only confirm that the results of the fuzzy economic model is consistent with the conventional crisp model, but also demonstrate that the proposed model is more flexible, intelligent and computationally efficient compared to the extension principle fuzzy mathematics approach. The developed model represent readily implemented feasibility analysis tool for use in the arena of uncertain economic decision-making.
Supporting Team Members Evaluation in Software Project Environments
Authors: Sergio F. Ochoa, Osvaldo Osorio, José A. Pino
Venue: Proceeding of the 2008 conference on Collaborative Decision Making: Perspectives and Challenges (2008)

Companies are increasingly encouraging employees to work cooperatively, to coordinate their activities in order to reduce costs, increase production, and improve services or just to augment the robustness of the organization. This is particularly relevant in the software industry where the available time frames are quite tight. However, many software companies do not formally evaluate their team performance because the available methods are complex, expensive, slow to deliver the results or error-prone. In case of software companies that evaluate team performance, they have also to deal with team members feeling about the fairness of such evaluations. This paper presents a method intended to evaluate the software team and their members' performance in a simple and fast manner, involving also a low application cost. The method, called Team Evaluation Method (TEM), is supported by a software tool, which reduces the application effort. The proposal has been used to evaluate software development teams, and the obtained results are satisfactory.
Pioneering Plus a Broad Product Line Strategy: Higher Profits or Deeper Losses?
Authors: William Boulding, Markus Christen
Venue: Management Science (2009)

Previous research suggests firms can build a market share advantage by preempting later entrants with a broad product line and expanding rapidly into related markets. Whether such a strategy leads to a pioneering profit advantage relative to followers also depends on its cost effects. In this paper, we examine when the market share advantage of a pioneering firm with a broad product line strategy translates into a profit advantage by examining the cost effects of this strategy. Using the profit impact of marketing strategies data and an estimation method that controls for various unobserved factors, we find significant differences between different industry settings. From these contrasting findings, we generate an emerging theoretical framework that we subject to empirical testing. We conjecture, and empirically verify, that creating a broad product line with a versioning strategy---creating variety from a standard product in anticipating customer demand---does not increase the pioneering cost disadvantage, and thus results in a pioneering profit advantage. On the other hand, with a tailoring strategy---creating variety by customizing a product to actual customer demand---a broad product line substantially increases the pioneering cost disadvantage, thereby making a preemption strategy counterproductive.
Rewriting Logic Specification of Membrane Systems with Promoters and Inhibitors
Authors: Oana Agrigoroaiei, Gabriel Ciobanu
Venue: Electronic Notes in Theoretical Computer Science (ENTCS) (2009)

Membrane systems represent a new model of computation involving parallel application of rules, communication between membranes and dissolving. Since rewriting logic is a general framework for concurrent systems, we connect it with the operational semantics of membrane systems. We use a new representation given by register membranes which are able to express the evolution involving rules with promoters and inhibitors. The evolution is expressed in terms of both dynamic and static allocation of resources to rules. It is proved that these semantics are equivalent. Dynamic allocation allows translation of the maximal parallel application of membrane rules into sequential rewritings. An implementation in Maude is provided.
Fast and Accurate Bounds on Linear Programs
Authors: Ernst Althaus, Daniel Dumitriu
Venue: Proceedings of the 8th International Symposium on Experimental Algorithms (2009)

We present an algorithm that certifies the feasibility of a linear program while using rational arithmetic as little as possible. Our approach relies on computing a feasible solution of the linear program that is as far as possible from satisfying an inequality at equality. To realize such an approach, we have to detect the set of inequalities that can only be satisfied at equality.Compared to previous approaches for this problem our algorithm has a much higher rate of success.
Plenary lecture IV: global optimization strategies for improved bandwidth management in wireless communications
Authors: Dimitrios A. Karras
Venue: Proceedings of the 10th WSEAS international conference on Mathematical methods, computational techniques and intelligent systems (2008)

Bandwidth management is one of the fundamental issues in wireless communications. The corresponding allocation schemes can not be static due to the dynamically changing traffic conditions and network performance. Thus, more sophisticated strategies adapted to current network conditions must be investigated and applied. Recently, various approaches have been proposed for channel allocation based on intelligent techniques such as multi-agent technology and genetic algorithms. These approaches constitute heuristic solutions to resource management problem. The goal of this plenary speech is two fold. First, is to present global optimization strategies for bandwidth management, based on computational intelligence techniques. Second, is to illustrate the development and application of a novel global optimization scheme, based on the ant colony optimization approach. Such an approach has not been proposed so far for solving the channel allocation problem in wireless communication systems. A comprehensive heuristic methodology based on global optimization and intelligent techniques like ant colony optimization and multi-agents is herein proposed. Simulation results show network performance improvement of the proposed global optimization strategy based on computational intelligence.
Evaluation Evaluation
Authors: David M. W. Powers
Venue: Proceeding of the 2008 conference on ECAI 2008: 18th European Conference on Artificial Intelligence (2008)

Over the last decade there has been increasing concern about the biases embodied in traditional evaluation methods for Natural Language Processing/Learning, particularly methods borrowed from Information Retrieval. Without knowledge of the Bias and Prevalence of the contingency being tested, or equivalently the expectation due to chance, the simple conditional probabilities Recall, Precision and Accuracy are not meaningful as evaluation measures, either individually or in combinations such as F-factor. The existence of bias in NLP measures leads to the 'improvement' of systems by increasing their bias, such as the practice of improving tagging and parsing scores by using most common value (e.g. water is always a Noun) rather than the attempting to discover the correct one. In this paper, we will analyze both biased and unbiased measures theoretically, characterizing the precise relationship between all these measures.
Computing and Minimizing Cache Vulnerability to Transient Errors
Authors: Wei Zhang
Venue: IEEE Design Test (2009)

Using a cache vulnerability factor to measure the susceptibility of cache memories to transient errors at the architecture level can help designers make appropriate cost and reliability trade-offs at early design cycles. Two early write-back strategies can also improve the reliability of write-back data caches without compromising performance. 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
Guarantees for the success frequency of an algorithm for finding Dodgson-election winners
Authors: Christopher M. Homan, Lane A. Hemaspaandra
Venue: Journal of Heuristics (2009)

In the year 1876 the mathematician Charles Dodgson, who wrote fiction under the now more famous name of Lewis Carroll, devised a beautiful voting system that has long fascinated political scientists. However, determining the winner of a Dodgson election is known to be complete for the &Theta;2 p level of the polynomial hierarchy. This implies that unless P=NP no polynomial-time solution to this problem exists, and unless the polynomial hierarchy collapses to NP the problem is not even in NP. Nonetheless, we prove that when the number of voters is much greater than the number of candidates—although the number of voters may still be polynomial in the number of candidates—a simple greedy algorithm very frequently finds the Dodgson winners in such a way that it “knows” that it has found them, and furthermore the algorithm never incorrectly declares a nonwinner to be a winner.
Evaluating an hepatic enzyme induction mechanism through coarse- and fine-grained measurements of an in silico liver
Authors: Glen E. P. Ropella, Sunwoo Park, C. Anthony Hunt
Venue: Complexity (2009)

Results from simulation experiments falsified the hypothesis that a uniform distribution of simulated drug passing through an in silico liver (ISL) will produce a uniform extent of enzyme induction (EI). Wet-lab EI experiments, as formulated, are infeasible. The simulated EI is intended to have a hepatic counterpart. The ISL is synthetic, physiologically based, fine-grained, and multi-agent. It has been validated against in situ drug disposition data. We discuss methodological considerations regarding the phenomenal manifold, multi-level observation, and manipulation of synthetic models and their referents. Interestingly, a lower probability of metabolism caused higher EI and, counter-intuitively, more extraction. &copy; 2008 Wiley Periodicals, Inc. Complexity, 2009 This article was submitted as an invited paper resulting from the &ldquo;Understanding Complex Systems&rdquo; conference held at the University of Illinois at Urbana-Champaign, May 2007.
Content-based image retrieval methods
Authors: N. S. Vassilieva
Venue: Programming and Computing Software (2009)

Creation of a content-based image retrieval system implies solving a number of difficult problems, including analysis of low-level image features and construction of feature vectors, multidimensional indexing, design of user interface, and data visualization. Quality of a retrieval system depends, first of all, on the feature vectors used, which describe image content. The paper presents a survey of common feature extraction and representation techniques and metrics of the corresponding feature spaces. Color, texture, and shape features are considered. A detailed classification of the currently known features' representations is given. Experimental results on efficiency comparison of various methods for representing and comparing image content as applied to the retrieval and classification tasks are presented.
Photorealistic Large-Scale Urban City Model Reconstruction
Authors: Charalambos Poullis, Suya You
Venue: IEEE Transactions on Visualization and Computer Graphics (2009)

The rapid and efficient creation of virtual environments has become a crucial part of virtual reality applications. In particular, civil and defense applications often require and employ detailed models of operations areas for training, simulations of different scenarios, planning for natural or man-made events, monitoring, surveillance, games, and films. A realistic representation of the large-scale environments is therefore imperative for the success of such applications since it increases the immersive experience of its users and helps reduce the difference between physical and virtual reality. However, the task of creating such large-scale virtual environments still remains a time-consuming and manual work. In this work, we propose a novel method for the rapid reconstruction of photorealistic large-scale virtual environments. First, a novel, extendible, parameterized geometric primitive is presented for the automatic building identification and reconstruction of building structures. In addition, buildings with complex roofs containing complex linear and nonlinear surfaces are reconstructed interactively using a linear polygonal and a nonlinear primitive, respectively. Second, we present a rendering pipeline for the composition of photorealistic textures, which unlike existing techniques, can recover missing or occluded texture information by integrating multiple information captured from different optical sensors (ground, aerial, and satellite).