ppxscal/embedding_network huggingface dataset:
ROC curves and video analysis optimization in intestinal capsule endoscopy
Authors: Fernando Vilariño, Ludmila I. Kuncheva, Petia Radeva
Venue: Pattern Recognition Letters (2006)

Wireless capsule endoscopy involves inspection of hours of video material by a highly qualified professional. Time episodes corresponding to intestinal contractions, which are of interest to the physician constitute about 1% of the video. The problem is to label automatically time episodes containing contractions so that only a fraction of the video needs inspection. As the classes of contraction and non-contraction images in the video are largely imbalanced, ROC curves are used to optimize the trade-off between false positive and false negative rates. Classifier ensemble methods and simple classifiers were examined. Our results reinforce the claims from recent literature that classifier ensemble methods specifically designed for imbalanced problems have substantial advantages over simple classifiers and standard classifier ensembles. By using ROC curves with the bagging ensemble method the inspection time can be drastically reduced at the expense of a small fraction of missed contractions.
Visual Categorization and Object Representation in Monkeys and Humans
Authors: N. Sigala, F. Gabbiani, N. K. Logothetis
Venue: Journal of Cognitive Neuroscience (2002)

We investigated the influence of a categorization task on the extraction and representation of perceptual features in humans and monkeys. The use of parameterized stimuli (schematic faces and fish) with fixed diagnostic features in combination with a similarity-rating task allowed us to demonstrate perceptual sensitization to the diagnostic dimensions of the categorization task for the monkeys. Moreover, our results reveal important similarities between human and monkey visual subordinate categorization strategies. Neither the humans nor the monkeys compared the new stimuli to class prototypes or based their decisions on conditional probabilities along stimulus dimensions. Instead, they classified each object according to its similarity to familiar members of the alternative categories, or with respect to its position to a linear boundary between the learned categories.
Flexible agent protocols via temporal and resource-based reasoning
Authors: Duc Q. Pham, James Harland
Venue: Proceedings of the fifth international joint conference on Autonomous agents and multiagent systems (2006)

In multi-agent systems, it has long been recognized that the traditional approaches to protocols which often used a fixed sequence of interactive actions as the basis are too brittle, and more flexible methods are needed. A crucial aspect of the development of such methods is the notion of commitments, which provides a mechanism for regulating interactions between agents. In this paper we investigate a rule-based approach to the specification of flexible protocols by means of a reasoning system which incorporates both temporal reasoning and resources-based reasoning and uses the notion of commitments.
A 3-A CMOS low-dropout regulator with adaptive Miller compensation
Authors: Xinquan Lai, Jianping Guo, Zuozhi Sun, Jianzhang Xie
Venue: Analog Integrated Circuits and Signal Processing (2006)

A 3-A CMOS low-dropout regulator (LDO) is presented by utilizing adaptive Miller compensation (AMC) technique, which provides high stability, as well as fast line and load transient responses. The proposed LDO has been fabricated in a standard 0.5 ¿m CMOS technology, and the die area is small as 1330 ¿m × 1330 ¿m with the area-efficient waffle layout for power transistors. Both load and line regulation are less than ±0.1%. And the output voltage can recover within 80 ¿s for full load changes. The power---supply rejection ratio (PSRR) at 20 KHz is ¿30 dB. Moreover, it is stable enough with a ceramic capacitor small to 2.2 ¿F, and the added series resistance is not needed.
A distribution of impact factors of journals in the area of software: an empirical study
Authors: Bibhuti Bhusan Sahoo, I. K. Ravichandra Rao
Venue: Information Processing and Management: an International Journal (2006)

Data from two bibliographic databases i.e. COMPENDEX and INSPEC have been collected on the broad subject software and related topics. The titles of the journals were extracted from the database. The impact factors of the titles were also collected in order to study the distribution of impact factors. An attempt has been made to identify a suitable model to describe a distribution of impact factors. It has been observed that a Gamma distribution fits the observed data very well with one of the parameters as mean of the distribution and other parameter as 1. Further it has been observed that the researchers are now publishing their articles in high impact factor journals.
Belief Update in Bayesian Networks Using Uncertain Evidence
Authors: Rong Pan, Yun Peng, Zhongli Ding
Venue: Proceedings of the 18th IEEE International Conference on Tools with Artificial Intelligence (2006)

This paper reports our investigation on the problem of belief update in Bayesian networks (BN) using uncertain evidence. We focus on two types of uncertain evidences, virtual evidence (represented as likelihood ratios) and soft evidence (represented as probability distributions). We review three existing belief update methods with uncertain evidences: virtual evidence method, Jeffrey's rule, and IPFP (iterative proportional fitting procedure), and analyze the relations between these methods. This indepth understanding leads us to propose two algorithms for belief update with multiple soft evidences. Both of these algorithms can be seen as integrating the techniques of virtual evidence method, IPFP and traditional BN evidential inference, and they have clear computational and practical advantages over the methods proposed by others in the past.
Using uncertainty in reputation methods to enforce cooperation in ad-hoc networks
Authors: Kevin Kane, James C. Browne
Venue: Proceedings of the 5th ACM workshop on Wireless security (2006)

This paper gives an approach to reputation computation that incorporates "uncertainty" based on subjective logic. Uncertainty can arise when a node joins the network and thus has no history, or when a node's behavior changes in a way that is not clearly malicious, but at least suspicious. This uncertainty indicates when a node evaluating the reputation rating of another node should poll its neighbors for recommendations, because its local opinion is not sufficiently well-informed.The uncertainty based algorithm has several parameters and the computed reputation depends on these parameters. To evaluate the effectiveness of the uncertainty based method and to determine the effect of the parameters on the reputation computations, we have implemented a simulation infrastructure for the behavior of ad-hoc networks using the uncertainty based scheme. The simulator can also use other previously proposed mechanisms for reputation computation. The simulator is used to determine optimal parameters for the various schemes and how well each scheme a) ensures cooperative nodes receive service when requested, and b) throttles the ability of free-loading (malicious) nodes to consume service without contributing. The simulations show that the reputation computation that incorporates uncertainty provides superior recognition of "malicious" behavior in a variety of ad-hoc network situations. These initial results are sufficiently promising to motivate continuing study of reputation computations incorporating uncertainty to additional models of malicious behavior and a broader range of network behaviors.
On the Stability of Evolution Galerkin Schemes Applied to a Two-Dimensional Wave Equation System
Authors: M. Lukácová-Medvidová, G. Warnecke, Y. Zahaykah
Venue: SIAM Journal on Numerical Analysis (2006)

The subject of the paper is the analysis of stability of the evolution Galerkin (EG) methods for the two-dimensional wave equation system. We apply von Neumann analysis and use the Fourier transformation to estimate the stability limits of both the first and the second order EG methods.
Epidemic-based approaches for reliable multicast in mobile ad hoc networks
Authors: Öznur Özkasap, Zülküf Genç, Emre Atsan
Venue: ACM SIGOPS Operating Systems Review (2006)

We present a classification of epidemic-based approaches utilized in the context of mobile ad hoc networks (MANET) with a focus on reliable multicast protocols. We provide a brief description of the other approaches to reliable multicasting in MANETs as well. Then, we describe our protocol, namely EraMobile, offering Epidemic-based Reliable and Adaptive Multicast for Mobile ad hoc networks. EraMobile's target is group applications requiring high-level of reliability and the protocol aims to provide fully reliable multicast data delivery with minimal network overhead even in the adverse network conditions. EraMobile utilizes an epidemic-based method in multicast operation to cope with dynamic and unpredictable topology changes arising from the mobility. Our epidemic mechanism does not require the maintenance of any tree- or mesh-like structure for multicasting. It also needs neither having global or partial view of the network nor having information of neighboring nodes and group members. Besides, it substantially minimizes the overhead incurred by eliminating redundant data transmissions. Another distinguishing feature of EraMobile is its capability of adapting to varying node densities in order to provide reliable data delivery in both sparse networks, where the network connectivity is prone to interruptions, and dense networks, where congestion is likely to occur. EraMobile is shown to achieve fully reliable multicast data delivery studied through extensive simulations by outperforming the other protocols compared, especially in terms of both packet delivery ratio and overhead efficiency.
Semantic Category Interference in Overt Picture Naming: Sharpening Current Density Localization by PCA
Authors: Burkhard Maess, Angela D. Friederici, Markus Damian, Antje S. Meyer, Willem J. M. Levelt
Venue: Journal of Cognitive Neuroscience (2002)

The study investigated the neuronal basis of the retrieval of words from the mental lexicon. The semantic category interference effect was used to locate lexical retrieval processes in time and space. This effect reflects the finding that, for overt naming, volunteers are slower when naming pictures out of a sequence of items from the same semantic category than from different categories. Participants named pictures blockwise either in the context of same- or mixed-category items while the brain response was registered using magnetoencephalography (MEG). Fifteen out of 20 participants showed longer response latencies in the same-category compared to the mixed-category condition. Event-related MEG signals for the participants demonstrating the interference effect were submitted to a current source density (CSD) analysis. As a new approach, a principal component analysis was applied to decompose the grand average CSD distribution into spatial subcomponents (factors). The spatial factor indicating left temporal activity revealed significantly different activation for the same-category compared to the mixed-category condition in the time window between 150 and 225 msec post picture onset. These findings indicate a major involvement of the left temporal cortex in the semantic interference effect. As this effect has been shown to take place at the level of lexical selection, the data suggest that the left temporal cortex supports processes of lexical retrieval during production.
Security Framework for P2P Based Grid Systems
Authors: T. N. Ellahi, B. Hudzia, L. Mcdermott, T. Kechadi
Venue: Proceedings of the Proceedings of The Fifth International Symposium on Parallel and Distributed Computing (2006)

Grid and P2P systems enable users to share resources across organization boundaries. A strong security system is an integral component of grid middleware to enable secure resource sharing at a very large scale. P2P grid systems combine approaches from both worlds to share resources at a very large scale. P2P grid systems have a different set of security requirements contrary to the traditional server based centralized grid systems. This paper proposes a decentralized security framework for P2P grid systems. This framework is part of a P2P based data grid middleware DGET (Data Grid Environment and Tools).
Enumeration of unrooted maps of a given genus
Authors: Alexander Mednykh, Roman Nedela
Venue: Journal of Combinatorial Theory Series B (2006)

Let Ng (f) denote the number of rooted maps of genus g having f edges. An exact formula for Ng (f) is known for g = 0 (Tutte, 1963), g = 1 (Arques, 1987), g = 2, 3 (Bender and Canfield, 1991). In the present paper we derive an enumeration formula for the number Θγ (e) of unrooted maps on an orientable surface Sγ of a given genus γ and with a given number of edges e. It has a form of a linear combination Σi,jci,jNgj (fi) of numbers of rooted maps Ngj (fi) for some gj ≤ γ and fi ≤ e. The coefficients ci,j are functions of γ and e. We consider the quotient Sγ/Zl of Sγ by a cyclic group of automorphisms Zl as a two-dimensional orbifold O. The task of determining ci,j requires solving the following two subproblems: (a) to compute the number Epio (Γ, Zl) of order-preserving epimorphisms from the fundamental group Γ of the orbifold O=Sγ/Zl onto Zl; (b) to calculate the number of rooted maps on the orbifold O which lifts along the branched covering Sγ → Sγ/Zl to maps on Sγ with the given number e of edges.The number Epio (Γ, Zl) is expressed in terms of classical number-theoretical functions. The other problem is reduced to the standard enumeration problem of determining the numbers Ng(f) for some g ≤ γ and f ≤ e. It follows that Θγ (e) can be calculated whenever the numbers Ng (f) are known for g ≤ γ and f ≤ e. In the end of the paper the above approach is applied to derive the functions Θγ(e) explicitly for γ ≤ 3. We note that the function Θγ(e) was known only for γ = 0 (Liskovets, 1981). Tables containing the numbers of isomorphism classes of maps with up to 30 edges for genus γ = 1, 2, 3 are presented.
Finding the Right Features for Instrument Classification of Classical Music
Authors: Da Deng, Christian Simmermacher, Stephen Cranefield
Venue: Proceedings of the International Workshop on on Integrating AI and Data Mining (2006)

In tackling data mining and pattern recognition tasks, finding a compact but effective set of features is often a crucial step in the whole problem solving process. In this paper we present an empirical study on feature selection for classical instrument recognition, using machine learning techniques to select and evaluate features extracted from a number of different feature schemes in terms of their classification performance. It is revealed that there is significant redundancy in existing feature schemes commonly used in practice. Our results suggest that further feature analysis research is necessary for optimising feature selection for the instrument recognition problem.
Incremental HLA-based distributed simulation cloning
Authors: Dan Chen, Stephen John Turner, Wentong Cai, Boon Ping Gan, Malcolm Yoke Hean Low
Venue: Proceedings of the 36th conference on Winter simulation (2004)

Distributed simulation cloning technology is designed to analyze alternative scenarios of a distributed simulation concurrently within the same execution session. The goal is to optimize the execution time for evaluating different scenarios by avoiding repeated computation. In terms of High Level Architecture (HLA) based simulations, a federate may make clones to explore different scenarios at decision points. It is desirable to use an incremental cloning mechanism to replicate only those federates whose states will be affected. This paper discusses the theory and issues involved in incremental distributed simulation cloning, which employs an event checking algorithm to ensure accurate sharing and initiates cloning only when absolutely necessary. Experiments have been performed to compare the performance of entire cloning and incremental cloning mechanisms. The experimental results indicate that cloning technologies can effectively reduce the time of executing multiple scenarios, and the incremental cloning mechanism significantly surpasses entire cloning in execution efficiency.
Mining databases of labeled trees using canonical forms
Authors: Richard R. Muntz
Venue:  (2005)

Tree structures are used extensively in domains such as computational biology, pattern recognition, XML databases, computer networks, and so on. One important problem in mining databases of labeled trees is to find frequently occurring subtrees. Discovering frequent subtrees has practical importance such as improving a user's understanding about a data source, helping database indexing and access method design, serving as the first step in classifying and clustering tree-structured data. In this thesis, we study this important problem of frequent subtree mining. We first give requisite background in graph theory and association rule mining. Then we give a formal definition of the frequent subtree mining problem. The main contributions of this thesis are three fold. Firstly, we define two canonical forms, the breadth-first canonical form (BFCF) and the depth-first canonical form (DFCF) that uniquely represent rooted unordered trees and free trees. These canonical forms introduce a one-to-one mapping between a labeled tree and a string. Based on the string representation, a total order is defined on labeled trees. Our canonical forms are the first ones of their type. Secondly, based on the canonical forms, we develop two algorithms that discover frequent subtrees from databases of various types of labeled trees. The first algorithm, FreeTreeMiner, which adapts the well-known Apriori algorithm in association rule mining, generates candidate subtrees in a level-by-level fashion. The second algorithm, HybridTreeMiner, generates candidate subtrees by traversing an enumeration tree of all frequent subtrees. Thirdly, to alleviate the issue of combinatorial explosion, we propose a computationally efficient algorithm, CMTreeMiner, that discovers closed and maximal frequent subtrees. CMTreeMiner is the first algorithm that directly mines closed and maximal frequent subtrees instead of using a post-processing pruning step. We study the performance of our algorithms and compare their performance with that of other algorithms from the literature through extensive experiments, using both synthetic data and data sets from real applications.
JavaScript instrumentation for browser security
Authors: Dachuan Yu, Ajay Chander, Nayeem Islam, Igor Serikov
Venue: Proceedings of the 34th annual ACM SIGPLAN-SIGACT symposium on Principles of programming languages (2007)

It is well recognized that JavaScript can be exploited to launch browser-based security attacks. We propose to battle such attacks using program instrumentation. Untrusted JavaScript code goes through a rewriting process which identifies relevant operations, modifies questionable behaviors, and prompts the user (a web page viewer) for decisions on how to proceed when appropriate. Our solution is parametric with respect to the security policy-the policy is implemented separately from the rewriting, and the same rewriting process is carried out regardless of which policy is in use. Be-sides providing a rigorous account of the correctness of our solution, we also discuss practical issues including policy management and prototype experiments. A useful by-product of our work is an operational semantics of a core subset of JavaScript, where code embedded in (HTML) documents may generate further document pieces (with new code embedded) at runtime, yielding a form of self-modifying code.
Memoized Forward Computation of Dynamic Slices
Authors: Wes Masri, Nagi Nahas, Andy Podgurski
Venue: Proceedings of the 17th International Symposium on Software Reliability Engineering (2006)

Forward computation of dynamic slices is necessary to support interactive debugging and online analysis of long running programs. However, the overhead of existing forward computing algorithms limits their use to nonprocessing intensive applications. Recent empirical studies have shown that slices tend to reoccur often during execution. This paper presents a new forward computing algorithm for dynamic slicing, which is based on the stronger assumption that the same set union operations need to be performed repeatedly during slice computation. We present the results of an empirical study contrasting the performance of our new algorithm to the performance of a basic forward computing algorithm that unconditionally merges slices influencing an executing statement. The results indicate that the new algorithm is substantially faster than the basic algorithm and often requires significantly less memory.
The Present and Future of Digital Rights Management
Authors: Stefan Bechtold
Venue: Proceedings of the Second International Conference on Automated Production of Cross Media Content for Multi-Channel Distribution (2006)

Over the last few years, Digital Rights Management (DRM) systems have become increasingly successful in various areas of digital content production and distribution. While DRM-related technology research has achieved a certain degree of maturity since the 1990's, the legal framework surrounding DRM systems remains in flux and is fiercely debated. This keynote speech first provides an overview of the various ways by which digital content is protected in a DRM system. The intertwining protection by technology, contracts, technology licenses and anti-circumvention regulations may lead to a new "property right" making copyright protection obsolete. However, there is a danger of over-protection: questions of fair use and other limitations to traditional copyright law have to be addressed. If competition is not able to solve this tension between the interests of content providers and the interests of users or the society at large -- which seems doubtful at least -- it is the law that has to provide a solution. The speech presents the different approaches legislatures in Europe and in the United States have adopted. Second, the speech discusses recent developments at the intersection of DRM and the law, in particular the discussions about DRM interoperability, patents on DRM technology, DRM standards, and the relationship between DRM and levy systems as well as between DRM and trusted computing. Third, the speech analyzes recent scholarship that attempts to solve legal and policy questions surrounding DRM on a technological level. The speech questions whether the tension between technological protection and public values such as fair use, privacy, competition and an innovation commons is really irreconcilable. It argues for a more nuanced approach that explores possibilities and limitations of a value-centered technology design of DRM systems. Only if technology research focuses on such questions, the disapproval of DRM systems by many legal scholars and policy activists could possibly diminish in the long term.
POCAp: A Software Process for Context-Aware Computing
Authors: Renato F. Bulcao Neto, Taciana Novo Kudo, Maria da Graca C. Pimentel
Venue: Proceedings of the IEEE/WIC/ACM international conference on Intelligent Agent Technology (2006)

Nowadays there has been a lack of research on software engineering issues for context-aware computing. Building upon concepts of the Semantic Web, we present the POCAp software process for developing context-aware applications that make use of ontology-based context information.