ppxscal/embedding_network huggingface dataset:
Refinement of Component Model Standards and Conventions
Authors: Hazleen Aris, Siti Salwah Salim
Venue: Proceedings of the 10th international conference on Software Reuse: High Confidence Software Reuse in Large Systems (2008)

One the research areas in component-oriented software development is component model development. Various component models have been defined and specified, but whether or not they meet the purpose of a component model is still a subject of discussion. This paper presents our effort in refining the standards and conventions of a component model in order to produce components that meet their purpose. Application of the refined standards and conventions to a selection of component models is also presented.
TUT Acoustic Source Tracking System 2007
Authors: Teemu Korhonen, Pasi Pertilä
Venue: Multimodal Technologies for Perception of Humans: International Evaluation Workshops CLEAR 2007 and RT 2007, Baltimore, MD, USA, May 8-11, 2007, Revised Selected Papers (2008)

This paper is a documentation of the acoustic person tracking system developed by TUT. The system performance was evaluated in the CLEAR 2007 evaluation. The proposed system is designed to track a speaker position in a meeting room domain using only audio data. Audio data provided for the evaluation consists of recordings from multiple microphone arrays. The meeting rooms are equipped with three to seven arrays.Speaker localization is performed by mapping pairwise cross-correlations of microphone signals into a three dimensional likelihood field. The resulting likelihood is used as source evidence for a particle filtering algorithm. A point estimate for the speaker position for each time frame is derived from the resulting sequential process. Results indicate an 85% success rate of localization with 15 cm average precision.
Automatic Delineation of Sulci and Improved Partial Volume Classification for Accurate 3D Voxel-Based Cortical Thickness Estimation from MR
Authors: Oscar Acosta, Pierrick Bourgeat, Jurgen Fripp, Erik Bonner, Sébastien Ourselin, Olivier Salvado
Venue: Proceedings of the 11th international conference on Medical Image Computing and Computer-Assisted Intervention - Part I (2008)

Accurate cortical thickness estimation in-vivo is important for the study of many neurodegenerative diseases. When using magnetic resonance images (MRI), accuracy may be hampered by artifacts such as partial volume (PV) as the cortex spans only a few voxels. In zones of opposed sulcal banks (tight sulci) the measurement can be even more difficult. The aim of this work is to propose a voxel-based cortical thickness estimation method from MR by integrating a mechanism for correcting sulci delineation after an improved partial volume classification. First, an efficient and accurate framework was developed to enhance partial volume classification with structural information. Then, the correction of sulci delineation is performed after a homotopic thinning of a cost function image. Integrated to our voxel-based cortical thickness estimation pipeline, the overall method showed a better estimate of thickness and a high reproducibility on real data (R 2 > 0.9). A quantitative analysis on clinical data from an Alzheimer's disease study showed significant differences between normal controls and Alzheimer's disease patients.
Plenary lecture I: inverse acoustic and electromagnetic obstacle scattering: theory and numerics
Authors: Jun Zou
Venue: Proceedings of the 8th WSEAS International Conference on Multimedia systems and signal processing (2008)

In this talk we shall present some breakthroughs that have been achieved in the past few years on inverse acoustic and electromagnetic obstacle scattering problems. Both theory and numerical simulations will be discussed. This is a joint work with Dr. Hongyu Liu (Washington University, Seattle) and supported by Hong Kong RGC grants (Project 404105 and Project 404606).
On completeness of feature spaces in blind steganalysis
Authors: Jan Kodovský, Jessica Fridrich
Venue: Proceedings of the 10th ACM workshop on Multimedia and security (2008)

Blind steganalyzers can be used for many diverse applications in steganography that go well beyond a mere detection of stego content. A blind steganalyzer can also be used for constructing targeted attacks or as an oracle for designing steganographic methods. The feature space itself provides a low-dimensional model of covers useful for benchmarking. These applications require the feature space to be complete in the sense that the features fully characterize the space of covers. Incomplete feature sets may skew benchmarking scores and lead to poor steganalysis. As a simple test of completeness, we propose a general approach for constructing steganographic methods that approximately preserve the whole feature vector and thus become practically undetectable by any steganalyzer that uses the same feature set. We demonstrate the plausibility of this approach, which we call the Feature Correction Method (FCM) by constructing the FCM for a 274-dimensional feature set from a state-of-the-art blind steganalyzer for JPEG images.
A Direct Measure for the Efficacy of Bayesian Network Structures Learned from Data
Authors: Gary F. Holness
Venue: Proceedings of the 5th international conference on Machine Learning and Data Mining in Pattern Recognition (2007)

Current metrics for evaluating the performance of Bayesian network structure learning includes order statistics of the data likelihood of learned structures, the average data likelihood, and average convergence time. In this work, we define a new metric that directly measures a structure learning algorithm's ability to correctly model causal associations among variables in a data set. By treating membership in a Markov Blanket as a retrieval problem, we use ROC analysis to compute a structure learning algorithm's efficacy in capturing causal associations at varying strengths. Because our metric moves beyond error rate and data-likelihood with a measurement of stability, this is a better characterization of structure learning performance. Because the structure learning problem is NP-hard, practical algorithms are either heuristic or approximate. For this reason, an understanding of a structure learning algorithm's stability and boundary value conditions is necessary. We contribute to state of the art in the data-mining community with a new tool for understanding the behavior of structure learning techniques.
Ant algorithms and simulated annealing for multicriteria dynamic programming
Authors: Sebastian Sitarz
Venue: Computers and Operations Research (2009)

The paper presents a comparison of ant algorithms and simulated annealing as well as their applications in multicriteria discrete dynamic programming. The considered dynamic process consists of finite states and decision variables. In order to describe the effectiveness of multicriteria algorithms, four measures of the quality of the nondominated set approximations are used.
Performance Evaluation of Multiple Approximate String Matching Algorithms Implemented with MPI Paradigm in an Experimental Cluster Environment
Authors: Panagiotis D. Michailidis, Konstantinos G. Margaritis
Venue: Proceedings of the 2008 Panhellenic Conference on Informatics (2008)

This paper describes and analyzes two high performance multiple string searching algorithms that we have optimized for cluster of heterogeneous workstations. The proposed parallel algorithms are based on dynamic master - worker programming paradigm. Experimental results show that these parallel algorithms are efficient: their search time is cut down significantly, whereas their communication cost stay at a low level.
Random sampling from a search engine's index
Authors: Ziv Bar-Yossef, Maxim Gurevich
Venue: Journal of the ACM (JACM) (2008)

We revisit a problem introduced by Bharat and Broder almost a decade ago: How to sample random pages from the corpus of documents indexed by a search engine, using only the search engine's public interface&quest; Such a primitive is particularly useful in creating objective benchmarks for search engines. The technique of Bharat and Broder suffers from a well-recorded bias: it favors long documents. In this article we introduce two novel sampling algorithms: a lexicon-based algorithm and a random walk algorithm. Our algorithms produce biased samples, but each sample is accompanied by a weight, which represents its bias. The samples, in conjunction with the weights, are then used to simulate near-uniform samples. To this end, we resort to four well-known Monte Carlo simulation methods: rejection sampling, importance sampling, the Metropolis--Hastings algorithm, and the Maximum Degree method. The limited access to search engines force our algorithms to use bias weights that are only &ldquo;approximate&rdquo;. We characterize analytically the effect of approximate bias weights on Monte Carlo methods and conclude that our algorithms are guaranteed to produce near-uniform samples from the search engine's corpus. Our study of approximate Monte Carlo methods could be of independent interest. Experiments on a corpus of 2.4 million documents substantiate our analytical findings and show that our algorithms do not have significant bias towards long documents. We use our algorithms to collect comparative statistics about the corpora of the Google, MSN Search, and Yahoo&excl; search engines.
Software Cost Estimation Models Using Radial Basis Function Neural Networks
Authors: Ali Idri, Azeddine Zahi, Emilia Mendes, Abdelali Zakrani
Venue: Software Process and Product Measurement: International Conference, IWSM-Mensura 2007, Palma de Mallorca, Spain, November 5-8, 2007. Revised Papers (2007)

Radial Basis Function Neural Networks (RBFN) have been recently studied due to their qualification as an universal function approximation. This paper investigates the use of RBF neural networks for software cost estimation. The focus of this study is on the design of these networks, especially their middle layer composed of receptive fields, using two clustering techniques: the C-means and the APC-III algorithms. A comparison between a RBFN using C-means and a RBFN using APC-III, in terms of estimates accuracy, is hence presented. This study uses the COCOMO'81 dataset and data on Web applications from the Tukutuku database.
3-D Shaded Computer Animation-Step by Step
Authors: Richard Chuang, Glenn Entis
Venue: IEEE Computer Graphics and Applications (1983)

A walk through the production process at this commercial CG animation house reveals an emphasis on software tools and the use of intermediate-stage graphics for design flexibility.
Fast and reliable resampling detection by spectral analysis of fixed linear predictor residue
Authors: Matthias Kirchner
Venue: Proceedings of the 10th ACM workshop on Multimedia and security (2008)

This paper revisits the state-of-the-art resampling detector, which is based on periodic artifacts in the residue of a local linear predictor. Inspired by recent findings from the literature, we take a closer look at the complex detection procedure and model the detected artifacts in the spatial and frequency domain by means of the variance of the prediction residue. We give an exact formulation on how transformation parameters influence the appearance of periodic artifacts and analytically derive the expected position of characteristic resampling peaks. We present an equivalent accelerated and simplified detector, which is orders of magnitudes faster than the conventional scheme and experimentally shown to be comparably reliable.
Efficiently Monitoring Nearest Neighbors to a Moving Object
Authors: Cheqing Jin, Weibin Guo
Venue: Proceedings of the 3rd international conference on Advanced Data Mining and Applications (2007)

Continuous monitoring k nearest neighbors in highly dynamic scenarios appears to be a hot topic in database research community. Most previous work focus on devising approaches with a goal to consume litter computation resource and memory resource. Only a few literatures aim at reducing communication overhead, however, still with an assumption that the query object is static. This paper constitutes an attempt on continuous monitoring k nearest neighbors to a dynamic query object with a goal to reduce communication overhead. In our RFA approach, a Range Filter is installed in each moving object to filter parts of data (e.g. location). Furthermore, RFA approach is capable of answering three kinds of queries, including precise kNN query, non-value-based approximate kNN query, and value-based approximate kNN query. Extensive experimental results show that our new approach achieves significant saving in communication overhead.
Risk maps on the Internet: Transparency and the management of risks
Authors: Albert Jacob Meijer
Venue: Information Polity (2005)

In this essay the consequences of the transparency of physical risks through the Internet are explored by posing three questions: do citizens in the Netherlands use risk maps to find out what risks there are in their neighbourhoods, does this enhance their involvement in the management of risks, and, do risk maps on the Internet and citizen involvement improve the quality of risk management? It is argued that transparency does not lead to a better informed citizenry since few citizens look at the risk maps on the Internet and, as a consequence, citizens are not more involved in the management of physical risks. In spite of the lack of citizen involvement, transparency does improve the quality of risk management. Transparency puts pressure on governments and companies and stimulates them into performing better. In addition to this optimistic conclusion, the essay also points at a dark side to openness: terrorists may use the information about physical risks to plan attacks.
Intrusion Objects with Shapes under Randomized Scheduling Algorithm in Sensor Networks
Authors: Yang Xiao, Hui Chen, Yanping Zhang, Xiaojiang Du, Bo Sun, Kui Wu
Venue: Proceedings of the 2008 The 28th International Conference on Distributed Computing Systems Workshops (2008)

Wireless sensor networks have many applications. In this paper, we are particularly interested in a sensor network which is used for monitoring a field to detect intrusion objects such as enemy tanks, enemy cars, etc. Since sensor nodes have limited energy supply, sensor networks may be configured to put some sensor nodes in sleep mode to save energy. This is a special case of a randomized scheduling algorithm. In this paper, we study the performance of the randomized scheduling algorithm via both analysis and simulation in terms of intrusion coverage intensity when an intrusion object occupies an area. We study the impact of the size of intrusion object on the sensor network’s configuration.
Multilayer Perceptrons for Bio-inspired Friction Estimation
Authors: Rosana Matuk Herrera
Venue: Proceedings of the 9th international conference on Artificial Intelligence and Soft Computing (2006)

Few years old children lift and manipulate unfamiliar objects more dexterously than today's robots. Therefore, it has arisen an interest at the artificial intelligence community to look for inspiration on neurophysiological studies to design better models for the robots. The estimation of the friction coefficient of the object's material is a crucial information in a human dexterous manipulation. Humans estimate the friction coefficient based on the responses of their tactile mechanoreceptors. In this paper, finite element analysis was used to model a finger and an object. Simulated human afferent responses were then obtained for different friction coefficients. Multiple multilayer perceptrons that received as input simulated human afferent responses, and gave as output an estimation of the friction coefficient, were trained and tested. A performance analysis was carried out to verify the influence of the following factors: number of hidden neurons, compression ratio of the input pattern, partitions of the input pattern. 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
Ordered Data Set Vectorization for Linear Regression on Data Privacy
Authors: Pau Medrano-Gracia, Jordi Pont-Tuset, Jordi Nin, Victor Muntés-Mulero
Venue: Proceedings of the 4th international conference on Modeling Decisions for Artificial Intelligence (2007)

Many situations demand from publishing data without revealing the confidential information in it. Among several data protection methods proposed in the literature, those based on linear regression are widely used for numerical data. The main objective of these methods is to minimize both the disclosure risk (DR) and the information lost (IL). However, most of these techniques try to protect the non-confidential attributes based on the values of the confidential attributes in the data set. In this situation, when these two sets of attributes are strongly correlated, the possibility of an intruder to reveal confidential data increases, making these methods unsuitable for many typical scenarios. In this paper we propose a new type of methods called LiROP¿ k methods that, based on linear regression, avoid the problems derived from the correlation between attributes in the data set. We propose the vectorization, sorting and partitioning of all values in the attributes to be protected in the data set, breaking the semantics of these attributes inside the record. We present two different protection methods: a synthetic protection method called LiROP s -k and a perturbative method, called LiROP p -k. We show that, when the attributes in the data set are highly correlated, our methods present lower DR than other protection methods based on linear regression.
Partial Domain Comprehension in Software Evolution and Maintenance
Authors: Maksym Petrenko, Václav Rajlich, Radu Vanciu
Venue: Proceedings of the 2008 The 16th IEEE International Conference on Program Comprehension (2008)

Partial comprehension is a necessity in the evolution and maintenance of very large software systems. The programmers form not only partial comprehension of the code, but also partial comprehension of the application domain. To describe the comprehension process, we introduce ontology fragments and investigate how programmers form, use and extend them before and during concept location; concept location is a prerequisite of code changes. We conducted case studies of concept location in two large systems, Eclipse and Mozilla, that both have more than 50,000 methods. Using grep search and ontology fragments, the programmers were able to locate the concepts after inspecting on average less than 10 methods and operating with ontology fragments of around 14 concepts, a very small fraction of the total.
Analysis of undamped oscillations generated by marginally stable fractional order systems
Authors: Mohammad Saleh Tavazoei, Mohammad Haeri, Narges Nazari
Venue: Signal Processing (2008)

In this paper, undamped oscillations generated by fractional order systems are studied. At first, the trajectories of marginally stable fractional order systems with commensurate order are investigated and the differences with the integer order case are highlighted. Then, amplitude and frequency of oscillations in the steady state are analytically determined for these systems. It is shown that for a linear time invariant commensurate fractional order system, the maximum number of frequencies exists in the Fourier spectrum of the oscillations is half of its inner dimension, which is the same property as in the linear time invariant integer order systems. However, we show that this property is not necessarily exists for the incommensurate fractional order systems. Finally, the paper is closed by posing an open problem in this filed.
Falcon-AO: A practical ontology matching system
Authors: Wei Hu, Yuzhong Qu
Venue: Web Semantics: Science, Services and Agents on the World Wide Web (2008)

In this paper, we introduce a general overview of Falcon-AO: a practical ontology matching system with acceptable to good performance and a number of remarkable features. Furthermore, Falcon-AO is one of the best systems in all kinds of tests in the latest three years' OAEI campaigns. Falcon-AO is written in Java, and is open source.
Cupping $\Delta_2^0$ Enumeration Degrees to 0e'
Authors: Mariya Ivanova Soskova, Guohua Wu
Venue: Proceedings of the 3rd conference on Computability in Europe: Computation and Logic in the Real World (2007)

In this paper we prove that every nonzero $\Delta^0_2$ e-degree is cuppable to 0 e' by a 1-generic $\Delta^0_2$ e-degree (so low and nontotal) and that every nonzero &omega;-c.e. e-degree is cuppable to 0 e' by an incomplete 3-c.e. e-degree.
Electroencephalogram (EEG) and Functional Electrical Stimulation (FES) System for Rehabilitation of Stroke Patients
Authors: Mitsuru Takahashi, Manabu Gouko, Koji Ito
Venue: Proceedings of the 2008 21st IEEE International Symposium on Computer-Based Medical Systems (2008)

Stroke is the leading cause of adult disability, and training in voluntary movement has been shown to be effective in rebuilding motor skills. We propose an EEG-FES system that can assist in the reconstruction of a closed-loop between motor commands and sensory feedbacks in stroke patients. The system uses event-related desynchronization (ERD) to reflect motor intentions. We did two pilot studies. One focused on extracting clear ERD from healthy subjects who must generally be trained for a few month to extract clear ERD. We also tested the effect of online visual feedback training. The results indicated that for some subjects, but not others, ERD could be extracted in a few days. The other study focused on whether FES (sensory feedback) affects ERD. The results indicated that there was no FES effect (leg stimulation) in leg motor area (Cz) ERD.
A Network of Interneurons Coupled by Electrical Synapses Behaves as a Coincidence Detector
Authors: Santi Chillemi, Michele Barbi, Angelo Garbo
Venue: Proceedings of the 2nd international work-conference on The Interplay Between Natural and Artificial Computation, Part I: Bio-inspired Modeling of Cognitive Tasks (2007)

Recent experiments show that inhibitory interneurons are coupled by electrical synapses. In this paper the information transmission properties of a network of three interneurons, coupled by electrical synapses alone, are studied by means of numerical simulations. It is shown that the network is capable to transfer the information contained in its presynapstic inputs when they are near synchronous: i.e. the network behaves as a coincidence detector. Thus, it is hypothesized that this property hold in general for networks of larger size. Lastly it is shown that these findings agree with recent experimental data.
Decision Procedure for Temporal Logic of Belief and Actions
Authors: Regimantas Pliuškevičius, Aida Pliuškevičienė
Venue: Informatica (2004)

A temporal logic of belief and actions (TLBA) is considered. The TLBA allows us to express informational and dynamic properties of computational agents. The considered fragment of TLBA allows one: (1) to present a deduction-based structured decision procedure; (2) to separate a decision procedure for so-called induction-free formulas and (3) to use only logical axioms for such formulas. The main new technical tool of the presented decision procedure is separation rules which incorporate traditional rules for the temporal operator &ldquo;next&rdquo;, belief modalities and action constants.