ppxscal/embedding_network huggingface dataset:
Segment Based Diffusion - A Post-Processing Step (Not Only) for Background Subtraction
Authors: Michael Unger, Mark Asbach
Venue: Proceedings of the 2008 Ninth International Workshop on Image Analysis for Multimedia Interactive Services (2008)

A classical approach to video object segmentation is background subtraction. Background subtraction starts by estimating a model of the background image of a scene and then calculating the likeliness that a given pixel of the current camera image belongs to the background model. Typically this is done by subtracting the background image from a given frame, where the difference image is usually thresholded and post-processed to find object boundaries. In this paper we present a method for enhanced post-processing that exploits color and texture information of the original video frame. This way we are able to extract pixel-exact object boundaries. Based on direct color segmentation of the video frame, an iterative method analog to biological diffusion and physical heat transfer processes, spreads information from the difference image over segment boundaries. For this purpose, diffusion resistances are defined between adjacent segments, based on color and texture similarities and common contour length. An iterative process calculates and transfers the flux of 'difference energy' between segments of the difference image. The resulting image allows for easy segmentation by thresholding. Experimental results show the validity of our approach.
Assisting in Reuse of Adaptive Hypermedia Creator's Models
Authors: Nadjet Zemirline, Yolaine Bourda, Chantal Reynaud, Fabrice Popineau
Venue: Proceedings of the 5th international conference on Adaptive Hypermedia and Adaptive Web-Based Systems (2008)

The design of Adaptive Hypermedia is a difficult task which can be made easier if generic systems and AH creators' models are reused. We address this design problem in the setting of the GLAM platform only made up of generic components. We present a rule-based approach helping an AH creator in reusing its user and domain models to create a specific adaptive hypermedia. This semi-automatic approach takes the creator's models as specialisations of GLAM generic models and requires the creator to express a minimum set of mappings between his models and the generic ones. The process results in a merged model consisting of the generic and the corresponding specific model. This merged model can be used by the adaptation model.
A Distributed Ontological Approach as a Basis for Software in the Context of Academic Programs
Authors: Richard Hackelbusch, H. -Jürgen Appelrath
Venue: Proceedings of the 3rd European conference on Technology Enhanced Learning: Times of Convergence: Technologies Across Learning Contexts (2008)

The implementation of a computer understandable representation of the semantics of academic programs is complex. That's why academic institutions struggle in implementing pervasive information systems that offer services to help all actors in this context. These services are demanded by, e. g., students who want to plan their curricula correctly, or who want to know which courses can be used for a different academic program or at a different academic institution. In this paper, we introduce a distributed ontological approach to represent the semantics of academic programs and their examination regulations, the universities' supply, and individual results. It allows academic institutions to implement applications that offer the demanded services and that use these ontologies as a common basis.
Supporting Law Enforcement in Digital Communities through Natural Language Analysis
Authors: Danny Hughes, Paul Rayson, James Walkerdine, Kevin Lee, Phil Greenwood, Awais Rashid, Corinne May-Chahal, Margaret Brennan
Venue: Proceedings of the 2nd international workshop on Computational Forensics (2008)

Recent years have seen an explosion in the number and scale of digital communities (e.g. peer-to-peer file sharing systems, chat applications and social networking sites). Unfortunately, digital communities are host to significant criminal activity including copyright infringement, identity theft and child sexual abuse. Combating this growing level of crime is problematic due to the ever increasing scale of today's digital communities. This paper presents an approach to provide automated support for the detection of child sexual abuse related activities in digital communities. Specifically, we analyze the characteristics of child sexual abuse media distribution in P2P file sharing networks and carry out an exploratory study to show that corpus-based natural language analysis may be used to automate the detection of this activity. We then give an overview of how this approach can be extended to police chat and social networking communities.
Intelligent social network analysis using granular computing
Authors: Ronald R. Yager
Venue: International Journal of Intelligent Systems (2008)

An introduction to some basic ideas of graph (relational network) theory is first provided. We then discuss some concepts from granular computing in particular the fuzzy set paradigm of computing with words. The natural connection between graph theory and granular computing, particularly fuzzy set theory, is pointed out. This connection is grounded in the fact that these are both set-based technologies. Our objective here is to take a step toward the development of intelligent social network analysis using granular computing. In particular one can start by expressing in a human-focused manner concepts associated with social networks then formalize these concepts using fuzzy sets and then evaluate these concepts with respect to social networks that have been represented using set-based relational network theory. We capture this approach in what we call the paradigm for intelligent social network analysis, PISNA. Using this paradigm, we provide definitions of a number of concepts related to social networks. &copy; 2008 Wiley Periodicals, Inc.
Standardization Model and Implementation of Event Type in Real Time Cyber Threats
Authors: Dong Hwi Lee, Kyong-Ho Choi, Jeom-Goo Kim, Kuinam J. Kim
Venue: Proceedings of the 2008 International Conference on Convergence and Hybrid Information Technology (2008)

The method which research a standardization from real time cyber threat is finding the suspicious indication above the attack against cyber space include internet worm, virus and hacking using analysis the event of each security system through correlation with the critical point, and draft a general standardization plan through statistical analysis of this evaluation result. It means that becomes the basis which constructs the effective cyber attack response system. Especially at the time of security accident occurrence, It overcomes the problem of existing security system through a definition of the event of security system and traffic volume and a concretize of database input method, and propose the standardization plan which is the cornerstone real time response and early warning system. A general standardization plan of this paper summarizes that put out of threat index, threat rating through adding this index and the package of early warning process, output a basis of cyber threat index calculation.
Querying Multigranular Spatio-temporal Objects
Authors: Elena Camossi, Michela Bertolotto, Elisa Bertino
Venue: Proceedings of the 19th international conference on Database and Expert Systems Applications (2008)

The integrated management of both spatial and temporal components of information is crucial in order to extract significant knowledge from datasets concerning phenomena of interest to a large variety of applications. Moreover, multigranularity, i.e., the capability of representing information at different levels of detail, enhances the data modelling flexibility and improves the analysis of information, enabling to zoom-in and zoom-out spatio-temporal datasets. Relying on an existing multigranular spatio-temporal extension of the ODMG data model, in this paper we describe the design of a multigranular spatio-temporal query language. We extend OQL value comparison and object navigation in order to access spatio-temporal objects with attribute values defined at different levels of detail.
Entertainment modeling through physiology in physical play
Authors: Georgios N. Yannakakis, John Hallam
Venue: International Journal of Human-Computer Studies (2008)

This paper is an extension of previous work on capturing and modeling the affective state of entertainment (''fun'') grounded on children's physiological state during physical game play. The goal is to construct, using representative statistics computed from children's physiological signals, an estimator of the degree to which games provided by the playground engage the players. Previous studies have identified the difficulties of isolating elements of physical activity attributed to reported entertainment derived (solely) from heart rate (HR) recordings. In the present article, a survey experiment on a larger scale and a physical activity control experiment for surmounting those difficulties are devised. In these experiments, children's HR, blood volume pulse (BVP) and skin conductance (SC) signals, as well as their expressed preferences of how much ''fun'' particular game variants are, are obtained using games implemented on the Playware physical interactive playground. Given effective data collection, a set of numerical features is computed from these measurements of the child's physiological state. A comprehensive statistical analysis shows that children's reported entertainment preferences correlate well with specific features of the recorded signals. Preference learning techniques combined with feature set selection methods permit the construction of user models that predict reported entertainment preferences given suitable signal features. The most accurate models are obtained through evolving artificial neural networks and are demonstrated and evaluated on a Playware game and a control task requiring physical activity. The best network is able to correctly match expressed preferences in 69.64% of cases on previously unseen data (p-value=0.0022) and indicates two dissimilar classes of children: those that prefer constantly energetic play of low mental/emotional load; and those that report as fun a dynamic play that involves high mental/emotional load independently of physical effort. The generality of the methodology, its limitations, its usability as a real-time feedback mechanism for entertainment augmentation and as a validation tool are discussed.
An absorbing Markov chain model for production systems with rework and scrapping
Authors: V. Madhusudanan Pillai, M. P. Chandrasekharan
Venue: Computers and Industrial Engineering (2008)

This work models the flow of material through the production system as an absorbing Markov chain characterising the uncertainty due to scrapping and reworking. A realistic estimate of material requirement computed by the model enables better system design, MRP, capacity requirement planning, and inventory control. The work identifies production system parameters under scrapping and reworking, and accurately estimates the quantity of raw materials required. This being a probabilistic model can handle the problem even when data on some intangible costs are not available.
Privacy on the Web: Facts, Challenges, and Solutions
Authors: Abdelmounaam Rezgui, Athman Bouguettaya, Mohamed Y. Eltoweissy
Venue: IEEE Security and Privacy (2003)

Despite important regulatory and technical efforts aimed at tackling aspects of the problem, privacy violation incidents on the Web continue to hit the headlines. The authors outline the salient issues and proposed solutions, focusing on generic Web users' Web privacy.
Communication Optimization for Medical Image Reconstruction Algorithms
Authors: Torsten Hoefler, Maraike Schellmann, Sergei Gorlatch, Andrew Lumsdaine
Venue: Proceedings of the 15th European PVM/MPI Users' Group Meeting on Recent Advances in Parallel Virtual Machine and Message Passing Interface (2008)

This paper presents experiences and results obtained in optimizing the parallel communication performance of a production-quality medical image reconstruction application. The fundamental communication operations in the application's principal algorithm are collective reductions. The overhead of these operations was reduced by transforming the algorithm to overlap its computation and communication. Several different approaches to communication progress were studied, both user-directed and asynchronous. Experimental results comparing the new approach to the previous implementation show overall application performance improvements of up to 8%, when run on 32 nodes.
Noninvasive Functional Imaging of Volumetric Cardiac Electrical Activity: A Human Study on Myocardial Infarction
Authors: Linwei Wang, Ken C. Wong, Heye Zhang, Pengcheng Shi
Venue: Proceedings of the 11th international conference on Medical Image Computing and Computer-Assisted Intervention - Part I (2008)

Identification of infarct substrates provides necessary guidance to the prevention and treatment of cardiac arrhythmias. Compared to diagnostic criteria of body surface potentials (BSP) or electrophysiological information on heart surfaces, the underlying volumetric cardiac electrical activity is of more direct clinical relevance in exhibiting patient-specific arrhythmic dynamics and arrhythmogenic substrates. We have developed a paradigm for noninvasive imaging of volumetric myocardial transmembrane potential from BSPs. In this paper, we present a human study for a patient with acute myocardial infarction. Using patient MRI and BSP data, the framework is able to reconstruct details of the complete arrhythmic electrical activity on the 3D myocardium of the patient. Exploring a subset of the results, the extent, centroid and affected segments of the infarct is correctly evaluated, with comparable performance to existent best results. This human study demonstrates the potential of the presented paradigm as a noninvasive functional imaging technique for patient-specific volumetric cardiac electrical activity in practice.
Vector-thread architecture and implementation
Authors: Krste Asanovic
Venue:  (2007)

This thesis proposes vector-thread architectures as a performance-efficient solution for all-purpose computing. The VT architectural paradigm unifies the vector and multithreaded compute models. VT provides the programmer with a control processor and a vector of virtual processors. The control processor can use vector-fetch commands to broadcast instructions to all the VPs or each VP can use thread-fetches to direct its own control flow. A seamless intermixing of the vector and threaded control mechanisms allows a VT architecture to flexibly and compactly encode application parallelism and locality. VT architectures can efficiently exploit a wide variety of loop-level parallelism, including non-vectorizable loops with cross-iteration dependencies or internal control flow. The Scale VT architecture is an instantiation of the vector-thread paradigm designed for low-power and high-performance embedded systems. Scale includes a scalar RISC control processor and a four-lane vector-thread unit that can execute 16 operations per cycle and supports up to 128 simultaneously active virtual processor threads. Scale provides unit-stride and strided-segment vector loads and stores, and it implements cache refill/access decoupling. The Scale memory system includes a four-port, non-blocking, 32-way set-associative, 32KB cache. A prototype Scale VT processor was implemented in 180nm technology using an ASIC-style design flow. The chip has 7.1 million transistors and a core area of 16.6 mm2, and it runs at 260 MHz while consuming 0.4&ndash;1.1 W. This thesis evaluates Scale using a diverse selection of embedded benchmarks, including example kernels for image processing, audio processing, text and data processing, cryptography, network processing, and wireless communication. Larger applications also include a JPEG image encoder and an IEEE 802.11a wireless transmitter. Scale achieves high performance on a range of different types of codes, generally executing 3-11 compute operations per cycle. Unlike other architectures which improve performance at the expense of increased energy consumption, Scale is generally even more energy efficient than a scalar RISC processor. (Copies available exclusively from MIT Libraries, Rm. 14-0551, Cambridge, MA 02139-4307. Ph. 617-253-5668; Fax 617-253-1690.)
Traces, Feedback, and the Geometry of Computation (Abstract)
Authors: Philip J. Scott
Venue: Proceedings of the 16th international symposium on Fundamentals of Computation Theory (2007)

The notion of feedback and information flow is a fundamental concept arising in many classical areas of computing. In the late 1980s and early 1990s, an algebraic structure dealing with cyclic operations emerged from various fields, including flowchart schemes, dataflow with feedback, iteration theories, action calculi in concurrency theory, proof theory (Linear Logic and Geometry of Interaction), and network algebra, as well as in pure mathematics. This structure, now known as a "traced monoidal category", was formally introduced in an influential paper of Joyal, Street and Verity (1996) from current work in topology and knot theory. However these authors were also keenly aware of its potential applicability. Since then, such structures --- with variations --- have been pursued in several areas of mathematics, logic and theoretical computer science, including game semantics, quantum programming languages and quantum protocols, and computational biology. We shall survey applications in logic and theoretical computer science and discuss progress towards an abstract geometry of algorithms.
Material Classification of Hyperspectral Images Using Unsupervised Fuzzy Clustering Methods
Authors: Soudeh Kasiri Bidhendi, Abbas Sarraf Shirazi, Narges Fotoohi, Mohammad Mehdi Ebadzadeh
Venue: Proceedings of the 2007 Third International IEEE Conference on Signal-Image Technologies and Internet-Based System (2007)

This paper presents a novel approach in classifying materials in Hyperspectral images. In particular, unlike other similar approaches in which every pixel in the image is mapped to one of the reference spectra, the proposed methods use the data itself to create clusters of pixels with the same material. This is done by using unsupervised fuzzy clustering methods. Here, two fuzzy clustering approaches have been addressed: Fuzzy C-Means clustering (FCM) and Fuzzy Relational Clustering (FRC). The proposed methods can also solve the problem of identifying the objects for which the radiance of light makes it barely hard to identify them as a single object e.g., a pitched roof. The proposed methods have been applied on the CASI image and the results show that they can successfully classify the materials in the image.
More Robust Hashing: Cuckoo Hashing with a Stash
Authors: Adam Kirsch, Michael Mitzenmacher, Udi Wieder
Venue: Proceedings of the 16th annual European symposium on Algorithms (2008)

Cuckoo hashing holds great potential as a high-performance hashing scheme for real applications. Up to this point, the greatest drawback of cuckoo hashing appears to be that there is a polynomially small but practically significant probability that a failure occurs during the insertion of an item, requiring an expensive rehashing of all items in the table. In this paper, we show that this failure probability can be dramatically reduced by the addition of a very small constant-sized stash. We demonstrate both analytically and through simulations that stashes of size equivalent to only three or four items yield tremendous improvements, enhancing cuckoo hashing's practical viability in both hardware and software. Our analysis naturally extends previous analyses of multiple cuckoo hashing variants, and the approach may prove useful in further related schemes.
Segmentation of Biological Cell Images for Sonification
Authors: Alistair D. N. Edwards, Geneviève Hines, Andy Hunt
Venue: Proceedings of the 2008 Congress on Image and Signal Processing, Vol. 2 - Volume 02 (2008)

Cervical cancer is one of the most preventable/treatable forms of cancer, due to the fact that precursor signs for the disease can be detected in microscopic examination of cervical cells. Currently these examinations are purely visual, but the project reported aims to process the visual images to present them in a complementary auditory form and thereby to improve diagnostic accuracy. Standard mean-shift image processing techniques have been successfully applied to extract nuclear data suitable for presentation in an auditory form.
Intermolecular interaction effects on second hyperpolarizabilities of clusters including charged species
Authors: Masayoshi Nakano, Ryohei Kishi, Nozomi Nakagawa, Suguru Ohta, Hideaki Takahashi, Shin-ichi Furukawa
Venue: Journal of Computational Methods in Sciences and Engineering (2006)

We investigate the intermolecular-interaction effects on the longitudinal second hyperpolarizabilities (&gamma;) for two types of &pi;&minus;&pi; stacking clusters: C$_{5}$H$_{7}^{&plus;}$ dimer and &pi;-conjugated main chains (C$_{n}$H$_{n&plus;2}$, 6 &les; n &les; 16) interacting in both end regions with two allyl cations (C$_{3}$H$_{5}^{&plus;})$. The &gamma; values are calculated by the finite-field approach using several ab initio molecular orbital and density functional methods. It is found that in the first model the &pi;&minus; &pi; interaction between the upper and lower &pi;-orbitals significantly reduces the magnitude of effective &gamma; per monomer, while the second model exhibits a remarkable enhancement of &gamma; values as compared to those of isolated main chains. The analysis using the hyperpolarizability density and orbital interaction elucidates that the reduction of longitudinal &gamma; value in the first model originates in the reduction of longitudinal &pi;-conjugated electron distributions due to the perpendicular &pi;&minus;&pi; orbital interactions, whereas the enhancement of longitudinal &gamma; in the second model is caused by the intermolecular charge transfer between both end perturbing molecules via the main chain. On the basis of these results, we discuss a novel guideline of controlling third-order nonlinear optical properties of clusters.
Performance Measures in Classification of Human Communications
Authors: Marina Sokolova, Guy Lapalme
Venue: Proceedings of the 20th conference of the Canadian Society for Computational Studies of Intelligence on Advances in Artificial Intelligence (2007)

This study emphasizes the importance of using appropriate measures in particular text classification settings. We focus on methods that evaluate how well a classifier performs. The effect of transformations on the confusion matrix are considered for eleven well-known and recently introduced classification measures. We analyze the measure's ability to retain its value under changes in a confusion matrix. We discuss benefits from the use of the invariant and non-invariant measures with respect to characteristics of data classes.