ppxscal/embedding_network huggingface dataset:
Rapid Answer Retrieval from Clinical Practice Guidelines at the Point of Care
Authors: Sek-Kwong Poon, Roberto A. Rocha, Guilherme De Fiol
Venue: Proceedings of the 19th IEEE Symposium on Computer-Based Medical Systems (2006)

We describe and report preliminary results of a prototype XML-based method that facilitates the retrieval and navigation of common practice guidelines by physicians at the point of care. The method can be invoked by clicking at "infobuttons" linked to problems in an electronic medical record. Each infobutton displays a list of questions that are categorized and sorted according to the classification proposed by Ely et al. The navigation is achieved through hyperlinks from each question to relevant parts of the guideline. Preliminary results indicate high physician acceptance. A prospective evaluation is now being launched, with the expectation that it will confirm this method as an efficient option for retrieving information from reference documents.
A simulation-based First-to-Default (FTD) Credit Default Swap (CDS) pricing approach under jump-diffusion
Authors: Tarja Joro, Anne R. Niu, Paul Na
Venue: Proceedings of the 36th conference on Winter simulation (2004)

In recent years, the credit derivatives market has grown explosively and credit derivatives have become popular tools for hedging credit risk of financial institutions. Among the more sophisticated credit derivatives are the ones where the contingent payoffs depend on the dependence relationship among several firms in a basket, such as First-to-Default Credit Default Swap. In this paper, we present a simulation-based First-to-Default Credit Derivative Swap pricing approach under jump-diffusion and compare it with the popular default-time approach via Copula.
Towards Ubiquitous Brushing for Information Visualization
Authors: Jonathan C. Roberts, Michael A. E. Wright
Venue: Proceedings of the conference on Information Visualization (2006)

Brushing is a collection of techniques to dynamically query and directly select elements on the visual display. Such interaction allows the user to explore the visualization, to interactively select a subset of points and see how these changes are updated in other related views. Traditionally, the artefacts that are 'brushed' are the plotted elements in the visualization (e.g. the points on a scatterplot, or the bars of a bar chart). In this paper we discuss the concept of Ubiquitous Brushing (UB), which brings together various different types of selection (whether in data space, screen space or views). Not only can users brush over elements in the display but also they can brush over various meta-information such as menus, legends or axis to affect the highlighted elements. The paper discusses the basic idea and demonstrates how subsequent UB operations can be compound together to provide useful dynamic filter operations.
Development of a new lightning detection system
Authors: Atsuo Ozaki, Yukio Hamatani, Hiroshi Aoki, Koichi Hirashima
Venue: Systems and Computers in Japan (2006)

Ground-based lightning detection systems are designed to aid aircraft in the airspace around Komatsu Airbase to avoid lightning strikes and electrical discharges. This system is provided with an information processing function that can integrally display and analyze weather conditions by making use of data acquired from multiple sensors and radar with the aim of handling weather conditions related to lightning that is peculiar to the Hokuriku region on the Japan Sea. In this research paper, the authors introduce the background, characteristics, and other aspects of this system, and describe a new ground-based lightning detection system whose construction was completed in February 2003, with the aim of improving the ground position accuracy of lightning discharges, rounding out the analysis and display processing, and improving the computer processing ability. It should be noted that it was confirmed from a number of cases that the position of lightning was mapped with good precision after this system was installed, and these cases are introduced in the present paper. &copy; 2006 Wiley Periodicals, Inc. Syst Comp Jpn, 37(11): 22&ndash;34, 2006; Published online in Wiley InterScience (). DOI 10.1002&sol;scj.20480
Lessons from LAMS for IMS Learning Design
Authors: James Roland Dalziel
Venue: Proceedings of the Sixth IEEE International Conference on Advanced Learning Technologies (2006)

LAMS (the Learning Activity Management System) is a Learning Design system with a particular focus on sequencing of collaborative learning activities. This paper reviews a number of lessons learned from the development of LAMS, and their implications for both the existing IMS Learning Design specification, and its future scope and purpose. It proposes a number of areas for further development.
Research for Web Usage Mining Model
Authors: Junjie Chen, Wei Liu
Venue: Proceedings of the International Conference on Computational Inteligence for Modelling Control and Automation and International Conference on Intelligent Agents Web Technologies and International Commerce (2006)

Web usage mining is a kind of data mining that it mines the information of server logs after users browse the Web pages. After introducing the staple technology and process of Web usage mining, the article advances an architecture of Web usage mining and presents the work principle of system. In addition, the article discusses some key technologies in system design such as session identification and data cleaning at length.
Holistic Comparison of Text Images for Content-Based Retrieval
Authors: Julinda Gllavata, Ermir Qeli, Bernd Freisleben
Venue: Proceedings of the Eighth IEEE International Symposium on Multimedia (2006)

The accurate recognition of text that appears in images/videos using analytical character recognition methods is often very difficult, despite the fact that the text might be correctly localized, segmented and bi- narized. This is mainly due to changing features of the text such as various fonts, or noise factors embed- ded in the image which are inherited from the com- plex background. In this paper, we treat the problem of comparing text images for content-based retrieval pur- poses, by presenting a holistic approach to this issue. First, the shape of text is represented by estimating the salient points in the text image. Then, alignment shape methods are used to establish the correspondence of the salient points. Finally, a measure is suggested to com- pute the dissimilarity between two text images based on the generated correspondence. Empirical evaluation of the proposed holistic comparison method has demon- strated its very good performance.
Model-typed Component Interfaces
Authors: Gernot Schmoelzer, Egon Teiniker, Christian Kreiner, Michael Thonhauser
Venue: Proceedings of the 32nd EUROMICRO Conference on Software Engineering and Advanced Applications (2006)

Component based software engineering (CBSE) allows to design and develop reusable software components that can be assembled to construct software systems via well defined interfaces. However, designing such reusable components for data intensive business logic often requires heavy data transfer between components over interfaces. Static interface definitions using basic data types or structures of such lead to large interfaces susceptible to modifications. The goal of this paper is to present model-typed interfaces based on generic interface parameters, which allows to transfer complex structured data between components. Providing such generic, model-defined types with data models specifying the parameter structure supports compatibility checks of model-typed interfaces at assembly time. The methodology is described platform independently and the coherency with our system development process is discussed. Moreover, a technology mapping to IDL and the CORBA Component Model (CCM) is illustrated.
Probabilistic Adaptive Random Testing
Authors: Kwok Ping Chan, T. Y. Chen, Dave Towey
Venue: Proceedings of the Sixth International Conference on Quality Software (2006)

Adaptive Random Testing (ART) methods are Software Testing methods which are based on Random Testing, but which use additional mechanisms to ensure more even and widespread distributions of test cases over an input domain. Restricted Random Testing (RRT) is a version of ART which uses exclusion regions and restricts test case generation to outside of these regions. RRT has been found to perform very well, but its use of strict exclusion regions (from within which test cases cannot be generated) has prompted an investigation into the possibility of modifying the RRT method such that all portions of the Input Domain remain available for test case generation throughout the duration of the algorithm. In this paper, we present a probabilistic approach, Probabilistic ART (PART), and explain two different implementations. Preliminary empirical data supporting the methods is also examined.
Building C# COM DLLs for APL
Authors: Ajay Askoolum
Venue: ACM SIGAPL APL Quote Quad (2004)

In this article, I present a visual guide to building and deploying a C# COM (Component Object Model) Interrop DLL (Dynamic Link Library) for APL using Visual C# 2005 Express Edition. This is not a tutorial on either C# or on Visual C# 2005 Express Edition, but simply an illustration of the process for building and COM DLL in C#.
Shape-from-shading with discontinuous image brightness
Authors: Fabio Camilli, Emmanuel Prados
Venue: Applied Numerical Mathematics (2006)

The Shape-from-Shading models in image analysis lead to first order Hamilton-Jacobi equations which may have several weak solutions (in the viscosity sense). Moreover, for real images, these equations are highly discontinuous in the space variable. The lack of uniqueness and the irregularity of the coefficients involve some troubles when we try to compute a solution. In order to avoid these difficulties, here we use recent results in the theory of viscosity solutions to characterize the maximal solution of these equations. Moreover we describe an approximation procedure via smooth equations with a unique viscosity solution.
An efficient parallel algorithm for finding the largest and the second largest elements from a list of elements
Authors: B. K. Sarkar, Shahid Jamal, Bhagirath Kumar
Venue: Proceedings of the 9th International Conference on Information Technology (2006)

This paper first presents two sequential algorithms following a new approach for finding the largest and the second largest elements from a list of n elements assuming n is multiple of 3. Another contribution of this paper is an EREW P-RAM(Exclusive Read and Exclusive Write -Parallel Random Access Machine) version of this sequential approach, runs in time O(logn) using only n/3 processors. This problem is useful to rank the winner and the runner in any event from many individuals
Numerical Solution of the Stationary State Schrödinger Equation Using Transparent Boundary Conditions
Authors: Curt A. Moyer
Venue: Computing in Science and Engineering (2006)

To solve the discrete version of the stationary state Schrödinger equation to Numerov accuracy, the author uses boundary conditions at the limits of the computational domain that mimic an interval of infinite extent. He also describes methods for finding particle energies, scattering coefficients, and partial-wave phase shifts.
A Generalized EM Approach for 3D Model Based Face Recognition under Occlusions
Authors: Michael De Smet, Rik Fransens, Luc Van Gool
Venue: Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 2 (2006)

This paper describes an algorithm for pose and illumination invariant face recognition from a single image under occlusions. The method iteratively estimates the parameters of a 3D morphable face model to approximate the appearance of a face in an image. Simultaneously, a visibility map is computed which segments the image into visible and occluded regions. The visibility map is incorporated into a probabilistic image formation model as a set of spatially correlated random variables. This leads to a Generalized Expectation-Maximization algorithm in which the estimation of the morphable model related parameters is interleaved with visibility computations. The validity of the algorithm is verified by a face recognition experiment using images from the publicly available AR Face Database.
Motor Area Activity During Mental Rotation Studied by Time-Resolved Single-Trial fMRI
Authors: Wolfgang Richter, Ray Somorjai, Randy Summers, Mark Jarmasz, Ravi S. Menon, Joseph S. Gati, Apostolos P. Georgopoulos, Carola Tegeler, Kamil Ugurbil, Seong-Gi Kim
Venue: Journal of Cognitive Neuroscience (2000)

The functional equivalence of overt movements and dynamic imagery is of fundamental importance in neuroscience. Here, we investigated the participation of the neocortical motor areas in a classic task of dynamic imagery, Shepard and Metzler&rsquo;s mental rotation task, by time-resolved single-trial functional Magnetic Resonance Imaging (fMRI). The subjects performed the mental-rotation task 16 times, each time with different object pairs. Functional images were acquired for each pair separately, and the onset times and widths of the activation peaks in each area of interest were compared to the response times. We found a bilateral involvement of the superior parietal lobule, lateral premotor area, and supplementary motor area in all subjects; we found, furthermore, that those areas likely participate in the very act of mental rotation. We also found an activation in the left primary motor cortex, which seemed to be associated with the right-hand button press at the end of the task period.
A method of digital watermarking by using the frequency masking effect
Authors: Shinya Ito, Hiroshi Tsubokawa
Venue: Systems and Computers in Japan (2006)

As various forms of digital content continue to be published, there has in recent years been progress in research on digital watermarks whose purpose is to protect copyrights. Digital watermarks that are resistant to various forms of destruction and attack by criminals have been proposed. In a conventional digital watermark, visual degradation of the image is reduced by performing embedding after searching for edge components when performing embedding in the low-frequency component. However, in these conventional methods, embedded information is lost under JPEG compression at a compression ratio that is ordinarily used (10 to 20&percnt; with respect to the original image). Thus, in this paper the authors propose a method to perform embedding in the lowest frequency region, which has been problematic in conventional digital watermarking, by using the masking effect, which has visual features different from those above. As a result, visual degradation of the image is reduced, and a digital watermark that is robust against even high compression ratios can be achieved. The authors verified how much loss of embedded information occurred after compression using the JPEG format when embedding was performed on sample images using their scheme. They show that even at high compression ratios, the loss of embedded information can be reduced. Moreover, they demonstrate that their method is effective even for other forms of image processing. &copy; 2006 Wiley Periodicals, Inc. Syst Comp Jpn, 37(11): 79&ndash;87, 2006; Published online in Wiley InterScience (). DOI 10.1002&sol;scj.10490
Expectation Consistent Approximate Inference
Authors: Manfred Opper, Ole Winther
Venue: The Journal of Machine Learning Research (2005)

We propose a novel framework for approximations to intractable probabilistic models which is based on a free energy formulation. The approximation can be understood as replacing an average over the original intractable distribution with a tractable one. It requires two tractable probability distributions which are made consistent on a set of moments and encode different features of the original intractable distribution. In this way we are able to use Gaussian approximations for models with discrete or bounded variables which allow us to include non-trivial correlations. These are neglected in many other methods. We test the framework on toy benchmark problems for binary variables on fully connected graphs and 2D grids and compare with other methods, such as loopy belief propagation. Good performance is already achieved by using single nodes as tractable substructures. Significant improvements are obtained when a spanning tree is used instead.
Reversible index-domain information hiding scheme based on side-match vector quantization
Authors: Chin-Chen Chang, Tzu-Chuen Lu
Venue: Journal of Systems and Software (2006)

Information hiding has become an interesting topic that receives more and more attention. Recently, many hiding techniques were proposed to directly conceal secret information on an image. However, for convenience and efficiency, images are usually stored and compressed by lossy or lossless compression mechanisms in indices format. The hidden information might be erased or cancelled when the stego image is lossy compressed. Hence, this paper proposes an information hiding scheme based on side-match vector quantization (SMVQ), which conceals the secret information on the indices of the SMVQ compressed images. The proposed scheme not only can embed information in the indices of the compressed image with low image distortion, but also can recover the original indices to reconstruct the SMVQ compressed image. As the experimental results indicated, the proposed scheme indeed outperforms other schemes in terms of image quality, hiding capacity, and compression rate.
Condition Matrix Based Genetic Programming for Rule Learning
Authors: Jin Feng Wang, Kin Hong Lee, Kwong Sak Leung
Venue: Proceedings of the 18th IEEE International Conference on Tools with Artificial Intelligence (2006)

Most genetic programming paradigms are population-based and require huge amount of memory. In this paper, we review the Instruction Matrix based Genetic Programming which maintains all program components in a instruction matrix (IM) instead of manipulating a population of programs. A genetic program is extracted from the matrix just before it is being evaluated. After each evaluation, the fitness of the genetic program is propagated to its corresponding cells in the matrix. Then, we extend the instruction matrix to the condition matrix (CM) for generating rule base from datasets. CM keeps some of characteristics of IM and incorporates the information about rule learning. In the evolving process, we adopt an elitist idea to keep the better rules alive to the end. We consider that genetic selection maybe lead to the huge size of rule set, so the reduct theory borrowed from Rough Sets is used to cut the volume of rules and keep the same fitness as the original rule set. In experiments, we compare the performance of Condition Matrix for Rule Learning (CMRL) with other traditional algorithms. Results are presented in detail and the competitive advantage and drawbacks of CMRL are discussed.
Wada Testing Reveals Frontal Lateralization for the Memorization of Words and Faces
Authors: W. M. Kelley, J. G. Ojemann, R. D. Wetzel, C. P. Derdeyn, C. J. Moran, D. T. Cross, J. L. Dowling, J. W. Miller, S. E. Petersen
Venue: Journal of Cognitive Neuroscience (2002)

Neuroimaging studies have suggested that specific regions of the frontal and medial temporal cortex are engaged during memory formation. Further, there is specialization across these regions such that verbal materials appear to preferentially engage the left regions while nonverbal materials primarily engage the right regions. An open question, however, has been to what extent frontal regions contribute to successful memory formation. The present study investigates this question using a reversible lesion technique known as the Wada test. Patients memorized words and unfamiliar faces while portions of their left and right hemispheres were temporarily anesthetized with sodium amytal. Subsequent memory tests revealed that faces were remembered better than words following left-hemisphere anesthesia, whereas words were remembered better than faces following right-hemisphere anesthesia. Importantly, inspection of the circulation affected by the amytal further suggests that these memory impairments did not result from direct anesthetization of the medial temporal regions. Taken in the context of the imaging findings, these results suggest that frontal regions may also contribute to memory formation in normal performance.
Automatic Single-Organ Segmentation in Computed Tomography Images
Authors: Ruchaneewan Susomboon, Daniela Raicu, Jacob Furst, David Channin
Venue: Proceedings of the Sixth International Conference on Data Mining (2006)

In this paper, we propose a hybrid approach for automatic single-organ segmentation in Computed Tomography (CT) data. The approach consists of three stages: first, a probability image of the organ of interest is obtained by applying a binary classification model obtained using pixel-based texture features; second, an adaptive split-and-merge segmentation algorithm is applied on the organ probability image to remove the noise introduced by the misclassified pixels; and third, the segmented organ's boundaries from the previous stage are iteratively refined using a region growing algorithm. While we applied our approach for liver segmentation in 2-D CT images, a challenging and important task in many medical applications, the proposed approach can be applied for the segmentation of any other organ in CT images. Moreover, the proposed approach can be extended to perform automatic multiple organ segmentation and to build context-sensitive reporting tools for computer-aided diagnosis applications.
Trace Analysis in Instrumented Collaborative Learning Environments
Authors: Christophe Courtin, Stephane Talbot
Venue: Proceedings of the Sixth IEEE International Conference on Advanced Learning Technologies (2006)

Observation activity, on instrumented collective learning situations, enables participants to appropriate themselves corresponding systems in their own practice. In this paper, we focus on the analysis stage of the observation process, but we underline the correlations between the different stages. We present an analysis model and a draft of trace description language. Finally, we explain in an example how an observer (e.g. teacher) can exploit collected information to understand particular episodes.
The probe gap model can underestimate the available bandwidth of multihop paths
Authors: Li Lao, Constantine Dovrolis, M. Y. Sanadidi
Venue: ACM SIGCOMM Computer Communication Review (2006)

The Probe Gap Model (PGM) was proposed as a lightweight and fast available bandwidth estimation method. Measurement tools such as Delphi and Spruce are based on PGM. Compared to estimation methods that require multiple iterations with different probing rates, PGM uses a single probing rate and it infers the available bandwidth from a direct relation between the input and output rates of measurement packet pairs. An important assumption behind the PGM model is that the measured path has a single bottleneck link that determines the available bandwidth of the end-to-end path. In this letter, we show that, even though PGM is accurate in the case of a single queue, it cannot estimate the available bandwidth of multi-hop paths, even if there is a single bottleneck in the path. Whether PGM is accurate or not depends on the routing of cross traffic relative to the measurement traffic. PGM is accurate when the cross traffic follows the same path with the measurement traffic. In the general case, however, PGM can significantly underestimate the available bandwidth of an end-to-end path.