ppxscal/embedding_network huggingface dataset:
A loss default simulation model of the federal bank deposit insurance funds
Authors: Rosalind L. Bennett, Daniel A. Nuxoll, Robert A. Jarrow, Michael C. Fu, Huiju Zhang
Venue: Proceedings of the 37th conference on Winter simulation (2005)

This paper discusses a simulation model that is used in a martingale valuation approach to measure and value the risk of the FDIC deposit insurance funds. The FDIC insurance funds capitalize a portfolio of insurance policies, each issued to depositors of an individual commercial bank. To evaluate this portfolio, our methodology evaluates the insurance policies for depositors at each individual bank and aggregates to obtain the risk of the entire portfolio. To adequately model the risks associated with credit, interest rate, deposit growth, and loss rate, a multi-dimensional system is formulated. The risk measurement and valuation results are based on Monte Carlo simulation of the system risks.
Improved Vehicle Classification in Long Traffic Video by Cooperating Tracker and Classifier Modules
Authors: Brendan Morris, Mohan Trivedi
Venue: Proceedings of the IEEE International Conference on Video and Signal Based Surveillance (2006)

Visual surveillance systems intend to extract meaning from a scene. Two initial steps for this extraction are the detection and tracking of objects followed by the classification of these objects. Often times these are viewed as separate problems where each is solved by an individual module. These tasks should not be done individually because they can help one another. This paper demonstrates the benefit gained both in tracking and classification through the communication between these individual modules. This is shown on a real-time system monitoring highway traffic. The system retreives online video at 10 frames/sec and conducts tracking and classification simultaneously. Results show an improvement from 74% to 88% accuracy in classification results.
A New Image Steganography for Internet Communications Based on Chaotic Sequences
Authors: Niansheng Liu, Donghui Guo, Gerard Parr
Venue: Proceedings of the 2006 International Conference on Intelligent Information Hiding and Multimedia (2006)

In this paper we propose a new image steganography to meet an increasing demand for effective and cheap digital security scheme for the Internet. This technique is based on chaotic sequences in the discrete wavelet transform domain of covert images. Multiple sensitive images are added to a covert image as a white noise-like form. The results of theoretical analysis and computer simulation show the new hiding technique has improved properties with high security, imperceptibility and capacity for hidden information in comparison with LSB. Such properties can be exploited in the quest for secure communications and document exchange over the Internet.
Classification and powerlaws: The logarithmic transformation: Research Articles
Authors: Loet Leydesdorff, Stephen Bensman
Venue: Journal of the American Society for Information Science and Technology (2006)

Logarithmic transformation of the data has been recommended by the literature in the case of highly skewed distributions such as those commonly found in information science. The purpose of the transformation is to make the data conform to the lognormal law of error for inferential purposes. How does this transformation affect the analysis? We factor analyze and visualize the citation environment of the Journal of the American Chemical Society (JACS) before and after a logarithmic transformation. The transformation strongly reduces the variance necessary for classificatory purposes and therefore is counterproductive to the purposes of the descriptive statistics. We recommend against the logarithmic transformation when sets cannot be defined unambiguously. The intellectual organization of the sciences is reflected in the curvilinear parts of the citation distributions while negative powerlaws fit excellently to the tails of the distributions. &copy; 2006 Wiley Periodicals, Inc.
Multi-Objective Clustering Ensemble
Authors: Katti Faceli, Andre C. P. L. F. de Carvalho, Marcilio C. P. de Souto
Venue: Proceedings of the Sixth International Conference on Hybrid Intelligent Systems (2006)

In this paper, we present an algorithm for cluster analysis that provides a robust way to deal with datasets presenting different types of clusters and allows finding more than one structure in a dataset. Our approach is based on ideas from cluster ensembles and multi-objective clustering. We apply a Pareto-based multi-objective genetic algorithm with a special crossover operator. Such an operator combines a number of partitions obtained according to different clustering criteria. As a result, our approach generates a concise and stable set of partitions representing different trade-offs between two validation measures related to different clustering criteria.
Full disjunctions: polynomial-delay iterators in action
Authors: Sara Cohen, Itzhak Fadida, Yaron Kanza, Benny Kimelfeld, Yehoshua Sagiv
Venue: Proceedings of the 32nd international conference on Very large data bases (2006)

Full disjunctions are an associative extension of the outer-join operator to an arbitrary number of relations. Their main advantage is the ability to maximally combine data from different relations while preserving all the original information. An algorithm for efficiently computing full disjunctions is presented. This algorithm is superior to previous ones in three ways. First, it is the first algorithm that computes a full disjunction with a polynomial delay between tuples. Hence, it can be implemented as an iterator that produces a stream of tuples, which is important in many cases (e.g., pipelined query processing and Web applications). Second, the total runtime is linear in the size of the output. Third, the algorithm employs a novel optimization that divides the relation schemes into biconnected components, uses a separate iterator for each component and applies outerjoins whenever possible. Combining efficiently full disjunctions with standard SQL operators is discussed. Experiments show the superiority of our algorithm over the state of the art.
Managing Distributed, Shared L2 Caches through OS-Level Page Allocation
Authors: Sangyeun Cho, Lei Jin
Venue: Proceedings of the 39th Annual IEEE/ACM International Symposium on Microarchitecture (2006)

This paper presents and studies a distributed L2 cache management approach through OS-level page allocation for future many-core processors. L2 cache management is a crucial multicore processor design aspect to overcome non-uniform cache access latency for good program performance and to reduce on-chip network traffic and related power consumption. Unlike previously studied hardwarebased private and shared cache designs implementing a "fixed" caching policy, the proposed OS-microarchitecture approach is flexible; it can easily implement a wide spectrum of L2 caching policies without complex hardware support. Furthermore, our approach can provide differentiated execution environment to running programs by dynamically controlling data placement and cache sharing degrees. We discuss key design issues of the proposed approach and present preliminary experimental results showing the promise of our approach.
Integration of simulation methods in control system for EB processing
Authors: V. T. Lazurik, V. M. Lazurik, G. F. Popov, Yu. V. Rogov
Venue: Proceedings of the 2003 International Conference on Physics and Control - Volume 3 (2003)

This paper will focus mainly on the integration features of mathematical simulation of electron beam (EB) processing into the control system (CS) of the radiation-technological line (RTL) incorporating an industrial electron accelerator with a scanner of electron beam and a conveyor. The motivation for this development is the creation of the CS that allow to realize the control of the absorbed dose distribution of EB within the irradiated materials in real-time mode. Because there is no direct express measurement methods for scanning EB of the absorbed dose distribution, which is one of the most important characteristic for all radiation-technological processes.
Spatial Reflectance Recovery under Complex Illumination from Sparse Images
Authors: Li Shen, Haruo Takemura
Venue: Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 2 (2006)

A major challenge in inverse reflectometry is the acquisition of spatially varying materials. In this paper, we introduce a method to recover spatial reflectance from a sparse set of images under general illumination. Specifically, we first remove the high-frequency varying diffuse reflection term by using a low-order spherical harmonic approximation. This allows us to directly estimate the specular properties with a cluster fitting process, which simplifies the fitting processes and addresses the problem of data inadequacy for sparse images. As a result, we can reconstruct a truly spatially varying BRDF model of the surface from less than 10 images. Experimental results will be presented in order to demonstrate the effectiveness of the proposed algorithm.
Using advanced technologies to connect schools to science museums
Authors: Sofoklis Sotiriou, Stamatina Anastopoulou, Sherman Rosenfeld, Marcelo Milrad
Venue: Proceedings of the Fourth IEEE International Workshop on Wireless, Mobile and Ubiquitous Technology in Education (2006)

Field trips in science centers and museums are often isolated from the school curriculum, missing the opportunity to link fun to science learning. This research describes the efforts to enhance the students and teachers experience when visiting a science center or museum. Broadband technologies are used to support students' activities before and after the visit to the science centre and mobile and wearable technologies are used to visualize invisible phenomena while the students visit the science center.
The Role of Story Cards and the Wall in XP teams: A Distributed Cognition Perspective
Authors: Helen Sharp, Hugh Robinson, Judith Segal, Dominic Furniss
Venue: Proceedings of the conference on AGILE 2006 (2006)

Much of the knowledge used within an XP team is tacit, i.e. it is hidden and intangible. Two tangible artefacts that carry information about the team's work are the index cards which capture stories and tasks to be implemented and the wall where they are displayed (which we refer to as the 'Wall'). It is widely acknowledged that these are key elements supporting the work of the XP team, but no systematic investigation of their role has been reported to date. In this paper, we focus on the use of these artefacts within one XP team. We use distributed cognition, a framework for analysing collaborative work, to explicate the information flows in, around and within the team that are supported by the index cards and the Wall. We then interrogate the models produced using this analysis to answer 'what if' questions.
An Event-related fMRI Study of Artificial Grammar Learning in a Balanced Chunk Strength Design
Authors: Matthew D. Lieberman, Grace Y. Chang, Joan Chiao, Susan Y. Bookheimer, Barbara J. Knowlton
Venue: Journal of Cognitive Neuroscience (2004)

Artificial grammar learning (Reber, 1967) is a form of implicit learning in which cognitive, rather than motor, implicit learning has been found. After viewing a series of letter strings formed according to a finite state rule system, people are able to classify new letter strings as to whether or not they are formed according to these grammatical rules despite little conscious insight into the rule structure. Previous research has shown that these classification judgments are based on knowledge of abstract rules as well as superficial similarity ("chunk strength") to training strings. Here we used event-related fMRI to identify neural regions involved in using both sources of information as test stimuli were designed to unconfound chunk strength from rule use. Using functional connectivity analyses, the extent to which the sources of information are complementary or competitive was also assessed. Activation in the right caudate was associated with rule adherence, whereas medial temporal lobe activations were associated with chunk strength. Additionally, functional connectivity analyses revealed caudate and medial temporal lobe activations to be strongly negatively correlated (r= -.88) with one another during the performance of this task.
A Maximum Entropy Model Application on Recognition of Metaphor Phenomena
Authors: Yang Xu
Venue: Proceedings of the 15th International Conference on Computing (2006)

Metaphor happening in our daily life language is a usual phenomenon, and recognizing them by the use of computer is becoming a valuable research task in the field of natural language processing, artificial intelligence, and even applied linguistics. This paper proposes a way to recognize metaphors based on Maximum Entropy Model after analyzing the features of metaphor, and reasons the rationality to build a recognition model using the statistical methods. The results of the experiment show that the model performs well at high precision and recall, as well as the f value, thus we come to the conclusion that such metaphor recognizing model based on Maximum Entropy Principle has a promising future.
The Role of Spared Calcarine Cortex and Lateral Occipital Cortex in the Responses of Human Hemianopes to Visual Motion
Authors: Antony B. Morland, Sandra Lê, Erin Carroll, Michael B. Hoffmann, Alidz Pambakian
Venue: Journal of Cognitive Neuroscience (2004)

Some patients, who are rendered perimetrically blind in one hemifield by cortical lesions, nevertheless exhibit residual visual capacities within their field defects. The neural mechanism that mediates the residual visual responses has remained the topic of considerable debate. One explanation posits the subcortical visual pathways that bypass the primary visual cortex and innervate the extrastriate visual areas as the substrate that underlies the residual vision. The other explanation is that small islands of the primary visual cortex remain intact and provide the signals for residual vision. We have performed behavioral and functional magnetic resonance imaging experiments to investigate the validity of the two explanations of residual vision. Our behavioral experiments indicated that of the seven hemianopes tested, two had the ability to discriminate the direction of a drifting grating. This residual visual response was shown with fMRI to be the result of spared islands of calcarine cortical activity in one of the hemianopes, whereas only lateral occipital activity was documented in the other patient. These results indicate that the underlying neural correlates of residual vision can vary between patients. Moreover, our study emphasizes the necessity of ruling out the presence of islands of preserved function and primary visual cortex before assigning residual visual capacities to the properties of visual pathways that bypass the primary visual cortex.
Research on Adaptive Synchrodrive Control Technology for Adjustable-Pitch System
Authors: Hongche Guo, Qingding Guo
Venue: Proceedings of the First International Conference on Innovative Computing, Information and Control - Volume 1 (2006)

This paper presents a robust control design for a variable-speed adjustable-pitch wind energy conversion system. An adaptive controller is designed to drive the turbine speed to extract invariable power from the wind and to allow pitch adjustment to power regulation. An adaptive controller is designed to drive the turbine speed to extract maximum power from the wind and to allow pith adjustment to constant power regulation. The simulations show the robustness of the controlled system.
Teaching regression with simulation
Authors: John H. Walker
Venue: Proceedings of the 36th conference on Winter simulation (2004)

Computer simulations can be used to teach complicated statistical concepts in linear regression more quickly and effectively than traditional lecture alone. In introductory applied statistics classes, the coverage of important statistical topics, such as the nature of the sampling distribution of the simple linear regression slope, the problem of multicollinearity in multiple linear regression, or the danger of extrapolation in predictions from multiple linear regression models, may be shortened or eliminated entirely for lack of time. Simulation can provide a way to introduce these topics in a brief, but memorable, way for introductory students or as the first step in a more thorough treatment for higher level students. This paper describes each simulation, discusses its pedagogical advantages, and gives sample computer output.
Robust License Plate Detection Using Covariance Descriptor in a Neural Network Framework
Authors: Fatih Porikli, Tekin Kocak
Venue: Proceedings of the IEEE International Conference on Video and Signal Based Surveillance (2006)

We present a license plate detection algorithm that employs a novel image descriptor. Instead of using conventional gradient filters and intensity histograms, we compute a covariance matrix of low-level pixel-wise features within a given image window. Unlike the existing approaches, this matrix effectively captures both statistical and spatial properties within the window. We normalize the covariance matrix using local variance scores and restructure the unique coefficients into a feature vector form. Then, we feed these coefficients into a multi-layer neural network. Since no explicit similarity or distance computation is required in this framework, we are able to keep the computational load of the detection process low. To further accelerate the covariance matrix extraction process, we adapt an integral image based data propagation technique. Our extensive analysis shows that the detection process is robust against noise, illumination distortions, and rotation. In addition, the presented method does not require careful fine tuning of the decision boundaries.
Modeling Age Progression in Young Faces
Authors: Narayanan Ramanathan, Rama Chellappa
Venue: Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 1 (2006)

We propose a craniofacial growth model that characterizes growth related shape variations observed in human faces during formative years. The model draws inspiration from the 'revised' cardioidal strain transformation model proposed in psychophysical studies related to craniofacial growth. The model takes into account anthropometric evidences collected on facial growth and hence is in accordance with the observed growth patterns in human faces across years. We characterize facial growth by means of growth parameters defined over facial landmarks often used in anthropometric studies. We illustrate how the age-based anthropometric constraints on facial proportions translate into linear and non-linear constraints on facial growth parameters and propose methods to compute the optimal growth parameters. The proposed craniofacial growth model can be used to predict one's appearance across years and to perform face recognition across age progression. This is demonstrated on a database of age separated face images of individuals under 18 years of age.
Deployment of A-globe multi-agent platform
Authors: David Šišlák, Martin Rehák, Michal Pěchouček, Dušan Pavlíček
Venue: Proceedings of the fifth international joint conference on Autonomous agents and multiagent systems (2006)

A-globe [2, 1] is a freeware, simulation-oriented multi-agent platform featuring agent migration, communication inaccessibility simulation and high scalability with moderate hardware requirements. Using dedicated simulation messaging together with 2D and 3D visualization support, large agent systems can be engineered, tested and visualized on a single machine. A-globe agents are fully-fledged JAVA agents, each with its own independent thread, that can autonomously migrate between platforms running on different hosts. Thanks to the separation of simulation and agent code, deployment of agents to embedded devices is straightforward. The platform is not natively FIPA-compliant, as the inter-operability was sacrificed to offer superior scalability and efficiency.
Asynchronous games 2: the true concurrency of innocence
Authors: Paul-André Melliès
Venue: Theoretical Computer Science (2006)

In game semantics, the higher-order value passing mechanisms of the λ-calculus are decomposed as sequences of atomic actions exchanged by a Player and its Opponent. Seen from this angle, game semantics is reminiscent of trace semantics in concurrency theory, where a process is identified to the sequences of requests it generates in the course of time. Asynchronous game semantics is an attempt to bridge the gap between the two subjects, and to see mainstream game semantics as a refined and interactive form of trace semantics. Asynchronous games are positional games played on Mazurkiewicz traces, which reformulate (and generalize) the familiar notion of arena game. The interleaving semantics of λ-terms, expressed as innocent strategies, may be analysed in this framework, in the perspective of true concurrency. The analysis reveals that innocent strategies are positional strategies regulated by forward and backward confluence properties. This captures, we believe, the essence of innocence. We conclude the article by defining a non-uniform variant of the λ-calculus, in which the game semantics of a λ-term is formulated directly as a trace semantics, performing the syntactic exploration or parsing of that λ-term.
Noise-enhanced phase synchronization of weakly coupled chaotic oscillators
Authors: J. Kurths, C. Zhou
Venue: Proceedings of the 2003 International Conference on Physics and Control - Volume 2 (2003)

It is well-known that noise degrades phase synchronization of periodic oscillators by inducing phase slips. Here we study constructive effects of noise on phase synchronization in coupled chaotic oscillators. We find that in the weak coupling regime below the synchronization threshold, noise can enhance phase synchronization significantly. This counterintuitive and constructive effect of noise is demonstrated in coupled Rossler chaotic oscillators with various measures of phase synchronization.
An efficient solver for Cache Miss Equations
Authors: N. Bermudo
Venue: Proceedings of the 2000 IEEE International Symposium on Performance Analysis of Systems and Software (2000)

Cache Miss Equations (CME) (S. Ghosh et al., 1997) is a method that accurately describes the cache behavior by means of polyhedra. Even though the computation cost of generating CME is a linear function of the number of references, solving them is a very time consuming task and thus trying to study a whole program may be infeasible. The paper presents effective techniques that exploit some properties of the particular polyhedra generated by CME. Such techniques reduce the complexity of the algorithm to solve CME, which results in a significant speedup when compared with traditional methods. In particular, the proposed approach does not require the computation of the vertices of each polyhedron, which has an exponential complexity.