ppxscal/embedding_network huggingface dataset:
Recursive Recovery of Position and Orientation from Stereo Image Sequences without Three-Dimensional Structures
Authors: Ying Kin Yu, Kin Hong Wong, Siu Hang, Michael Ming Yuen Chang
Venue: Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 1 (2006)

Traditional vision-based 3-D motion estimation algorithms for robots require given or calculated 3-D models while the motion is being tracked. We propose a high-speed extended-Kalman-filter-based approach that recovers position and orientation from stereo image sequences without prior knowledge as well as the procedure for the reconstruction of 3-D structures. Empowered by the use of the trifocal tensor, the computation step of 3-D models can be eliminated. The algorithm is thus more flexible and can be applied to a wide range of domains. The twist motion model is also adopted to parameterize the 3-D motion such that the motion representation in the proposed algorithm is robust and minimal. As the number of parameters to be estimated is reduced, our algorithm is more efficient, stable and accurate compared to traditional approaches. The proposed method has been verified using a real image sequence with ground truth.
Exploring the constraints of human behavior representation
Authors: John C. Giordano, Paul F. Reynolds,  Jr., David C. Brogan
Venue: Proceedings of the 36th conference on Winter simulation (2004)

Human behavior representation (HBR) is an elusive, yet critical goal for many in the simulation community. Requirement specifications related to HBR often exceed current capabilities. There exist a number of tools, techniques and frameworks to model and simulate HBR, but they are constrained and do not generalize well. Even with a vibrant research community, certain HBR characteristics remain beyond our grasp, unless some unforeseen disruptive technologies emerge. We survey the state of the practice for HBR, discuss ongoing research, and identify what appear to be insurmountable challenges. Along with exposing the essential characteristics of HBR and their current level of maturity, we propose a generational framework for considering HBR capabilities. While a number of HBR issues have been addressed in the literature, there is no published discussion explicitly detailing its constraints and limitations.
Task Reweighting under Global Scheduling on Multiprocessors
Authors: Aaron Block, James H. Anderson, UmaMaheswari C. Devi
Venue: Proceedings of the 18th Euromicro Conference on Real-Time Systems (2006)

We consider schemes for enacting task share changes "a process called reweighting" on real-time multiprocessor platforms. Our particular focus is reweighting schemes that are deployed in environments in which tasks may frequently request significant share changes. Prior work has shown that fair scheduling algorithms are capable of reweighting tasks with minimal allocation error and that partitioning-based scheduling algorithms can reweight tasks with better average-case performance, but greater error. However, preemption and migration overheads can be high in fair schemes. In this paper, we consider the question of whether global scheduling techniques can improve the accuracy of reweighting relative to partitioning-based schemes and provide improved average-case performance relative to fair-scheduled systems. Our conclusion is that, for soft real-time systems, global scheduling techniques provide a good mix of accuracy and average-case performance.
300mm time constrained queue loop management
Authors: Erik Hertzler, David Van Sickle
Venue: Proceedings of the 37th conference on Winter simulation (2005)

In semiconductor processing there are some portions of the processing line where the time between a wafer leaving an operation and being processed at some subsequent operation must be managed or else process defects may occur that can negatively impact the resulting wafer. These time constrained process loops are commonly referred to as "Queue Loops" because wafers are held in queue until there is high confidence the wafers can be processed through the loop within the predetermined process timeframe. The problem in building this confidence resides in being able to synchronize production capacity within each loop while being careful to balance between factory favorable cycle-time and cost effective toolset capacity. A simulation modeling methodology was developed to identify the trade-offs between time through a loop measured in cycle-time and synchronized toolset capacity.
Robust information-theoretic clustering
Authors: Christian Böhm, Christos Faloutsos, Jia-Yu Pan, Claudia Plant
Venue: Proceedings of the 12th ACM SIGKDD international conference on Knowledge discovery and data mining (2006)

How do we find a natural clustering of a real world point set, which contains an unknown number of clusters with different shapes, and which may be contaminated by noise? Most clustering algorithms were designed with certain assumptions (Gaussianity), they often require the user to give input parameters, and they are sensitive to noise. In this paper, we propose a robust framework for determining a natural clustering of a given data set, based on the minimum description length (MDL) principle. The proposed framework, Robust Information-theoretic Clustering (RIC), is orthogonal to any known clustering algorithm: given a preliminary clustering, RIC purifies these clusters from noise, and adjusts the clusterings such that it simultaneously determines the most natural amount and shape (subspace) of the clusters. Our RIC method can be combined with any clustering technique ranging from K-means and K-medoids to advanced methods such as spectral clustering. In fact, RIC is even able to purify and improve an initial coarse clustering, even if we start with very simple methods such as grid-based space partitioning. Moreover, RIC scales well with the data set size. Extensive experiments on synthetic and real world data sets validate the proposed RIC framework.
RISE: A Grid-Based Self-Configuring and Self-Healing Remote System Image Management Environment
Authors: Jonghyun Lee, Karpjoo Jeong, Hanku Lee, Inho Lee, Sangmoon Lee, Dosik Park, Changsung Lee, Woojin Yang
Venue: Proceedings of the Second IEEE International Conference on e-Science and Grid Computing (2006)

Autonomic remote system image management support (e.g., remote system installation and backup) is crucial for the management of clusters in large scale grid computing environments in which clusters at different locations are integrated into a single large sale computing system. We propose a Grid-based remote image management environment (called RISE) which is designed to support ease of use, high performance installation, and resiliency against failure and configuration changes. Major features of the RISE system are: (1) remote system image installation, backup and recovery via a web-based simple and intuitive user interface, (2) parallel installation, (3) backup image databases (2) self-configuration (autonomic configuration propagation and recovery protocol), (3) self-healing (autonomic backup image database replication and recovery). The development of the system with no support for grid environments has been completed and its commercial version by Samsung Electronics has been available since the June of 2006. The development of the grid support version is under-way.
Some characterizations of finite Sturmian words
Authors: Aldo de Luca, Alessandro De Luca
Venue: Theoretical Computer Science (2006)

In this paper, we give some new characterizations of words which are finite factors of Sturmian words. An enumeration formula for primitive finite Sturmian words is given. Moreover, we provide two linear-time algorithms to recognize whether a finite word is Sturmian.
Chaos Numbers
Authors: Chefi Ketata, Mysore G. Satish, M. Rafiqul Islam
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)

Nature is characterized by its chaotic behavior. To understand better its phenomena, it is essential to use appropriate tools to achieve the best definition possible of its chaos variables and processes. One of the main tools is mathematics. Mathematics deals with numbers. Classical mathematics falls short since it does not take into account the dynamic and evolutionary state of numbers. This paper introduces a novel meaning for numbers. Then, various arithmetic operations are established. Such operations comprise addition, subtraction, multiplication, and division. Addition is the process of calculating the sum of two or more numbers. Subtraction is the act of deducting one number from another. Multiplication is the procedure of adding a number to itself a particular number of times. Division is the operation of calculating the number of times one number is contained in another. This paper lays the foundation for chaos arithmetic, which deals with nature perpetual evolution.
Attraction region of planar linear systems with one unstable pole and saturated feedback
Authors: J.-Y. Favez, Ph. Mullhaupt, B. Srinivasan, D. Bonvin
Venue: Journal of Dynamical and Control Systems (2006)

The bifurcation of the attraction region for planar systems with one stable and one unstable pole under a saturated linear state feedback is considered. The attraction region can have either an unbounded hyperbolic shape or be bounded by a limit cycle. An analytical condition, under which either of these boundary shapes occurs, is given with a formal proof. This condition is based on the relationship between the stable and unstable manifolds associated with secondary saddle equilibrium points, whose presence is caused by the saturation on the input.
A Robust Superimposed Caption Box Content Understanding for Sports Videos
Authors: Huang-Chia Shih, Chung-Lin Huang
Venue: Proceedings of the Eighth IEEE International Symposium on Multimedia (2006)

This paper proposes a semantics understanding system to interpret the superimposed caption box (SCB) in sports videos of which the template of SCB is presumably not a priori. The semantics in SCB represent the digested key information of the sports video content. Most of the previous studies assume that the SCB template is known as a priori, and require the representative character bitmaps. The SCB understanding system consists of SCB extraction, character extraction, digit/text character recognition, digital object interpretation using labeling mechanism. In the experiments, we will illustrate that the system can interpret the SCB in basketball and baseball game videos successfully.
Workflow-Driven Ontologies: An Earth Sciences Case Study
Authors: Leonardo Salayandia, Paulo Pinheiro da Silva, Ann Q. Gates, Flor Salcedo
Venue: Proceedings of the Second IEEE International Conference on e-Science and Grid Computing (2006)

A goal of the Geosciences Network (GEON) is to develop cyber-infrastructure that will allow earth scientists to discover access, integrate and disseminate knowledge in distributed environments such as the Web, changing the way in which research is conducted. The earth sciences community has begun the complex task of creating ontologies to support this effort. A challenge is to coalesce the needs of the earth scientists, who wish to capture knowledge in a particular discipline through the ontology, with the need to leverage the knowledge to support technology that will facilitate computation, for example, by helping the composition of services. This paper describes an approach for defining workflow-driven ontologies that capture classes and relationships from domain experts and use that knowledge to support composition of services. To demonstrate the capability afforded by this type of ontology, the paper presents examples of workflow specifications generated from a workflow-driven ontology that has been defined for representing knowledge about gravity data.
A hybrid agent-cellular space modeling approach for fire spread and suppression simulation
Authors: Xiaolin Hu, Alexandre Muzy, Lewis Ntaimo
Venue: Proceedings of the 37th conference on Winter simulation (2005)

This paper presents a first effort to integrate DEVS-based cellular space models with agent models using dynamic structure DEVS for the simulation of forest fire spread and suppression. The main focus is on the interaction between mobile agents (such as fire fighters, air-tankers) and forest cells. DEVS models' dynamic structure modeling capability is applied where couplings between mobile agents and forest cells are dynamically added and removed when the agents move in the cellular space. Two methods, a time-based method and an event-based method, are discussed to update a mobile agent's position in a cellular space. A system architecture is presented and a prototype fire spread and suppression example is implemented. Based on this initial work, we hope to understand more about the nature of this hybrid agent-cellular space approach and to apply it to the modeling and simulation of forest fires and other ecological applications.
From truth to computability I
Authors: Giorgi Japaridze
Venue: Theoretical Computer Science (2006)

The recently initiated approach called computability logic is a formal theory of interactive computation. It understands computational problems as games played by a machine against its environment, and uses logical formalism to describe valid principles of computability, with formulas representing computational problems and logical operators standing for operations on computational problems. The concept of computability that lies under this approach is a generalization of Church-Turing computability from simple, two-step (question/answer, input/output) problems to problems of arbitrary degrees of interactivity. Restricting this concept to predicates, which are understood as computational problems of zero degree of interactivity, yields exactly classical truth. This makes computability logic a generalization and refinement of classical logic.The foundational paper "Introduction to computability logic" [G. Japaridze, Ann. Pure Appl. Logic 123 (2003) 1-99] was focused on semantics rather than syntax, and certain axiomatizability assertions in it were only stated as conjectures. The present contribution contains a verification of one of such conjectures: a soundness and completeness proof for the deductive system CL3 which axiomatizes the most basic first-order fragment of computability logic called the finite-depth, elementary-base fragment. CL3 is a conservative extension of classical predicate calculus in the language which, along with all of the (appropriately generalized) logical operators of classical logic, contains propositional connectives and quantifiers representing the so called choice operations. The atoms of this language are interpreted as elementary problems, i.e. predicates in the standard sense. Among the potential application areas for CL3 are the theory of interactive computation, constructive applied theories, knowledgebase systems, systems for resource-bound planning and action.This paper is self-contained as it reintroduces all relevant definitions as well as main motivations. It is meant for a wide audience and does not assume that the reader has specialized knowledge in any particular subarea of logic or computer science.
A Robust Video Object Tracking by Using Active Contours
Authors: Mohand Said Allili, Djemel Ziou
Venue: Proceedings of the 2006 Conference on Computer Vision and Pattern Recognition Workshop (2006)

In this paper, we propose a novel object tracking algorithm in video sequences. The formulation of our tracking model is based on variational calculus, where region and boundary information cooperate for object boundary localization by using active contours. In the approach, only the segmentation of the objects in the first frame is required for initialization. The evolution of the object contours on a current frame aims to find the boundary of the objects by minimizing the Kullback-Leibler distance of the region features distribution in the vicinity of the contour to the objects versus the background respectively. We show the effectiveness of the approach on examples of object tracking performed on real video sequences.
Relevance judgment in epistemic and hedonic information searches
Authors: Yunjie Xu
Venue: Journal of the American Society for Information Science and Technology (2007)

Research in information science now regards users' relevance judgment as subjective perception. However, user-centered studies in the extant literature mainly focus on relevance judgment in problem solving contexts in which the situational relevance of a document is the main concern for users. This study investigates users' relevance judgment in non-problem-solving contexts, i.e., when users search information for epistemic value or entertainment. It is posited that informative relevance and affective relevance should be the main concerns for users. Based on H. P. Grice's (1975, 1989) communication theory and Y. Xu and Z. Chen's (2006) framework, this study tests the significance of topicality, novelty, reliability, understandability, and scope to informative relevance and affective relevance in non-problem-solving contexts. This empirical study finds novelty, reliability, and topicality to be key aspects of informative relevance. &copy; 2007 Wiley Periodicals, Inc.
Investigating the Neural Basis of the Auditory Continuity Illusion
Authors: Fatima T. Husain, Thomas P. Lozito, Antonio Ulloa, Barry Horwitz
Venue: Journal of Cognitive Neuroscience (2005)

In this study, we investigated one type of auditory perceptual grouping phenomena&mdash;the auditory continuity illusion (also called temporal induction). We employed a previously developed, neurobiologically realistic, large-scale neural network model of the auditory processing pathway in the cortex, ranging from the primary auditory cortex to the prefrontal cortex, and simulated temporal induction without changing any model parameters. The model processes tonal contour stimuli, composed of combinations of upward and downward FM sweeps and tones, in a delayed match-to-sample task. The local electrical activities of the neuronal units of the model simulated accurately the experimentally observed electrophysiological data, where available, and the model's simulated BOLD-fMRI data were quantitatively matched with experimental fMRI data. In the present simulations, intact stimuli were matched with fragmented versions (i.e., with inserted silent gaps). The ability of the model to match fragmented stimuli declined as the duration of the gaps increased. However, when simulated broadband noise was inserted into these gaps, the matching response was restored, indicating that a continuous stimulus was perceived. The electrical activities of the neuronal units of the model agreed with electrophysiological data, and the behavioral activity of the model matched human behavioral data. In the model, the predominant mechanism implementing temporal induction is the divergence of the feedforward connections along the auditory processing pathway in the temporal cortex. These simulation results not only attest to the robustness of the model, but further predict the primary role of the anatomical connectivity of the auditory processing areas in mediating the continuity illusion.
Model Driven Data Warehousing for Business Performance Management
Authors: Pawan Chowdhary, George Mihaila, Hui Lei
Venue: Proceedings of the IEEE International Conference on e-Business Engineering (2006)

Traditional data warehouses are manually designed starting from specific requirements and anticipated data analysis needs. As a result there is frequently a disconnect between business process models, business definition of data artifacts and the data stored in the data warehouses as they are often designed manually and in isolation. Hence it has always been a challenge to keep the data warehouse in sync with the continuously changing business process models, resulting in both high maintenance costs and lost opportunities. In this paper we present our Model Driven Data Warehousing (MDDW) approach in the area of Business Performance Management (BPM). The purpose of MDDW is to bridge the gap between the business process models and the data warehouse models, thus enable the rapid adaptation to changes in the business environment. We describe our modeling framework comprising the various modeling elements and meta-models that capture both business and IT data artifacts.
Avoiding coincidental correctness in boundary value analysis
Authors: R. M. Hierons
Venue: ACM Transactions on Software Engineering and Methodology (TOSEM) (2006)

In partition analysis we divide the input domain to form subdomains on which the system's behaviour should be uniform. Boundary value analysis produces test inputs near each subdomain's boundaries to find failures caused by incorrect implementation of the boundaries. However, boundary value analysis can be adversely affected by coincidental correctness---the system produces the expected output, but for the wrong reason. This article shows how boundary value analysis can be adapted in order to reduce the likelihood of coincidental correctness. The main contribution is to cases of automated test data generation in which we cannot rely on the expertise of a tester.
STARMINE: a visualization system for cyber attacks
Authors: Yusuke Hideshima, Hideki Koike
Venue: Proceedings of the 2006 Asia-Pacific Symposium on Information Visualisation - Volume 60 (2006)

In cyber attack monitoring systems, various types of visualizations, such as geographical visualization, temporal visualization, logical visualization, are being used. Each visualization has its own advantages and disadvantages. Since it is important to analyze the information from different viewpoints and to make a right decision in practical cyber attack monitoring, these visualization should be highly integrated.This paper describes a visualization system for cyber threat monitoring named STARMINE, which integrates three different views, that is geographical, temporal, and logical views, of the cyber threat in 3-D space. Since three views are seen simultaneously and are synchronized, it is helpful for administrators to analyze the threats much more easily. As an example, the propagation of Sasser.D worm were shown.
Panoramic 3D Reconstruction Using Rotational Stereo Camera with Simple Epipolar Constraints
Authors: Wei Jiang, Masatoshi Okutomi, Shigeki Sugimoto
Venue: Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 1 (2006)

In this paper, we propose a novel method for panoramic 3D scene recovery using rotational stereo cameras with simple epipolar constraints. By rotating two parallel stereo cameras about a vertical axis with a constant velocity, we acquire two sampled spacio-temporal volumes which are made of the sequential images captured by a uniform angular interval. The two spacio-temporal volumes can be resampled into a set of multi-perspective panoramas. We analyze the epipolar geometry among images (panoramas and original images) of two spacio-temporal volumes. The result shows that only three types of simple epipolar constraints (epipolar line is row or column of image) exist in the two spacio-temporal volumes. Then we compute a depth map from four image pairs using a multi-baseline algorithm with the three types of epipolar constraints; that is horizontal, vertical and combination of them. Experimental results using both synthetic and real images show that our approach produces high quality panoramic 3D reconstruction.