ppxscal/embedding_network huggingface dataset:
Robust control of time-delay chaotic systems
Authors: Xinping Guan, Changchun Hua
Venue: Proceedings of the 2003 International Conference on Physics and Control - Volume 2 (2003)

Robust control problem of nonlinear time delay chaotic systems is investigated. For such uncertain systems, we propose adaptive feedback controller and novel nonlinear feedback controller. They are both independent of the time delay and can render the corresponding closed-loop systems globally uniformly ultimately bounded stable. The simulations on controlling logistic system are made and the results show the controllers are feasible.
Putting context into schema matching
Authors: Philip Bohannon, Eiman Elnahrawy, Wenfei Fan, Michael Flaster
Venue: Proceedings of the 32nd international conference on Very large data bases (2006)

Attribute-level schema matching has proven to be an important first step in developing mappings for data exchange, integration, restructuring and schema evolution. In this paper we investigate contextual schema matching, in which selection conditions are associated with matches by the schema matching process in order to improve overall match quality. We define a general space of matching techniques, and within this framework we identify a variety of novel, concrete algorithms for contextual schema matching. Furthermore, we show how common schema mapping techniques can be generalized to take more effective advantage of contextual matches, enabling automatic construction of mappings across certain forms of schema heterogeneity. An experimental study examines a wide variety of quality and performance issues. In addition, it demonstrates that contextual schema matching is an effective and practical technique to further automate the definition of complex data transformations.
Discriminant analysis algorithms for face recognition
Authors: Pong Chi Yuen
Venue:  (2006)

Face Recognition research started in the late 70s and a number of algorithms/systems have been developed in the last decade. Among various algorithms, appearance-based approach is one of the promising approaches in face recognition. Linear Discriminant Analysis (LDA) and Principal Component Analysis (PCA) are two most popular feature extraction and dimension reduction techniques used in the appearance-based approach. From classification point of view, generally, LDA-based algorithms perform better than that of PCA-based algorithms. However, there are two major problems when applying LDA in face recognition. The first one is the small sample size (S3) problem. It occurs when the image dimension is larger than the number of training samples. In turn, the within-class scatter matrix becomes singular. The second is the complicated and nonlinear image distributions when the images are captured under different poses and illuminations. In this thesis, discriminant analysis algorithms are designed and proposed, from the subspace approach and the regularization approach, to overcome these two limitations. In the subspace approach, a new Subspace-LDA (SLDA) method is proposed to solve the S3 problem. Compared with the existing LDA-based face recognition methods for solving S3 problem, the proposed SLDA method is more efficient and gives better performance. By applying the kernel trick in the SLDA method, a Kernel Subspace-LDA (KSLDA) method is proposed to solve the nonlinear face image distribution problem. One of the crucial factors in the Kernel approach is the determination of the kernel parameters which highly affect the generalization performance of the kernel-based learning methods. To further improve the performance of our proposed KSLDA method, an automatic parameter estimation algorithm based on eigenvalue stability, namely the Eigenvalue Stability Bounded Margin Maximization (ESBMM), is developed. This thesis also explores the regularization approach to solve the above-mentioned two problems. By applying the kernel trick into one-parameter regularized discriminant analysis (RDA) method, a kernel-based one-parameter regularized Fisher discriminant (K1PRFD) method is proposed. A gradient decent-based algorithm is also developed to find the optimal regularization parameter. In the final part, to utilize different advantages of different classifiers, a weighted combination scheme is proposed to integrate different kinds of face recognition algorithms. (Abstract shortened by UMI.)
The Optimization of Complex XML Queries over XML Streams under DTD
Authors: Weidong Yang, Qingming Wang, Wei Wang, Baile Shi
Venue: Proceedings of the Seventh International Conference on Web-Age Information Management Workshops (2006)

Time and Space complexity is a critical factor for a successful stream-based continuous query processing system. In this paper, we address the optimization of complex XML queries over XML Streams by using the semantic and structural constraints of its DTD. The optimization is preprocessed before the runtime of matching XML stream against user's queries in order to simplify XPathes. An approach that processes complex twig patterns with OR-predicates and AND-predicates over XML document streams is also described in this paper, which can be also be used without DTDs.
Speaking of Privacy
Authors: Carl E. Landwehr
Venue: IEEE Security and Privacy (2006)

When Plato, quoting Socrates, said "the unexamined life is not worth living," he was talking about self-examination. Today, it seems every life is examined, but more frequently by others than by ourselves.
Data Exploration Combining Kinetic and Static Visualization Displays
Authors: Fanhai Yang, Howard Goodell, Ronald Pickett, Robert Bobrow, Alexander Baumann, Alexander Gee, Georges Grinstein
Venue: Proceedings of the Fourth International Conference on Coordinated & Multiple Views in Exploratory Visualization (2006)

We describe interactions between kinetic (moving) and static information displays. We have implemented "moxel" kinetic displays in a classic discovery platform with many standard information visualization and analytic tools, and experimented with interactions between them. Moxels, which generalize pixels, are an advanced, moving, form of iconographic display of the kind first developed in static form by Pickett and White (1966). As with the static graphic icons of those early displays, moxels provide a way of mapping together in one image multiple data variables, but with potentially more potency with in-place motion. We show examples of how the two kinds of displays have been integrated, and discuss issues with the integration of dynamic and static visualizations in a single environment. We discuss several interaction paradigms between them including linked brushing, multiple selections, and operations on selected regions.
Toward Inductive Logic Programming for Collaborative Problem Solving
Authors: Jian Huang, Adrian R. Pearce
Venue: Proceedings of the IEEE/WIC/ACM international conference on Intelligent Agent Technology (2006)

In this paper, we tackle learning in distributed systems and the fact that learning does not necessarily involve the participation of agents directly in the inductive process itself. Instead, many systems frequently employ multiple instances of induction separately. The paper's main contribution is a new approach that tightly integrates processes of induction between distributed agents, based on inductive logic programming techniques, for a wider class of problem solving tasks. The approach combines inverse entailment with an epistemic approach to reasoning about knowledge, facilitating a systematic approach to the sharing of knowledge and invention of predicates only when required. We illustrate the approach for learning declarative program fragments and for a well-known path planning problem and compare results empirically to (multiple instances of) single agent-based induction over varying distributions of data. Given a chosen path planning algorithm, our algorithm enables agents to combine their local knowledge in an effective way to avoid central control while significantly reducing communication costs.
Epipolar Geometry of Central Projection Systems Using Veronese Maps
Authors: Joao P. Barreto, Kostas Daniilidis
Venue: Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 1 (2006)

We study the epipolar geometry between views acquired by mixtures of central projection systems including catadioptric sensors and cameras with lens distortion. Since the projection models are in general non-linear, a new representation for the geometry of central images is proposed. This representation is the lifting through Veronese maps of the image plane to the 5D projective space. It is shown that, for most sensor combinations, there is a bilinear form relating the lifted coordinates of corresponding image points. We analyze the properties of the embedding and explicitly construct the lifted fundamental matrices in order to understand their structure. The usefulness of the framework is illustrated by estimating the epipolar geometry between images acquired by a paracatadioptric system and a camera with radial distortion.
Transform from Models to Service Description Based on MDA
Authors: Bin Yu, Chen Zhang, Yang Zhao
Venue: Proceedings of the 2006 IEEE Asia-Pacific Conference on Services Computing (2006)

Within MDA framework, system models can be built up on an abstract level that is independent from the platform. Later on, this abstract model can be transmitted into service description, which is related to specific platform on the implementation level. In Web Services applications, this transition has a great advantage. Because, while the model of implementation changes from one case to another to fit the different platforms, the model of whole system, on a higher abstract level, stays the same. Thus, the efficiency is promoted. This paper firstly discusses the extension of UML for Web Services, and then it presents the modeling process of WSDL. Finally, it gives the rules and arithmetic of transition from models to WSDL documents in detail.
An Image Encryption Approach Based on a New Two-Dimensional Map
Authors: Feng Huang, Yong Feng
Venue: Proceedings of the 2006 International Conference on Intelligent Information Hiding and Multimedia (2006)

In this paper a new two-dimensional map is proposed. It is a process of stretch-and-fold. Firstly a square image is divide two parts according diagonal. Secondly each part of image is stretch respectively and joins a line. Lastly the line is fold over to a new square image of same size. The map divides into the left map and the right map. The process shuffles the positions of image pixels. Comparing the prevalent twodimensional map, Cat map and Baker map, the new map has simple formulation, big keys space which is fit for image encryption. An image encryption scheme based on the map is developed. The numbers of the left map and the right map are used as the key. The deciphering process is opposite using the same keys. The results of simulation show that it can be used in real-time image encryption applications.
A Scalable Multi-tier Architecture for the National Taiwan University Hospital Information System based on HL7 Standard
Authors: T. H. Yang, P. H. Cheng, C. H. Yang, F. Lai, C. L. Chen, H. H. Lee, K. P. Hsu, C. H. Chen, C. T. Tan, Y. S. Sun
Venue: Proceedings of the 19th IEEE Symposium on Computer-Based Medical Systems (2006)

This article describes the successful experiences of National Taiwan University Hospital (NTUH) in moving from IBM Mainframe to connected networking computer systems. We use multi-tier architecture and HL7 standard to implement our new outpatient Hospital Information System (HIS). The NTUH HIS is a complex environment with several operating systems, databases, and information systems. We adopt Service- Oriented Architecture (SOA) to reduce the complex relations between systems and solve data consistency problems among databases. We also show that the distributed architecture can provide us stable and reasonable system performances. Our main contribution is proving that the distributed environment with HL7 standard and SOA can sustain in a highly demanding environment.
A Navigation Interface for Adaptive m-Learning Applications
Authors: Laercio Sambuc dos Anjos, Jose M. Parente de Oliveira
Venue: Proceedings of the Sixth IEEE International Conference on Advanced Learning Technologies (2006)

Some researches have used concept maps to support navigation in m-Learning applications. Nevertheless, as this navigation support is not very flexible, adaptation to learner characteristics is not possible. Aiming at overcoming such limitation, a navigation interface for m-Learning based on concept map with the capability of adapting to some learner's characteristics has been conceived. Despite a preliminary prototype has been implemented, it has been possible to visualize the soundness of the proposed solution.
Unsupervised Change Detection in Remote-Sensing Images using One-dimensional Self-Organizing Feature Map Neural Network
Authors: Swarnajyoti Patra, Susmita Ghosh, Ashish Ghosh
Venue: Proceedings of the 9th International Conference on Information Technology (2006)

In this paper, we propose an unsupervised changedetection technique based on Self-Organizing Feature Map neural network that discriminates the "difference image" by constructing two clusters. In the proposed network, the number of input neurons is equal to the dimension of the input pattern while the number of output neurons is two. To confirm the effectiveness of the proposed technique a comparative study is made with another existing contextsensitive technique.
Optimal Short-Time Features for Music/Speech Classification of Compressed Audio Data
Authors: A. Rizzi, M. Buccino, M. Panella, A. Uncini
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)

This paper deals with the Music/Speech classification problem, starting from a set of features extracted directly from compressed audio data. The proposed classification system is able to label audio sequences stored as compressed MPEG layer III files. Decoding and analyzing in a unique stage is a fundamental tool for audio streaming applications, such as real time classification. Moreover, the techniques described herein provide useful tools in the management (data tagging, summarization, etc.) of a digital music library. The adopted set of short-time features are computed from the spectral information available in the decoding stage. In this paper, we show that for the classification problem at hand this set of features is redundant and can be dramatically pruned. To this aim we used an optimization strategy based on principal component analysis and genetic algorithms. The results show a very interesting classification accuracy using just one short-time feature.
PISGrid: A Semantic Grid Infrastructure of Establishing Dynamic Virtual Organizations According to Requirement for Press Industry
Authors: Hejie Chen, Ben Liu, Wei He
Venue: Proceedings of the 2006 IEEE/WIC/ACM international conference on Web Intelligence and Intelligent Agent Technology (2006)

Information technology has already been applied in the press industry. But information can't be shared in the press industry chain. In order to solve isolated information island, this paper presents a grid_based infrastructure which adopts the Semantic Web and the Grid. One character of the infrastructure is that ontologies realize semantic information and semantic service. Another character of this infrastructure is that grid services can dynamically establish a virtual organization in terms of information flow, logistical flow and workflow.
Gender identification using a general audio classifier
Authors: H. Harb, Liming Chen
Venue: Proceedings of the 2003 International Conference on Multimedia and Expo - Volume 1 (2003)

In the context of content-based multimedia indexing gender identification using speech signal is an important task. Existing techniques are dependent on the quality of the speech signal making them unsuitable for the video indexing problems. In this paper we introduce a novel gender identification approach based on a general audio classifier. The audio classifier models the audio signal by the first order spectrum's statistics in 1s windows and uses a set of neural networks as classifiers. The presented technique shows robustness to adverse audio compression and it is language independent. We show how practical considerations about the speech in audio-visual data, such as the continuity of speech, can further improve the classification results which attain 92%.
Model-based Human Motion Description in Ergonomic Database Application
Authors: Sayaka Imai, Yoshinari Kanamori
Venue: Proceedings of the 21st International Conference on Data Engineering Workshops (2005)

This paper presents a modeling method of human motion for the purpose of constructing a human body/structure/motion database. Various representation methods of the human body and of its motions are used in Computer Graphics, Virtual Reality, etc. Furthermore, measuring and analyzing methods of human motion using for instance 3D digitizers, high resolution video cameras are presented in many fields such as rehabilitation, ergonomic design and production planning. Besides, many new applications that can analyze the human motion from a medical point of view are available. In the future of these fields, we consider that a database system which can manage various human data and support flexible query operations is needed. In order to compare a new captured human body/structure/motion data with another human data in a computer system, the data need to be unified and to correspond to semantics. We focused on the modeling of human motion by including an example motion, describing its actual motion and semantically associating the example with the motion. In fact, in a previous work, we defined the concept of Hub which represents an example motion. We also defined the concept of Mediator which not only represents the individual motion characteristics but also associates the Hub with the real human motion data detected from multimedia such as videos. To extend our previous work, we now consider the notion of order in the sequences of the human motion. In that we introduce the concepts of Atomic Unit and Motion Graph. These concepts allow us to analyze human motionsand to compare their sequences. Indeed they are a good way to unify data from various applications.
COCA: A Contract-Based Infrastructure for Composing Adaptive Multimedia Systems
Authors: Zhinan Zhou, Philip K. McKinley
Venue: Proceedings of the 26th IEEE International ConferenceWorkshops on Distributed Computing Systems (2006)

Achieving acceptable quality of service in highly dynamic computing environments requires not only adaptation and reconfiguration of individual components of the system, but also collaboration among these components. To address these issues in adaptive multimedia applications, we propose COCA, a contract-based collaborative adaptation infrastructure. COCA uses contract specifications to describe the relationships among different system components, to generate code that realizes adaptive functionality, and to govern system-wide adaptive behavior during execution. COCA also provides a set of reusable adaptation services that enable legacy components to be integrated into an adaptive system. We demonstrate the use of COCA to construct an adaptive multimedia conferencing system from a collection of existing components that were not originally designed for interoperation.
Practical Methods for Geometric and Photometric Correction of Tiled Projector
Authors: Michael Harville, Bruce Culbertson, Irwin Sobel, Dan Gelb, Andrew Fitzhugh, Donald Tanguay
Venue: Proceedings of the 2006 Conference on Computer Vision and Pattern Recognition Workshop (2006)

We describe a novel, practical method to create largescale, immersive displays by tiling multiple projectors on curved screens. Calibration is performed automatically with imagery from a single uncalibrated camera, without requiring knowledge of the 3D screen shape. Composition of 2D-mesh-based coordinate mappings, from screen-tocamera and from camera-to-projectors, allows image distortions imposed by the screen curvature and camera and projector lenses to be geometrically corrected together in a single non-parametric framework. For screens that are developable surfaces, we show that the screen-to-camera mapping can be determined without some of the complication of prior methods, resulting in a display on which imagery is undistorted, as if physically attached like wallpaper. We also develop a method of photometric calibration that unifies the geometric blending, brightness scaling, and black level offset maps of prior approaches. The functional form of the geometric blending is novel in itself. The resulting method is more tolerant of geometric correction imprecision, so that visual artifacts are significantly reduced at projector edges and overlap regions. Our efficient GPUbased implementation enables a single PC to render multiple high-resolution video streams simultaneously at frame rate to arbitrary screen locations, leaving the CPU largely free to do video decompression and other processing.
UAV Linear and Nonlinear Estimation Using Extended Kalman Filter
Authors: Abhijit G. Kallapur, Sreenatha G. Anavatti
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)

UAV state and parameter estimation for three dynamic models is presented using techniques of Extended Kalman Filter. Two nonlinear models and one linear model are used for the identification of a small Unmanned Aerial Vehicle (UAV), all of which are derived from a common UAV coupled, dynamic model.
Bandwidth and latency analysis of modified deficit round robin scheduling algorithms
Authors: Luciano Lenzini, Enzo Mingozzi, Giovanni Stea
Venue: Proceedings of the 1st international conference on Performance evaluation methodolgies and tools (2006)

Deficit Round Robin (DRR) is a scheduling algorithm which provides fair queuing at O(1) complexity. However, due to its round robin structure, its latency properties are not adequate for latency-critical applications, such as voice. For this reason, router manufacturers implement variants of the DRR algorithm which guarantee lower latencies to one (or a subset of) queue(s). In this paper we evaluate the performance of two such variants, both of which are known as Modified Deficit Round Robin, currently implemented in commercial routers. The comparison is carried out analytically, by deriving the latency and bandwidth sharing properties of both algorithms, and by simulation.