ppxscal/embedding_network huggingface dataset:
A generic architecture for adaptable multimedia services provision: illustration by a scenario
Authors: Zakia Kazi-Aoul, Isabelle Demeure, Jean-Claude Moissinac
Venue: Proceedings of the 1st French-speaking conference on Mobility and ubiquity computing (2004)

This paper introduces a generic architecture for the provision of adaptable services to mobile terminal users. The architecture involves the use of component technologies for the service logic and the use of MPEG-7 and MPEG-21 functionalities that enable the description, processing and adaptation of multimedia flows.The requirements for adaptable services are motivated by the presentation of an adaptation scenario. The functioning of the architecture is illustrated by the same scenario.
Streaming video: an experiment in new aesthetics
Authors: Jim Bizzocchi
Venue: Proceedings of the 5th conference on Creativity cognition (2005)

In my research program, Ambient Video, I am investigating the impact of the introduction of large, high-resolution, flat-screen displays on the aesthetics and techniques that will be used in productions created in the future when this type of display is common. This paper for Creativity & Cognition 2005 provides background and context for the exhibition of a video art work, Streaming Video, which has been created as part of the research.
Generation of Non-Redundant Summary Based on Sum of Similarity
Authors: Yang Sun, Soon Cheol Park
Venue: Proceedings of the International Conference on Information Technology: Coding and Computing (ITCC'05) - Volume II - Volume 02 (2005)

This paper proposes an efficient method to extract the most important and non-redundant sentence segments based on sum of similarity. The new characteristics of our method are listed as follows: 1) we use preprocessing to delete the additional information (comma parenthesis) that won't turn up in the summarization; 2) redesign the vector similarity between a pair of sentences by using sum of similarity; 3) in order to maximize topic diversity, we use a strikingly different redundancy reducing ways other than MMR.. Experimental results show that our approach compares favorably with some other summary systems.
Tangent-Corrected Embedding
Authors: Ali Ghodsi, Jiayuan Huang, Finnegan Southey, Dale Schuurmans
Venue: Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Volume 1 - Volume 01 (2005)

Images and other high-dimensional data can frequently be characterized by a low dimensional manifold (e.g. one that corresponds to the degrees of freedom of the camera). Recently, nonlinear manifold learning techniques have been used to map images to points in a lower dimension space, capturing some of the dynamics of the camera or the subjects. In general, these methods do not take advantage of any prior understanding of the dynamics we might have, relying instead on local Euclidean distances that can be misleading in image space. In practice, we frequently have some prior knowledge regarding the transformations that relate images (e.g. rotation, translation, etc). We present a method for augmenting existing embedding techniques with additional information derived from known transformations, either in the form of tangent spaces that locally characterize the manifold or distances derived from reconstruction errors. The extra information is incorporated directly into the cost function of the embedding technique. The techniques we augment are largely attractive because there is a closed form solution for their cost optimization. Our approach likewise produces a closed form solution for the augmented cost function. Experiments demonstrate the effectiveness of the approach on a variety of image data.
Site selection and placement techniques
Authors: H. H. Loomis
Venue: ACM SIGDA Newsletter (1977)

The manufacturing-related tasks in the engineering design of digital systems are those processes which translate a logic design into a functioning physical system. That is, they begin with a description of the system as an interconnection of logic units (such as gates, flip-flops, counters, memories, ALU's, etc.) transforming it into a description of the placement of physical modules and the wiring which interconnects specific terminals on these modules. This portion of the design process has been the one which first saw substantial application of computing, vastly improving the speed, accuracy and capacity of the design organization. It is in this area still that the bulk of the production digital design automation systems are categorized.
Event-Based Blackboard Architecture for Multi-Agent Systems
Authors: Jing Dong, Shanguo Chen, Jun-Jang Jeng
Venue: Proceedings of the International Conference on Information Technology: Coding and Computing (ITCC'05) - Volume II - Volume 02 (2005)

Developing large multi-agent systems is a complex task involving the processes of the requirement, architecture, design and implementation of these systems. In particular, the architectural design is critical to cope with the increasing size and complexity of these systems. The multi-agent system that accesses a central repository is typically based on the Blackboard architectural pattern. However, the control strategies of the agents are inherently complex. In this paper, we present an event-based control strategy to manage the access of central repository by multi-agents. In this approach, the Blackboard pattern is composed with the Implicit Invocation pattern to separate the control policies from the control component so that the architecture is ease of evolution, reuses and changes.
On the efficiency of a bearings-only instrumental variable estimator for target motion analysis
Authors: Kutluyil Doǧançay
Venue: Signal Processing (2005)

The maximum-likelihood (ML) estimator for bearings-only target motion analysis does not admit a closed-from solution and must be implemented iteratively. Iterative ML estimators require an initialization close to the true solution to avoid divergence. Recently a closed-form asymptotically unbiased instrumental variable estimator has been proposed to alleviate the convergence problems associated with iterative ML estimators. This paper establishes the asymptotic efficiency of the closed-form instrumental variable estimator by showing that its error covariance matrix approaches the Cramer-Rao lower bound for sufficiently small bearing noise as the number of measurements tends to infinity.
Run-time Detection of Heap-based Overflows
Authors: William Robertson, Christopher Kruegel, Darren Mutz, Fredrik Valeur
Venue: Proceedings of the 17th USENIX conference on System administration (2003)

Buffer overflows belong to the most common class of attacks on today's Internet. Although stack-based variants are still by far more frequent and well-understood, heap-based overflows have recently gained more attention. Several real-world exploits have been published that corrupt heap management information and allow arbitrary code execution with the privileges of the victim process.This paper presents a technique that protects the heap management information and allows for run-time detection of heap-based overflows. We discuss the structure of these attacks and our proposed detection scheme that has been implemented as a patch to the GNU Lib C. We report the results of our experiments, which demonstrate the detection effectiveness and performance impact of our approach. In addition, we discuss different mechanisms to deploy the memory protection.
Grid as a bioinformatic tool
Authors: N. Jacq, C. Blanchet, C. Combet, E. Cornillot, L. Duret, K. Kurata, H. Nakamura, T. Silvestre, V. Breton
Venue: Parallel Computing (2004)

The grid is a promising tool to resolve the crucial issue of software and data integration in biology. In this paper, we have reported on our experience in the deployment of bioinformatic grid applications within the framework of the DataGrid project. These applications inquired the potential impact of grids for CPU demanding algorithms and bioinformatics web portals and for the update and distribution of biological databases.Grid computing tests showed how resources sharing improves the current practice of bioinformatics. Reached performance demonstrated the interest of the grid tool.
BBN: description of the PLUM system as used for MUC-5
Authors: Ralph Weischedel, Damaris Ayuso, Sean Boisen, Heidi Fox, Robert Ingria, Tomoyoshi Matsukawa, Constantine Papageorgiou, Dawn MacLaughlin, Masaichiro Kitagawa, Tsutomu Sakai, June Abe, Hiroto Hosihi, Yoichi Miyamoto, Scott Miller
Venue: Proceedings of the 5th conference on Message understanding (1993)

Traditional approaches to the problem of extracting data from texts have emphasized hand-crafted linguistic knowledge. In contrast, BBN's PLUM system (Probabilistic Language Understanding Model) was developed as part of an ARPA-funded research effort on integrating probabilistic language models with more traditional linguistic techniques. Our research and development goals are:&bull; more rapid development of new applications,&bull; the ability to train (and re-train) systems based on user markings of correct and incorrect output,&bull; more accurate selection among interpretations when more than one is found, and&bull; more robust partial interpretation when no complete interpretation can be found.
Object-centered representation and reasoning: an application to computer-aided design
Authors: Mihai Barbuceanu
Venue: Issue 87 (January 1984) (1984)

This paper presents an investigation in object-centered representation and problem-solving, carried out in the area of CAD. The goal is the creation of a framework for building expert systems for CAD applications.The facilities, this framework is composed of, are based on an object-centered representation language. Around this language, two main reasoning activities have been introduced. The first, implements a style of problem-solving by instantiation which develops an instantiation concept comprising of a variety of cognitive activities and which demonstrates high versatility through its applications to project network building, constraint directed reasoning, and simulation. The second, by means of object-centered modeling of rule representations, easily integrates forward and backward reasoning in a facility used as a powerful tool for understanding and modifying design.A number of important capabilities covering essential aspects of the design process are shown to derive naturally from the cooperative use of the above mentioned reasoning activities.
Discovering unexpected information for technology watch
Authors: François Jacquenet, Christine Largeron
Venue: Proceedings of the 8th European Conference on Principles and Practice of Knowledge Discovery in Databases (2004)

The purpose of technology watch is to gather, process and integrate the scientific and technical information that is useful to economic players. In this article, we propose to use text mining techniques to automate processing of data found in scientific text databases. The watch activity introduces an unusual difficulty compared with conventional areas of application for text mining techniques since, instead of searching for frequent knowledge hidden in the texts, the target is unexpected knowledge. As a result, the usual measures used for knowledge discovery have to be revised. For that purpose, we have developed the UnexpectedMiner system using new measures for to estimate the unexpectedness of a document. Our system is evaluated using a base that contains articles relating to the field of machine learning.
Cross-domain service change notification via trader federation
Authors: Banjong Huongrat, Twittie Senivongse
Venue: Proceedings of the 2004 international symposium on Information and communication technologies (2004)

The nature of distribution and autonomy in an open environment makes it difficult to maintain a consistent view of service provision among distributed groups of clients. In the case that services are changed, their clients should be informed properly in order to reduce unexpected outcome of using the changed services. This paper presents an extension to our previous CORBA-based change notification system that can notify service changes of several kinds to subscribing clients in a single trader domain. Now the notification is extended for remote clients in a trader federation, meaning that clients who obtain remote services via federated traders can now be informed of remote service changes. The concept of service contracts in RM-ODP traders is adopted since the contract can be seen as a subscription of the importing trader to be notified of changes in those remote services listed in the contract.
Automatic Feature Extraction for Classifying Audio Data
Authors: Ingo Mierswa, Katharina Morik
Venue: Machine Learning (2005)

Today, many private households as well as broadcasting or film companies own large collections of digital music plays. These are time series that differ from, e.g., weather reports or stocks market data. The task is normally that of classification, not prediction of the next value or recognizing a shape or motif. New methods for extracting features that allow to classify audio data have been developed. However, the development of appropriate feature extraction methods is a tedious effort, particularly because every new classification task requires tailoring the feature set anew.This paper presents a unifying framework for feature extraction from value series. Operators of this framework can be combined to feature extraction methods automatically, using a genetic programming approach. The construction of features is guided by the performance of the learning classifier which uses the features. Our approach to automatic feature extraction requires a balance between the completeness of the methods on one side and the tractability of searching for appropriate methods on the other side. In this paper, some theoretical considerations illustrate the trade-off. After the feature extraction, a second process learns a classifier from the transformed data. The practical use of the methods is shown by two types of experiments: classification of genres and classification according to user preferences.
Eventual practical stability of impulsive differential equations with time delay in terms of two measurements
Authors: Yu Zhang, Jitao Sun
Venue: Journal of Computational and Applied Mathematics (2005)

In this paper we introduce a new stability--eventual practical stability for impulsive differential equations with time delay. By using Lyapunov functions and comparison principle, we will get some criteria of eventual practical stability, eventual practical quasistability and strong eventual practical stability for impulsive differential equations with time delay in terms of two measurements.
Cerebral Vascular Atlas Generation for Anatomical Knowledge Modeling and Segmentation Purpose
Authors: N. Passat, C. Ronse, J. Baruthio, J.-P. Armspach, C. Maillot
Venue: Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Volume 2 - Volume 02 (2005)

Magnetic resonance angiography (MRA) is currently used for cerebral flowing blood visualization. Many segmentation-methods have been proposed for brain vessel segmentation, in order to help analyzing the huge data (generally more than 10¿ voxels) provided by MRA acquisitions. Recently, a new family of segmentation algorithms, involving high level anatomical knowledge, has been studied. These new algorithms require a way to model and store this knowledge. An efficient and general approach to reach that goal consists in using atlases. In this paper a method is proposed to create vascular atlases of the brain, containing information useful for vessel segmentation purpose. This atlas creation process, designed for phase-contrast MRA (PC-MRA), is composed of four steps: segmentation, quantification, registration and data fusion. It uses a region-growing algorithm for vessel segmentation, a skeleton and vessel size determination algorithm, based on discrete geometry, for determination of quantitative properties, and a topology preserving non-rigid registration method to fuse the information. This method, which has been applied to a 18 PC-MRA database, enables to create vascular atlases containing information on brain vessels position, density, size and orientation. The generated atlases are essentially devoted to segmentation purpose but can also be used for anatomical description or pathology detection.
Learning Appearance Manifolds from Video
Authors: Ali Rahimi, Ben Recht, Trevor Darrell
Venue: Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Volume 1 - Volume 01 (2005)

The appearance of dynamic scenes is often largely governed by a latent low-dimensional dynamic process. We show how to learn a mapping from video frames to this low-dimensional representation by exploiting the temporal coherence between frames and supervision from a user. This function maps the frames of the video to a low-dimensional sequence that evolves according to Markovian dynamics. This ensures that the recovered low-dimensional sequence represents a physically meaningful process. We relate our algorithm to manifold learning, semi-supervised learning, and system identification, and demonstrate it on the tasks of tracking 3D rigid objects, deformable bodies, and articulated bodies. We also show how to use the inverse of this mapping to manipulate video.
Apply Incremental Classification for a P2P MOD System
Authors: Tien-Chin Wang, Tsung-Han Chang, Tsung-Hung Chen, Peter Wang
Venue: Proceedings of the 19th International Conference on Advanced Information Networking and Applications - Volume 2 (2005)

With the fast development of technology and science, there come various changes and demands in consumer service market. The plan integrating "Broadband Network" with "Application Service" is potential and farsighted in network industry. Academic and technological institutes start researching and promoting the MOD (multimedia on demand) system, which transits multimedia information and provides users interactive interface via setop-box in broadband network. Implement cost, learning content and user behaviors might be taken into account when constructing MOD system. Besides, how to increase the MODýs capability of interaction and portability is a practical issue. Sharing and participating are of great importance for network users. This paper first proposes a digital content platform, which combines peer-to-peer (P2P) technology and sharable content object reference model (SCORM). Such a mechanism makes it possible for content providers to share versatile multimedia information with others in digital channel. Followed by a description of file sharing methods in P2P framework. Then we advocate incremental k-Nearest-Neighbor (k-NN) algorithm analyzing SCORM metadata and user access records to improve system load, content feature classification efficiency, file index distribution and user query-feedback speed.
From linear time to branching time
Authors: Orna Kupferman, Moshe Y. Vardi
Venue: ACM Transactions on Computational Logic (TOCL) (2005)

Model checking is a method for the verification of systems with respect to their specifications. Symbolic model-checking, which enables the verification of large systems, proceeds by calculating fixed-point expressions over the system's set of states. The &mu;-calculus is a branching-time temporal logic with fixed-point operators. As such, it is a convenient logic for symbolic model-checking tools. In particular, the alternation-free fragment of &mu;-calculus has a restricted syntax, making the symbolic evaluation of its formulas computationally easy. Formally, it takes time that is linear in the size of the system. On the other hand, specifiers find the &mu;-calculus inconvenient. In addition, specifiers often prefer to use linear-time formalisms. Such formalisms, however, cannot in general be translated to the alternation-free &mu;-calculus, and their symbolic evaluation involves nesting of fixed-points, resulting in time complexity that is quadratic in the size of the system. In this article, we characterize linear-time properties that can be specified in the alternation-free &mu;-calculus. We show that a linear-time property can be specified in the alternation-free &mu;-calculus iff it can be recognized by a deterministic B&uuml;chi automaton. We study the problem of deciding whether a linear-time property, specified by either an automaton or an LTL formula, can be translated to an alternation-free &mu;-calculus formula, and describe the translation, when possible.
SPHINX: A Fault-Tolerant System for Scheduling in Dynamic Grid Environments
Authors: Jang-uk In, Paul Avery, Richard Cavanaugh, Laukik Chitnis, Mandar Kulkarni, Sanjay Ranka
Venue: Proceedings of the 19th IEEE International Parallel and Distributed Processing Symposium (IPDPS'05) - Papers - Volume 01 (2005)

A grid consists of high-end computational, storage, and network resources that, while known a priori, are dynamic with respect to activity and availability. Efficient scheduling of requests to use grid resources must adapt to this dynamic environment while meeting administrative policies. In this paper, we describe a framework called SPHINX that can administrate grid policies, and schedule complex and data intensive scientific applications. We present experimental results for several scheduling strategies that effectively utilize the monitoring and job-tracking information provided by SPHINX. These results demonstrate that SPHINX can effectively schedule work across a large number of distributed clusters that are owned by multiple units in a virtual organization in a fault-tolerant way in spite of the highly dynamic nature of the grid and complex policy issues. The novelty lies in use of effective monitoring of resources and job execution tracking in making scheduling decisions and fault-tolerance - something that is missed in todayýs grid environments.
Elsewhere
Venue: IEEE Internet Computing (2005)

Review of Internet-related stories in IEEE, Computer Society, and trade press.
Reinforcement Learning Hierarchical Neuro-Fuzzy Politree Model for Control of Autonomous Agents
Authors: Karla Figueiredo, Marley Vellasco, Marco Pacheco, Flavio Souza
Venue: Proceedings of the Fourth International Conference on Hybrid Intelligent Systems (2004)

This work presents a new hybrid neuro-fuzzy model for automatic learning of actions taken by agents. The main objective of this new model is to provide an agent with intelligence, making it capable, by interacting with its environment, to acquire and retain knowledge for reasoning (infer an action). This new model, named Reinforcement Learning Hierarchical Neuro-Fuzzy Politree (RL-HNFP), descends from the Reinforcement Learing Hierarchical Neuro-Fuzzy BSP (RL-HNFB) that uses Binary Space Partitioning. By using hierarchical partitioning methods, together with the Reinforcement Learning (RL) methodology, a new class of Neuro-Fuzzy Systems (SNF) was obtained, which executes, in addition to automatically learning its strucutre, the autonomous learning of the actions to be taken by an agent. These characteristics represent an important differential when compared with the existing intelligent agents learning systems. The obtained results demonstrate the potential of this new model, which operates without any prior information, such as number of rules, rules specification, or number of partitions that the input space should have.