ppxscal/embedding_network huggingface dataset:
Statistical signal processing in broadband reflectometry
Authors: F. D. Nunes, J. M. N. Leitao
Venue: Proceedings of the Acoustics, Speech, and Signal Processing,1994. on IEEE International Conference - Volume 04 (1994)

Microwave broadband reflectometry is used to determine the spatial distribution of plasma density (density profile) in experimental nuclear fusion devices. The position of each plasma reflecting layer is evaluated by Abel integration of the phase rate of the reflectometric signal that results from mixing the plasma incident and reflected waves. The signal processing problem is cast in the stochastic nonlinear filtering framework. The phase/frequency corresponding to the reflecting layer dynamics is modeled as a two-dimensional Markovian process, from which only one component (phase) is observed. Guided by these (noisy) observations a suboptimal filter propagates the joint (phase/frequency) a posteriori probability density function, allowing to estimate the phase rate. The purpose is to develop a robust and versatile tool to process reflectometric data.
Whole-program compilation in MLton
Authors: Stephen Weeks
Venue: Proceedings of the 2006 workshop on ML (2006)

MLton is a stable, robust, widely ported, Standard ML (SML) compiler that generates efficient executables. Whole-program compilation is the key to MLton's success, significantly improving both correctness and efficiency. Whole-program compilation makes possible a number of optimizations that reduce or eliminate the cost of SML's powerful abstraction mechanisms, such as parametric modules, polymorphism, and higher-order functions. It also allows MLton to use a simply-typed, first-order, intermediate language. By structuring the bulk of MLton's optimizer as small passes on whole programs in this simple intermediate language, it is easy to implement and debug new optimizations. This intermediate language uses a variant of standard control-flow graphs and static single assignment form, which makes it easy to implement traditional local optimizations as well. Having the whole program also enables standard data representations such as unboxed integers and arrays, as well as efficient representations for user-defined data structures.This talk will describe MLton's approach to whole-program compilation, covering the optimizations and the intermediate languages, as well as some of the engineering challenges that were overcome to make it feasible to use MLton on programs with over one hundred thousand lines. It will also cover the history of the MLton project from its inception in 1997 until now, and give some lessons learned and thoughts on the future of MLton.
Scalability of closed-loop video delivery service
Authors: Wei Shu, Min-You Wu
Venue: Proceedings of the 2003 International Conference on Multimedia and Expo - Volume 1 (2003)

Scalability is a key issue of on-line video service. Different methods have been proposed for the closed-loop video service, such as batching and patching. However, scalability itself has not been formally defined and the condition for a scalable system is not well studied yet. This paper studies scalability and the condition for scalable systems. It is found that when the arrival rate is across the threshold /spl Theta/ the system becomes scalable. This threshold value depends only on the number of videos, video length, and request distribution. We present an analysis for batching and patching. Comparison of batching, patching, and a new method, scheduled video delivery (SVD), is presented in this paper.
Analyzing Effects of Intra-Uterine Cocaine Exposure on Adolescent Brain Structure with Symmetric Diffeomorphisms
Authors: Brian B. Avants, H. Hurt, J. Giannetta, C. L. Epstein, D. Shera, J. Wang, J. C. Gee
Venue: Proceedings of the 2006 Conference on Computer Vision and Pattern Recognition Workshop (2006)

Cocaine exposure (CE) nzug conzpronzise the developing brain through disruption of neural ontogeny in dopaminergic systems, erects seconda? to fetal hypoxenzia, and, perhaps, via altered cei-ebro\iascular I-eactivity. Although studies in adult cocaine addicts show decreases in gi-ay nzattel; white inattel; and fiinctional connectivity there are few investigations to date regarding intra-uterine cocaine exposure (IUCE) in young subjects. The existing literature suggests that long term CE coitsequeitces irt adolescents nzap be subtle 01- nzasked by other variables. Tlzei-efore, sensitive nzethods of analysis are needed. Here, we describe our most recent methods for deriving an optiinal pediatric atlas froin the 49 subject IUCE population invoh>edi n this study. Our nzetlzod, synznzetric nornzalization (SyN), is entirely syimnetric, in that both the pair wise registmtion and gi-oup wise I-egistmtion methods do not depend on the ordering of the input data. The method eliminates atlas selection by deriving an optiinal shape and intensity atlas fi'oin the data. PreliininaFy results using SyN indicate signijcant size dvfei- ewes in caudate rtuclei arid the spleniunz of the c o p i s callosunz, suggesting CE-i-elated detrinzent to the dopanzinergic and visiial systems. Fiirthernzore, we have found that, in conzparison, statistical parametric mapping (SPM) does not pi-oduce sigrti$cartt I-esults.
A Content Modeling Approach as Basis for the Support of the Overall Content Creation Process
Authors: Lasse Lehmann, Abdelhak Aqqal, Christoph Rensing, Pavlina Chikova, Katrina Leyking, Ralf Steinmetz
Venue: Proceedings of the Sixth IEEE International Conference on Advanced Learning Technologies (2006)

The conception and production of new e-learning content in a corporate environment is expensive and time-consuming. In this paper we propose a content modeling approach as part of an authoring management platform. This platform aims to make the cooperative process of conception and production of elearning content faster, easier to manage and equips knowledge domain experts with a tool, which does not demand for media and didactic experience.
Space efficient algorithms for directed series-parallel graphs
Authors: Andreas Jakoby, Maciej Liśkiewicz, Rüdiger Reischuk
Venue: Journal of Algorithms (2006)

The subclass of directed series-parallel graphs plays an important role in computer science. Whether a given graph is series-parallel is a well studied problem in algorithmic graph theory, for which fast sequential and parallel algorithms have been developed in a sequence of papers. Also methods are known to solve the reachability and the decomposition problem for series-parallel graphs time efficiently. However, no dedicated results have been obtained for the space complexity of these problems when restricted to series-parallel graphs - the topic of this paper.Deterministic algorithms are presented for the recognition, reachability, decomposition and the path counting problem for series-parallel graphs that use only logarithmic space. Since for arbitrary directed graphs reachability and path counting are believed not to be solvable in Logspace, the main contribution of this work are novel deterministic path finding routines that work correctly in series-parallel graphs, and a characterization of series-parallel graphs by forbidden subgraphs that can be tested space-efficiently. The space bounds are best possible, i.e. the decision problem is shown to be L-complete with respect to AC0-reductions. They have also implications for the parallel time complexity of these problems when restricted to series-parallel graphs.Finally we sketch how these results can be generalized to extension of the series-parallel graph family: to graph with multiple sources or multiple sinks and to the minimal vertex series-parallel graphs.
Annotating Image Regions Using Spatial Context
Authors: Zhiyong Wang, David D. Feng, Zheru Chi, Tian Xia
Venue: Proceedings of the Eighth IEEE International Symposium on Multimedia (2006)

Image annotation plays an important role in bridging the semantic gap between low level features and high level semantic contents in image access. In this paper, such a task is tackled by annotating regions which are primitives of a visual scene. We propose a probabilistic model to characterize spatial context for region annotation. Such a model provides a unifying framework integrating both feature distribution models and spatial context models. A wide range of advanced modeling techniques can be utilized to further extend this framework. The approach is also potentially scalable to a large number of semantic concepts and a large number of images. Experimental results based on simple parametric models demonstrate promising results of our approach by investigating the impacts of neighbors, segmentation, and visual features.
A multicast packet forwarding mechanism for WCDMA networks using routing lists
Authors: Antonios Alexiou, Dimitrios Antonellis, Christos Bouras
Venue: Proceedings of the 2nd ACM international workshop on Wireless multimedia networking and performance modeling (2006)

This paper proposes a multicast scheme for the packet forwarding mechanism in the Universal Mobile Telecommunications System (UMTS). The scheme relies on the introduction of the Permanent Multicast Routing List (PMRL) and Temporary Multicast Routing List (TMRL) in each node of the network except UEs. In the PMRL we record the nodes of the next level that the messages for every multicast group should be forwarded. The TMRL is useful for the temporary record of information from the path from the mobile users to the GGSN. Additionally, a Multicast Group List (MGL) is kept in the GGSN which records the members of each multicast group. These lists lead to the decrement of the transmitted packets and the more efficient use of the network resources in the multicast routing in UMTS. We analyze the exact steps that the multicast packets are transmitted to the members of each multicast group. Furthermore, special issues such as joining/leaving a multicast service are described
Homology assessment and molecular sequence alignment
Authors: Aloysius J. Phillips
Venue: Journal of Biomedical Informatics (2006)

Hypotheses of homology are the basis of phylogenetic analysis. All character data are considered to be equivalent regardless of the source of those characters. Putative homology statements are designated based on observations of similarity. Pairwise sequence alignment using the Needleman Wunsch algorithm is the basis for similarity maximization between molecular sequences. Multiple sequence alignment uses this algorithm in a topologically hierarchical framework. The resulting hypotheses of homology are tested in conjunction with character congruence through parsimony. This review introduces some underlying principles of phylogenetic analysis as they pertain homology testing and DNA sequence alignment.
Modelling the Environment of a Mobile Robot with the Embedded Flow State Machine
Authors: Branko Šter, Andrej Dobnikar
Venue: Journal of Intelligent and Robotic Systems (2006)

A type of topological approach to mobile robot navigation is discussed and experimentally evaluated. The environment as experienced by a moving robot is treated as a dynamical system. Simple types of reactive behavior are supplemented with eventual decisions to switch between them. When switching criteria are defined, the system may be described in the form similar to a finite state machine. Since it is embedded in the environment and dependent on the sensory flow of the robot, we introduce the term "Embedded flow state machine" (EFSM). We implemented it with a recurrent neural network, trained on a sequence of sensory contents and actions. One of the main virtues of this approach is that no explicit localization is required, since the recurrent neural network holds the state implicitly. The EFSM is applicable to multi-step prediction of sensory information and the travelled distances between decision points, given a sequence of decisions at decision points. Thus, the optimal path to a specified goal can be sought. One of the main issues is, for how many steps ahead the prediction is reliable enough. In other words, is it feasible to perform environment modelling and path planning in this manner? The approach is tested on a miniature mobile robot, equipped with proximity sensors and a color video camera. Decision `points,' where deviations from the wall-following behavior are allowed, are based on color object recognition. In the case of an experimental environment of medium complexity, this approach was successful.
Business Services as a New Operational Model for Enterprises and Ecosystems
Authors: J. L. C. Sanz, N. Nayak, V. Becker
Venue: Proceedings of the The 8th IEEE International Conference on E-Commerce Technology and The 3rd IEEE International Conference on Enterprise Computing, E-Commerce, and E-Services (2006)

Enterprises continue to face the challenge of cost effective operations and thus, standardization and openness are becoming an imperative for operational efficiencies at a much higher business level than information systems and related IT infrastructure. Business processes have governed enterprise operational modeling for several decades and have provided the basis for many business transformation approaches. Business processes have thus become an early form of standardization and their continuous maturity has given rise to a very important outsourcing market that has helped companies produce substantial savings [1]. However, there is a clear need for new ways of modeling enterprise operations that exploit deeper levels of industry-specific commonalities across companies, thus realizing further economies of scale while yielding more savings and enhanced resilience. This paper introduces the concept of Business Service-based modeling of companies and related ecosystems as an innovative approach for attaining these goals. The concept of "services" is not new. Service Oriented Architectures (SOA), related web services and other service standardization efforts are well-known today. However, the focus of existing service models is primarily integration of IT systems based on interoperability. These models, which are targeted towards solution implementers, do not adequately address the needs of higher level, business-oriented modeling within the context of a service-oriented operation and corresponding service-oriented ecosystems.
Secure performance enhancing proxy: to ensure end-to-end security and enhance TCP performance over IPv6 wireless networks
Authors: Venkatesh Obanaik, Lillykutty Jacob, A. L. Ananda
Venue: Computer Networks: The International Journal of Computer and Telecommunications Networking (2006)

It is a well known fact that TCP is incapacitated to distinguish congestion losses in the wired network from corruption losses occurring in the wireless link and this inability results in poor performance of TCP in a hybrid wired-cum-wireless scenario. Most of the solutions previously proposed to address this problem are designed oblivious of the security considerations and violate end-to-end TCP semantics. Achieving improved TCP performance together with ensuring end-to-end security necessitates the co-existence of security mechanisms like IPSEC and performance enhancing solutions. However, IP security and TCP performance have been traditionally dealt with in a mutually exclusive manner. We propose an innovative mechanism, Secure Performance Enhancing Proxy (SPEP), to address the seemingly arduous problem of enhancing TCP performance over wireless networks, preserving end-to-end TCP semantics as well as ensuring end-to-end security. The proposed SPEP scheme decouples error detection and error distinction mechanism from error recovery mechanism which not only facilitates in performance improvement but also offers multifarious advantages discussed in the paper. We have implemented the proposed scheme in FreeBSD 4.5 and conducted experiments in a controlled test bed setup. Our results show improved TCP performance in a secured environment with introduction of minimal overhead.
Evaluating bidding strategies for simultaneous auctions
Authors: Teddy Candale, Sandip Sen
Venue: Proceedings of the fifth international joint conference on Autonomous agents and multiagent systems (2006)

Bidding for multiple items or bundles on online auctions raises challenging problems. We assume that an agent has a valuation function that returns its valuation for an arbitrary bundle. In the real world all or most of the items of interest to an agent is not present in a single combinatorial auction. We study the problem of bidding for multiple items in a set of simultaneous auctions, each of which sell only a single unit of a particular item. Hence an agent has to bid in multiple auctions to obtain preferred item bundles. While an optimal bidding strategy is known when bidding in sequential auctions, only suboptimal strategies are available when bidding for items sold in auctions running simultaneously. To decide on an agent's bid for simultaneous auctions, we investigate a multi-dimensional bid improvement strategy, which is optimal given an infinite number of restarts. We provide a comparison of this algorithm with existing ones, both in terms of utilities generated and computation time, along with a discussion of the strengths and weaknesses of these strategies.
The transfusion medicine tutor: the use of expert-systems technology to teach students and provide support to practitioners in antibody identification
Authors: Jodi Heintz Obradovich, Stephanie Guerlain, Philip J. Smith, Jack W. Smith,  Jr., Sally Rudmann, Larry Sachs, John Svirbley, Melanie Kennedy, Patricia L. Strohm
Venue: Proceedings of the 1996 international conference on Learning sciences (1996)

The studies presented here provide data regarding the effectiveness of the expert-system-based Transfusion Medicine Tutor (TMT) when used by medical technology students and medical technologists in performing an important problem-solving task, the identification alloantibodies in a patient's blood for the purpose of finding compatible blood for transfusion. TMT monitors for slips and mistakes during the evaluation of patient cases, and provides suggestions to the student or technologist when a potential concern is detected. Use of that system was found to reduce errors in final answers on various multiple antibody cases by 30%-62% by practicing medical technologists. Similarly, use of a modified version of the system for teaching was found to enhance learning by 87--93%.
Category-Specific Representations of Social and Nonsocial Knowledge in the Human Prefrontal Cortex
Authors: J. N. Wood, S. G. Romero, M. Makale, J. Grafman
Venue: Journal of Cognitive Neuroscience (2003)

Complex social behavior and the relatively large size of the prefrontal cortex are arguably two of the characteristics that distinguish humans from other animals. Grafman presented a framework concerning how the prefrontal cortex (PFC) controls complex behavior using stored structured event complexes (SECs). We report behavioral and imaging data from a modified go/no-go paradigm in which subjects had to classify words (semantic) and phrases (SEC) according to category. In experimental trials, subjects classified items according to social or nonsocial activity; in control trials, they classified items according to font. Subjects were faster to classify social than nonsocial semantic items, with the reverse pattern evident for the social and nonsocial SEC items. In addition, the conditions were associated with different patterns of PFC activation. These results suggest that there are different psychological and neural substrates for social and nonsocial semantic and SEC representations.
Toolpath Pattern Comparison: Contour-Parallel with Direction-Parallel
Authors: Tawfik T. EL-Midany, Ahmed Elkeran, Hamdy Tawfik
Venue: Proceedings of the conference on Geometric Modeling and Imaging: New Trends (2006)

During rough cut machining of sculptured parts, appropriate selection of a tool path pattern in each cutting plane can significantly improve productivity. In this paper, various feasible toolpath patterns are investigated. A feedrate machining time model that takes into account CNC machine acceleration and deceleration for automatically identifying the most productive toolpath pattern is developed. This model is then used to compare the total machining time for common five types of toolpath patterns. The compared toolpath patterns are normal zigzag, smooth zigzag, normal spiral, smooth spiral and fishtail spiral. The results show that the optimal toolpath pattern is dependent on part geometry, physical characteristic of used CNC machine tool (accelerator and decelerator, continuous path, look ahead, and etc.) and cutting conditions (tool diameter, feedrate, and etc.). The developed comparing method has been implemented in Visual C++. Many examples are used to illustrate the developed method.
Design and Implementation of NAREGI Problem Solving Environment for Large-Scale Science Grid
Authors: Hiroyuki Kanazawa, Yasuyoshi Itou, Motohiro Yamada, Yutaka Miyahara, Yoshikazu Hayase, Shigeo Kawata, Hitohide Usami
Venue: Proceedings of the Second IEEE International Conference on e-Science and Grid Computing (2006)

NAREGI is a Japanese National Grid Project started in 2003, whose chief aim is to develop a set of Grid middleware to serve as a basis for future e- Science. In this paper, we describe a software tool called NAREGI-PSE (Problem Solving Environment), which aims to supports the scientists' works for scientific computer simulations on widely-distributed heterogeneous grid computing environment. Its core component is implemented as WSRF services based on some grid standards, such as Application Contents Service specification. NAREGI-PSE achieves functions sharing peculiar applications in each research community, which is implemented as Virtual Organization. The shared application program is easily compiled and deployed to grid environment using NAREGI-PSE.
On approximate learning by multi-layered feedforward circuits
Authors: Bhaskar DasGupta, Barbara Hammer
Venue: Theoretical Computer Science (2005)

We deal with the problem of efficient learning of feedforward neural networks. First, we consider the objective to maximize the ratio of correctly classified points compared to the size of the training set. We show that it is NP-hard to approximate the ratio within some constant relative error if architectures with varying input dimension, one hidden layer, and two hidden neurons are considered where the activation function in the hidden layer is the sigmoid function, and the situation of epsilon-separation is assumed, or the activation function is the semilinear function. For single hidden layer threshold networks with varying input dimension and n hidden neurons, approximation within a relative error depending on n is NP-hard even if restricted to situations where the number of examples is limited with respect to n.Afterwards, we consider the objective to minimize the failure ratio in the presence of misclassification errors. We show that it is NP-hard to approximate the failure ratio within any positive constant for a multilayered threshold network with varying input dimension and a fixed number of neurons in the hidden layer if the thresholds of the neurons in the first hidden layer are zero. Furthermore, even obtaining weak approximations is almost NP-hard in the same situation.
Computer Society Connection
Authors: Bob Ward
Venue: Computer (2006)

Topics include results of the 2006 Taulbee Survey, new Computer Society editors in chief, and Computer Society college scholarships.