ppxscal/embedding_network huggingface dataset:
Visually Elegant and Robust Semi-Fiducials for Geometric Registration in Mixed Reality
Authors: Ryuhei Tenmoku, Yusuke Yoshida, Fumihisa Shibata, Asako Kimura, Hideyuki Tamura
Venue: Proceedings of the 2007 6th IEEE and ACM International Symposium on Mixed and Augmented Reality (2007)

This paper describes a novel image-based geometric registration method using visually elegant and robust semi-fiducial markers in mixed reality (MR). Most traditional visual markers stand out against the background, i.e., they can be recognized and identified easily. Here, we try to construct new visual markers for MR registration, which achieve a good balance between visual elegance and robustness. As the first step, we propose "two-tone colored markers". These markers have the following characteristics: 1) color similar to that of the background object, 2) placed at the corners of real objects in an inconspicuous manner. This paper describes the registration method using two-tone colored markers and a few experiments.
Entertainment character for information display
Authors: Tetsuya Saito, Kenichi Hirota, Junichi Hoshino
Venue: Proceedings of the 2008 International Conference on Advances in Computer Entertainment Technology (2008)

In games and movies that use characters, utterances are important expressions of action. However, currently, interactive characters have their conversation topics prepared beforehand by the creator. If the topics are few, they repeat the same content with fixed variations, resulting in the user losing interest. In this paper, we propose the concept of entertainment character for emotional information display. We use RSS, which provides live feeds on news and weather forecasts on the Internet, to provide real-world information thereby enriching characters conversation topics. And, we generate various conversations between the user and the characters by adding topics related to the utterances and feelings appropriate to the topic for improving the expressiveness of talk.
A Rule-Based Prefetching Approach for Object-Based Storage Device
Authors: Shuibing He, Dan Feng, Chunhua Li, Yanli Yuan
Venue: International Journal of Distributed Sensor Networks (2009)

Capturing the advantages of NAS and SAN, Object-based Storage System (OBSS) is becoming an active research area. OBSS is composed of clients, metadata server, and Object-based Storage Devices (OSDs). Similar to the prefetching of file and block, object prefetching is also an effective method to reduce the object access latency in OSD. However, the existing methods focus on intra-object prefetching [1] and they limit the prefetching capability among objects to a certain extent. In this paper, we present a novel inter-object prefetching approach which considers the characteristics of the object access in OSD. This approach adopts a kind of data mining technique called sequential pattern mining to find the object access sequential patterns [2], then produces the object sequential rules according to the patterns, and finally prefetches objects according to the rules and the object access context. The whole process includes the following three modules: Object Request Service Module. It maintains a current object access context, which is a l-length recently accessed object sequence. Furthermore, it appends new object information to the historic object access stream when an object is accessed. Sequential Rules Mining Module. It is composed of the object sequences preprocessing, the sequential pattern mining and the sequential rules producing modules. The preprocessing module divides the object access stream into many subsequences. Base on the discovered object sequential patterns gained by the sequential pattern mining module, object access sequential rules table is constructed. Prefetching Engine Module. When the current requested object is not in the object cache, the prefetching engine selects a matched rule with the highest confidence from the rules table according to the context, then chooses the corresponding objects and preloads them into the object cache. Simulated experimental results show that both prediction accuracy and object hit rate can be improved comparing with the Group-based prefetching method [3] which can also be used for object prefetching.
Amplifying community content creation with mixed initiative information extraction
Authors: Raphael Hoffmann, Saleema Amershi, Kayur Patel, Fei Wu, James Fogarty, Daniel S. Weld
Venue: Proceedings of the 27th international conference on Human factors in computing systems (2009)

Although existing work has explored both information extraction and community content creation, most research has focused on them in isolation. In contrast, we see the greatest leverage in the synergistic pairing of these methods as two interlocking feedback cycles. This paper explores the potential synergy promised if these cycles can be made to accelerate each other by exploiting the same edits to advance both community content creation and learning-based information extraction. We examine our proposed synergy in the context of Wikipedia infoboxes and the Kylin information extraction system. After developing and refining a set of interfaces to present the verification of Kylin extractions as a non primary task in the context of Wikipedia articles, we develop an innovative use of Web search advertising services to study people engaged in some other primary task. We demonstrate our proposed synergy by analyzing our deployment from two complementary perspectives: (1) we show we accelerate community content creation by using Kylin's information extraction to significantly increase the likelihood that a person visiting a Wikipedia article as a part of some other primary task will spontaneously choose to help improve the article's infobox, and (2) we show we accelerate information extraction by using contributions collected from people interacting with our designs to significantly improve Kylin's extraction performance.
Fly Out Blue
Authors: Jack (Ming-Huei) Shih
Venue: ACM SIGGRAPH ASIA 2008 computer animation festival (2008)

A man going through his mid-life crisis becomes fascinated with flying and fantasises about a more exciting life for himself.
Exact average coverage probabilities and confidence coefficients of confidence intervals for discrete distributions
Authors: Hsiuying Wang
Venue: Statistics and Computing (2009)

For a confidence interval (L(X),U(X)) of a parameter &theta; in one-parameter discrete distributions, the coverage probability is a variable function of &theta;. The confidence coefficient is the infimum of the coverage probabilities, inf&theta;P&theta;( &theta;&epsilon;(L(X), U(X))). Since we do not know which point in the parameter space the infimum coverage probability occurs at, the exact confidence coefficients are unknown. Beside confidence coefficients, evaluation of a confidence intervals can be based on the average coverage probability. Usually, the exact average probability is also unknown and it was approximated by taking the mean of the coverage probabilities at some randomly chosen points in the parameter space. In this article, methodologies for computing the exact average coverage probabilities as well as the exact confidence coefficients of confidence intervals for one-parameter discrete distributions are proposed. With these methodologies, both exact values can be derived.
Knowledge Management Challenges in Customer Support: A Case Study
Authors: Marko Jäntti, Kirsi Tanskanen, Jukka Kaukola
Venue: Proceedings of the 2009 International Conference on Information, Process, and Knowledge Management (2009)

Knowledge management plays an important role in customer support processes such as incident management and problem management. Knowledge-oriented approach on customer support provides an IT organization with several benefits including faster incident resolution times and better identification of systematic incidents. Unfortunately, little attention has focused on examining challenges in customer support from the knowledge management perspective. In this study, the research question is: what kind of knowledge management challenges can arise in customer support. A case study method was used as a research method. Several knowledge management-related challenges were found, such as challenges in documenting incident resolutions and classifying incidents, a lack of public knowledge base and the missing knowledge flow for urgent incidents.
A greedy location management scheme using predictive dynamic reservation into dynamic set method
Authors: Ahmad Almunayyes
Venue: Proceedings of the 4th Asian Conference on Internet Engineering (2008)

Integration of WLAN hotspots into next generation cellular networks requires considerations on location management, resource allocation, handoff algorithms and their sensitivity to mobility related features such as velocity of the mobile and the handoff delay. This article presents architecture for seamless location-aware integration of WLAN hotspots into cellular networks and provides an analysis for an optimal handoff decision in moving in and out of a hotspot. For a mobile station, it may be beneficial to know the whereabouts of the hotspots in order to facilitate optimal handoff between the two access networks. In an integrated cellular-WLAN environment, one has to consider location management as part of mobility management due to differences in the cell sizes of the two overlapping technologies. In this paper, we present a new handoff and call admission strategy for cellular networks in downtown areas. The new strategy is based on predictive dynamic reservation mechanism for which the location management involves two processes: find the current cell of a mobile node, and, update location information of a mobile node. During the find and update processes, we use two new methods for location management based on replication of location information in a dominating set and in a hierarchical dominating set. Our hierarchical dominating set using the greedy algorithm had the least update cost followed by the hierarchical scheme then the dominating set scheme respectively.
Measuring the Performance and Reliability of Production Computational Grids
Authors: Omid Khalili, Jiahua He, Catherine Olschanowsky, Allan Snavely, Henri Casanova
Venue: Proceedings of the 7th IEEE/ACM International Conference on Grid Computing (2006)

In this work we report on data gathered via a deployment of a monitoring and benchmarking infrastructure on two production grid platforms, TeraGrid and Geon. Our result show that these production grids are rather unavailable, with success rates for benchmark and application runs between 55% and 80%. We also found that performance fluctuation was in the 50% range, expectedly mostly due to batch schedulers. We also investigate whether the execution time of a typical grid application can be predicated based on previous runs of simple benchmarks. Perhaps surprisingly, we find that application execution time can be predicted with a relative error as low as 9%.
A direct adaptive neural command controller design for an unstable helicopter
Authors: M. Vijaya Kumar, S. Suresh, S. N. Omkar, Ranjan Ganguli, Prasad Sampath
Venue: Engineering Applications of Artificial Intelligence (2009)

This paper presents an off-line (finite time interval) and on-line learning direct adaptive neural controller for an unstable helicopter. The neural controller is designed to track pitch rate command signal generated using the reference model. A helicopter having a soft inplane four-bladed hingeless main rotor and a four-bladed tail rotor with conventional mechanical controls is used for the simulation studies. For the simulation study, a linearized helicopter model at different straight and level flight conditions is considered. A neural network with a linear filter architecture trained using backpropagation through time is used to approximate the control law. The controller network parameters are adapted using updated rules Lyapunov synthesis. The off-line trained (for finite time interval) network provides the necessary stability and tracking performance. The on-line learning is used to adapt the network under varying flight conditions. The on-line learning ability is demonstrated through parameter uncertainties. The performance of the proposed direct adaptive neural controller (DANC) is compared with feedback error learning neural controller (FENC).
Specifying computer-based counseling systems in health care: A new approach to user-interface and interaction design
Authors: Dominikus Herzberg, Nicola Marsden, Peter Kübler, Corinna Leonhardt, Sabine Thomanek, Hartmut Jung, Annette Becker
Venue: Journal of Biomedical Informatics (2009)

Computer-based counseling systems in health care play an important role in the toolset available for medical doctors to inform, motivate and challenge their patients according to a well-defined therapeutic goal. The design, development and implementation of such systems require close collaboration between users, i.e. patients, and developers. While this is true of any software development process, it can be particularly challenging in the health counseling field, where there are multiple specialties and extremely heterogeneous user groups. In order to facilitate a structured design approach for counseling systems in health care, we developed (a) an iterative three-staged specification process, which enables early involvement of potential users in the development process, and (b) a specification language, which enables an author to consistently describe and define user interfaces and interaction designs in a stepwise manner. Due to the formal nature of our specifications, our implementation has some unique features, like early execution of prototypes, automated system generation and verification capabilities.
Decision-analytic models for breast cancer: do currently published models meet the requirements of personalized medicine?
Authors: Beate Jahn, Nikolai Mühlberger, Johannes Wurm, Uwe Siebert
Venue: Proceedings of the 40th Conference on Winter Simulation (2008)

Objective: To give an insight into the structure and methodology of simulation approaches used for evaluating interventions in breast-cancer. Research increasingly focuses on personalized strategies in medicine. Therefore, conventional clinical studies, genomic and proteomic (--omics) and biomarker studies need to be translated into patient-tailored prediction rules and treatment decisions. Recommendations for future comprehensive breast-cancer simulation are derived based on published simulations and requirements arising from personalized medicine, Methods: A systematic literature review is performed and information on study design, simulation framework etc. are extracted. Strengths and limitations are assesed. Results: The review shows how currently available models encompass the underlying biologic disease progression, treatment effects including complications and economic outcomes. We expect that these models are limited with respect to information from --omics and biomarker studies. Discrete-event-simulation and agent-based simulation approaches are discussed. Conclusions: This work provides an essential basis for further simulation approaches to evaluate personalized breast-cancer treatment.
An Efficient and Robust Decentralized Algorithm for Detecting the Global Convergence in Asynchronous Iterative Algorithms
Authors: Jacques M. Bahi, Sylvain Contassot-Vivier, Raphaël Couturier
Venue: High Performance Computing for Computational Science - VECPAR 2008: 8th International Conference, Toulouse, France, June 24-27, 2008. Revised Selected Papers (2008)

In this paper we present a practical, efficient and robust algorithm for detecting the global convergence in any asynchronous iterative process. A proven theoretical version, together with a first practical version, was presented in [1]. However, the main drawback of that first practical version was to require the determination of the maximal communication time between any couple of nodes in the system during the entire iterative process. The version presented in this paper does not require any additional information on the parallel system while always ensuring correct detections.
The Generalized Stable Allocation Problem
Authors: Brian C. Dean, Namrata Swar
Venue: Proceedings of the 3rd International Workshop on Algorithms and Computation (2009)

We introduce and study the generalized stable allocation problem, an "ordinal" variant of the well-studied generalized assignment problem in which we seek a fractional assignment that is stable (in the same sense as in the classical stable marriage problem) with respect to a two-sided set of ranked preference lists. We develop an O(m logn) algorithm for solving this problem in a bipartite assignment graph with n nodes and m edges. When edge costs are present, we show that it is NP-hard to compute a stable assignment of minimum cost, a result that stands in stark contrast with most other stable matching problems (e.g., the stable marriage and stable allocation problems) for which we can efficiently optimize over the set of all stable assignments.
A complete proof on the solution procedure for non-instantaneous deteriorating items with permissible delay in payment
Authors: Kun-Jen Chung
Venue: Computers and Industrial Engineering (2009)

Ouyang et al. [Ouyang, L. Y., Wu, K. S., & Yang C. T. (2006). A study on an inventory model for non-instantaneous deteriorating items with permissible delay in payments. Computers &Industrial Engineering, 51, 637-651] present an inventory model for non-instantaneous deteriorating items with permissible delay in payments. They develop some theorems to characterize the optimal solutions and provide an easy-to-use method to find the optimal replenishment cycle time. Although, their inventory models are correct and interesting, processes of arguments to derive those theorems and the easy-to-use method to search for the optimal replenishment cycle time are not complete. So, the main purpose of this paper is to overcome those shortcomings and present complete proofs for Ouyang et al. (2006).
An O(n log n) algorithm for maximum st-flow in a directed planar graph
Authors: Glencora Borradaile, Philip Klein
Venue: Journal of the ACM (JACM) (2009)

We give the first correct O(n log n) algorithm for finding a maximum st-flow in a directed planar graph. After a preprocessing step that consists in finding single-source shortest-path distances in the dual, the algorithm consists of repeatedly saturating the leftmost residual s-to-t path.
Design methods for pipeline & delta-sigma A-to-D converters with convex optimization
Authors: Kazuo Matsukawa, Takashi Morie, Yusuke Tokunaga, Shiro Sakiyama, Yosuke Mitani, Masao Takayama, Takuji Miki, Akinori Matsumoto, Koji Obata, Shiro Dosho
Venue: Proceedings of the 2009 Asia and South Pacific Design Automation Conference (2009)

In system LSIs, costs of analog circuits are getting increased relatively for rapid cost reduction of digital circuits. To satisfy given specifications in the analog design, including low power and small area, designers have to select an optimal solution among large combination of the following alternatives: which architecture should be adopted; what type of transistors should be taken; and whether digitally assisting technologies should be used or not, etc. A design based on experience and intuition cannot lead to the optimum in a short time. A comprehensive approach to the optimization, based on circuit theory, is now required. Convex optimization procedure can solve the formulae which represent circuit performance with over hundreds of design variables. We have constructed optimization environments for pipelined and delta-sigma analog-to-digital converters (ADCs) in consideration of the digitally assisting techniques and layout constraints. Both 12-bit pipelined ADCs and a 5th-order delta-sigma modulator were designed with the optimizer, and achieved top-ranked power efficiency.
DIALOG: a distributed processor organization for database machine
Authors: Benjamin W. Wah, S. Bing Yao
Venue: Proceedings of the May 19-22, 1980, national computer conference (1980)

The conventional physical storage mechanism of a computer system is usually comprised of a memory hierarchy that stores program and data. The requirement for high performance and low cost is achieved through a combination of memories of different speeds. By automatically managing the files so that the most frequently used files reside in fast storage, an overall speed comparable to the speed of the fastest memory can be achieved. However, with the applications of large databases, the maintenance of large files on a conventional memory hierarchy becomes increasingly difficult. Most database applications perform a small number of simple operations on a large amount of data. Usually only a small fraction of the data accessed is required by the application. It is more cost effective to perform database operations directly on the data in the secondary storage in order to avoid the transfer of unnecessary data across different levels of the memory hierarchy. The Database Machine (DBM) is the result of an architectural approach which distributes processing power closer to the devices on which data are stored and offloads database processing functions from the main computer [LAN79].
A Semantic QoS-Based Web Service Discovery Engine for Over-Constrained QoS Demands
Authors: Kyriakos Kritikos, Dimitris Plexousakis
Venue: Service-Oriented Computing - ICSOC 2007 Workshops: ICSOC 2007, International Workshops, Vienna, Austria, September 17, 2007, Revised Selected Papers (2009)

The success of the Web Service (WS) paradigm has led to a proliferation of available WSs. Semantic discovery mechanisms have been invented to overcome UDDI's syntactic discovery solution by providing more precise results. However, the problem remains as many functionally-equivalent WSs are returned. Its solution comes in terms of semantic QoS-based description and discovery of WSs. We have already presented a rich and extensible ontology language for QoS-based WS description that is called OWL-Q and we have proposed a semantic QoS metric matching algorithm. Based on this algorithm, we have extended a Constraint-Programming-based approach for QoS-based WS discovery. In this paper, we show an extension of OWL-Q with SWRL rules and propose a modification to the metric matching algorithm to make it more feasible. Moreover, we propose and analyze an automated approach for semantic QoS-based WS discovery that provides solutions even for over-constrained QoS-based WS demands.
Clustering dynamic PET images on the Gaussian distributed sinogram domain
Authors: Mustafa E. Kamasak
Venue: Computer Methods and Programs in Biomedicine (2009)

Segmentation of dynamic PET images is an important preprocessing step for kinetic parameter estimation. The time activity curve (TAC) of individual pixels has very low signal-to-noise ratio (SNR). Therefore, the kinetic parameters estimated from the TAC of an individual pixel may not be accurate, and these estimations may have very high spatial variance. To alleviate this problem, pixels with similar kinetic characteristics are clustered into regions, and TACs of pixels within each region are averaged to increase SNR. It has recently been shown that clustering dynamic PET images in the sinogram domain is better than clustering them in the reconstructed image domain [M.E. Kamasak, B. Bayraktar, Clustering dynamic PET images on the projection domain, IEEE Trans. Nucl. Sci. 54 (3) (June 2007) 496-503.]. In that study, the sinograms are assumed to have Poisson distribution. The clusters and TACs of the clusters are then chosen to maximize the posterior probability of the measured sinograms. Although the raw sinogram data are Poisson distributed, the sinogram data corrected for scatter, randoms, attenuation etc. are not Poisson distributed anymore. In this paper, we describe how to cluster dynamic PET images on the sinogram domain when the sinograms are Gaussian distributed.