ppxscal/embedding_network huggingface dataset:
Efficient top-k aggregation of ranked inputs
Authors: Nikos Mamoulis, Man Lung Yiu, Kit Hung Cheng, David W. Cheung
Venue: ACM Transactions on Database Systems (TODS) (2007)

A top-k query combines different rankings of the same set of objects and returns the k objects with the highest combined score according to an aggregate function. We bring to light some key observations, which impose two phases that any top-k algorithm, based on sorted accesses, should go through. Based on them, we propose a new algorithm, which is designed to minimize the number of object accesses, the computational cost, and the memory requirements of top-k search with monotone aggregate functions. We provide an analysis for its cost and show that it is always no worse than the baseline &ldquo;no random accesses&rdquo; algorithm in terms of computations, accesses, and memory required. As a side contribution, we perform a space analysis, which indicates the memory requirements of top-k algorithms that only perform sorted accesses. For the case, where the required space exceeds the available memory, we propose disk-based variants of our algorithm. We propose and optimize a multiway top-k join operator, with certain advantages over evaluation trees of binary top-k join operators. Finally, we define and study the computation of top-k cubes and the implementation of roll-up and drill-down operations in such cubes. Extensive experiments with synthetic and real data show that, compared to previous techniques, our method accesses fewer objects, while being orders of magnitude faster.
A Practical Evaluation of the Nautilus6 Operational Home Agent Service
Authors: Martin Andre
Venue: Proceedings of the International Multi-Conference on Computing in the Global Information Technology (2007)

This paper presents a practical evaluation of the IPv6 mobility service recently opened by the Nautilus6 working group to make the usage of Mobile IPv6 accessible to a wide range of people. The mentioned service also aims at demonstrating by the practice the feasibility of a Mobile IPv6 deployment and thus contributing to the spread of this mobility protocol. The service presented in this paper is structured around three distinct entities: a Home Agent which is the main server for mobility, a web interface to simplify the operations involving the user and a Live CD as an immediate tool to use the service. This paper also introduces the SONAR measurement tool and presents a concrete example of how it can be used to monitor the activity of a Home Agent. Finally this document proposes solutions for a better Mobile IPv6 experience with the latter service, based on the results of an experiment held during a four-day conference.
Bank Customers' Channel Preferences for Requesting Account Balances
Authors: Tommi Laukkanen
Venue: Proceedings of the 40th Annual Hawaii International Conference on System Sciences (2007)

Electronic applications in banking have enhanced customers' ability to control the balances and latest transactions of their bank accounts. Many banks today offer this service also via mobile channel further improving customers' capability to use the service anytime anywhere. This paper analyses online bank customers', namely Internet and mobile users', diverse electronic channel preferences for requesting account balances. Conjoint analysis is used in order to measure the utility these two groups of customers attach to different attributes of electronic channels. The results show that the two groups of customers face different needs in consumption of the service. While mobile users put the greatest attention to flexible service access point, the Internet users value the screen size of a device the most. The results suggest Nokia Communicator type of device as an optimal channel for current mobile users, while those currently without experience in mobile banking show no interest in devices smaller than personal computer.
Power-aware single- and multipath geographic routing in sensor networks
Authors: Shibo Wu, K. Selçuk Candan
Venue: Ad Hoc Networks (2007)

Nodes in a sensor network, operating on power limited batteries, must save power to minimize the need for battery replacement. We note that the range of transmission has a significant effect on the power consumption of both the transmitting node and listeners. This paper first presents a Geographical Power Efficient Routing (GPER) protocol for sensor networks. Each sensor node makes local decisions as to how far to transmit: therefore, the protocol is power efficient, localized, highly distributed, and scalable. In GPER, given a final destination, each node first establishes a subdestination within its maximum radio range. The node, however, may decide to relay the packet to this subdestination through an intermediary node or alter the subdestination if this will preserve power. Traditional deterministic geographic routing algorithms aim at achieving close to the shortest weighted paths. However, they normally stick to the same paths for the same source/destination pairs. This may conversely drain the nodes on these paths and result in short network life when the communication in the network is unevenly distributed. Thus, we further investigate a set of probabilistic multipath routing algorithms, which generate braided multipaths based only on local information. The algorithms have less communication and storage overhead than conventional on-demand multipath routing algorithms, while providing greater resilience to node failures. Simulations on NS2 show that GPER almost halves the power consumption in the network relative to alternative geographic routing algorithms. Furthermore, in situations where the communication tasks are non-uniformly distributed, probabilistic multipath routing contributes up to an additional 30% to network lifetime.
Abrupt shot change detection using an unsupervised clustering of multiple features
Authors: Kai-Kuang Ma
Venue: Proceedings of the Acoustics, Speech, and Signal Processing, 2000. on IEEE International Conference - Volume 04 (2000)

We propose an efficient method to detect abrupt shot changes in a video sequence by using an unsupervised clustering. Most conventional shot change detection algorithms use only one kind of frame-by-frame difference feature such as pixel difference or histogram difference, so they can be applied to only specific situations. Another problem is the determination of appropriate threshold values to check the existence of shot changes. To overcome these problems we use several kinds of features simultaneously and propose a modified k-means clustering algorithm which changes the initial cluster center adaptively. Experimental results show that the proposed algorithm works well.
AGNI: a multi-threaded middleware for distributed scripting
Authors: M. Ranganathan, Marc Bednarek, Fernand Pors, Doug Montgomery
Venue: Proceedings of the 7th conference on USENIX Tcl/Tk - Volume 7 (2000)

We present the design of a AGNI - a Tcl 8.1 based Middleware for building reactive, extensible, reconfigurable distributed systems, based upon an abstraction we call Mobile Streams. Using our system, a distributed, event-driven application can be scripted from a single point of control and dynamically extended and re-configured while it is in execution. Our system is suitable for building a wide variety of applications; for example, distributed test, conferencing and control-oriented applications. We illustrate the use of our system by presenting example applications.
Using Agile Practices to Spark Innovation in a Small to Medium Sized Business
Authors: Ken H. Judy, Ilio Krumins-Beens
Venue: Proceedings of the 40th Annual Hawaii International Conference on System Sciences (2007)

The media industry is challenged to find new lines of business as technology redefines content, distribution and customer expectations. This is a case study of Oxygen Media where a CEO leading an innovation program partnered with her agile software development team. It spans nine months and details how top-down, bottom-up interaction lead to a new consumer software initiative. The strategy described evolved as the sum of small decisions taken over time driven by vision and filtered through Oxygen's corporate culture. At each step, the company's actions were informed by Scrum/XP practices and values. This paper draws support for Oxygen Media's emergent strategy in Nonaka and Takeuchi's five phase model for organizational knowledge creation. This model explains why Oxygen Media has had initial success in its innovation effort. It is also instructive where the model departs from Oxygen Media's strategy and points to challenges yet to be addressed by the company.
Using Neuro-Fuzzy Approach to Reduce False Positive Alerts
Authors: Riyad Alshammari, Sumalee Sonamthiang, Mohsen Teimouri, Denis Riordan
Venue: Proceedings of the Fifth Annual Conference on Communication Networks and Services Research (2007)

One of the major problems of Intrusion Detection Systems (IDS) at the present is the high rate of false alerts that the systems produce. These alerts cause problems to human analysts to repeatedly and intensively analyze the false alerts to initiate appropriate actions. We demonstrate the advantages of using a hybrid neuro-fuzzy approach to reduce the number of false alarms. The neuro-fuzzy approach was experimented with different background knowledge sets in DARPA 1999 network traffic dataset. The approach was evaluated and compared with RIPPER algorithm. The results shows that the neurofuzzy approach significantly reduces the number of false alarms more than the RIPPER algorithm and requires less background knowledge sets.
Designing Linux for wearable and ubiquitous computing
Authors: Thad Starner
Venue: Proceedings of the 3rd annual conference on Atlanta Linux Showcase - Volume 3 (1999)

According to DARPA, we are approaching the production of 8 billion microprocessors a year. Only 2% of these processors are used in devices commonly considered a "computer" by the public, and the most common operating systems address only a fraction of this market. As computers shrink, integrating into the user's clothing or disappearing into the environment, the desktop will be replaced as the dominate software platform for users. However, current desktop operating systems and the prevaling paradigms are ill-prepared for this change as evidenced by the billion dollars invested in pen computing in the early 1990's without a successful product (remedied with the relatively recent release of the Palm Pilot and its "rule-breaking" approach). Linux is a clear contender for the future operating system of choice across a wide range of devices and user interfaces due to its scalability, real-time capabilities, reliability, design, pricing, development cost, and immunity to obsolescence. However, the Linux community must be aware of upcoming computing trends and direct the operating system appropriately. This talk will examine how Linux and other open source projects are being used in the wearable computing community and will discuss the difficult issues foreseen by the wearable and ubiquitous computing communities.
I'll Buy That! Cybersecurity in the Internet Marketplace
Authors: Shari Lawrence Pfleeger, Martin Libicki, Michael Webber
Venue: IEEE Security and Privacy (2007)

Interviews with chief security officers in the Internet supply chain (those companies that provide Internet services or encourage people to use the Internet) reveal dramatically different attitudes about corporate cybersecurity. The authors' preliminary investigation suggests that a company's market discipline explains these differences.
Systematic intermediate sequence removal for reduced memory accesses
Authors: Christophe Poucet, Stylianos Mamagkakis, David Atienza, Francky Catthoor
Venue: Proceedingsof the 10th international workshop on Software compilers for embedded systems (2007)

Modern software applications are growing in complexity and demand very intensive use of data. Therefore, a wide variety of data structures are utilized to facilitate the storage and access to these vast amounts of computed information. Additionally, the need for reliable software design and the development of large applications following the object-oriented paradigm increase the amount of dynamic buffers and redundant accesses to the data stored in these buffers. In this paper, we propose a systematic, design optimization methodology to remove these intermediate dynamic buffers, thereby reducing the memory accesses of the targeted applications without altering the input-output behaviour of the algorithms. The reduction is focused on sequences and is especially relevant for embedded systems, which have limited on-chip communication bandwidth and the energy consumption of the memory subsystem is high, due to the energy consumption associated with each memory access. The effectiveness of the proposed methodology is assessed in a 3D reconstruction multimedia application and shows a significant reduction in memory accesses. In addition, the general trends for memory improvement and the scalability of our approach are supported as well by a parameterized benchmark set.
Promoting depth of knowledge through a new quiz format to improve problem solving abilities
Authors: C. F. Yokomoto
Venue: Proceedings of the 30th Annual Frontiers in Education - Volume 01 (2000)

A novel quiz format is described which is designed to help engineering students improve: (1) problem solving abilities, (2) deep learning, and (3) personal knowledge base. The new quiz format breaks the traditional quiz into two parts, where students are asked to write words that express the limits of their knowledge of the announced quiz topic followed by a short problem solving quiz. The aim of the student is to determine the relationship between the demonstrated knowledge base and the quality of the solution of the quiz problem. An extended aim is to develop a model that describes the relationships between the knowledge base and problem solving success in order to develop training interventions. The ACM Portal is published by the Association for Computing Machinery. Copyright © 2010 ACM, Inc. Terms of Usage Privacy Policy Code of Ethics Contact Us Useful downloads: Adobe Acrobat QuickTime Windows Media Player Real Player
Evaluating healthcare information systems through an "enterprise" perspective
Authors: N. A. D. Connell, T. P. Young
Venue: Information and Management (2007)

Here we reflect upon the design and implementation of large-scale healthcare IS, noting the tendency of such systems to gravitate from a delivery (clinical) to a control (managerial) emphasis. Drawing on the concept of the 'enterprise model', we examined how adopting different perspectives of the enterprise might inform both design and evaluative criteria. Three areas of tension were identified; these prompted us to consider some elements that contribute to a framework that can guide the implementation and evaluation of healthcare applications. We proposed an illustrative conceptual model which, while not claiming to identify causal factors for success or failure, nevertheless gives indications of the interplay between the areas of tension.
Performance analysis of a track before detect dynamic programming algorithm
Authors: L. A. Johnston
Venue: Proceedings of the Acoustics, Speech, and Signal Processing, 2000. on IEEE International Conference - Volume 01 (2000)

"track-before-detect" (TBD) is a target tracking technique where the data is processed over a number of frames before decisions on target existence are made. The aim of this paper is to use extreme value theory to analyse the performance of a dynamic programming based TBD algorithms. Asymptotic expressions are obtained for the false alarm and track detection probabilities using extremal analysis of limiting distributions. Apart from fitting the simulated results far more accurately than previous works in the TBD literature, our analysis does not require the unrealistic assumptions of independence and Gaussianity.
Analysis of ESPRIT based joint angle-frequency estimation
Authors: A. N. Lemma
Venue: Proceedings of the Acoustics, Speech, and Signal Processing, 2000. on IEEE International Conference - Volume 05 (2000)

High-resolution parameter estimation techniques have been applied to jointly estimate multiple signal parameters. We consider the problem of determining the directions and center frequencies of a number of narrow-band sources in a certain frequency band of interest. We present a joint angle-frequency estimation method, based on the multidimensional ESPRIT algorithm. A perturbation error analysis gives bounds on the parameter estimates, and provides optimal values for the temporal and spatial smoothing parameters. The analysis is shown to be consistent with simulation results.
Graphical models for visual object recognition and tracking
Authors: William T. Freeman, Alan S. Willsky
Venue:  (2006)

We develop statistical methods which allow effective visual detection, categorization, and tracking of objects in complex scenes. Such computer vision systems must be robust to wide variations in object appearance; the often small size of training databases, and ambiguities induced by articulated or partially occluded objects. Graphical models provide a powerful framework for encoding the statistical structure of visual scenes, and developing corresponding learning and inference algorithms. In this thesis, we describe several models which integrate graphical representations with nonparametric statistical methods. This approach leads to inference algorithms which tractably recover high-dimensional, continuous object pose variations, and learning procedures which transfer knowledge among related recognition tasks. Motivated by visual tracking problems, we first develop a nonparametric extension of the belief propagation (BP) algorithm. Using Monte Carlo methods, we provide general procedures for recursively updating particle-based approximations of continuous sufficient statistics. Efficient multiscale sampling methods then allow this nonparametric BP algorithm to be flexibly adapted to many different applications. As a particular example, we consider a graphical model describing the hand's three-dimensional (3D) structure, kinematics, and dynamics. This graph encodes global hand pose via the 3D position and orientation of several rigid components, and thus exposes local structure in a high-dimensional articulated model. Applying nonparametric BP, we recover a hand tracking algorithm which is robust to outliers and local visual ambiguities. Via a set of latent occupancy masks, we also extend our approach to consistently infer occlusion events in a distributed fashion. In the second half of this thesis, we develop methods for learning hierarchical models of objects, the parts composing them, and the scenes surrounding them. Our approach couples topic models originally developed for text analysis with spatial transformations, and thus consistently accounts for geometric constraints. By building integrated scene models, we may discover contextual relationships, and better exploit partially labeled training images. We first consider images of isolated objects, and show that sharing parts among object categories improves accuracy when learning from few examples. Turning to multiple object scenes, we propose nonparametric models which use Dirichlet processes to automatically learn the number of parts underlying each object category, and objects composing each scene. Adapting these transformed Dirichlet processes to images taken with a binocular stereo camera, we learn integrated, 3D models of object geometry and appearance. This leads to a Monte Carlo algorithm which automatically infers 3D scene structure from the predictable geometry of known object categories. (Copies available exclusively from MIT Libraries, Rm. 14-0551, Cambridge, MA 02139-4307. Ph. 617-253-5668; Fax 617-253-1690.)
2D factorizable FIR principal component filter banks
Authors: Bo Xuan
Venue: Proceedings of the Acoustics, Speech, and Signal Processing, 1996. on Conference Proceedings., 1996 IEEE International Conference - Volume 03 (1996)

There has been a growing interest in investigating signal-adaptive multirate filter banks. These filter banks are designed to match the statistical properties of input signals. In particular, one type of filter bank, the principal component filter bank (PCFB), minimizes the mean squared error between the input and the associated output when only a limited number of subbands are retained for reconstruction, hence they have the optimal energy compaction property. It has been proven that PCFBs maximize the theoretical coding gain (TCG) of the system. While PCFBs have the most energy compactness and attain the maximum TCG, it is not feasible to implement them in practice since they are IIR with no closed form. This paper deals with FIR filter banks which maximize the TCG.
The Complexity of Proving the Discrete Jordan Curve Theorem
Authors: Phuong Nguyen, Stephen A. Cook
Venue: Proceedings of the 22nd Annual IEEE Symposium on Logic in Computer Science (2007)

The Jordan Curve Theorem (JCT) states that a simple closed curve divides the plane into exactly two connected regions. We formalize and prove the theorem in the context of grid graphs, under different input settings, in theories of bounded arithmetic that correspond to small complexity classes. The theory V^0 (corresponding to AC^0(2)) proves that any set of edges that form disjoint cycles divides the grid into at least two regions. The theory V^0 (corresponding to AC^0) proves that any sequence of edges that form a simple closed curve divides the grid into exactly two regions. As a consequence, the Hex tautologies and the st-Connectivity tautologies have polynomial size AC^0(2)-Frege-proofs, which improves results of Buss which only apply to the stronger proof system TC^0-Frege.
A parametric approach to vocal tract length normalization
Authors: E. Eide, H. Gish
Venue: Proceedings of the Acoustics, Speech, and Signal Processing, 1996. on Conference Proceedings., 1996 IEEE International Conference - Volume 01 (1996)

Differences in vocal tract size among individual speakers contribute to the variability of speech waveforms. The first-order effect of a difference in vocal tract length is a scaling of the frequency axis; a female speaker, for example, exhibits formants roughly 20% higher than the formants of from a male speaker, with the differences most severe in open vocal tract configurations. We describe a parametric method of normalisation which counteracts the effect of varied vocal tract length. The method is shown to be effective across a wide range of recognition systems and paradigms, but is particularly helpful in the case of a small amount of training data.
Incorporating human visual system (HVS) models into the fractal image compression
Authors: H. Lin
Venue: Proceedings of the Acoustics, Speech, and Signal Processing, 1996. on Conference Proceedings., 1996 IEEE International Conference - Volume 04 (1996)

According to the collage theorem, the encoding distortion for fractal image compression is directly related to the metric used in the encoding process. In this paper, we introduce a perceptually meaningful distortion measure based on the human visual system's nonlinear response to luminance and the visual masking effects. Blackwell's (1946) psychophysical raw data on contrast threshold are first interpolated as a function of background luminance and visual angle, and is then used as an error upper bound for perceptually lossless image compression. For a variety of images, experimental results show that the algorithm produces a compression ratio of 8:1 to 10:1 without introducing visual artifacts.
Computationally Complete
Authors: Michael Jay Schillaci
Venue: Computing in Science and Engineering (2007)

The revamped Books Department kicks off its debut with a review of Rubin Landau's new book from Princeton University Press, "AFirst Course in Scientific Computing: Symbolic, Graphic, and Numeric Modeling Using Maple, Java, Mathematica, and Fortran90."