ppxscal/embedding_network huggingface dataset:
Compiler Optimization Technique for Data Cache Prefetching Using a Small CAM Array
Authors: Chi-Hung Chi
Venue: Proceedings of the 1994 International Conference on Parallel Processing - Volume 01 (1994)

With advances in compiler optimization and program flow analysis, software assisted cache prefetching schemes using PREFETCH instructions are now possible. Although data can be prefetched accurately into the cache, the runtime overhead associated with these schemes often limits their practical use. In this paper, we propose a new scheme, called the Stride_CAM Data Prefetching (SCP), to prefetch array references with constant strides accurately. Compared to current software assisted data prefetching schemes, the SCP scheme has much lower runtime overhead without sacrificing prefetching accuracy. Our result showed that the SCP scheme is particularly suitable for computing intensive scientific applications where cache misses are mainly due to array references with constant strides and they can be prefetched very accurately by this SCP scheme.
A rotation, scale and translation resilient public watermark
Authors: M. Wu
Venue: Proceedings of the Acoustics, Speech, and Signal Processing, 1999. on 1999 IEEE International Conference - Volume 04 (1999)

Summary form only given. Watermarking algorithms that are robust to the common geometric transformations of rotation, scale and translation (RST) have been reported for cases in which the original unwatermarked content is available at the detector so as to allow the transformations to be inverted. However, for public watermarks the problem is significantly more difficult since there is no original content to register with. Two classes of solution have been proposed. The first embeds a registration pattern into the content while the second seeks to apply detection methods that are invariant to these geometric transformations. This paper describes a public watermarking method which is invariant (or bares a simple relation) to the common geometric transforms of rotation, scale, and translation. It is based on the Fourier-Mellin transform which has previously been suggested. We extend this work, using a variation based on the Radon transform. The watermark is inserted into a projection of the image. The properties of this projection are such that RST transforms produce simple or no effects on the projection waveform. When a watermark is inserted into a projection, the signal must eventually be back projected to the original image dimensions. This is a one to many mapping that allows for considerable flexibility in the watermark insertion process. We highlight some theoretical and practical issues that affect the implementation of an RST invariant watermark. Finally, we describe preliminary experimental results.
Trust in global computing systems as a limit property emerging from short range random interactions
Authors: V. Liagkou, E. Makri, P. Spirakis, Y. C. Stamatiou
Venue: Proceedings of the The Second International Conference on Availability, Reliability and Security (2007)

Today we are experiencing a major reconsideration of the computing paradigm, as witnessed by the abundance and increasing frequency of use of terms such as ambient intelligence, ubiquitous computing, disappearing computer, grid computer, global computing and mobile ad-hoc networks. Systems that can be described with such terms are of a dynamic, with no clear physical boundary, nature and it seems that it is impossible (or, at least, difficult) to define sharply a number of important properties holding with certainty as well as holding throughout the whole lifetime of the system. One such system property, which is important for the viability of a system, is trust. Our departure point is the assumption that it seems very difficult to define static system properties related to trust and expect that they hold eternally in the rapidly changing systems falling under the new computing paradigm. One should, rather, attempt to define trust in terms of properties that hold with some limiting probability as the the system grows and try to establish conditions that ensure that "good properties hold almost certainly. Based on this viewpoint, in this paper we provide a new framework for defining trust through formally definable properties that hold, almost certainly, in the limit in randomly growing combinatorial structures that model "shapeless computing systems (e.g. ad-hoc networks), drawing on results that establish the threshold behavior of predicates written in the first and second order logic.
Wavelet-based image coder with channel-optimized trellis-coded quantization
Authors: Tuyet-Trang Lam
Venue: Proceedings of the Acoustics, Speech, and Signal Processing, 1999. on 1999 IEEE International Conference - Volume 06 (1999)

This paper presents a wavelet-based image coder optimized for transmission over binary symmetric channels (BSC). The proposed coder uses a channel-optimized trellis-coded quantization (COTCQ) stage that is designed to optimize the image coding based on the channel characteristics. This optimization is performed only at the level of the source encoder, and does not include any channel coding for error protection. Consequently, the proposed channel-optimized image coder is especially suitable for wireless transmission due to its reduced complexity. Furthermore, the improvement over TCQ-based image coders is significant. Examples are presented to illustrate the performance of the proposed COTCQ-based image coder.
Self-securing storage: protecting data in compromised system
Authors: John D. Strunk, Garth R. Goodson, Michael L. Scheinholtz, Craig A. N. Soules, Gregory R. Ganger
Venue: Proceedings of the 4th conference on Symposium on Operating System Design & Implementation - Volume 4 (2000)

Self-securing storage prevents intruders from undetectably tampering with or permanently deleting stored data. To accomplish this, self-securing storage devices internally audit all requests and keep old versions of data for a window of time, regardless of the commands received from potentially compromised host operating systems. Within the window, system administrators have this valuable information for intrusion diagnosis and recovery. Our implementation, called S4, combines log-structuring with journal-based metadata to minimize the performance costs of comprehensive versioning. Experiments show that self-securing storage devices can deliver performance that is comparable with conventional storage systems. In addition, analyses indicate that several weeks worth of all versions can reasonably be kept on state-of-the-art disks, especially when differencing and compression technologies are employed.
Blind multi-user combining at the base station for asynchronous CDMA systems
Authors: O. M. Medina
Venue: Proceedings of the Acoustics, Speech, and Signal Processing, 1996. on Conference Proceedings., 1996 IEEE International Conference - Volume 05 (1996)

This paper studies the potential benefits of antenna arrays in cellular CDMA communications and proposes a powerful scheme to undertake the array processing at the base station in CDMA mobile systems. The proposed technique exploits the temporal structure of CDMA signals. The necessary information is extracted directly from the received signals, thus no training signal or "a priori" spatial information is required. Making use of the overall information present at the receiver after the despreading, the technique presented, jointly with singular value decomposition, estimates the generalized steering vector for each user. Then, an optimal combining of the signal received at each antenna is undertaken, achieving substantial robustness against fading and near-far problems.
Model-Based Cyber Security
Authors: Galen Rasche, Erin Allwein, Michael Moore, Ben Abbott
Venue: Proceedings of the 14th Annual IEEE International Conference and Workshops on the Engineering of Computer-Based Systems (2007)

This paper presents an approach for automatically verifying the correctness of cyber security applications through formal analysis guided by hierarchical models of the network, its applications, and potential attacks. This work is motivated by the need for a more intuitive, automated systems-level approach to determining the overall security characteristics of a large network. Given the complex nature of security tools and their general lack of interoperability, it is difficult for system designers to make definitive statements about the nature of their network defense. Our work focuses on creating an environment in which security experts can model the security aspects of complex networks using a graphical notation that is intuitive and natural for them, then automatically perform security activities such as formally verifying the safety of the network against known threats and exploring the network design for potential vulnerabilities. The environment is designed to utilize third party tools for performing these activities and concentrates on integration of these tools within a common modeling framework.
Adaptive, intelligent presentation of information for the museum visitor in PEACH
Authors: Oliviero Stock, Massimo Zancanaro, Paolo Busetta, Charles Callaway, Antonio Krüger, Michael Kruppa, Tsvi Kuflik, Elena Not, Cesare Rocchi
Venue: User Modeling and User-Adapted Interaction (2007)

The study of intelligent user interfaces and user modeling and adaptation is well suited for augmenting educational visits to museums. We have defined a novel integrated framework for museum visits and claim that such a framework is essential in such a vast domain that inherently implies complex interactivity. We found that it requires a significant investment in software and hardware infrastructure, design and implementation of intelligent interfaces, and a systematic and iterative evaluation of the design and functionality of user interfaces, involving actual visitors at every stage. We defined and built a suite of interactive and user-adaptive technologies for museum visitors, which was then evaluated at the Buonconsiglio Castle in Trento, Italy: (1) animated agents that help motivate visitors and focus their attention when necessary, (2) automatically generated, adaptive video documentaries on mobile devices, and (3) automatically generated post-visit summaries that reflect the individual interests of visitors as determined by their behavior and choices during their visit. These components are supported by underlying user modeling and inference mechanisms that allow for adaptivity and personalization. Novel software infrastructure allows for agent connectivity and fusion of multiple positioning data streams in the museum space. We conducted several experiments, focusing on various aspects of PEACH. In one, conducted with 110 visitors, we found evidence that even older users are comfortable interacting with a major component of the system.
An approach towards an event-fed solution for slowly changing dimensions in data warehouses with a detailed case study
Authors: Tho Manh Nguyen, A. Min Tjoa, Jaromir Nemec, Martin Windisch
Venue: Data Knowledge Engineering (2007)

From the point of view of a data warehouse system, collecting and receiving information from source systems is crucial for all subsequent business intelligence applications. Incoming information can generally be classified into two types: (1) the state-oriented data and (2) event-oriented data or transactional data, which contains information about the change performed by processes on the instances of information objects. On the way towards achieving the goal of a full-fledged active data warehouse it becomes more and more important to provide data with minimal latency. In this paper we focus on dimensional data which is provided by general data warehouse applications. The information transfer is performed via messages containing the change of information on the dimension instances. The proposed approach is able to validate the event-messages, reconstruct the complete history of the dimension and provide a well applicable ''comprehensive slowly changing dimension'' (cSCD) interface for queries on the historical and current state of the dimension. A description of the prototype implementation for this kind of an ''active integration'' in a data warehouse and a case study at T-Mobile conclude the paper.
Toward Exploratory Test-Instance-Centered Diagnosis in High-Dimensional Classification
Authors: Charu C. Aggarwal
Venue: IEEE Transactions on Knowledge and Data Engineering (2007)

High-dimensional data is a difficult case for most subspace-based classification methods because of the large number of combinations of dimensions, which have discriminatory power. This is because there are an exponential number of combinations of dimensions that could decide the correct class instance, and this combination could vary with data locality and test instance. Therefore, most summarized models such as decision trees and rule-based systems only aim to have a global summary of the data, which is used for classification. Because of this incompleteness, a particular classification model may be more or less suited to individual test instances. Furthermore, it may not provide sufficient insight into the most representative characteristics of a particular test instance. This is undesirable for many classification applications in which the diagnostic reasoning behind the classification of a test instance is as important as the classification process itself. In an interactive application, a user may find it more valuable to develop a diagnostic decision support method, which can reveal significant classification behaviors of exemplar records. Such an approach has the additional advantage of being able to optimize the decision process for the individual record in order to design more effective classification methods. In this paper, we propose the Subspace Decision Path (SD-Path) method, which provides the user with the ability to interactively explore a small number of nodes of a hierarchical decision process so that the most significant classification characteristics for a given test instance are revealed. In addition, the SD-Path method can provide enormous interpretability by constructing views of the data in which the different classes are clearly separated out. Even in difficult cases where the classification behavior of the test instance is ambiguous, the SD-Path method provides a diagnostic understanding of the characteristics, which results in this ambiguity. Therefore, this method combines the abilities of the human and the computer in creating an effective diagnostic tool for instance-centered high-dimensional classification.
Art & complexity: an exploration of aesthetics
Authors: Guy Birkin
Venue: Proceedings of the 6th ACM SIGCHI conference on Creativity cognition (2007)

This PhD thesis is centred on the idea of complexity as an aesthetic factor. The project aims to explore the role of visual complexity in the making and perception of contemporary art. An experimental methodology combines creative practice with empirical studies of human response to variations in complexity of images. Tools from complexity theory and neuroscience are used to create images and conduct tests of aesthetic perception.
Using sensorranks for in-network detection of faulty readings in wireless sensor networks
Authors: Xiang-Yan Xiao, Wen-Chih Peng, Chih-Chieh Hung, Wang-Chien Lee
Venue: Proceedings of the 6th ACM international workshop on Data engineering for wireless and mobile access (2007)

In this paper, the problem of determining faulty readings in a wireless sensor network without compromising detection of important events is studied. By exploring correlations between readings of sensors, a correlation network is built based on similarity between readings of two sensors. By exploring Markov Chain in the network, a mechanism for rating sensors in terms of the correlation, called SensorRank, is developed. In light of SensorRank, an efficient in-network voting algorithm, called TrustVoting, is proposed to determine faulty sensor readings. Performance studies are conducted via simulation. Experimental results show that the proposed algorithm outperforms majority voting and distance weighted voting, two state-of-the-art approaches for in-network faulty reading detection.
Calibration Based Methods for Substrate Modeling and Noise Analysis for Mixed-Signal SoCsc
Authors: Sankar P. Debnath, Ganesh P. Kumar, S Jairam
Venue: Proceedings of the 20th International Conference on VLSI Design held jointly with 6th International Conference: Embedded Systems (2007)

A novel and an extremely fast substrate model creation and noise analysis methodology is presented. The method takes a prototype floorplan or layout as an input and outputs a detailed 2-D plot of the noise voltage distribution at the surface. Estimated noise injection is attached to a substrate model to compute noise distribution across the die. An adaptive finite element based extraction method is described for modeling. The model is then calibrated to an extracted substrate model based on various parameters like surface and bulk resistivity. The method is optimized for both accuracy and speed. It is also shown how a designer can perform various what-if analysis with this flow in both pre-layout and post-layout phases. Grounding schemes and isolation structures are then discussed with various what-if analysis. Finally simulation data and results from an actual design are shown where this methodology has been applied.
Determining Implementation Expertise from Bug Reports
Authors: John Anvik, Gail C. Murphy
Venue: Proceedings of the 29th International Conference on Software Engineering Workshops (2007)

As developers work on a software product they accumulate expertise, including expertise about the code base of the software product. We call this type of expertise "implementation expertise'. Knowing the set of developers who have implementation expertise for a software product has many important uses. This paper presents an empirical evaluation of two approaches to determining implementation expertise from the data in source and bug repositories. The expertise sets created by the approaches are compared to those provided by experts and evaluated using the measures of precision and recall. We found that both approaches are good at finding all of the appropriate developers, although they vary in how many false positives are returned.
A class-based language model for large-vocabulary speech recognition extracted from part-of-speech statistics
Authors: C. Samuelsson
Venue: Proceedings of the Acoustics, Speech, and Signal Processing, 1999. on 1999 IEEE International Conference - Volume 01 (1999)

A novel approach is presented to class-based language modeling based on part-of-speech statistics. It uses a deterministic word-to-class mapping, which handles words with alternative part-of-speech assignments through the use of ambiguity classes. The predictive power of word-based language models and the generalization capability of class-based language models are combined using both linear interpolation and word-to-class backoff, and both methods are evaluated. Since each word belongs to one precisely ambiguity class, an exact word-to-class backoff model can easily be constructed. Empirical evaluations on large-vocabulary speech-recognition tasks show perplexity improvements and significant reductions in word error-rate.
Affine differential geometry analysis of human arm movements
Authors: Tamar Flash, Amir A. Handzel
Venue: Biological Cybernetics (2007)

Humans interact with their environment through sensory information and motor actions. These interactions may be understood via the underlying geometry of both perception and action. While the motor space is typically considered by default to be Euclidean, persistent behavioral observations point to a different underlying geometric structure. These observed regularities include the &#x201c;two-thirds power law&#x201d;, which connects path curvature with velocity, and &#x201c;local isochrony&#x201d;, which prescribes the relation between movement time and its extent. Starting with these empirical observations, we have developed a mathematical framework based on differential geometry, Lie group theory and Cartan&#x2019;s moving frame method for the analysis of human hand trajectories. We also use this method to identify possible motion primitives, i.e., elementary building blocks from which more complicated movements are constructed. We show that a natural geometric description of continuous repetitive hand trajectories is not Euclidean but equi-affine. Specifically, equi-affine velocity is piecewise constant along movement segments, and movement execution time for a given segment is proportional to its equi-affine arc-length. Using this mathematical framework, we then analyze experimentally recorded drawing movements. To examine movement segmentation and classification, the two fundamental equi-affine differential invariants&#x2014;equi-affine arc-length and curvature are calculated for the recorded movements. We also discuss the possible role of conic sections, i.e., curves with constant equi-affine curvature, as motor primitives and focus in more detail on parabolas, the equi-affine geodesics. Finally, we explore possible schemes for the internal neural coding of motor commands by showing that the equi-affine framework is compatible with the common model of population coding of the hand velocity vector when combined with a simple assumption on its dynamics. We then discuss several alternative explanations for the role that the equi-affine metric may play in internal representations of motion perception and production.
SIP-based IEEE802.21 media independent handover: a BT Intel collaboration
Authors: K. N. Choong, V. S. Kesavan, S. L. Ng, F. Carvalho, A. L. Low, C. Maciocco
Venue: BT Technology Journal (2007)

In this paper, we look at various mobility management protocols and handover frameworks in use in BT. We also report on the results from a collaborative proof of concept mixed network prototype for a seamless handover system using Intel's early implementation of the IEEE802.21 media-independent handover standard. The paper reports the design, implementation and deployment issues/options of a handover mechanism using the Intel framework which includes a connection manager and mixed network IEEE802.21 adaptation layer together with BT's SIP-based audio/video application in a heterogeneous Wi-Fi, WiMAX and Ethernet network environment.
Reconstruction-optimized lapped orthogonal transforms
Authors: S. S. Hemami
Venue: Proceedings of the Acoustics, Speech, and Signal Processing, 1996. on Conference Proceedings., 1996 IEEE International Conference - Volume 03 (1996)

Packetized image communication over lossy channels presents a reconstruction problem at the decoder. To date, reconstruction algorithms have been developed for fixed coding techniques. This paper examines the dual problem-a block-based coding technique, namely a family of lapped orthogonal transforms (LOTs), is designed to maximize the reconstruction performance of a fixed reconstruction algorithm. Mean-reconstruction, in which missing coefficient blocks are replaced with averages of their available neighbors, is selected for simplicity and implementation ease. A reconstruction criterion is defined in terms of mean-squared error, and is used to define the reconstruction gain. A family of LOTs is then designed to consider both reconstruction gain and coding gain. Reconstruction capability and compression are exchanged, and the LOT family consists of transforms that provide increasing reconstruction capability with lower coding gain. A transform can therefore be selected based on channel loss characteristics, desired reconstruction performance, and desired compression.