ppxscal/embedding_network huggingface dataset:
Variations: an interactive musical sculpture
Authors: Bruce Wands
Venue: Proceedings of the 5th conference on Creativity cognition (2005)

Variations is an ongoing exploration of multi-channel and interactive music experienced through a sculptural interface. The interface functions as a means by which participants can create their own mix of the music by interacting with elements of a sculpture that consists of individual modules composed of a cube that contains a speaker, a tube and a removable ball that controls which channel of music they hear. Since one or more individuals may interact with the sculpture at any given time, there is an infinite variety of music that can be heard. This paper will discuss the evolution of the sculptural interface and the creative approach used in composing multi-channel and interactive music.
Using Associative Classification for Predicting HIV-1 Drug Resistance
Authors: Anantaporn Srisawat, Boonserm Kijsirikul
Venue: Proceedings of the Fourth International Conference on Hybrid Intelligent Systems (2004)

Drug resistance testing, genotyping or phenotyping, is an important role in management of HIV-1 infections. To overcome the drawbacks of genotyping and phenotyping in predicting the HIV-1 drug resistance, predicting of phenotypic resistance from genotypic data is an interesting task. In this paper, the CBA algorithm was used to discover the relationship between the amino acid positions and drug susceptibility and to construct the classifiers to predict phenotypic resistance for 6 protease inhibitors. The performance of the prediction was measured by 10-fold cross-validation. The best model provided the accuracy between 84.11% and 92.64% for all 6 protease inhibitors. In addition, the average accuracy of 6 drugs of the prediction using the CBA algorithm provided the best performance when compared with HIVdb, SVM, and REG algorithms.
From the Editor in Chief: Air System Information Management
Authors: Robert E. Filman
Venue: IEEE Internet Computing (2004)

People, whose intelligence is critical for difficult tasks and unusual circumstances, are not as efficient as computers for tasks that can be automated. Better information sharing can lead to higher system capacity, more efficient utilization, and safer operations. Better information sharing through greater automation is possible, though not necessarily easy.
A Sparse Object Category Model for Efficient Learning and Exhaustive Recognition
Authors: R. Fergus, P. Perona, A. Zisserman
Venue: Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Volume 1 - Volume 01 (2005)

We present a "parts and structure" model for object category recognition that can be learnt efficiently and in a semi-supervised manner: the model is learnt from example images containing category instances, without requiring segmentation from background clutter. The model is a sparse representation of the object, and consists of a star topology configuration of parts modeling the output of a variety of feature detectors. The optimal choice of feature types (whose repertoire includes interest points, curves and regions) is made automatically. In recognition, the model may be applied efficiently in an exhaustive manner, bypassing the need for feature detectors, to give the globally optimal match within a query image. The approach is demonstrated on a wide variety of categories, and delivers both successful classification and localization of the object within the image.
Web Page Caching in Java Web Applications
Authors: David A. Turner
Venue: Proceedings of the International Conference on Information Technology: Coding and Computing (ITCC'05) - Volume II - Volume 02 (2005)

Many Web applications serve pages that change infrequently, such as catalog pages within a shopping application or a calendar of events on a university web site. Such pages change only when a staff member logs in, and updates data on which the pages are based. Without caching, requests for such pages result in redundant read operations on the database and generation of HTML from a collection of HTML generating components. In this paper, we explain how we decrease this processing overhead in Java Web applications by caching infrequently changing Web pages.
A modified hotelling deflation scheme for inverting matrices
Authors: Anthony F. Gangi, James N. Shapiro
Venue: ACM SIGNUM Newsletter (1974)

The Hotelling Deflation Algorithm can be modified to generate, with almost no additional effort, the inverse of a matrix simultaneously as its eigenvectors and eigenvalues are being determined. The method is particularly appropriate for small computers (or programmable calculators) with limited memory because the modified matrix occupies the same memory space used for the original matrix.
File System Forensic Analysis
Authors: Brian Carrier
Venue:  (2005)

The Definitive Guide to File System Analysis: Key Concepts and Hands-on TechniquesMost digital evidence is stored within the computer's file system, but understanding how file systems work is one of the most technically challenging concepts for a digital investigator because there exists little documentation. Now, security expert Brian Carrier has written the definitive reference for everyone who wants to understand and be able to testify about how file system analysis is performed.Carrier begins with an overview of investigation and computer foundations and then gives an authoritative, comprehensive, and illustrated overview of contemporary volume and file systems: Crucial information for discovering hidden evidence, recovering deleted data, and validating your tools. Along the way, he describes data structures, analyzes example disk images, provides advanced investigation scenarios, and uses today's most valuable open source file system analysis tools-including tools he personally developed. Coverage includes Preserving the digital crime scene and duplicating hard disks for "dead analysis" Identifying hidden data on a disk's Host Protected Area (HPA) Reading source data: Direct versus BIOS access, dead versus live acquisition, error handling, and more Analyzing DOS, Apple, and GPT partitions; BSD disk labels; and Sun Volume Table of Contents using key concepts, data structures, and specific techniques Analyzing the contents of multiple disk volumes, such as RAID and disk spanning Analyzing FAT, NTFS, Ext2, Ext3, UFS1, and UFS2 file systems using key concepts, data structures, and specific techniques Finding evidence: File metadata, recovery of deleted files, data hiding locations, and more Using The Sleuth Kit (TSK), Autopsy Forensic Browser, and related open source toolsWhen it comes to file system analysis, no other book offers this much detail or expertise. Whether you're a digital forensics specialist, incident response team member, law enforcement officer, corporate security specialist, or auditor, this book will become an indispensable resource for forensic investigations, no matter what analysis tools you use.Brian Carrier has authored several leading computer forensic tools, including The Sleuth Kit (formerly The @stake Sleuth Kit) and the Autopsy Forensic Browser. He has authored several peer-reviewed conference and journal papers and has created publicly available testing images for forensic tools. Currently pursuing a Ph.D. in Computer Science and Digital Forensics at Purdue University, he is also a research assistant at the Center for Education and Research in Information Assurance and Security (CERIAS) there. He formerly served as a research scientist at @stake and as the lead for the @stake Response Team and Digital Forensic Labs. Carrier has taught forensics, incident response, and file systems at SANS, FIRST, the @stake Academy, and SEARCH.Brian Carrier's http://www.digital-evidence.org contains book updates and up-to-date URLs from the book's references.© Copyright Pearson Education. All rights reserved.
Microspaces: a compact javaspaces alternative for teaching net-centric computing in Java
Authors: Ron Coleman, Anil Bhardwaj, Albert Delucca, Gary Finke, Anthony Sofia, Michael Jutt, Sachin Batra
Venue: Journal of Computing Sciences in Colleges (2004)

We introduce MicroSpaces, an Open Source project we develop and support for teaching net-centric computing in Java. A Linda system, MicroSpaces is virtually identical to JavaSpaces at the API level yet MicroSpaces is simpler to manage, more compact, and better suited to one-semester projects, study of network programming principles, and supervised research. We describe the MicroSpaces goals, architecture, and applications for teaching purposes.
Local Leader Election, Signal Strength Aware Flooding, and Routeless Routing
Authors: Gilbert Chen, Joel W. Branch, Boleslaw K. Szymanski
Venue: Proceedings of the 19th IEEE International Parallel and Distributed Processing Symposium (IPDPS'05) - Workshop 12 - Volume 13 (2005)

We have identified a fundamental operator in wireless networks that we named the local leader election in which the goal is to select a node in a spatially close neighborhood. We present a simple and efficient solution to the local leader election problem by making use of both: (i) implicit synchronization points, commonly observable by all nodes in the same neighborhood, and (ii) the prioritized backoff delay, dependent on the desired probability of each node becoming a leader. We then show that both flooding and routing are instances of the local leader election problem, so our general solution naturally applies. By relating the backoff delay to the signal strength of the received packet, we have designed a variant of flooding named Signal Strength Aware Flooding (SSAF) that can improve its efficiency. By using a different metric to derive the backoff delay, we have designed a new generation wireless routing protocol, that we named the Routeless Routing protocol that possesses several interesting properties.
A Cryptographically Sound Dolev-Yao Style Security Proof of an Electronic Payment System
Authors: Michael Backes, Markus Durmuth
Venue: Proceedings of the 18th IEEE workshop on Computer Security Foundations (2005)

We present the first cryptographically sound Dolev-Yao-style security proof of a comprehensive electronic payment system. The payment system is a slightly simplified variant of the 3KP payment system and comprises a variety of different security requirements ranging from basic ones like the impossibility of unauthorized payments to more sophisticated properties like disputability. We show that the payment system is secure against arbitrary active attacks, including arbitrary concurrent protocol runs and arbitrary manipulation of bitstrings within polynomial time if the protocol is implemented using provably secure cryptographic primitives. Although we achieve security under cryptographic definitions, our proof does not have to deal with probabilistic aspects of cryptography and is hence within the scope of current proof tools. The reason is that we exploit a recently proposed Dolev-Yao-style cryptographic library with a provably secure cryptographic implementation. Together with composition and preservation theorems of the underlying model, this allows us to perform the actual proof effort in a deterministic setting corresponding to a slightly extended Dolev-Yao model.
Automatic recognition of sleep spindles in EEG via radial basis support vector machine based on a modified feature selection algorithm
Authors: Nurettin Ac&#x0131;r, C&#x00fc;neyt G&#x00fc;zeli&#x015f;
Venue: Neural Computing and Applications (2005)

This paper presents an application of a radial basis support vector machine (RB-SVM) to the recognition of the sleep spindles (SSs) in electroencephalographic (EEG) signal. The proposed system comprises of two stages. In the first stage, for feature extraction, a set of raw amplitude values, a set of discrete cosine transform (DCT) coefficients, a set of discrete wavelet transform (DWT) approximation coefficients and a set of adaptive autoregressive (AAR) parameters are calculated and extracted from signals separately as four different sets of feature vectors. Thus, four different feature vectors for the same data are comparatively examined. In the second stage, these features are then selected by a modified adaptive feature selection method based on sensitivity analysis, which mainly supports input dimension reduction via selecting the most significant feature elements. Then, the feature vectors are classified by a support vector machine (SVM) classifier, which is relatively new and powerful technique for solving supervised binary classification problems due to it&#x2019;s generalization ability. Visual evaluation, by two electroencephalographers (EEGers), of 19 channel EEG records of six subjects showed that the best performance is obtained with an RB-SVM providing an average sensitivity of 97.7%, an average specificity of 97.4% and an average accuracy of 97.5%.
On error bounds for the Gautschi-type exponential integrator applied to oscillatory second-order differential equations
Authors: Volker Grimm
Venue: Numerische Mathematik (2005)

This paper studies a numerical method for second-order oscillatory differential equations in which high-frequency oscillations are generated by a linear time- and/or solution-dependent part. For constant linear part, it is known that the method allows second-order error bounds independent of the product of the step-size with the frequencies and is therefore a long-time-step method. Most real-world problems are not of that kind and it is important to study more general equations. The analysis in this paper shows that one obtains second-order error bounds even in the case of a time- and/or solution-dependent linear part if the matrix is evaluated at averaged positions.
Using Hardware to Configure a Load-Balanced Switch
Authors: Srikanth Arekapudi, Shang-Tse Chuang, Isaac Keslassy, Nick McKeown
Venue: IEEE Micro (2005)

The load-balanced switch is a promising way to scale router capacity. In this 100-terabit-per-second router, an optical switch spreads traffic evenly among linecards. When the network operator adds or removes linecards, reconfiguring the switch can be time consuming, but a polynomial-time algorithm drastically reduces the required memory-intensive operations, yielding a switch-reconfiguration time below 50 ms.
Performance evaluation of an adaptive backoff scheme for WLAN: Research Articles
Authors: Qixiang Pang, Soung C. Liew, Jack Y. B. Lee, Victor C. M. Leung
Venue: Wireless Communications Mobile Computing (2004)

In this paper, a simple self-adaptive contention window adjustment algorithm for 802.11 wireless local area networks (WLAN) is proposed and analyzed. Numerical results show that the new algorithm outperforms the standard 802.11 window adjustment algorithm. Compared with the standard and previously proposed enhancement algorithms, a salient feature of our algorithm is that it performs well in both heavy and light contention cases regardless of the packet sizes and physical versions. Moreover, the adaptive window adjustment algorithm is simpler than previously proposed schemes in that no live measurement of the WLAN traffic activity is needed. Copyright &copy; 2004 John Wiley & Sons, Ltd.
Prolonging the Lifetime of Wireless Sensor Networks via Prolonging the Lifetime of Wireless Sensor Networks via
Authors: Stanislava Soro, Wendi B. Heinzelman
Venue: Proceedings of the 19th IEEE International Parallel and Distributed Processing Symposium (IPDPS'05) - Workshop 12 - Volume 13 (2005)

Organizing wireless sensor networks into clusters enables the efficient utilization of the limited energy resources of the deployed sensor nodes. However, the problem of unbalanced energy consumption exists, and it is tightly bound to the role and to the location of a particular node in the network. If the network is organized into heterogeneous clusters, where some more powerful nodes take on the cluster head role to control network operation, it is important to ensure that energy dissipation of these cluster head nodes is balanced. Oftentimes the network is organized into clusters of equal size, but such equal clustering results in an unequal load on the cluster head nodes. Instead, we propose an Unequal Clustering Size (UCS) model for network organization, which can lead to more uniform energy dissipation among the cluster head nodes, thus increasing network lifetime. Also, we expand this approach to homogeneous sensor networks and show that UCS can lead to more uniform energy dissipation in a homogeneous network as well.
On the rational summation problem
Authors: S. P. Tsarev
Venue: Programming and Computing Software (2005)

A partial proof of the van Hoeij-Abramov conjecture on the algorithm of definite rational summation is given. The results obtained underlie an algorithm for finding a wide class of sums of the form $$\sum\limits_{k = 0}^{n - 1} {R\left( {k,n} \right)} $$ .
A tutor on subprogram implementation
Authors: Eric Fernandes, Amruth Kumar
Venue: Journal of Computing Sciences in Colleges (2005)

Subprogram implementation is one of the harder topics for students in the Comparative Programming Languages course. In order to help students learn the implementation of non-local referencing in subprograms, we developed a problem-solving tutor. The tutor covers static chaining and display method for static scope and deep and shallow access for dynamic scope, in the context of a language that allows nested subprograms. In this paper, we will describe the design of the tutor, and present the results of evaluating it in our Programming Languages course.
Channel-State Based Scheduling in Wireless Sensor Networks for Reliable Transmission
Authors: P. Sharma
Venue: Proceedings of the 19th IEEE International Parallel and Distributed Processing Symposium (IPDPS'05) - Workshop 12 - Volume 13 (2005)

Reliability of data in energy-constrained sensor networks is limited due to low powered transmissions. Improvement in transmission reliability through channel-state based scheduling is proposed. In a cluster, a time-shared channel between sensor nodes to the cluster head is considered in a Rayleigh fading environment. A 2-state Markov model is presented to partition the received envelope into fade and non-fade states. The state-partitioning threshold is derived as a function of bit error probability and average duration of transmission, in addition to other channel and transmission parameters. It is shown that the channelstate based scheduling can guarantee bit error probability, arbitrarily close to zero at the cost of increasing idle channel time. Increasing the number of sensor nodes in the cluster can offset the increase in idle channel time.
An entropy-based interpretation of retrieval status value-based retrieval, and its application to the computation of term and query discrimination value: Research Articles
Authors: Sándor Dominich, Júlia Góth, Tamás Kiezer, Zoltán Szlávik
Venue: Journal of the American Society for Information Science and Technology (2004)

The concepts of Shannon information and entropy have been applied to a number of information retrieval tasks such as to formalize the probabilistic model, to design practical retrieval systems, to cluster documents, and to model texture in image retrieval. In this report, the concept of entropy is used for a different purpose. It is shown that any positive Retrieval Status Value (RSV)-based retrieval system may be conceived as a special probability space in which the amount of the associated Shannon information is being reduced; in this view, the retrieval system is referred to as Uncertainty Decreasing Operation (UDO). The concept of UDO is then proposed as a theoretical background for term and query discrimination power, and it is applied to the computation of term and query discrimination values in the vector space retrieval model. Experimental evidence is given as regards such computation; the results obtained compare well to those obtained using vector-based calculation of term discrimination values. The UDO-based computation, however, presents advantages over the vector-based calculation: It is faster, easier to assess and handle in practice, and its application is not restricted to the vector space model. Based on the ADI test collection, it is shown that the UDO-based Term Discrimination Value (TDV) weighting scheme yields better retrieval effectiveness than using the vector-based TDV weighting scheme. Also, experimental evidence is given to the intuition that the choice of an appropriate weighting scheme and similarity measure depends on collection properties, and thus the UDO approach may be used as a theoretical basis for this intuition. &copy; 2005 Wiley Periodicals, Inc.
LabVIEW Digital Signal Processing, 1 edition
Authors: Cory Clark
Venue:  (2005)

LabVIEW Digital Signal Processing teaches engineers how to use the graphical programming language to create virtual instruments to handle to most sophisticated DSP applications. From basic filters to complex sampling mechanisms to signal generators, LabVIEW virtual instruments (VIs) can make DSP work faster and much less expensive – a particular boon to the many engineers working on cutting edge communications systems.Table of contentsPart 1: Getting StartedChapter 1: Digital Communications and LabVIEWChapter 2: Getting a Signal into LabVIEWPart 2: Building BlocksChapter 3: Spectral AnalysisChapter 4: Digital FiltersChapter 5: Multirate Signal Processing in LabVIEWChapter 6: Generating Signals with LabVIEWPart 3: Building a Communication SystemChapter 7: Assembling the PiecesChapter 8: System PerformanceChapter 9: Optimizing LabVIEW Signal ProcessingAPPENDIX A: VI REFERENCEAPPENDIX B: HARDWARE RESOURCESINDEX
Guest Column: NP-complete problems and physical reality
Authors: Scott Aaronson
Venue: ACM SIGACT News (2005)

Can NP-complete problems be solved efficiently in the physical universe? I survey proposals including soap bubbles, protein folding, quantum computing, quantum advice, quantum adiabatic algorithms, quantum-mechanical nonlinearities, hidden variables, relativistic time dilation, analog computing, Malament-Hogarth spacetimes, quantum gravity, closed timelike curves, and "anthropic computing." The section on soap bubbles even includes some "experimental" results. While I do not believe that any of the proposals will let us solve NP-complete problems efficiently, I argue that by studying them, we can learn something not only about computation but also about physics.
A model of overt visual attention based on scale-space theory
Authors: Shunji Satoh, Shogo Miyake
Venue: Systems and Computers in Japan (2004)

This paper proposes a vision model for object detection based on scale-space theory, considering knowledge obtained in neurophysiology and human visual characteristics obtained in visual psychology. The proposed model is principally composed of (a) the early vision model and (b) the attention calculation model. In this paper, it is shown first that the visual characteristics can be described by a discretized scale space, considering their multichannel property, spatial nonuniformity, and orientation selectivity. The early vision model is formulated. Next, the attention calculation model and the operation algorithm are formulated on the basis of the knowledge obtained by scale-space theory. The numerical experiments reveal that the proposed model has the following properties. (i) For objects with a high intensity difference, the center of overt attention moves to the center of the object. (ii) The spatial extent of overt&sol;covert attention can be calculated adequately. (iii) The object is captured at the central region of the retina, where the resolution is the highest. Since the proposed model is based on scale-space theory, the theory or model can be easily extended. There are other advantages from an engineering standpoint, such as simple structure, easy implementation, small computational requirements, and very few parameters to be adjusted. &copy; 2004 Wiley Periodicals, Inc. Syst Comp Jpn, 35(10): 1&ndash;13, 2004; Published online in Wiley InterScience (). DOI 10.1002&sol;scj.10708