ppxscal/embedding_network huggingface dataset:
Causeway: operating system support for controlling and analyzing the execution of distributed programs
Authors: Anupam Chanda, Khaled Elmeleegy, Alan L. Cox, Willy Zwaenepoel
Venue: Proceedings of the 10th conference on Hot Topics in Operating Systems - Volume 10 (2005)

In this paper we introduce Causeway, operating system support facilitating the development of meta-applications, like priority scheduling and performance debugging, that control and analyze the execution of distributed programs. Meta-applications use Causeway to inject and access metadata on application execution paths to implement their specific goals. Causeway has two components: (1) interfaces to inject and access metadata and (2) mechanisms to automate propagation of meta-data. Using Causeway we could rapidly implement a distributed priority scheduling system where priority of a task is injected and propagated as metadata, and accessed to implement global priority scheduling. This required writing only about 150 lines of code on top of Causeway. With this system we demonstrate global priority scheduling on an implementation of the TPC-W benchmark.
Computing View-normalized Body Parts Trajectories
Authors: Frederic Jean, Robert Bergevin, Alexandra Branzan Albu
Venue: Proceedings of the Fourth Canadian Conference on Computer and Robot Vision (2007)

This paper proposes an approach to compute viewnormalized body part trajectories of pedestrians from monocular video sequences. The proposed approach first extracts the 2D trajectories of both feet and of the head from tracked silhouettes. On that basis, it segments the walking trajectory into piecewise linear segments. Finally, a normalization process is applied to head and feet trajectories over each obtained straight walking segment. View normalization makes head and feet trajectories appear as if seen from a fronto-parallel viewpoint. The latter is assumed to be optimal for gait modeling and recognition purposes. The proposed approach is fully automatic as it requires neither manual initialization nor camera calibration.
Visual Data Mining in Software Archives To Detect How DevelopersWork Together
Authors: Peter Weibgerber, Mathias Pohl, Michael Burch
Venue: Proceedings of the 29th International Conference on Software Engineering Workshops (2007)

Analyzing the check-in information of open source software projects which use a version control system such as CVS or SUBVERSION can yield interesting and important insights into the programming behavior of developers. As in every major project tasks are assigned to many developers, the development must be coordinated between these programmers. This paper describes three visualization techniques that help to examine how programmers work together, e.g. if they work as a team or if they develop their part of the software separate from each other. Furthermore, phases of stagnation in the lifetime of a project can be uncovered and thus, possible problems are revealed. To demonstrate the usefulness of these visualization techniques we performed case studies on two open source projects. In these studies interesting patterns of developers' behavior, e.g. the specialization on a certain module can be observed. Moreover, modules that have been changed by many developers can be identified as well as such ones that have been altered by only one programmer.
Design and implementation of index structures for fuzzy spatial databases: Research Articles
Authors: Aziz Sözer, Adnan Yazıcı
Venue: International Journal of Intelligent Systems (2007)

Over the years database management systems have evolved to include spatially referenced data. Because spatial data are complex and have a number of unique constraints (i.e., spatial components and uncertain properties), spatial database systems can be effective only if the spatial data are properly handled at the physical level. Therefore, it is important to develop an effective spatial and aspatial indexing technique to facilitate flexible spatial and&#x002F;or aspatial querying for such databases. For this purpose we introduce an indexing approach to use (fuzzy) spatial and (fuzzy) aspatial data. We use a number of spatial index structures, such as Multilevel Grid File (MLGF), G-tree, R-tree, and R&ast;-tree, for fuzzy spatial databases and compare the performances of these structures for various flexible queries. &copy; 2007 Wiley Periodicals, Inc. Int J Int Syst 22: 805&ndash;826, 2007.
A Method for Estimating the Precision of Placename Matching
Authors: Martin Doerr, Manos Papagelis
Venue: IEEE Transactions on Knowledge and Data Engineering (2007)

Information in digital libraries and information systems frequently refers to locations or objects in geographic space. Digital gazetteers are commonly employed to match the referred placenames with actual locations in information integration and data cleaning procedures. This process may fail due to missing information in the gazetteer, multiple matches, or false positive matches. We have analyzed the cases of success and reasons for failure of the mapping process to a gazetteer. Based on these, we present a statistical model that permits estimating 1) the completeness of a gazetteer with respect to the specific target area and application, 2) the expected precision and recall of one-to-one mappings of source placenames to the gazetteer, 3) the semantic inconsistency that remains in one-to-one mappings, and 4) the degree to which the precision and recall are improved under knowledge of the identity of higher levels in a hierarchy of places. The presented model is based on statistical analysis of the mapping process of a large set of placenames itself and does not require any other background data. The statistical model assumes that a gazetteer is populated by a stochastic process. The paper discusses how future work could take deviations from this assumption into account. The method has been applied to a real case.
Bump in the ether: a framework for securing sensitive user input
Authors: Jonathan M. McCune, Adrian Perrig, Michael K. Reiter
Venue: Proceedings of the annual conference on USENIX '06 Annual Technical Conference (2006)

We present Bump in the Ether (BitE), an approach for preventing user-space malware from accessing sensitive user input and providing the user with additional confidence that her input is being delivered to the expected application. Rather than preventing malware from running or detecting already-running malware, we facilitate user input that bypasses common avenues of attack. User input traverses a trusted tunnel from the input device to the application. This trusted tunnel is implemented using a trusted mobile device working in tandem with a host platform capable of attesting to its current software state. Based on a received attestation, the mobile device verifies the integrity of the host platform and application, provides a trusted display through which the user selects the application to which her inputs should be directed, and encrypts those inputs so that only the expected application can decrypt them. We describe the design and implementation of BitE, with emphasis on both usability and security issues.
Content-based publish/subscribe with structural reflection
Authors: Patrick Th. Eugster, Rachid Guerraoui
Venue: Proceedings of the 6th conference on USENIX Conference on Object-Oriented Technologies and Systems - Volume 6 (2001)

This paper presents a pragmatic way of implementing content-based publish/subscribe in a strongly typed object-oriented language. In short, we use structural reflection to implement filter objects through which applications express their subscription patterns. Our approach is pragmatic in the sense that it alleviates the need for any specific subscription language. It preserves encapsulation of message objects and helps avoiding errors. We illustrate our approach in the context of Distributed Asynchronous Collections (DACs), programming abstractions for message-oriented interaction. DACs are implemented in Java, whose inherent reflective capabilities fully satisfy the requirements of our content-based subscription scheme. Our approach is however not limited to the context of DACs, but could be put to work easily in other existing event-based systems.
Defining what digital curators do and what they need to know: the digccurr project
Authors: Christopher A. Lee, Helen R. Tibbo, John C. Schaefer
Venue: Proceedings of the 7th ACM/IEEE-CS joint conference on Digital libraries (2007)

The DigCCurr (Digital Curation Curriculum) project is developing a graduate level curricular framework, course modules, and experiential components to prepare students for digital curation in various environments. This paper summarizes a draft and guiding principles behind a matrix of digital curation knowledge and competencies, which are serving as the basis for our curriculum design efforts.
Autonomic Goal-Oriented Business Process Management
Authors: Dominic Greenwood, Giovanni Rimassa
Venue: Proceedings of the Third International Conference on Autonomic and Autonomous Systems (2007)

This paper outlines an autonomic approach to business process management using goal-oriented principles and autonomous agent technology employing the well-known BDI method. We discuss how the structure of common business processes can be mapped onto goal-oriented models where achievement points are represented by goals and the task structures used to reach them are represented by plans. The flexibility afforded by this approach implies that autonomic feedback loops are created between the business process incarnation and its autonomous controller, which may be extended to the multiple process case where several controllers interact to form extended feedback relationships. We introduce a set of technologies designed to deliver these features in real-world applications and support the position with a case study in the domain of Engineering Change Management.
Adaptive defense against various network attacks
Authors: Cliff C. Zou, Nick Duffield, Don Towsley, Weibo Gong
Venue: Proceedings of the Steps to Reducing Unwanted Traffic on the Internet on Steps to Reducing Unwanted Traffic on the Internet Workshop (2005)

In defending against various network attacks, such as Distributed Denial-of-Service (DDoS) attacks or worm attacks, a defense system needs to deal with various network conditions and dynamically changing attacks. In this paper, we introduce an "adaptive defense" principle based on cost minimization - a defense system adaptively adjusts its configurations according to the network condition and attack severity in order to minimize the combined cost introduced by false positives (misidentify normal traffic as attack) and false negatives (misidentify attack traffic as normal) at any time. In this way, the adaptive defense system generates fewer false alarms in normal situations (or under light attacks) with relaxed defense configurations, while protecting a network or a server more vigorously under severe attacks. Specifically, we present detailed adaptive defense system designs for defending against two major network attacks: SYN flood DDoS attack and Internet worm infection. The adaptive defense is a high-level system design that can be built on top of various non-adaptive detection and filtering algorithms, which makes it applicable for a wide range of security defenses.
A study of meta-linguistic features in spontaneous speech processing
Authors: Shrikanth Narayanan
Venue:  (2006)

Speech is a crucial component in human computer interaction. While tremendous progress has been made in automatic speech recognition, speech transcription, which is the output of automatic speech recognition, is far from providing all the information that one could retrieve from speech. For example, prominence, rate of speech all carry important information in speech and are crucial to speech perception. Inclusion of such meta-linguistic features can facilitate better machine recognition and understanding of speech. In this thesis, we illustrate various research progress in study of the meta-linguistic features. Firstly, we proposed an acoustic measure of speech rate without speech recognition. It includes various spectral, temporal and smoothing algorithms to identify the syllable nucleus, which is easily converted to speech rate measure by dividing the length of speech. The parameters of the algorithm is optimized by Monte-Carlo simulation followed by a sensitivity analysis. Secondly, we extend the syllable nucleus estimation algorithm to provide an acoustic measure of prominence. It fuses features such as syllable duration, spectral intensity and pitch patterns to score prominence on a continuous scale. We proposed parametric shape based features to identify the pitch shape and demonstrate its usefulness in prominence detection. Beyond direct evaluation on manually transcribed prominence, linguistic correlation with part of speech was used to measure prominence. Thirdly, we use rate and prominence feature and many other acoustic features to automatically detect utterance boundary and disfluency. We extract features from pitch breaks and their surrounding regions. Such process includes a piecewise linear stylization of pitch coutour. A rule based approach and a machine learning approach are proposed and compared on various boundary and disfluency events. Lastly, we use all the above features to study speech acts detection, specifically distinguishing between wh-questions and statements. The prominence of first two syllables and their timings are found to be useful for such task.
Low Power Implementation for Minimum Norm Sorting and Block Upper Tri-angularization of Matrices used in MIMO Wireless Systems
Authors: Zahid Khan, Tughrul Arslan, John S. Thompson, Ahmet T. Erdogan
Venue: Proceedings of the 20th International Conference on VLSI Design held jointly with 6th International Conference: Embedded Systems (2007)

Multiple Input - Multiple Output (MIMO) wireless technology involves highly complex vectors and matrix computations which are directly related to increased power and area consumption. This paper proposes an area and power efficient VLSI architecture that can serve the dual purpose of minimum norm sorting of rows as well as upper/lower block tri-angularization of matrices. The resources inside the architecture are shared among both operations and only primitive computations are used. Results indicate saving in silicon real estate as well as power consumption compared to previous architecture without degrading performance.
A Memory-Constrained Scalability Metric
Authors: Mark A. Fienup, S. C. Kothari
Venue: Proceedings of the 1994 International Conference on Parallel Processing - Volume 03 (1994)

A performance evaluation metric called CMP scalability is introduced This metric is useful in analyzing performance of a parallel algorithm as the number of processors grows but the memory size per processor is fixed. The CMP scalability metric is derived for the parallel Matrix Multiplication (MM). Gauss Jordan Elimination (GJE), and Fast Fourier Transform (FFT). These examples show that the CMP scalability metric and the isoefficiency metric really address different aspects of scalability and could lead to very different conclusions. According to the CMP scalability analysis FFT is more scalable than GJE. Interestingly, conclusions drawn from the isoefficiency analysis are quite the opposite. The CMP scalability metric, and so also the isoefficiency metric, is a function indicating the asymptotic behavior as the number of processors becomes large. However, the CMP analysis can also help to analyze the performance of an algorithm on a given architecture with a limited number of processors. We present such an analysis of the three algorithms on a 16K processor MasPar MP-1 machine.
Construction and computational complexity of pooling designs
Authors: Weili Wu
Venue:  (2006)

DNA contains major information to control the development of any organism. This had been a distant dream until two restriction enzymes and DNA ligases were discovered in 1970s. This made it possible to manipulate DNA, create DNA Library and decode DNA. DNA Library Screening is very expensive since the number of defectives (probes) is very small when compared to the huge number of candidates (clones). It is a typical instance of group testing. Using d-disjunct matrices to construct non-adaptive pooling designs has been proved to be an efficient algorithm. Researchers have been trying different constructions by using different methods over the last two decades. There are two major problems in the previous works. The first is there is no general setting in pooling designs. The second one is there is no general procedure or tool to construct pooling designs. I propose a general setting in pooling design and a general procedure for constructing d-disjunct matrices by using the simplicial complex and graph property. The interactions between proteins are important in many biological functions. I use a complete graph to describe the protein-protein interaction problem, however the algorithm is not that efficient. I then use a d-disjunct matrix to solve the protein-protein interaction problem, and proposed four constructions for d-disjunct matrix, two non-adaptive algorithms and a generalization. Using non-unique probe brought a new challenge to the traditional pooling design. One positive outcome is a set of candidates rather than just one. The fundamental problem, that whether all viruses can be identified by using only non-unique probes, is solved in this dissertation. We found that all n viruses cannot be identified without using unique probes. Furthermore, for the considered n viruses, only n-2 viruses can be identified by using only non-unique probes. I conclude this dissertation with some useful conclusions on the computational complexity of pooling designs by reducing from the known NP problems.
Online Sequential Prediction via Incremental Parsing: The Active LeZi Algorithm
Authors: Karthik Gopalratnam, Diane J. Cook
Venue: IEEE Intelligent Systems (2007)

Prediction is important in various domains. Intelligent systems that can predict future events can make more informed, and therefore more reliable, decisions. Active LeZi, an online sequential prediction algorithm that can reason about the future in stochastic domains, uses an information-theoretic approach to analyze synthetic data, UNIX command data, and sequential data obtained from the MavHome smart home environment.
An adaptive system identification Java simulation for Internet based courseware
Authors: A. Xavier
Venue: Proceedings of the 28th Annual Frontiers in Education - Volume 01 (1998)

In this paper, an educational software tool on adaptive filters is presented. The simulation software is written in Java and provides an interactive environment that allows students to investigate and understand adaptive filters. The program exposes students to the concepts and applications of adaptive filters with special emphasis on convergence properties. The different adaptive algorithms that are implemented include LMS, NLMS, BLMS, IIR-LMS and IIR-SHARF. A frequency response visualization module was also developed to observe the magnitude and phase response for the corresponding pole-zero placement in the z-domain. This software tool supports an online software laboratory in the digital signal processing class. The paper also provides examples of possible laboratory exercises.
A practical procedure for identifying time-varying nonlinear systems using basis sequence approximations
Authors: J. C. Ralston
Venue: Proceedings of the Acoustics, Speech, and Signal Processing, 1996. on Conference Proceedings., 1996 IEEE International Conference - Volume 05 (1996)

We approximate a class of time-varying nonlinear models, called the time-varying Hammerstein series, using basis sequences in order to reduce the number of coefficients required in system modelling. The problem is motivated by the practical need to parsimoniously characterise time-varying nonlinear systems. A significant advantage of the approach is that only a single input-output record is required to obtain least-squares estimates of the model parameters. The judicious selection of basis sequence is also discussed. The method represents a simple and practical time-varying nonlinear system identification procedure. Examples are presented to demonstrate the usefulness of the technique.
Active contours: an overview with applications to motion artifact cancellation in MRI
Authors: D. L. Guidry
Venue: Proceedings of the Acoustics, Speech, and Signal Processing, 1999. on 1999 IEEE International Conference - Volume 06 (1999)

Motion can be estimated by detecting the edges of a moving object using active contours, and registering them together to obtain the motion model parameters. This idea can be applied to patient motion during the acquisition of an MRI to eliminate motion artifacts in the image. The data obtained during the MRI acquisition, the k-space, can be divided into several subbands such that each subband is acquired in a small fraction of the full imaging time. These subbands create invariant tissue feature maps called subband images. Using active contours, the relative motion is analyzed across the different subband images to determine the motion parameters. Using these motion parameters it is possible to correct the subbands, thus correcting the k-space. This has the potential to yield clear, noise-free MR images.
Efficient Automatic Resolution of Encoding Conflicts Using STG Unfoldings
Authors: Victor Khomenko
Venue: Proceedings of the Seventh International Conference on Application of Concurrency to System Design (2007)

Synthesis of asynchronous circuits from Signal Transition Graphs (STGs) involves resolution of state encoding conflicts by means of refining the STG specification. In this paper, a fully automatic technique for resolving such conflicts by means of insertion of new signals is proposed. It is based on conflict cores, i.e., sets of transitions causing encoding conflicts, which are represented at the level of finite and complete unfolding prefixes, and a SAT solver is used to find where in the STG the transitions of new signals should be inserted. The experimental results show significant improvements over the state space based approach in terms of runtime and memory consumption, as well as some improvements in the quality of the resulting circuits.
Membrane Systems with Marked Membranes
Authors: Robert Brijder, Matteo Cavaliere, Agustín Riscos-Núòez, Grzegorz Rozenberg, Dragoş Sburlan
Venue: Electronic Notes in Theoretical Computer Science (ENTCS) (2007)

Membrane computing is a biologically inspired computational paradigm. Motivated by brane calculi we investigate membrane systems which differ from conventional membrane systems by the following features: (1) biomolecules (proteins) can move through the regions of the systems, and can attach onto (and de-attach from) membranes, and (2) membranes can evolve depending on the attached molecules. The evolution of membranes is performed by using rules that are motivated by the operation of pinocytosis (the pino rule) and the operation of cellular dripping (the drip rule) that take place in living cells. We show that such membrane systems are computationally universal. We also show that if only the second feature is used then one can generate at least the family of Parikh images of the languages generated by programmed grammars without appearance checking (which contains non-semilinear sets of vectors). If, moreover, the use of pino/drip rules is non-cooperative (i.e., not dependent on the proteins attached to membranes), then one generates a family of sets of vectors that is strictly included in the family of semilinear sets of vectors. We also consider a number of decision problems concerning reachability of configurations and boundness.