ppxscal/embedding_network huggingface dataset:
Resilient multi-core systems: a hierarchical formal model for N-variant executions
Authors: Axel Krings, Li Tan, Clinton Jeffery, Robert Rinker
Venue: Proceedings of the 5th Annual Workshop on Cyber Security and Information Intelligence Research: Cyber Security and Information Intelligence Challenges and Strategies (2009)

This research presents a hierarchical formal model capable of providing adjustable levels of service and quality of assurance, which is especially suitable for multi-core processor systems. The multi-layered architecture supports multiple levels of fault detection, masking, and dynamic load balancing. Unlike traditional fault-tolerant architectures that treat service requirements uniformly, each layer of the assured architecture implements a different level of services and information assurances. The system achieves load balancing by moving between layers of different complexity. Functionalities at different layers range from essential services necessary to satisfy the most stringent requirements for information assurance and system survivability at the lowest layer, to increasingly sophisticated functionalities with extended capabilities and complexity at higher layers. Low-layer functionalities can be used to monitor the behavior of high-layer functionalities. At each layer of the assured architecture, N-variant implementations make efficient use of multi-core hardware. The degree of the introduced redundancy in each layer determines the mix of faults that can be tolerated. The use of hybrid fault models allows us to consider fault types ranging from benign faults to Byzantine faults. Our framework extends recent work in N-variant systems for intrusion detection, which are demonstrated to be special cases. Furthermore, it allows the movement in a tradeoff space between (1) the levels of assurance provided at different layers, (2) the levels of redundancy used at specific layers, which determine the fault types that can be tolerated, and (3) the desired run-time overhead.
Research Article: A comparative study of the single crystal X-ray determination and molecular modelling of the binding of oligomycin to ATP Synthase
Authors: Roderic C. E. Green, Alfred E. Thumser, David Povey, José W. Saldanha, Brian S. Potter, Rex A. Palmer, Brendan J. Howlin
Venue: Computational Biology and Chemistry (2009)

Recently published X-ray structures of three common forms, A, B and C, of oligomycin, including absolute configurations, are investigated to examine their binding to ATP Synthase. The X-ray studies reveal regions with differences in three-dimensional structure and hydrogen bonding propensity between the oligomycins, which may be associated with their potential to bind to sites on ATP Synthase. Computational docking studies carried out using MOE with the X-ray structures and an homology model of the F"O domain of ATP Synthase from Escherichia coli, are used to derive an induced fit pocket. Docking of all oligomycins to this pocket indicate that the B and C forms bind more tightly than the A form. Consideration of the single crystal X-ray data alone indicate the B form may be the best inhibitor and that O(24) is the most important ligating group for binding, this is supported by the docking data. The latter reveals Asn214 and other key proton translocating residues to be the main residues contacted by the inhibitor. These data allow the binding modes of different forms of oligomycin to be deduced from X-ray single crystal data supported by molecular modelling and computational docking studies.
Using Data Accessibility for Resource Selection in Large-Scale Distributed Systems
Authors: Jinoh Kim, Abhishek Chandra, Jon B. Weissman
Venue: IEEE Transactions on Parallel and Distributed Systems (2009)

Large-scale distributed systems provide an attractive scalable infrastructure for network applications. However, the loosely coupled nature of this environment can make data access unpredictable, and in the limit, unavailable. We introduce the notion of accessibility to capture both availability and performance. An increasing number of data-intensive applications require not only considerations of node computation power but also accessibility for adequate job allocations. For instance, selecting a node with intolerably slow connections can offset any benefit to running on a fast node. In this paper, we present accessibility-aware resource selection techniques by which it is possible to choose nodes that will have efficient data access to remote data sources. We show that the local data access observations collected from a node's neighbors are sufficient to characterize accessibility for that node. By conducting trace-based, synthetic experiments on PlanetLab, we show that the resource selection heuristics guided by this principle significantly outperform conventional techniques such as latency-based or random allocations. The suggested techniques are also shown to be stable even under churn despite the loss of prior observations.
The superstar packing problem
Authors: Marek Janata, J&#x00e1;cint Szab&#x00f3;
Venue: Combinatorica (2009)

Hell and Kirkpatrick proved that in an undirected graph, a maximum size packing by a set of non-singleton stars can be found in polynomial time if this star-set is of the form {S 1, S 2, ..., S k } for some k&#x2208;&#x2124;+ (S i is the star with i leaves), and it is NP-hard otherwise. This may raise the question whether it is possible to enlarge a set of stars not of the form {S 1, S 2, ..., S k } by other non-star graphs to get a polynomially solvable graph packing problem. This paper shows such families of depth 2 trees. We show two approaches to this problem, a polynomial alternating forest algorithm, which implies a Berge-Tutte type min-max theorem, and a reduction to the degree constrained subgraph problem of Lov&#x00e1;sz.
A distributed ant-based algorithm for numerical optimization
Authors: Peter Korošec, Jurij Šilc
Venue: Proceedings of the 2009 workshop on Bio-inspired algorithms for distributed systems (2009)

This paper presents a new, distributed approach to the numerical optimization problem. The algorithm is based on ant-stigmergy metaheuristics, where indirect coordination between the ants drives the search procedure towards the optimal solution. Indirect coordination offers a high degree of parallelism and therefore a straightforward distributed implementation. For the communication between processes a MPICH2 for Windows library is used. The cost-function evaluation is an important part of the numerical optimization and is usually realized as a black-box simulator. Therefore, an algorithm analysis according to the simulator's time complexity is discussed.
Evidence for haptic memory
Authors: Ron Shih, Adam Dubrowski, Heather Carnahan
Venue: Proceedings of the World Haptics 2009 - Third Joint EuroHaptics conference and Symposium on Haptic Interfaces for Virtual Environment and Teleoperator Systems (2009)

The purpose of these experiments was to investigate the minimum duration of haptic memory representations. The term haptic memory can be defined as the ability to retain impressions of haptically acquired information after the original stimulus is absent. Participants repeatedly picked up objects of various masses. The time interval between the final practice lift of each object and a test lift was manipulated. In the 0 second delay condition, there was no delay between the release of the object after the final practice lift and the test lift. In the 2 and 10 second delay conditions there was a 2 or 10 second delay, respectively, between the release of the object after the last practice lift, and the test lift. Greater peak grip force was produced for the first lift compared to the subsequent practice lifts. In the 0 second delay condition, the peak grip force used in the test lift was similar to the last practice lift. As the delay increased to 10 seconds, the peak grip forces used were similar to that of the first lift. Even after a 2 second delay the peak grip force was greater than that of the last practice lift. Peak torque also followed these same patterns. The present results suggest that the haptic representation of object mass is short-lived (≪ 2 s) and has a duration and decay similar to visual iconic memory.
The QuALiM question answering demo: supplementing answers with paragraphs drawn from Wikipedia
Authors: Michael Kaisser
Venue: Proceedings of the 46th Annual Meeting of the Association for Computational Linguistics on Human Language Technologies: Demo Session (2008)

This paper describes the online demo of the QuALiM Question Answering system. While the system actually gets answers from the web by querying major search engines, during presentation answers are supplemented with relevant passages from Wikipedia. We believe that this additional information improves a user's search experience.
Optimization of Top-k Spatial Preference Queries' Execution Process Based on Similarity of Preferences
Authors: Marcin Gorawski, Kamil Dowlaszewicz
Venue: Proceeding of the 2008 conference on New Trends in Multimedia and Network Information Systems (2008)

A detailed description of top-k spatial preference queries and the schema of their execution will be presented. Then, it discusses existing R-tree based top-k spatial preference queries' execution algorithms and the optimization methods they utilize. Moreover, the paper presents a new optimization technique and an algorithm capable of utilizing it together with other methods. Finally, an analysis of proposed method's efficiency is presented.
Ancient buddhist, vedic and multiple intelligences pedagogies: a paradigm for the development of home schooling and distance learning environments
Authors: Lourdes Arguelles
Venue:  (2008)

There is a growing need in contemporary Western Buddhist communities for home schooling and distance learning. Religious, pedagogic, economic, geographic and security issues are motivating Western Buddhist parents to request and create home schooling and distance learning educational environments that will support Buddhist values and incorporate electronic technologies. In part, this increased need for home schooling and distance learning has intensified due to the increasing number of Westerners converting to Buddhism. These new Buddhist educational environments will require the integration of Buddhist values and practices with the demands of secular governments for standardized curriculum and evaluation practices. Multiple intelligence pedagogies, in a sense, are continuations of the ancient Vedic and Buddhist use of skillful means to meet the needs of a diverse population. This study argues that the integration of Buddhist, Vedic and Multiple Intelligence pedagogies will become a paradigm for the development of home schooling and learning environments is best based on the insights of practices derived from meditation practices. Buddhist sutras and shastras, mandalas, chanting, and skillful means practices, and an examination of theory and practice of education based on multiple intelligences. An integral part of this study is the development of a Moodle.com website shell, which can house an interactive model of a multimedia distance learning and home schooling 11th and 12th grade with a focus on psychology. This model curriculum is for an Introduction to Psychology course. This curriculum will be based on the content standards adopted by the State of California Board of Education and utilize traditional Buddhist pedagogies within a Multiple Intelligences and multimedia web environment. The study argues that such a distance learning and home schooling website will demonstrate a successful integration of traditional Buddhist pedagogy with contemporary Western pedagogies. The study also lays the groundwork for the development of a Buddhist Educational Network (TBEN). TBEN will be an educational intranet and internet-based pedagogic portal designed to serve the Western Buddhist communities. TBEN will also be available to non-Buddhist communities. TBEN offers a Buddhist-oriented Virtual Campus learning environment for distance learning and home schooling. Finally, this study includes and is largely based on an auto-ethnographic approach to my personal involvement with Vajrayana Buddhism.
Toward Fully Automatic Geo-Location and Geo-Orientation of Static Outdoor Cameras
Authors: Nathan Jacobs, Nathaniel Roman, Robert Pless
Venue: Proceedings of the 2008 IEEE Workshop on Applications of Computer Vision (2008)

Automating tools for geo-locating and geo-orienting static cameras is a key step in creating a useful global imaging network from cameras attached to the Internet. We present algorithms for partial camera calibration that rely on access to accurately time-stamped images captured over time from cameras that do not move. To support these algorithms we also offer a method of camera viewpoint change detection, or "tamper detection", which determines if a camera has moved in the challenging case when images are only captured every half hour. These algorithms are tested on a subset of the AMOS (Archive of Many Outdoor Scenes) database, and we present preliminary results that highlight the promise of these approaches.
Nonlinear Filtering and Smoothing: An Introduction to Martingales, Stochastic Integrals and Estimation
Authors: Venkatarama Krishnan
Venue:  (2005)

Appropriate for upper-level undergraduates and graduate students, this volume addresses the fundamental concepts of martingales, stochastic integrals, and estimation. Written by an engineer for engineers, it emphasizes applications. Many theorems feature heuristic proofs; others include rigorous proofs to reinforce physical understanding. Numerous end-of-chapter problems enhance the book's practical value.
“Counting Your Customers” One by One: A Hierarchical Bayes Extension to the Pareto/NBD Model
Authors: Makoto Abe
Venue: Marketing Science (2009)

This research extends a Pareto/NBD model of customer-base analysis using a hierarchical Bayesian (HB) framework to suit today's customized marketing. The proposed HB model presumes three tried and tested assumptions of Pareto/NBD models: (1) a Poisson purchase process, (2) a memoryless dropout process (i.e., constant hazard rate), and (3) heterogeneity across customers, while relaxing the independence assumption of the purchase and dropout rates and incorporating customer characteristics as covariates. The model also provides useful output for CRM, such as a customer-specific lifetime and survival rate, as by-products of the MCMC estimation. Using three different types of databases---music CD for e-commerce, FSP data for a department store and a music CD chain, the HB model is compared against the benchmark Pareto/NBD model. The study demonstrates that recency-frequency data, in conjunction with customer behavior and characteristics, can provide important insights into direct marketing issues, such as the demographic profile of best customers and whether long-life customers spend more.
A two-level implicit non-uniform mesh cubic spline method of O(k2h1-1+kh1+h13) for the parabolic equation Ɛuxx=φ(x,t,u,ux,ut)
Authors: R. K. Mohanty
Venue: Neural, Parallel Scientific Computations (2008)

We present a new two-level implicit high accuracy variable mesh cubic spline method for the non-linear parabolic partial differential equation Ɛuxx= φ(x, t, u, ux, ut), 0<x<1, t>0 subject to appropriate initial and Dirichlet boundary conditions prescribed, where Ɛ>0 is a small real constant. The proposed variable mesh approximation produces at each time level a cubic spline function which can be used to obtain the solution at any point in the range 0<x<1. The presented variable mesh strategy is applicable to parabolic equations in polar coordinates. In all the cases, we require only 3-spatial variable grid points. The stability analysis for diffusion equations on a non-uniform mesh shows that the linear cubic spline scheme is unconditionally stable. The advantage of using this new variable mesh method is highlighted computationally especially for better stability with a relatively large time step.
Technical Section: Estimating body shape of dressed humans
Authors: Nils Hasler, Carsten Stoll, Bodo Rosenhahn, Thorsten Thormählen, Hans-Peter Seidel
Venue: Computers and Graphics (2009)

The paper presents a method to estimate the detailed 3D body shape of a person even if heavy or loose clothing is worn. The approach is based on a space of human shapes, learned from a large database of registered body scans. Together with this database we use as input a 3D scan or model of the person wearing clothes and apply a fitting method, based on ICP (iterated closest point) registration and Laplacian mesh deformation. The statistical model of human body shapes enforces that the model stays within the space of human shapes. The method therefore allows us to compute the most likely shape and pose of the subject, even if it is heavily occluded or body parts are not visible. Several experiments demonstrate the applicability and accuracy of our approach to recover occluded or missing body parts from 3D laser scans.
Improving the performance of the random walk model for answering complex questions
Authors: Yllias Chali, Shafiq R. Joty
Venue: Proceedings of the 46th Annual Meeting of the Association for Computational Linguistics on Human Language Technologies: Short Papers (2008)

We consider the problem of answering complex questions that require inferencing and synthesizing information from multiple documents and can be seen as a kind of topic-oriented, informative multi-document summarization. The stochastic, graph-based method for computing the relative importance of textual units (i.e. sentences) is very successful in generic summarization. In this method, a sentence is encoded as a vector in which each component represents the occurrence frequency (TF*IDF) of a word. However, the major limitation of the TF*IDF approach is that it only retains the frequency of the words and does not take into account the sequence, syntactic and semantic information. In this paper, we study the impact of syntactic and shallow semantic information in the graph-based method for answering complex questions.
VC dimension and inner product space induced by Bayesian networks
Authors: Youlong Yang, Yan Wu
Venue: International Journal of Approximate Reasoning (2009)

Bayesian networks are graphical tools used to represent a high-dimensional probability distribution. They are used frequently in machine learning and many applications such as medical science. This paper studies whether the concept classes induced by a Bayesian network can be embedded into a low-dimensional inner product space. We focus on two-label classification tasks over the Boolean domain. For full Bayesian networks and almost full Bayesian networks with n variables, we show that VC dimension and the minimum dimension of the inner product space induced by them are 2^n-1. Also, for each Bayesian network N we show that VCdim(N)=Edim(N)=2^n^-^1+2^i if the network N^' constructed from N by removing X"n satisfies either (i) N^' is a full Bayesian network with n-1 variables, i is the number of parents of X"n, and i
A sparsity driven kernel machine based on minimizing a generalization error bound
Authors: Dori Peleg, Ron Meir
Venue: Pattern Recognition (2009)

A new sparsity driven kernel classifier is presented based on the minimization of a recently derived data-dependent generalization error bound. The objective function consists of the usual hinge loss function penalizing training errors and a concave penalty function of the expansion coefficients. The problem of minimizing the non-convex bound is addressed by a successive linearization approach, whereby the problem is transformed into a sequence of linear programs. The algorithm produced comparable error rates to the standard support vector machine but significantly reduced the number of support vectors and the concomitant classification time.
Exploiting N-best hypotheses for SMT self-enhancement
Authors: Boxing Chen, Min Zhang, Aiti Aw, Haizhou Li
Venue: Proceedings of the 46th Annual Meeting of the Association for Computational Linguistics on Human Language Technologies: Short Papers (2008)

Word and n-gram posterior probabilities estimated on N-best hypotheses have been used to improve the performance of statistical machine translation (SMT) in a rescoring framework. In this paper, we extend the idea to estimate the posterior probabilities on N-best hypotheses for translation phrase-pairs, target language n-grams, and source word reorderings. The SMT system is self-enhanced with the posterior knowledge learned from N-best hypotheses in a re-decoding framework. Experiments on NIST Chinese-to-English task show performance improvements for all the strategies. Moreover, the combination of the three strategies achieves further improvements and outperforms the baseline by 0.67 BLEU score on NIST-2003 set, and 0.64 on NIST-2005 set, respectively.
MEMS micro fluxgate sensors with mutual vertical excitation coils and detection coils
Authors: Chong Lei, Ren Wang, Yong Zhou, Zhimin Zhou
Venue: Microsystem Technologies (2009)

As a classic Earth magnetic field sensor, fluxgate magnetic sensors have great potential applications in many fields. This paper presents a new 3D micro-solenoid fluxgate magnetic sensor based on the MEMS technique. The excitation coils were placed vertically to the detection coils on the chip plane, around a rectangular shaped magnetic core. Polyimide was used to insulate coils and magnetic core. Width of copper conductor lines is 50&#x00a0;&#x03bc;m, and line space is 50&#x00a0;&#x03bc;m. The design of such fluxgate magnetic sensor followed second harmonic signal selecting method. Phase-lock amplifier was used to get second harmonic signal output by detection coils. The linear range of 0&#x2013;80&#x00a0;&#x03bc;T with sensitivity of 6.7&#x00a0;V/T was achieved from the fabricated sensor with excitation current of 430&#x00a0;mA and the operational frequency of 40&#x00a0;KHz. As the excitation current was 470&#x00a0;mA, linear range of 0&#x2013;50&#x00a0;&#x03bc;T with sensitivity of 21.7&#x00a0;V/T was achieved.
Facial Expression Recognition in Video Sequences
Authors: Shenchuan Tai, Hungfu Huang
Venue: Proceedings of the 6th International Symposium on Neural Networks: Advances in Neural Networks - Part III (2009)

This paper proposes asystem forthe facial expression recognition. Firstly, we perform noise reduction by a median filter of facial expression image. Then, a cross-correlation of optical flow and mathematical models from the facial points are used. To define these facial points of interest in the first frame of an input face sequence image, which utilize manually marker. The facial points were automatically tracked by a cross-correlation, which is based on optical flow,and then extracted the feature vectors. The mathematical model extracts features from the feature vectors. An ELMAN neural network was applied to classify expressions. The performances of the proposed facial expressions recognition were computed by Cohn---Kanade facial expressions database. This proposed approach achieved a high recognition rate.
Teachers Discovering Computers: Integrating Technology and Digital Media in the Classroom, 5th edition
Authors: Gary B. Shelly, Thomas J. Cashman, Glenda A. Gunter, Randolph E. Gunter
Venue: Shelly Cashman Series (2007)

This title covers up-to-date topics in computer concepts, Internet and digital media integration, interactivity, extraordinary visual drawings and photographs, and unprecedented currency.