ppxscal/embedding_network huggingface dataset:
Homological illusions of persistence and stability
Authors: Herbert Edelsbrunner
Venue:  (2008)

In this thesis we explore and extend the theory of persistent homology, which captures topological features of a function by pairing its critical values. The result is represented by a collection of points in the extended plane called persistence diagram. We start with the question of ridding the function of topological noise as suggested by its persistence diagram. We give an algorithm for hierarchically finding such &epsiv;-simplifications on 2-manifolds as well as answer the question of when it is impossible to simplify a function in higher dimensions. We continue by examining time-varying functions. The original algorithm computes the persistence pairing from an ordering of the simplices in a triangulation and takes worst-case time cubic in the number of simplices. We describe how to maintain the pairing in linear time per transposition of consecutive simplices. A side effect of the update algorithm is an elementary proof of the stability of persistence diagrams. We introduce a parametrized family of persistence diagrams called persistence vineyards and illustrate the concept with a vineyard describing a folding of a small peptide. We also base a simple algorithm to compute the rank invariant of a collection of functions on the update procedure. Guided by the desire to reconstruct stratified spaces from noisy samples, we use the vineyard of the distance function restricted to a 1-parameter family of neighborhoods of a point to assess the local homology of a sampled stratified space at that point. We prove the correctness of this assessment under the assumption of a sufficiently dense sample. We also give an algorithm that constructs the vineyard and makes the local assessment in time at most cubic in the size of the Delaunay triangulation of the point sample. Finally, to refine the measurement of local homology the thesis extends the notion of persistent homology to sequences of kernels, images, and cokernels of maps induced by inclusions in a filtration of pairs of spaces. Specifically, we note that persistence in this context is well defined, we prove that the persistence diagrams are stable, and we explain how to compute them. Additionally, we use image persistence to cope with functions on noisy domains.
Navigation and Annotation with Formal Concept Analysis
Authors: Peter Eklund, Jon Ducrou
Venue: Knowledge Acquisition: Approaches, Algorithms and Applications: Pacific Rim Knowledge Acquisition Workshop, PKAW 2008, Hanoi, Vietnam, December 15-16, 2008, Revised Selected Papers (2009)

AnnotationSleuth is software to experiment with knowledge acquisition using Formal Concept Analysis (FCA). The system extends a standard search and browsing interface to feature a conceptual neighborhood centered on a formal concept derived from curatorial tags in a museum management system. The neighborhood of a concept is decorated with upper and lower neighbors in a concept lattice. Movement through the information space is achieved by the addition and removal of attributes resulting in more general and specialized formal concepts respectively. AnnotationSleuth employs several search methods: attribute search based on a control vocabulary, query refinement and query-by-example. A number of management interfaces are included to enable content to be added and tagged, the control vocabulary to be extended or conceptual scales to be defined. AnnotationSleuth, is an extensible environment for the creation of attribute lists and conceptual scales and can subsequently be used to flexibly navigate a collection of digital objects based on any user-defined semantic theme.
Predictive control of fast-sampled systems using the delta-operator
Authors: V. Kadirkamanathan, C. Halauca, S. R. Anderson
Venue: International Journal of Systems Science (2009)

This article formulates a δ-operator Generalised Predictive Control (GPC) framework for models described in state-space: an SS-delta-GPC algorithm. Currently such a description is unavailable, although similar approaches have been made from the perspective of using the discrete gradient approximations as an emulator of the continuous-time system. The SS-delta-GPC algorithm is demonstrated to improve on the round-off errors encountered when using the shift-operator under conditions of fast-sampling and finite word lengths.
File-system intrusion detection by preserving MAC DTS: a loadable kernel module based approach for LINUX kernel 2.6.x
Authors: Suvrojit Das, Arijit Chattopadhayay, Dipesh Kumar Kalyani, Monojit Saha
Venue: Proceedings of the 5th Annual Workshop on Cyber Security and Information Intelligence Research: Cyber Security and Information Intelligence Challenges and Strategies (2009)

Every operating system has its own set of critical files, whose access is generally protected by access control mechanisms, native to the operating system. The importance of such files also simultaneously invites their inspection, unauthorized modification and tampering. So, the need for preserving the authenticity of these critical files along with tracking any unauthorized access to them demands paramount importance. This addresses the need of a good file-system intrusion detection system which is capable of monitoring and tracking any accidental, benign, malicious, intentional changes made to the files that reside in the file-system. For any file the MAC DTS, i.e. the modification, access and creation date and timestamp is a major parameter which can be helpful in detecting any unauthorized access to the documents and monitoring file system intrusion in a broader perspective. So by preserving the MAC DTS we can gain crucial evidence about unauthorized access in the file system. This paper proposes one solution to preserve the MAC DTS for the LINUX operating system (kernel version 2.6.x) with pre-installed plug-ins in the form of Loadable Kernel Modules (LKM).
Supportive communication, sense of virtual community and health outcomes in online infertility groups
Authors: Jennifer L. Welbourne, Anita L. Blanchard, Marla D. Boughton
Venue: Proceedings of the fourth international conference on Communities and technologies (2009)

Women are turning to online health groups to deal with the stresses and complications of infertility. Online groups may provide a resource that is potentially absent in their face-to-face communities. This study examines how the sense of virtual community (SOVC) that develops in these groups serves as a buffer between perceived stress and physical health symptoms. A sample of 122 women from two virtual communities completed an online survey. Results show that observing the exchange of emotional support was positively related to SOVC while observing informational support was negatively related to SOVC. Further, SOVC was negatively related to physical health symptoms and additionally, served as a buffer between stress and physical health symptoms. Implications for SOVC and virtual health community research are discussed.
Hybrid difference schemes for a singularly perturbed second order ordinary differential equation with a discontinuous convection coefficient arising in chemical reactor theory
Authors: R. Mythili Priyadharshini, N. Ramanujam
Venue: Neural, Parallel Scientific Computations (2008)

In this paper, two hybrid difference schemes for singularly perturbed second order ordinary differential equations with a small parameter multiplying the highest derivative with a discontinuous convection coefficient are presented. Parameter-uniform error bounds for the numerical solution and numerical derivative are established. Numerical results are provided to illustrate the theoretical results.
Plenary lecture: advances in automated diagnostic systems
Authors: Elif Derya Ubeyli
Venue: Proceedings of the 10th WSEAS international conference on Neural networks (2009)

ANN models are computational modeling tools that have recently emerged and found extensive acceptance in many disciplines for modeling complex real-world problems. ANNs produce complicated nonlinear models relating the inputs (the independent variables of a system) to the outputs (the dependent predictive variables). ANNs are valuable tools in the medical field for the development of decision support systems. Important tools in modern decision-making, in any field, include those that allow the decision-maker to assign an object to an appropriate group, or classification. Clinical decision-making is a challenging, multifaceted process. Its goals are precision in diagnosis and institution of efficacious treatment. Achieving these objectives involves access to pertinent data and application of previous knowledge to the analysis of new data in order to recognize patterns and relations. Practitioners apply various statistical techniques in processing data to assist in clinical decision-making and to facilitate the management of patients. As the volume and complexity of data have increased, use of digital computers to support data analysis has become a necessity. In addition to computerization of standard statistical analysis, several other techniques for computer-aided data classification and reduction, generally referred to as ANN, have evolved. The ANN model discussed above has expanded in two directions. First, time series analysis and medical image analysis supply important parameters to medical decision making process and the parameters can be used as the input of the ANN model. The second direction of expansion includes databases available locally or through internet access. In the present study, advances in automated diagnostic systems will be presented.
Bayes-nash equilibria of the generalized second price auction
Authors: Renato D. Gomes, Kane S. Sweeney
Venue: Proceedings of the tenth ACM conference on Electronic commerce (2009)

We develop a Bayes-Nash analysis of the Generalized Second Price (GSP) auction. First, we characterize the efficient Bayes-Nash equilibrium of the GSP when such an equilibrium exists. We obtain sufficient conditions on click-through rates that guarantee existence and show that an efficient equilibrium may fail to exist if click-through rates across slots are sufficiently close. Next, we derive the counter-intuitive result that the seller's revenue may decrease as click-through rates increase. Fortunately, we show that setting optimal reserve prices reverses this result. Further, we prove that the GSP possesses no mixed strategy equilibrium and that no inefficient equilibrium can be symmetric.
From disease ontology to disease-ontology lite
Authors: Pan Du, Gang Feng, Jared Flatow, Jie Song, Michelle Holko, Warren A. Kibbe, Simon M. Lin
Venue: Bioinformatics (2009)

Subjective methods have been reported to adapt a general-purpose ontology for a specific application. For example, Gene Ontology (GO) Slim was created from GO to generate a highly aggregated report of the human-genome annotation. We propose statistical methods to adapt the general purpose, OBO Foundry Disease Ontology (DO) for the identification of gene-disease associations. Thus, we need a simplified definition of disease categories derived from implicated genes. On the basis of the assumption that the DO terms having similar associated genes are closely related, we group the DO terms based on the similarity of gene-to-DO mapping profiles. Two types of binary distance metrics are defined to measure the overall and subset similarity between DO terms. A compactness-scalable fuzzy clustering method is then applied to group similar DO terms. To reduce false clustering, the semantic similarities between DO terms are also used to constrain clustering results. As such, the DO terms are aggregated and the redundant DO terms are largely removed. Using these methods, we constructed a simplified vocabulary list from the DO called Disease Ontology Lite (DOLite). We demonstrated that DOLite results in more interpretable results than DO for gene-disease association tests. The resultant DOLite has been used in the Functional Disease Ontology (FunDO) Web application at http://www.projects.bioinformatics.northwestern.edu/fundo. Contact: s-lin2@northwestern.edu
On the significance of synchroneity in emergent systems
Authors: Adam Campbell, Annie S. Wu
Venue: Proceedings of The 8th International Conference on Autonomous Agents and Multiagent Systems - Volume 1 (2009)

The goal of this paper is to explore the effects of synchronization on distributed decision making processes. In particular, we examine the dynamics of a spatially distributed multiagent system where agents use local information to make role assignments. By investigating several role assignment procedures for this problem, we find that, in general, system stability increases as the number of agents that make a decision at any particular time decreases. This result is promising, because in a physical, distributed system the time at which agents make their decisions would most likely not be synchronized. Although the two decision making procedures examined in this paper are similar, their dynamics with respect to synchronization are very different. One shows a linear relationship between synchronization and system behavior, whereas a non-linear relationship is seen with the second method. We demonstrate the significance of synchroneity on the dynamics of these complex systems and argue that it should be taken into account when studying the behaviors of multi-agent systems that utilize emergent coordination.
The role of tag suggestions in folksonomies
Authors: Dirk Bollen, Harry Halpin
Venue: Proceedings of the 20th ACM conference on Hypertext and hypermedia (2009)

Most tagging systems support the user in the tag selection process by providing tag suggestions, or recommendations, based on a popularity measurement of tags other users provided when tagging the same resource. The majority of theories and mathematical models of tagging found in the literature assume that the emergence of power laws in tagging systems is mainly driven by the imitation behavior of users when observing tag suggestions provided by the user interface of the tagging system. We present experimental results that show that the power law distribution forms regardless of whether or not tag suggestions are presented to the users.
Internet Simplified
Authors: Paul McFedries
Venue:  (2009)

The content boom on the Internet has been explosive in the past few years with more than a billion people surfing worldwide. Internet Simplified shows beginning level computer users how to get comfortable surfing the web and how to navigate the flood of information once they find what they're looking for. Users will find helpful information on the most talked about newcomers to the online world such as social networking sites like Facebook and MySpace, blogging, and downloading media content from YouTube and iTunes, as well as an introduction to the old standbys such as email, auction sites, and instruction for safe surfing. Coverage on how to safeguard against viruses and SPAM and keep computers free from unwanted visitors is approached in a gentle, user-friendly manner so anyone can apply the techniques and be free from troublesome intrusions. Full-color screen shots and numbered, step-by-step instructions guide readers through the intricacies of navigating the web in a friendly, approachable way. The updated design features a more sophisticated look and larger fonts and images to make this a perfect reference for all ages.
Convex sets with semidefinite representation
Authors: Jean B. Lasserre
Venue: Mathematical Programming: Series A and B (2009)

We provide a sufficient condition on a class of compact basic semialgebraic sets $${{\bf K} \subset \mathbb{R}^n}$$for their convex hull co(K) to have a semidefinite representation (SDr). This SDr is explicitly expressed in terms of the polynomials g j that define K. Examples are provided. We also provide an approximate SDr; that is, for every fixed $${\epsilon > 0}$$, there is a convex set $${{\bf K}_\epsilon}$$such that $${{\rm co}({\bf K}) \subseteq {\bf K}_{\epsilon} \subseteq {\rm co}({\bf K}) + \epsilon {\bf B}}$$(where B is the unit ball of $${\mathbb{R}^n}$$), and $${{\bf K}_\epsilon}$$has an explicit SDr in terms of the g j &#x2019;s. For convex and compact basic semi-algebraic sets K defined by concave polynomials, we provide a simpler explicit SDr when the nonnegative Lagrangian L f associated with K and any linear $${f \in \mathbb{R}[X]}$$is a sum of squares. We also provide an approximate SDr specific to the convex case.
Facial Expression Recognition Based on FB2DPCA and Multi-classifier Fusion
Authors: Bin Hua, Ting Liu
Venue: Proceedings of the 2009 Second International Conference on Information and Computing Science - Volume 02 (2009)

A method of feature block two-dimensional principal component analysis (FB2DPCA) and multi-classifier combination is proposed for facial expression recognition. First, FB2DPCA is applied to extract human facial expression features, and then the expression classified result is obtained based on multi-classifier fusion with fuzzy integral. This proposed method is validated through the results of experiments on JAFFE facial expression database, and a high recognition rate is also achieved.
A-WING: an ad hoc wireless inter-network gateway
Authors: D. Brogan, I. Ganchev, M. O'Droma
Venue: International Journal of Network Management (2009)

This paper presents a design and implementation of a novel ad hoc wireless inter-network gateway and research platform (A-WING) which supports heterogeneous wireless and wired networking infrastructures and ad hoc wireless protocols. The driving goal is to explore and realize ways of increasing the 'always best connected' options for mobile wireless devices. The platform currently supports IEEE 802.11 (Wi-Fi), IEEE 802.3 (Ethernet), Bluetooth, IPv4, IPv6, broadcasting and multicasting, stream and datagram transport protocols. The gateway can be readily expanded by the addition of new functionality or support for other networking hardware. This functional variety and inbuilt extensibility ensures that A-WING can facilitate research into multi-mode multi-protocol wireless networking. The A-WING design is based on a new generic description of link layer services called the '9Cs' and includes a new method for the hierarchical description of networks incorporating nodes with multiple interfaces together with the development of a new XML schema for network, node and interface descriptive inter-nodal messaging.
The N-policy for an unreliable server with delaying repair and two phases of service
Authors: Gautam Choudhury, Jau-Chuan Ke, Lotfi Tadj
Venue: Journal of Computational and Applied Mathematics (2009)

This paper deals with an M^X/G/1 with an additional second phase of optional service and unreliable server, which consist of a breakdown period and a delay period under N-policy. While the server is working with any phase of service, it may break down at any instant and the service channel will fail for a short interval of time. Further concept of the delay time is also introduced. If no customer arrives during the breakdown period, the server becomes idle in the system until the queue size builds up to a threshold value N(>=1). As soon as the queue size becomes at least N, the server immediately begins to serve the first phase of regular service to all the waiting customers. After the completion of which, only some of them receive the second phase of the optional service. We derive the queue size distribution at a random epoch and departure epoch as well as various system performance measures. Finally we derive a simple procedure to obtain optimal stationary policy under a suitable linear cost structure.
A platform for the development and the validation of HWIP components starting from reference software specifications
Authors: Christophe Lucarz, Marco Mattavelli, Julien Dubois
Venue: EURASIP Journal on Embedded Systems (2008)

Signal processing algorithms become more and more efficient as a result of the developments of new standards. It is particularly true in the field video compression. However, at each improvement in efficiency and functionality, the complexity of the algorithms is also increasing. Textual specifications, that in the past were the original form of specifications, have been substituted by reference software which became the starting point of any design flow leading to implementation. Therefore, designing an embedded application has become equivalent to port a generic software on a, possibly heterogeneous, embedded platform. Such operation is getting more and more difficult because of the increased algorithm complexity and the wide range of architectural solutions. This paper describes a new platform aiming at supporting a step-by-step mapping of reference software (i.e., generic and nonoptimized software) into software and hardware implementations. The platform provides a seamless interface between the software and hardware environments with profiling capabilities for the analysis of data transfers between hardware and software. Such profiling capabilities help the designer to achieve different implementations aiming at specific objectives such as the optimization of hardware processing resources, of the memory architectures, or the minimization of data transfers to reach low-power designs.
Finding the Most Interesting Association Rules by Aggregating Objective Interestingness Measures
Authors: Tri Thanh Nguyen Le, Hiep Xuan Huynh, Fabrice Guillet
Venue: Knowledge Acquisition: Approaches, Algorithms and Applications: Pacific Rim Knowledge Acquisition Workshop, PKAW 2008, Hanoi, Vietnam, December 15-16, 2008, Revised Selected Papers (2009)

Association rule post-processing is a research challenge in KDD. In this post-processing task, objective interestingness measures are very useful for finding interesting rules possessing certain characteristics. Till now, the usual method for using objective interestingness measures is to select one or several suitable measures for filtering rules. This paper proposes a new approach to aggregate a set of interestingness measures using the Choquet integral as an advanced aggregation operator. Since an objective interestingness measure is considered as a point of view on rule quality, the aggregation of a set of objective interestingness measures can extract rules satisfying many points of view. The experiment is carried out on different groups (i.e. different natures) of objective interestingness measures to observe their behaviors.
Batch-Learning Self-Organizing Map for Predicting Functions of Poorly-Characterized Proteins Massively Accumulated
Authors: Takashi Abe, Shigehiko Kanaya, Toshimichi Ikemura
Venue: Proceedings of the 7th International Workshop on Advances in Self-Organizing Maps (2009)

As the result of the decoding of large numbers of genome sequences, numerous proteins whose functions cannot be identified by the homology search of amino acid sequences have accumulated and remain of no use to science and industry. Establishment of novel prediction methods for protein function is urgently needed. We previously developed Batch-Learning SOM (BL-SOM) for genome informatics; here, we developed BL-SOM to predict functions of proteins on the basis of similarity in oligopeptide composition of proteins. Oligopeptides are component parts of a protein and involved in formation of its functional motifs and structural parts. Concerning oligopeptide frequencies in 110,000 proteins classified into 2853 function-known COGs (clusters of orthologous groups), BL-SOM could faithfully reproduce the COG classifications, and therefore, proteins whose functions have been unidentified with homology searches could be related to function-known proteins. BL-SOM was applied to predict protein functions of large numbers of proteins obtained from metagenome analyses.