ppxscal/embedding_network huggingface dataset:
Organization and integration of biomedical knowledge with concept maps for key peroxisomal pathways
Authors: A.M. Willemsen, G.A. Jansen, J.C. Komen, S. van Hooff, H.R. Waterham, P.M.T. Brites, R.J.A. Wanders, A.H.C. van Kampen
Venue: Bioinformatics (2008)

Motivation: One important area of clinical genomics research involves the elucidation of molecular mechanisms underlying (complex) disorders which eventually may lead to new diagnostic or drug targets. To further advance this area of clinical genomics one of the main challenges is the acquisition and integration of data, information and expert knowledge for specific biomedical domains and diseases. Currently the required information is not very well organized but scattered over biological and biomedical databases, basic text books, scientific literature and experts’ minds and may be highly specific, heterogeneous, complex and voluminous. Results: We present a new framework to construct knowledge bases with concept maps for presentation of information and the web ontology language OWL for the representation of information. We demonstrate this framework through the construction of a peroxisomal knowledge base, which focuses on four key peroxisomal pathways and several related genetic disorders. All 155 concept maps in our knowledge base are linked to at least one other concept map, which allows the visualization of one big network of related pieces of information. Availability: The peroxisome knowledge base is available from www.bioinformaticslaboratory.nl (Support → Web applications). Contact: a.h.vankampen@amc.uva.nl Supplementary information: Supplementary data is available from www.bioinformaticslaboratory.nl (Research → Output → Publications → KB_SuppInfo)
Fractional programming methodology for multi-attribute group decision-making using IFS
Authors: Deng-Feng Li, Yong-Chun Wang, Shu Liu, Feng Shan
Venue: Applied Soft Computing (2009)

Owing to more vague concepts frequently represented in decision data, mathematical objects introduced by K.T. Atanassov and studied under the name ''intuitionistic fuzzy set'' (IFS) are more flexibly used to model real-life decision situations. The aim of this paper is to develop a new methodology for solving multi-attribute group decision-making problems using IFS, in which multiple attributes are explicitly considered. In this methodology, for each decision maker in the group two auxiliary fractional programming models are derived from the TOPSIS to determine the relative closeness coefficient intervals of alternatives, which are aggregated for the group to generate the ranking order of all alternatives by computing their optimal degrees of membership based on the ranking method of interval numbers. The implementation process of the method proposed in this paper is illustrated with a numerical example.
Using Visualization Process Graphs to Improve Visualization Exploration
Authors: T. J. Jankun-Kelly
Venue: Provenance and Annotation of Data and Processes: Second International Provenance and Annotation Workshop, IPAW 2008, Salt Lake City, UT, USA, June 17-18, 2008. Revised Selected Papers (2008)

Visualization exploration is an iterative process of setting parameters, rendering, and evaluating results. This process can be recorded and analyzed in order to make visualization exploration more efficient and more effective. This work describes methods for visualizing the visualization process using new visualization process graphs; several visualization process relations are introduced to construct these graphs. These methods were used to analyze and improve a network routing visualization, and the results of this analysis are presented. Through this analysis, redundant exploration was quickly identified and eliminated.
Radar detection of wetland ecosystems: a review
Authors: Floyd M. Henderson, Anthony J. Lewis
Venue: International Journal of Remote Sensing (2008)

Periodically, reviews of our knowledge of radar-wetland relationships and detection parameters have been provided by various authors. Since the publication of these works, additional research has been completed. Five major remote sensing journals spanning the years 1965-2007 formed the basis of this review. The vast majority of significant material found its way into these mainstream journals in one aspect or another. A short history of Synthetic Aperture Radar (SAR)-wetlands discovery based on earlier reviews is followed by an update on radar-related wetland research. Although some trends emerged with regard to which wavelengths or polarizations to use, there was variation in optimum season/time of year and selection of multitemporal imagery. What is evident throughout the recent literature is that multidimensional radar data sets are attaining an accepted role in operational situations needing information on wetland presence, extent and conditions.
MetalDetector
Authors: Marco Lippi, Andrea Passerini, Marco Punta, Burkhard Rost, Paolo Frasconi
Venue: Bioinformatics (2008)

Summary: The web server MetalDetector classifies histidine residues in proteins into one of two states (free or metal bound) and cysteines into one of three states (free, metal bound or disulfide bridged). A decision tree integrates predictions from two previously developed methods (DISULFIND and Metal Ligand Predictor). Cross-validated performance assessment indicates that our server predicts disulfide bonding state at 88.6% precision and 85.1% recall, while it identifies cysteines and histidines in transition metal-binding sites at 79.9% precision and 76.8% recall, and at 60.8% precision and 40.7% recall, respectively. Availability: Freely available at http://metaldetector.dsi.unifi.it Contact: metaldetector@dsi.unifi.it Supplementary Information: Details and data can be found at http://metaldetector.dsi.unifi.it/help.php
Tag recommendations based on tensor dimensionality reduction
Authors: Panagiotis Symeonidis, Alexandros Nanopoulos, Yannis Manolopoulos
Venue: Proceedings of the 2008 ACM conference on Recommender systems (2008)

Social tagging is the process by which many users add metadata in the form of keywords, to annotate and categorize information items (songs, pictures, web links, products etc.). Collaborative tagging systems recommend tags to users based on what tags other users have used for the same items, aiming to develop a common consensus about which tags best describe an item. However, they fail to provide appropriate tag recommendations, because: (i) users may have different interests for an information item and (ii) information items may have multiple facets. In contrast to the current tag recommendation algorithms, our approach develops a unified framework to model the three types of entities that exist in a social tagging system: users, items and tags. These data is represented by a 3-order tensor, on which latent semantic analysis and dimensionality reduction is performed using the Higher Order Singular Value Decomposition (HOSVD) technique. We perform experimental comparison of the proposed method against two state-of-the-art tag recommendations algorithms with two real data sets (Last.fm and BibSonomy). Our results show significant improvements in terms of effectiveness measured through recall/precision.
An approach for promoting contribution in GAF-based ad hoc networks: design and implementation
Authors: Chalermek Intanagonwiwat, Sutthipong Lertmanorat
Venue: Proceedings of the 11th international symposium on Modeling, analysis and simulation of wireless and mobile systems (2008)

In wireless ad hoc networks, all nodes are routers that are required to forward packets for each other. Undoubtedly, nodes that forward more packets will run out of power before others will. To save energy, some nodes may become selfish and refuse to forward packets. As a result, the overall system performance will be degraded with the increased number of selfish nodes. This problem is more severe in networks that employ a wake-sleep schedule for energy savings (e.g., GAF-based networks). Even if a few of active nodes (leader nodes in GAF) are selfish, such a network may be virtually partitioned. Therefore, we propose two schemes to detect and to punish selfish nodes as well as to reduce the possibility of virtual network partition: SWD and GAFSWD. In SWD, only GAF-leader nodes are watchdogs. This watchdog concept is further developed into GAFSWD whereby non-leader nodes take turn to be additional watchdogs for detecting selfish nodes and to be candidates for alternative routes when needed. The results indicate that our schemes achieve significantly better fair ratio and delivery ratio while incurring small false conviction under investigated scenarios.
Efficient error recovery with network coding in underwater sensor networks
Authors: Zheng Guo, Bing Wang, Peng Xie, Wei Zeng, Jun-Hong Cui
Venue: Ad Hoc Networks (2009)

Before the wide deployment of underwater sensor networks becomes a reality, one challenge to be met is efficient error recovery in the presence of high error probability, long propagation delays and low acoustic bandwidth. We believe that network coding is a promising technique for this purpose due to Eq. (1) the computational capability of underwater sensor nodes, and Eq. (2) the broadcast nature of acoustic channels. In this paper, we propose an efficient error-recovery scheme that carefully couples network coding and multiple paths. Through an analytical study, we provide guidance on how to choose parameters in our scheme and demonstrate that the scheme is efficient in both error recovery and energy consumption. We evaluate the performance of this proposed scheme through simulation, and the simulation confirms the results from the analytical study.
Polynomials that Sign Represent Parity and Descartes' Rule of Signs
Authors: Saugata Basu, Nayantara Bhatnagar, Parikshit Gopalan, Richard J. Lipton
Venue: Computational Complexity (2008)

A real polynomial P(X 1, ... , X n ) sign represents f : A n ¿ {0, 1} if for every (a 1, ... , a n ) ¿ A n , the sign of P(a 1, ... ,a n ) equals $$(-1)^{f(a_{1}, \ldots ,a_{n})}$$ . Such sign representations are well-studied in computer science and have applications to computational complexity and computational learning theory. The work in this area aims to determine the minimum degree and sparsity possible for a polynomial that sign represents a function f. While the degree of such polynomials is relatively well-understood, far less is known about their sparsity. Known bounds apply only to the cases where A = {0, 1} or A = {¿1, +1}.In this work, we present a systematic study of tradeoffs between degree and sparsity of sign representations through the lens of the parity function. We attempt to prove bounds that hold for any choice of set A. We show that sign representing parity over {0,... , m ¿ 1} n with the degree in each variable at most m ¿ 1 requires sparsity at least m n . We show that a tradeoff exists between sparsity and degree, by exhibiting a sign representation that has higher degree but lower sparsity. We show a lower bound of n(m ¿ 2) + 1 on the sparsity of polynomials of any degree representing parity over {0,... ,m ¿ 1} n . We prove exact bounds on the sparsity of such polynomials for any two element subset A. The main tool used is Descartes' Rule of Signs, a classical result in algebra, relating the sparsity of a polynomial to its number of real roots. As an application, we use bounds on sparsity to derive circuit lower bounds for depth-two AND-OR-NOT circuits with a Threshold Gate at the top.
PuReD-MCL
Authors: T. Theodosiou, N. Darzentas, L. Angelis, C. A. Ouzounis
Venue: Bioinformatics (2008)

Motivation: Biomedical literature is the principal repository of biomedical knowledge, with PubMed being the most complete database collecting, organizing and analyzing such textual knowledge. There are numerous efforts that attempt to exploit this information by using text mining and machine learning techniques. We developed a novel approach, called PuReD-MCL (Pubmed Related Documents-MCL), which is based on the graph clustering algorithm MCL and relevant resources from PubMed. Methods: PuReD-MCL avoids using natural language processing (NLP) techniques directly; instead, it takes advantage of existing resources, available from PubMed. PuReD-MCL then clusters documents efficiently using the MCL graph clustering algorithm, which is based on graph flow simulation. This process allows users to analyse the results by highlighting important clues, and finally to visualize the clusters and all relevant information using an interactive graph layout algorithm, for instance BioLayout Express 3D. Results: The methodology was applied to two different datasets, previously used for the validation of the document clustering tool TextQuest. The first dataset involves the organisms Escherichia coli and yeast, whereas the second is related to Drosophila development. PuReD-MCL successfully reproduces the annotated results obtained from TextQuest, while at the same time provides additional insights into the clusters and the corresponding documents. Availability: Source code in perl and R are available from http://tartara.csd.auth.gr/~theodos/ Contact: theodos@csd.auth.gr
A Multi-Versioning Scheme for Intention Preservation in Collaborative Editing Systems*
Authors: Liyin Xue, Mehmet A. Orgun, Kang Zhang
Venue: Computer Supported Cooperative Work (2008)

Although the multi-version approach to consistency maintenance has been widely discussed and implemented in database systems, version control systems, and asynchronous groupware systems, its potential in real-time groupware systems is largely unexplored. Intention preservation is an important aspect of consistency maintenance in real-time collaborative editing systems, where multiple users cooperate with each other by concurrently editing the same document. The multi-version approach is supposed to be able to preserve individual users' concurrent conflicting intentions. In this article, we propose a new multi-versioning scheme that can preserve not only concurrent conflicting intentions but also contextual intentions while achieving convergence of the document under editing. By extending an existing multi-versioning scheme to a general one that specifies the conditions for convergence, we decouple the discussion of convergence from that of intention preservation. By constraining the general scheme, we arrive at the novel scheme that guarantees to preserve users' intentions. The correctness of the scheme has been formally verified. The design of an algorithm for consistent version composition and identification has been discussed in detail.
Using genetic algorithm to select the presentation order of training patterns that improves simplified fuzzy ARTMAP classification performance
Authors: Ramaswamy Palaniappan, Chikkanan Eswaran
Venue: Applied Soft Computing (2009)

The presentation order of training patterns to a simplified fuzzy ARTMAP (SFAM) neural network affects the classification performance. The common method to solve this problem is to use several simulations with training patterns presented in random order, where voting strategy is used to compute the final performance. Recently, an ordering method based on min-max clustering was introduced to select the presentation order of training patterns based on a single simulation. In this paper, another single simulation method based on genetic algorithm is proposed to obtain the presentation order of training patterns for improving the performance of SFAM. The proposed method is applied to a 40-class individual classification problem using visual evoked potential signals and three other datasets from UCI repository. The proposed method has the advantages of improved classification performance, smaller network size and lower training time compared to the random ordering and min-max methods. When compared to the random ordering method, the new ordering scheme has the additional advantage of requiring only a single simulation. As the proposed method is general, it can also be applied to a fuzzy ARTMAP neural network when it is used as a classifier.
Comparison of MODIS and Landsat TM5 images for mapping tempo-spatial dynamics of Secchi disk depths in Poyang Lake National Nature Reserve, China
Authors: GuofenG Wu, Jan De Leeuw, Andrew K. Skidmore, Herbert H. T. Prins, Yaolin Liu
Venue: International Journal of Remote Sensing (2008)

Landsat has successfully been applied to map Secchi disk depth of inland water bodies. Operational use for monitoring a dynamic variable like Secchi disk depth is however limited by the 16-day overpass cycle of the Landsat system and cloud cover. Low spatial resolution Moderate Resolution Imaging Spectroradiometer (MODIS) image captured twice a day could potentially overcome these problems. However, its potential for mapping Secchi disk depth of inland water bodies has so far rarely been explored. This study compared two image sources, MODIS and Landsat Thematic Mapper (TM), for mapping the tempo-spatial dynamics of Secchi disk depth in Poyang Lake National Nature Reserve, China. Secchi disk depths recorded at weekly intervals from April to October in 2004 and 2005 were related to 5 Landsat TM and 22 MODIS images respectively. Two multiple regression models including the blue and red bands of Landsat TM and MODIS respectively explained 83% and 88% of the variance of the natural logarithm of Secchi disk depth. The standard errors of the predictions were 0.20 and 0.37 m for Landsat TM and MODIS-based models. A high correlation (r = 0.94) between the predicted Secchi disk depth derived from the two models was observed. A discussion of advantages and disadvantages of both sensors leads to the conclusion that MODIS offers the possibility to monitor water transparency more regularly and cheaply in relatively big and frequently cloud covered lakes as is with Poyang Lake.
Modeling, simulation and optimal control for an aircraft of aileron-less folding wing
Authors: Zheng Jie Wang, Shijun Guo, Wei Li
Venue: WSEAS Transactions on Systems and Control (2008)

The purpose of this paper is to discuss the method of modeling and control system design for a loitering aircraft of aileron-less folding wing. A nonlinear model of the aircraft was established, and then linearized by small disturbance method. The lateral-directional stability augmentation options were analyzed through the root locus plots. The pole placement method based on linear quadratic regulator (LQR) technology was used to achieve desirable dynamic characteristics. In the analysis, the state parameters which represent rapid oscillation states of the aircraft such as roll rate and yaw rate were set as primary control parameters in the inner loop. The states oscillated slowly such as rolling angle and yaw angle were set as main control parameters in the outer loop. Based on the self-organizing fuzzy control algorithm, the aircraft can be controlled to fly in a desired path. Two types of course control plan were investigated and verified. The results show that the control plans are feasible and the control system is adequately robust to meet the requirements of the course control.
The prospects for psychological science in human-computer interaction
Authors: Allen Newell, Stuart K. Card
Venue: Human-computer interaction (1985)

This paper discusses the prospects of psychology playing a significant role in the progress of human-computer interaction. In any field, hard science (science that is mathematical or otherwise technical) has a tendency to drive out softer sciences, even if the softer sciences have important contributions to make. It is possible that, as computer science and artificial intelligence contributions to human-computer interaction mature, this could happen to psychology. It is suggested that this trend might be prevented by hardening the applicable psychological science. This approach, however, has been critized on the grounds that the resulting body of knowledge would be too low level, too limited in scope, too late to affect computer technology, and too difficult to apply. The prospects for overcoming each of these obstacles are analyzed here.
Mining significant tree patterns in carbohydrate sugar chains
Authors: Kosuke Hashimoto, Ichigaku Takigawa, Motoki Shiga, Minoru Kanehisa, Hiroshi Mamitsuka
Venue: Bioinformatics (2008)

Motivation: Carbohydrate sugar chains or glycans, the third major class of macromolecules, hold branch shaped tree structures. Glycan motifs are known to be two types: (1) conserved patterns called ‘cores’ containing the root and (2) ubiquitous motifs which appear in external parts including leaves and are distributed over different glycan classes. Finding these glycan tree motifs is an important issue, but there have been no computational methods to capture these motifs ef.ciently. Results: We have developed an ef.cient method for mining motifs or significant subtrees from glycans. The key contribution of this method is: (1) to have proposed a new concept, ‘á-closed frequent subtrees’, and an ef.cient method for mining all these subtrees from given trees and (2) to have proposed to apply statistical hypothesis testing to rerank the frequent subtrees in signi.cance. We experimentally veri.ed the effectiveness of the proposed method using real glycans: (1)We examined the top 10 subtrees obtained by our method at some parameter setting and con.rmed that all subtrees are significant motifs in glycobiology. (2) We applied the results of our method to a classi.cation problem and found that our method outperformed other competing methods, SVM with three different tree kernels, being all statistically significant. Contact: mami@kuicr.kyoto-u.ac.jp Supplementary information: Supplementary data are available at Bioinformatics online.
Geometry, Student Edition, 1 edition
Authors: McGraw-Hill
Venue:  (2007)

THE PROGRAM STUDENTS NEED; THE FOCUS TEACHERS WANT! Glencoe Geometry is a key program in our vertically aligned high school mathematics series developed to help all students achieve a better understanding of mathematics and improve their mathematics scores on todays high-stakes assessments.
A direct-construction approach to multidimensional realization and LFR uncertainty modeling
Authors: Li Xu, Huijin Fan, Zhiping Lin, N. K. Bose
Venue: Multidimensional Systems and Signal Processing (2008)

This article proposes a direct-construction realization procedure that simultaneously treats all the involved variables and/or uncertain parameters and directly generates an overall multidimensional (n-D) Roesser model realization or linear fractional representation (LFR) model for a given n-D polynomial or causal rational transfer matrix. It is shown for the first time that the realization problem for an n-D transfer matrix G(z 1, . . . , z n ), which is assumed without loss of generality to be strictly causal and given in the form of G(z 1, . . . , z n )=N r (z 1, . . . , z n )D r ¿1 (z 1,..., z n ) with D r (0, . . . , 0)=I and N r (0, . . . , 0) = 0, can be essentially reduced to the construction of an admissible n-D polynomial matrix ¿ for which there exist real matrices A, B, C such that N r (z 1, . . . , z n ) = CZ¿ and ¿ D r ¿1 (z 1, . . . , z n ) = (I ¿ AZ)¿1 B with Z being the corresponding variable and/or uncertainty block structure, i.e., $${Z={\rm diag} \{z_1I_{r_1},\ldots,z_nI_{r_n} \}}$$ . This important fact reveals a substantial difference between the 1-D and n-D (n ¿ 2) realization problems as in the 1-D case ¿ can only be a monomial matrix and never a polynomial one. Necessary and sufficient conditions for ¿ to satisfy the above restrictions are given and algorithms are proposed for the construction of such an admissible n-D polynomial matrix ¿ with low order (for an arbitrary but fixed field of coefficients) and the corresponding realization. Symbolic and numerical examples are presented to illustrate the basic ideas as well as the effectiveness of the proposed procedure.