ppxscal/embedding_network huggingface dataset:
Supervised prediction of drug–target interactions using bipartite local models
Authors: Kevin Bleakley, Yoshihiro Yamanishi
Venue: Bioinformatics (2009)

Motivation:In silico prediction of drug–target interactions from heterogeneous biological data is critical in the search for drugs for known diseases. This problem is currently being attacked from many different points of view, a strong indication of its current importance. Precisely, being able to predict new drug–target interactions with both high precision and accuracy is the holy grail, a fundamental requirement for in silico methods to be useful in a biological setting. This, however, remains extremely challenging due to, amongst other things, the rarity of known drug–target interactions. Results: We propose a novel supervised inference method to predict unknown drug–target interactions, represented as a bipartite graph. We use this method, known as bipartite local models to first predict target proteins of a given drug, then to predict drugs targeting a given protein. This gives two independent predictions for each putative drug–target interaction, which we show can be combined to give a definitive prediction for each interaction. We demonstrate the excellent performance of the proposed method in the prediction of four classes of drug–target interaction networks involving enzymes, ion channels, G protein-coupled receptors (GPCRs) and nuclear receptors in human. This enables us to suggest a number of new potential drug–target interactions. Availability: An implementation of the proposed algorithm is available upon request from the authors. Datasets and all prediction results are available at http://cbio.ensmp.fr/~yyamanishi/bipartitelocal/. Contact: kevbleakley@gmail.com Supplementary information:Supplementary data are available at Bioinformatics online.
Adaptative User Interfaces to Promote Independent Ageing
Authors: Cecilia Vera-Muñoz, Mercedes Fernández-Rodríguez, Patricia Abril-Jiménez, María Fernanda Cabrera-Umpiérrez, María Teresa Arredondo, Sergio Guillén
Venue: Proceedings of the 5th International on ConferenceUniversal Access in Human-Computer Interaction. Part II: Intelligent and Ubiquitous Interaction Environments (2009)

During the last years, the EU population is experiencing an increasing aging process. This tendency is motivating the emergence of new needs and the appearance of diverse services and applications oriented improve the quality of life of senior citizens. The creation of such services requires the use of technological advances and design techniques specifically focused on addressing elderly requirements. This paper presents the adaptative user interfaces that have been developed in the context of an EU funded project, PERSONA, aiming to provide different services to promote independent aging.
Microarray Time-Series Data Clustering via Multiple Alignment of Gene Expression Profiles
Authors: Numanul Subhani, Alioune Ngom, Luis Rueda, Conrad Burden
Venue: Proceedings of the 4th IAPR International Conference on Pattern Recognition in Bioinformatics (2009)

Genes with similar expression profiles are expected to be functionally related or co-regulated. In this direction, clustering microarray time-series data via pairwise alignment of piece-wise linear profiles has been recently introduced. We propose a k-means clustering approach based on a multiple alignment of natural cubic spline representations of gene expression profiles. The multiple alignment is achieved by minimizing the sum of integrated squared errors over a time-interval, defined on a set of profiles. Preliminary experiments on a well-known data set of 221 pre-clustered Saccharomyces cerevisiae gene expression profiles yields excellent results with 79.64% accuracy.
Views on Fuzzy Sets and Systems from Different Perspectives: Philosophy and Logic, Criticisms and Applications, 1st edition
Authors: Rudolf Seising
Venue: Studies In Fuzziness And Soft Computing (2009)

In our new century, the theory of fuzzy sets and systems is in the core of "Soft Computing" and "Computational Intelligence" and has become a normal scientific theory in the fields of exact sciences and engineering and it is well on its way to becoming normal in the soft sciences as well. This book is a collection of the views of numerous scholars in different parts of the world who are involved in various research projects concerning fuzziness in science, technology, economic systems, social sciences, logics and philosophy. This volume demonstrates that there are many different views of the theory of fuzzy sets and systems and of their interpretation and applications in diverse areas of our cultural and social life. The ACM Portal is published by the Association for Computing Machinery. Copyright © 2010 ACM, Inc. Terms of Usage Privacy Policy Code of Ethics Contact Us Useful downloads: Adobe Acrobat QuickTime Windows Media Player Real Player
Modeling of Nonlinear Deformation Considering Temperature and Hydrostatic Pressure Using Genetic-Neural Networks
Authors: Bing-Rui Chen, Xia-Ting Feng, Cheng-Xiang Yang
Venue: Proceedings of the 2009 WASE International Conference on Information Engineering - Volume 01 (2009)

Combining genetic algorithms and artificial neural networks, a hybrid genetic-neural method was proposed for modeling the nonlinear dynamic deformation system considering the effect of environmental factors. This method describes the characteristic of nonlinear evolvement of deformation using ANN (the artificial neural network) whose structure (including nodes of input layer and hide layer) is automatically searched by GA (the genetic algorithm). The learning-samples and the testing-samples for training and testing the prediction function of ANN are made up of the input of ANN, which includes the temperature, the hydrostatic pressure and the time-series, while the desired output includes only the deformation. The ANN is trained by the learning-samples and is tested by the testing-samples. The practical example shows that the model constituted by this algorithm has more accurate predicting result and better predicting performance.
Combining Coarse-Grained Software Pipelining with DVS for Scheduling Real-Time Periodic Dependent Tasks on Multi-Core Embedded Systems
Authors: Hui Liu, Zili Shao, Meng Wang, Junzhao Du, Chun Jason Xue, Zhiping Jia
Venue: Journal of Signal Processing Systems (2009)

In this paper, we combine coarse-grained software pipelining with DVS (Dynamic Voltage/Frequency Scaling) for optimizing energy consumption of stream-based multimedia applications on multi-core embedded systems. By exploiting the potential of multi-core architecture and the characteristic of streaming applications, we propose a two-phase approach to solve the energy minimization problem for periodic dependent tasks on multi-core processors with discrete voltage levels. With our approach, in the first phase, we propose a coarse-grained task-level software pipelining algorithm called RDAG to transform the periodic dependent tasks into a set of independent tasks based on the retiming technique (Leiserson and Saxe, Algorithmica 6:5---35, 1991). In the second phase, we propose two DVS scheduling algorithms for energy minimization. For single-core processors, we propose a pseudo-polynomial algorithm based on dynamic programming that can achieve optimal solution. For multi-core processors, we propose a novel scheduling algorithm called SpringS which works like a spring and can effectively reduce energy consumption by iteratively adjusting task scheduling and voltage selection. We conduct experiments with a set of benchmarks from E3S (Dick 2008) and TGFF ( http://ziyang.ece.northwestern.edu/tgff/ ) based on the power model of the AMD Mobile Athlon4 DVS processor. The experimental results show that our technique can achieve 12.7% energy saving compared with the algorithms in Zhang et al. (2002) on average.
Filtering Spam in Social Tagging System with Dynamic Behavior Analysis
Authors: Bo Liu, Ennan Zhai, Huiping Sun, Yelu Chen, Zhong Chen
Venue: Proceedings of the 2009 International Conference on Advances in Social Network Analysis and Mining (2009)

Spam in social tagging systems introduced by some malicious participants has become a serious problem for its global popularizing. Some studies which can be deduced to static user data analysis have been presented to combat tag spam, but either they do not give an exact evaluation or the algorithms’ performances are not good enough. In this paper, we proposed a novel method based on analysis of dynamic user behavior data for the notion that users’ behaviors in social tagging system can reflect the quality of tags more accurately. Through modeling the different categories of participants’ behaviors, we extract tag-associated actions which can be used to estimate whether tag is spam, and then present our algorithm that can filter the tag spam in the results of social search. The experiment results show that our method indeed outperforms the existing methods based on static data and effectively defends against the tag spam in various spam attacks.
Combined Malicious Node Discovery and Self-Destruction Technique for Wireless Sensor Networks
Authors: Daniel-Ioan Curiac, Madalin Plastoi, Ovidiu Banias, Constantin Volosencu, Roxana Tudoroiu, Alexa Doboli
Venue: Proceedings of the 2009 Third International Conference on Sensor Technologies and Applications (2009)

With the continuous development of the wireless technology, securing wireless sensor networks became more and more a crucial but also a demanding task. In this paper we propose a combined strategy that is meant to discover malicious nodes within a wireless sensor network and to expel them from the network using a self-destruction node technique. Basically, we will compare every sensor reading with its estimated value provided by an autoregressive predictor. In case the difference between the two values is bigger then a chosen threshold, the sensor node becomes suspicious and a decision block is activated. If this block decides that the node is malicious, a self-destruction procedure will be started against that specific node.
Research on Double-Motor Synchronous System Based on AC Servo System
Authors: Shuanghui Hao, Jinghe Shi, Ruqi Ma, Minghui Hao
Venue: Proceedings of the 2009 International Conference on Measuring Technology and Mechatronics Automation - Volume 02 (2009)

Double-motor synchronous control system using master-slave structure based on AC servo system is researched in this paper. For the synchronous system, the instructions are input into the master system, and then the slave system can follow in time. In this paper, firstly, the advantages and disadvantages of double-motor system using master-slave structure are discussed. Then, the cumulated position error during the instructions transmission is resolved by translating the position or speed instructions into absolute position instructions, and the same period control strategy that mechanical cycle and current cycle is executed in one control cycle is also proposed, by which the instructions are executed synchronously. At last, the foundation of improved position control cycle and the influence of feed forward compensation are researched. The synchronous control system researched in this paper has simple structure, high response and extensive use.
Generating hard satisfiable formulas by hiding solutions deceptiveily
Authors: Haixia Jia, Cristopher Moore, Doug Strain
Venue: Proceedings of the 20th national conference on Artificial intelligence - Volume 1 (2005)

To test incomplete search algorithms for constraint satisfaction problems such as 3-SAT, we need a source of hard, but satisfiable, benchmark instances. A simple way to do this is to choose a random truth assignment A, and then choose clauses randomly from among those satisfied by A. However, this method tends to produce easy problems, since the majority of literals point toward the "hidden" assignment A. Last year, (Achlioptas, Jia, & Moore 2004) proposed a problem generator that cancels this effect by hiding both A and its complement A. While the resulting formulas appear to be just as hard for DPLL algorithms as random 3-SAT formulas with no hidden assignment, they can be solved by WalkSAT in only polynomial time. Here we propose a new method to cancel the attraction to A, by choosing a clause with t > 0 literals satisfied by A with probability proportional to qt for some q < 1. By varying q, we can generate formulas whose variables have no bias, i.e., which are equally likely to be true or false; we can even cause the formula to "deceptively" point away from A. We present theoretical and experimental results suggesting that these formulas are exponentially hard both for DPLL algorithms and for incomplete algorithms such as WalkSAT.
Leveraging Higher Order Dependencies between Features for Text Classification
Authors: Murat C. Ganiz, Nikita I. Lytkin, William M. Pottenger
Venue: Proceedings of the European Conference on Machine Learning and Knowledge Discovery in Databases: Part I (2009)

Traditional machine learning methods only consider relationships between feature values within individual data instances while disregarding the dependencies that link features across instances. In this work, we develop a general approach to supervised learning by leveraging higher-order dependencies between features. We introduce a novel Bayesian framework for classification named Higher Order Naive Bayes (HONB). Unlike approaches that assume data instances are independent, HONB leverages co-occurrence relations between feature values across different instances. Additionally, we generalize our framework by developing a novel data-driven space transformation that allows any classifier operating in vector spaces to take advantage of these higher-order co-occurrence relations. Results obtained on several benchmark text corpora demonstrate that higher-order approaches achieve significant improvements in classification accuracy over the baseline (first-order) methods.
Mining Phrases from Syntactic Analysis
Authors: Miloš Jakubíček, Aleš Horák, Vojtěch Kovář
Venue: Proceedings of the 12th International Conference on Text, Speech and Dialogue (2009)

In this paper we describe the exploitation of the syntactic parser synt to obtain information about syntactic structures (such as noun or verb phrases) of common sentences in Czech. These phrases/structures are from the analysis point of view usually identical to nonterminals in the grammar used by the parser to find possible valid derivations of the given sentence. The parser has been extended in such a way that enables its highly ambiguous output to be used for mining those phrases unambiguously and offers several ways how to identify them. To achieve this, some previously unused results of syntactic analysis have been evolved leading to more precise morphological analysis and hence also to deeper distinction among various syntactic (sub)structures. Finally, an application for shallow valency extraction and punctuation correction is presented.
Grouping MPI Processes for Partial Checkpoint and Co-migration
Authors: Rajendra Singh, Peter Graham
Venue: Proceedings of the 15th International Euro-Par Conference on Parallel Processing (2009)

When trying to use shared resources for parallel computing, performance guarantees cannot be made. When the load on one node increases, a process running on that node will experience slow down. This can quickly affect overall application performance. Slow running processes can be checkpointed and migrated to more lightly loaded nodes to sustain application performance. To do this, however, it must be possible to; 1) identify affected processes and 2) checkpoint and migrate them independently of other processes which will continue to run.A problem occurs when a slow running process communicates frequently with other processes. In such cases, migrating the single process is insufficient. The communicating processes will quickly block waiting to communicate with the migrating process preventing them from making progress. Also, if a process is migrated "far" from those it communicates with frequently, performance will be adversely affected.To address this problem, we present an approach to identify and group processes which we expect to be frequent communicators in the near future. Then, when one or more process is performing poorly, the entire group is checkpointed and co-migrated. This helps to improve overall application performance in shared resource environments.
GIS-Based Risk Assessment for Regional Flood Disaster
Authors: Zhang Hailin, Jie Yi, Zhang Xuesong, Jing Gaoliao, Yang Yi, He Baoyin
Venue: Proceedings of the 2009 International Conference on Environmental Science and Information Application Technology - Volume 02 (2009)

Based on the digital topographic map of 1/ 250000 scale, a primary assessment for flood risk in Hubei Province has been made by use of the strong function on space analysis and overlapping of GIS (Geographic Information System) platform. Firstly, through analysis and digitization, four raster coverages are obtained about the following factors that compose flood risk: precipitation, topography, water system (including rivers, lakes and reservoirs) and frequency of historical floods. Secondly, a map of assessment for flood risk in Hubei Province is made by overlapping these raster coverages of the four factors. Results show that, the flood risk is highest in Jianghan Plain and Xiangyang Plain, their risk classification value is 5; it is less high in the edge areas of the plain and low in hill areas, the risk classification value is 4; most part of the mountain areas in west, northeast and southeast of Hubei Province have relative lower flood risk of classification value 2; the high mountain area of Shenlongjia has lowest flood risk of classification value 1. The above result is agreed with the facts of flood disaster occurred in history.
A Conversation with David Shaw
Venue: Queue (2009)

In a rare interview, David Shaw discusses how he's using computer science to unravel the mysteries of biochemistry. Bonus: Listen to an audio clip of material not found in the text version.
CHAOS: A Data Stream Analysis Architecture for Enterprise Applications
Authors: Chetan Gupta, Song Wang, Ismail Ari, Ming Hao, Umeshwar Dayal, Abhay Mehta, Manish Marwah, Ratnesh Sharma
Venue: Proceedings of the 2009 IEEE Conference on Commerce and Enterprise Computing (2009)

In this paper, we describe the design of our architecture for Continuous, Heterogeneous Analysis Over Streams, aka CHAOS that combines stream processing, approximation techniques, mining, complex event processing and visualization. CHAOS, with the novel concept of Computational Stream Analysis Cube, provides an effective, scalable platform for near real time processing of business and enterprise streams. We describe our approach with a real data center temperature analysis application.
Complex text processing by the temporal context machines
Authors: Juyang Weng, Qi Zhang, Mingmin Chi, Xiangyang Xue
Venue: Proceedings of the 2009 IEEE 8th International Conference on Development and Learning (2009)

It is largely unknown how the brain deals with time. Hidden Markov Model (HMM) has a probability based mechanism to deal with time warping, but no effective online method exists that can deal with general active temporal abstraction. By online, we mean that the agent must respond to spatial and temporal context immediately while a sensory stream flows in. By general active temporal context, we mean active (learned) attention selects desirable temporal subsets within a dynamic length of recent history (e.g., beyond bigrams and trigrams). By temporal abstraction, we mean using abstract meaning of context, supervised at the motor end, instead of iconic forms. This paper reports four experiments of complex text processing using the framework of a general-purpose developmental spatiotemporal agent called Temporal Context Machines (TCM), demonstrating its power of forming online, active, abstract, temporal contexts. We show that it perfectly (100%) solved a hypothetic problem called New Sentence Problem — after the TCM has learned synonyms under the corresponding contexts, it successfully recognized all possible new sentences (formed from the synonyms) that it has not learned. We show the TCM dealt with the Word Sense Disambiguation Problem where words are ambiguous without context. TCMs were also applied to the Part-of-Speech Problem, where the part of speech of the words in English language is identified according to contexts. In the fourth experiment, TCMs were employed to deal with the challenging Chunking Problem, in which subsequences of words are grouped and classified according to English linguistic units.
Describing Dynamic Biological Systems in SPDL and SCDL
Authors: Charles C. N. Wang, David A. Hecht, Han C. W. Hsiao, Phillip C. Y. Sheu, Jeffrey J. P. Tsai
Venue: Proceedings of the 2009 Ninth IEEE International Conference on Bioinformatics and Bioengineering (2009)

Semantic Capability Description Language (SCDL) plays an important role as a common language and provides a generic format for problem formalization. In this paper we extend SCDL to include dynamic biological systems. A new process description language SPDL (Semantic Process Description Language) is presented and several queries as well as their corresponding SPDL descriptions are provided that are relevant to biological research. These include metabolic pathway searches and modeling of enzyme kinetics.
Building a Textual Entailment System for the RTE3 Competition. Application to a QA System
Authors: Adrian Iftene
Venue: Proceedings of the 2008 10th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing (2008)

Textual entailment recognition (RTE) is the task of deciding, when given two text fragments, whether the meaning of one text is entailed (can be inferred) from the other text. Last year, we built our first Textual Entailment (TE) system, with which we participated in the RTE3 competition. The main idea of this system is to transform the hypothesis making use of extensive semantic knowledge from sources like DIRT, WordNet, Wikipedia and acronyms database. Additionally, the system applies complex grammar rules for rephrasing in English and uses the results of a module we built to acquire the extra background knowledge needed. In the first part, we presented the system architecture and the results, whose best run ranked 3rd in RTE3 among 45 participating runs of 26 groups.The second part of the paper presents the manner in which we adapted the TE system in order to include it in a Question Answering (QA) system. The aim of using the TE system as a module in the general architecture of a QA system is to improve the ranking between possible answers for questions in which the answer type is Measure, Person, Location, Date and Organization.