ppxscal/embedding_network huggingface dataset:
A Combinatorial Approach to Genome-Wide Ortholog Assignment: Beyond Sequence Similarity Search
Authors: Tao Jiang
Venue: Proceedings of the 18th annual symposium on Combinatorial Pattern Matching (2007)

The assignment of orthologous genes between a pair of genomes is a fundamental and challenging problem in comparative genomics. Existing methods that assign orthologs based on the similarity between DNA or protein sequences may make erroneous assignments when sequence similarity does not clearly delineate the evolutionary relationship among genes of the same families. In this paper, we present a new approach to ortholog assignment that takes into account both sequence similarity and evolutionary events at genome level, where orthologous genes are assumed to correspond to each other in the most parsimonious evolving scenario under genome rearrangement and gene duplication. It is then formulated as a problem of computing the signed reversal distance with duplicates between two genomes of interest, for which an efficient heuristic algorithm was constructed based on solutions to two new optimization problems, minimum common partition and maximum cycle decomposition. Following this approach, we have implemented a high-throughput system for assigning orthologs on a genome scale, called MSOAR, and tested it on both simulated data and real genome sequence data. Our predicted orthologs between the human and mouse genomes are strongly supported by ortholog and protein function information in authoritative databases, and predictions made by other key ortholog assignment methods such as Ensembl, Homologene, INPARANOID, and HGNC. The simulation results demonstrate that MSOAR in general performs better than the iterated exemplar algorithm of D. Sankoff's in terms of identifying true exemplar genes.This is joint work with X. Chen (Nanyang Tech. Univ., Singapore), Z. Fu (UCR), J. Zheng (NCBI), V. Vacic (UCR), P. Nan (SCBIT), Y. Zhong (SCBIT), and S. Lonardi (UCR).
Ensemble of Dipolar Neural Networks in Application to Survival Data
Authors: Małgorzata Kretowska
Venue: Proceedings of the 9th international conference on Artificial Intelligence and Soft Computing (2006)

In the paper the ensemble of dipolar neural networks (EDNN) for analysis of survival data is proposed. The tool is build on the base of the learning sets, which contain the data from clinical studies following patients response for a given treatment. Such datasets may contain incomplete (censored) information on patients failure times. The proposed method is able to cope with censored observations and as the result returns the aggregated Kaplan-Meier survival function. The prediction ability of the received tool as well as the significance of individual features is verified by the Brier score, $\tilde{D}_{S,x}$ and $\hat{D}_x$ measures of predictive accuracy. 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
Agreement without knowing everybody: a first step to dynamicity
Authors: Mohssen Abboud, Carole Delporte-Gallet, Hugues Fauconnier
Venue: Proceedings of the 8th international conference on New technologies in distributed systems (2008)

We study in this paper the consensus problem in asynchronous models where the set of participating processes is not known. We prove that in this model the consensus is impossible to be solved even if no process may crash. We prove that the asynchronous model augmented with failure detector &Sigma;, which enables to realize a quorum, is sufficient to circumvent this impossibility result. For this, we present an algorithm solving the consensus problem in this model.
Aspect-Oriented Model Weaving Beyond Model Composition and Model Transformation
Authors: Pablo Sánchez, Lidia Fuentes, Dominik Stein, Stefan Hanenberg, Rainer Unland
Venue: Proceedings of the 11th international conference on Model Driven Engineering Languages and Systems (2008)

Research in Aspect-Oriented Software Development (AOSD) has brought up powerful abstractions in order to specify under which conditions an aspect affects the base software. So far, Model-Driven Development (MDD) approaches to AOSD have mostly concentrated on the weaving process and, as a result, they have come up with manifold ways to compose aspect models and base models. All too often, however, the approaches disregard the benefits that the aspect-oriented abstractions can bring to software development, though. This paper discusses the implications that such negligence has on the specification of aspect-oriented models in MDD. Furthermore, it presents a weaver that is able to cope with sophisticated join point selection abstractions, as they are known from many aspect-oriented programming languages, and which go far beyond the selection capabilities provided by current model weavers. By means of this weaver, models can realize both a higher separation of concerns as well as a higher level of abstraction.
Analysing High-Level Help-Seeking Behaviour in ITSs
Authors: Moffat Mathews, Tanja Mitrović, David Thomson
Venue: Proceedings of the 5th international conference on Adaptive Hypermedia and Adaptive Web-Based Systems (2008)

In this paper, we look at initial results of data mining students' help-seeking behaviour in two ITSs: SQL-Tutor and EER-Tutor. We categorised help given by these tutors into high-level (HLH) and low-level help (LLH), depending on the amount of help given. Each student was grouped into one of ten groups based on the frequency with which they used HLH. Learning curves were then plotted for each group. We asked the question, "Does a student's help-seeking behaviour (especially the frequency with which they use HLH) affect learning?" We noticed similarities between results for both tutors. Students who were very frequent users of HLH showed the lowest learning, both in learning rates and depth of knowledge. Students who were low to medium users of HLH showed the highest learning rates. Least frequent users of HLH had lower learning rates but showed higher depth of knowledge and a lower initial error rate, suggesting higher initial expertise. These initial results could suggest favouring pedagogical strategies that provide low to medium HLH to certain students.
Handling Linguistic Values in Knowledge Acquisition
Authors: Dae-Young Choi
Venue: Proceedings of the 8th international conference on Adaptive and Natural Computing Algorithms, Part I (2007)

An algorithmic approach for handling linguistic values defined in the same linguistic variable is proposed. It can explicitly capture the differences of individuals' subjectivity regarding linguistic values. The proposed approach can be employed as a useful tool for discovering hidden relationship among linguistic values. Thus, it provides a basis for improving the precision of knowledge acquisition in handling linguistic values. We apply the proposed approach to a collective linguistic assessment among multiple experts.
Dependencies in Structures of Decision Tables
Authors: Wojciech Ziarko
Venue: Proceedings of the international conference on Rough Sets and Intelligent Systems Paradigms (2007)

The presentation is focused on the introduction and the investigation of probabilistic dependencies between attribute-defined partitions of a universe in hierarchies of probabilistic decision tables learned from data. The dependencies are expressed through two measures: the probabilistic generalization of the Pawlak's measure of the dependency between attributes and the expected certainty gain measure. The expected certainty gain measure reflects the subtle grades of probabilistic dependence of events. The measures are reviewed and it is shown how they can be extended to dependencies existing in hierarchical structures of decision tables.
Multi-class Vehicle Type Recognition System
Authors: Xavier Clady, Pablo Negri, Maurice Milgram, Raphael Poulenard
Venue: Proceedings of the 3rd IAPR workshop on Artificial Neural Networks in Pattern Recognition (2008)

This paper presents a framework for multiclass vehicle type (Make and Model) identification based on oriented contour points. A method to construct a model from several frontal vehicle images is presented. Employing this model, three voting algorithms and a distance error allows to measure the similarity between an input instance and the data bases classes. These scores could be combined to design a discriminant function. We present too a second classification stage that employ scores like vectors. A nearest-neighbor algorithm is used to determine the vehicle type. This method have been tested on a realistic data set (830 images containing 50 different vehicle classes) obtaining similar results for equivalent recognition frameworks with different features selections [12]. The system also shows to be robust to partial occlusions.
Motion Detection Using Spiking Neural Network Model
Authors: Qingxiang Wu, T. M. Mcginnity, Liam Maguire, Jianyong Cai, G. D. Valderrama-Gonzalez
Venue: Proceedings of the 4th international conference on Intelligent Computing: Advanced Intelligent Computing Theories and Applications - with Aspects of Artificial Intelligence (2008)

Inspired by the behaviour of the human visual system, a spiking neural network is proposed to detect moving objects in a visual image sequence. The structure and the properties of the network are detailed in this paper. Simulation results show that the network is able to perform motion detection for dynamic visual image sequence. Boundaries of moving objects are extracted from an active neuron group. Using the boundary, a moving object filter is created to take the moving objects from the grey image. The moving object images can be used to recognise moving objects. The moving tracks can be recorded for further analysis of behaviours of moving objects. It is promising to apply this approach to video processing domain and robotic visual systems.
StreamKrimp: Detecting Change in Data Streams
Authors: Matthijs Leeuwen, Arno Siebes
Venue: Proceedings of the 2008 European Conference on Machine Learning and Knowledge Discovery in Databases - Part I (2008)

Data streams are ubiquitous. Examples range from sensor networks to financial transactions and website logs. In fact, even market basket data can be seen as a stream of sales. Detecting changes in the distribution a stream is sampled from is one of the most challenging problems in stream mining, as only limited storage can be used. In this paper we analyse this problem for streams of transaction data from an MDL perspective. Based on this analysis we introduce the StreamKrimp algorithm, whichuses the Krimp algorithm to characterise probability distributions with code tables. With these code tables, StreamKrimp partitions the stream into a sequence of substreams. Each switch of code table indicates a change in the underlying distribution. Experiments on both real and artificial streams show that StreamKrimp detects the changes while using only a very limited amount of data storage.
Communication-Aware Scheduling Algorithm Based on Heterogeneous Computing Systems
Authors: Youlin Ruan, Gan Liu, Jianjun Han, Qinghua Li
Venue: Proceedings of the 7th international conference on Computational Science, Part I: ICCS 2007 (2007)

This paper proposes a new scheduling model that integrates the communication awareness into task scheduling. A scheduling algorithm is proposed for the new model, which can produce optimal schedule by serializing the communications edges. Experiment results show the significantly improved accuracy and efficiency of the new model and algorithm.
Data-Driven Jacobian Adaptation in a Multi-model Structure for Noisy Speech Recognition
Authors: Yong-Joo Chung, Keun-Sung Bae
Venue: Proceedings of the 3rd Iberian conference on Pattern Recognition and Image Analysis, Part II (2007)

We propose a data-driven approach for the Jacobian adaptation (JA) to make it more robust against the noisy environments in speech recognition. The reference hidden Markov model (HMM) in the JA is trained directly with the noisy speech for improved acoustic modeling instead of using the model composition methods like the parallel model combination (PMC). This is made possible by estimating the Jacobian matrices and other statistical information for the adaptation using the Baum-Welch algorithm during the training. The adaptation algorithm has shown to give improved robustness especially when used in a multi-model structure. From the speech recognition experiments based on HMMs, we could find the proposed adaptation method gives better recognition results compared with conventional HMM parameter compensation methods and the multi-model approach could be a viable solution in the noisy speech recognition.
Providing Memory QoS Guarantees for Real-Time Applications
Authors: A. Marchand, P. Balbastre, I. Ripoll, A. Crespo
Venue: Proceedings of the 2008 14th IEEE International Conference on Embedded and Real-Time Computing Systems and Applications (2008)

Nowadays, systems often integrate a variety of applications whose service requirements are heterogeneous. Consequently, systems must be able to concurrently serve applications which rely on different constraints. This raises the problem of the dynamic distribution of the system resources (CPU, memory, network, etc.). Therefore, an integrated Quality of Service (QoS) management is needed so as to efficiently assign resources according to the various application demands. Within this paper, we focus on a dynamic approach of QoS management for memory resource allocation based on the Skip-Over model. We detail our solution and we show how it improves the service of task memory requests while providing them guarantees. Quantitative results using the TLSF allocator have been performed in order to evaluate the memory failure probability with and without memory QoS manager.
Applying Link Grammar Formalism in the Development of English-Indonesian Machine Translation System
Authors: Teguh Bharata Adji, Baharum Baharudin, Norshuhani Zamin
Venue: Proceedings of the 9th AISC international conference, the 15th Calculemas symposium, and the 7th international MKM conference on Intelligent Computer Mathematics (2008)

In this paper, we present a Machine Translation (MT) system from English to Indonesian by applying Link Grammar (LG) formalism. The Annotated Disjunct (ADJ) technique available in the LG formalism is utilized to map English sentences into equivalent Indonesian sentences. The ADJ is a promising technique to deal with target languages that do not have grammar formalism, parser, and corpus available like Indonesian language. An experimental evaluation shows that the applicability of LG for Indonesian language worked as expected. We have also discussed some significant issues to be considered in future development.
A post-processed 3D visualization tool for forest fire simulations
Authors: Alexandre Muzy, David RC Hill, Mathieu Joubert, Eric Innocenti
Venue: Proceedings of the 1st international conference on Simulation tools and techniques for communications, networks and systems & workshops (2008)

A collaboration between simulationists and scientists working on fire spread and ecology led to the design of a 3D visualization tool. This tool is a post-processor which can be linked to existing discrete event fire spread models. An object-oriented analysis and design has been retained to produce flexible open source software. The tool developed can produce realistic 3D landscape rendering of fire spread on regular PC. This software is now used in Corsica to help in prospective studies around the region of Montegrosso.
Local Topology of Social Network Based on Motif Analysis
Authors: Krzysztof Juszczyszyn, Przemysław Kazienko, Katarzyna Musiał
Venue: Proceedings of the 12th international conference on Knowledge-Based Intelligent Information and Engineering Systems, Part II (2008)

Network motifs --- small subgraphs that reflect local topology can be used to discover general profile and properties of the network. Analysis of motifs for the large social networks derived from email communication is presented in the paper. The distribution of motifs in all analyzed real social networks is very similar one another and can be treated as the network fingerprint. This property is most distinctive for stronger human relationships.
Simulation of the Effect of Intermittent Flow in Polycrystals on the Basis of Cellular Automata and Relaxation Element Method
Authors: Ye. Ye. Deryugin, G. V. Lasko, S. Schmauder
Venue: Proceedings of the 8th international conference on Cellular Automata for Reseach and Industry (2008)

The simulation of the effect of intermittent flow in polycrystals is performed on the basis of cellular automata and relaxation element method. Each cell (representing element of a structure) has an ability to switch its state by discrete jump in stresses (or plastic deformation), prescribed by a definite relaxation element which is put in the center of the cell. Interaction of the field of internal stresses from structural elements, undergone plastic deformation occurs automatically, following the superposition principle. The results are in a good agreement with known experimental findings.
Time-Area Optimized Public-Key Engines: $\mathcal{MQ}$-Cryptosystems as Replacement for Elliptic Curves?
Authors: Andrey Bogdanov, Thomas Eisenbarth, Andy Rupp, Christopher Wolf
Venue: Proceeding sof the 10th international workshop on Cryptographic Hardware and Embedded Systems (2008)

In this paper ways to efficiently implement public-key schemes based on ultivariate uadratic polynomials ($\mathcal{MQ}$-schemes for short) are investigated. In particular, they are claimed to resist quantum computer attacks. It is shown that such schemes can have a much better time-area product than elliptic curve cryptosystems. For instance, an optimised FPGA implementation of amended TTS is estimated to be over 50 times more efficient with respect to this parameter. Moreover, a general framework for implementing small-field $\mathcal{MQ}$-schemes in hardware is proposed which includes a systolic architecture performing Gaussian elimination over composite binary fields.
An IP and GEP Based Dynamic Decision Model for Stock Market Forecasting
Authors: Yuehui Chen, Qiang Wu, Feng Chen
Venue: Proceedings of the 4th international symposium on Neural Networks: Advances in Neural Networks (2007)

The forecasting models for stock market index using computational intelligence such as Artificial Neural networks(ANNs) and Genetic programming(GP), especially hybrid Immune Programming (IP) Algorithm and Gene Expression Programming(GEP) have achieved favorable results. However, these studies, have assumed a static environment. This study investigates the development of a new dynamic decision forecasting model. Application results prove the higher precision and generalization capacity of the predicting model obtained by the new method than static models.
Experiences with Application Development for Autonomic Networks
Authors: Karl-André Skevik, Matti Siekkinen, Vera Goebel, Thomas Plagemann
Venue: Proceedings of the 3rd IEEE international workshop on Modelling Autonomic Communications Environments (2008)

ANA is a project that examines legacy-free future networking architectures, with a focus on autonomicity. The programming model used in ANA dispenses with the rigid layers of the OSI model and instead uses bricks that can be combined to build a compartment offering the functionality required by an application. Restrictions such as TCP always being layered on top of IP do not exist, with e.g., arbitrary bricks offering transport functionality being usable to communicate with other nodes in a compartment. Application functionality is divided among specialized bricks, giving a clean and non-monolithic design. We have designed a P2P-like distributed streaming system from scratch, and designed an information sharing system by adapting an existing structured P2P system for ANA. In this paper, we report our experiences on the benefits and pitfalls of application and service development for ANA, and draw some conclusions on suitable design approaches for such novel "disruptive" network architectures.
An Evolutionary Algorithm with Diversified Crossover Operator for the Heterogeneous Probabilistic TSP
Authors: Yu-Hsin Liu, Rong-Chang Jou, Cheng-Chieh Wang, Ching-Shu Chiu
Venue: Proceedings of the 4th international conference on Modeling Decisions for Artificial Intelligence (2007)

This paper focuses on investigating the effectiveness of the diversified crossover (DCX) operator under an evolutionary algorithm framework to solve the PTSP. Different combinations of four well-performed crossover operators for the TSP/PTSP, i.e., edge recombination (ER) crossover, order crossover (OX), order based crossover (OBX), and position based crossover (PBX), were used to investigate its effects. A set of numerical experiments were conducted to test the validity of the proposed strategy based on 90 randomly generated test instances. The numerical results showed that the DCX operator, especially by combining ER and OX crossover operators, can most effectively solve heterogeneous PTSP in most of the tested instances in comparison with the single crossover operator used in most of the previous studies. These findings show the potential of merging the proposed DCX operator into the solution framework of evolutionary algorithm, genetic algorithm or memetic algorithm for effectively solving other complicated optimization problems.
Experience on the Air Force UNIVAC
Authors: Robert Kopp
Venue: Papers and discussions presented at the Dec. 8-10, 1953, eastern joint AIEE-IRE computer conference: information processing systems---reliability and requirements (1953)

The purpose of this paper is to discuss those factors the Air Force finds to have the most impact on electronic-computer reliability. In order to accomplish this purpose, I shall tell the story, in a general way, of the Air Force's experience with the UNIVAC for the past 18 months. During this time it has been under the sole control of the DCS/Comptroller, Headquarters, United States Air Force. I shall correlate these experiences with the reliability aspect of electronic computation.
Service License Composition and Compatibility Analysis
Authors: G. R. Gangadharan, Michael Weiss, Vincenzo D'Andrea, Renato Iannella
Venue: Proceedings of the 5th international conference on Service-Oriented Computing (2007)

Services enable the transformation of the World Wide Web as distributed interoperable systems interacting beyond organizational boundaries. Service licensing enables broader usage of services and a means for designing business strategies and relationships. A service license describes the terms and conditions for the use and access of the service in a machine interpretable way that services could be able to understand. Service-based applications are largely grounded on composition of independent services. In that scenario, license compatibility is a complex issue, requiring careful attention before attempting to merge licenses. The permissions and the prohibitions imposed by the licenses of services would deeply impact the composition. Thus, service licensing requires a comprehensive analysis on composition of these rights and requirements conforming to the nature of operations performed and compensation of services used in composition. In this paper, we analyze the compatibility of service license by describing a matchmaking algorithm. Further, we illustrate the composability of service licenses by creating a composite service license, that is compatible with the licenses being composed.