Aygul Jamal, M. Baboulin, Amal Khabou, M. Sosonkina
We illustrate how the distributed parallel Algebraic Recursive Multilevel Solver based on MPI can be adapted for heterogeneous CPU/GPU architectures. The tasks performed on the GPU are related to the preconditioning of each part of the distributed matrix (local preconditioning) which is handled in the distributed version by each MPI process. The solving step remains on the CPU. In our implementation, the local preconditioning can be based either on the randomization of the last Schur complement system in the multilevel recursive process, or on an Incomplete LU factorization from the MAGMA library. Numerical experiments show that a promising performance improvement can be obtained using either randomized multilevel recursive preconditioning or Incomplete LU preconditioning for large enough matrices. Each preconditioning method ensures a good performance for a given set of matrices.
{"title":"A Hybrid CPU/GPU Approach for the Parallel Algebraic Recursive Multilevel Solver pARMS","authors":"Aygul Jamal, M. Baboulin, Amal Khabou, M. Sosonkina","doi":"10.1109/SYNASC.2016.069","DOIUrl":"https://doi.org/10.1109/SYNASC.2016.069","url":null,"abstract":"We illustrate how the distributed parallel Algebraic Recursive Multilevel Solver based on MPI can be adapted for heterogeneous CPU/GPU architectures. The tasks performed on the GPU are related to the preconditioning of each part of the distributed matrix (local preconditioning) which is handled in the distributed version by each MPI process. The solving step remains on the CPU. In our implementation, the local preconditioning can be based either on the randomization of the last Schur complement system in the multilevel recursive process, or on an Incomplete LU factorization from the MAGMA library. Numerical experiments show that a promising performance improvement can be obtained using either randomized multilevel recursive preconditioning or Incomplete LU preconditioning for large enough matrices. Each preconditioning method ensures a good performance for a given set of matrices.","PeriodicalId":268635,"journal":{"name":"2016 18th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing (SYNASC)","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-09-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116699190","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This paper is about copying on artificial agents humans’ perception of time and their ability to producecondensed short stories out of large free texts. We propose a model intended to objectivize processes that help to achievethis reasoning behaviour on machines.
{"title":"The Time Yards Model - Rethinking the Way to Look at Texts","authors":"D. Cristea","doi":"10.1109/SYNASC.2016.016","DOIUrl":"https://doi.org/10.1109/SYNASC.2016.016","url":null,"abstract":"This paper is about copying on artificial agents humans’ perception of time and their ability to producecondensed short stories out of large free texts. We propose a model intended to objectivize processes that help to achievethis reasoning behaviour on machines.","PeriodicalId":268635,"journal":{"name":"2016 18th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing (SYNASC)","volume":"36 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117346738","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
S. Dellacherie, E. Jamelot, O. Lafitte, R. Mouhamad
We obtain an analytic solution of a monodimensionalstationary system coupling two simplified models, one solving the thermohydraulic equations, the other onesolving the neutronic diffusion equation with one energygroup (characterized by the diffusion coefficient, the absorptionand the fission cross sections which are assumed to dependonly on temperature). This analytic solution relies on theconstruction of two auxiliary functions. Realistic values of thecross sections (given at some values of the temperature) yield, by interpolation, approximate expressions for the cross sections. Projection of these functions on a 2d space using finite elementmethod leads to a approximate simplified ODE, from whichone deduces an approximation of the analytic solution usingincomplete Jacobi elliptic integrals.
{"title":"Numerical Results for the Coupling of a Simple Neutronics Diffusion Model and a Simple Hydrodynamics Low Mach Number Model without Coupling Codes","authors":"S. Dellacherie, E. Jamelot, O. Lafitte, R. Mouhamad","doi":"10.1109/SYNASC.2016.030","DOIUrl":"https://doi.org/10.1109/SYNASC.2016.030","url":null,"abstract":"We obtain an analytic solution of a monodimensionalstationary system coupling two simplified models, one solving the thermohydraulic equations, the other onesolving the neutronic diffusion equation with one energygroup (characterized by the diffusion coefficient, the absorptionand the fission cross sections which are assumed to dependonly on temperature). This analytic solution relies on theconstruction of two auxiliary functions. Realistic values of thecross sections (given at some values of the temperature) yield, by interpolation, approximate expressions for the cross sections. Projection of these functions on a 2d space using finite elementmethod leads to a approximate simplified ODE, from whichone deduces an approximation of the analytic solution usingincomplete Jacobi elliptic integrals.","PeriodicalId":268635,"journal":{"name":"2016 18th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing (SYNASC)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130368177","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Satisfiability Checking is a relatively young research area, aiming at the development of efficient software technologies for checking the satisfiability of existentially quantified logical formulas. Besides the success story of SAT solving for propositional logic, SAT-modulo-theories (SMT) solvers offer sophisticated solutions for different theories. When targeting arithmetic theories, SMT solvers also make use of decision procedures rooted in Symbolic Computation. In this paper we give a brief introduction to SMT solving, discuss differences to Symbolic Computation, and illustrate the potentials and obstacles for embedding Symbolic Computation techniques in SMT solving on the example of the Cylindrical Algebraic Decomposition.
{"title":"Symbolic Computation Techniques in Satisfiability Checking","authors":"E. Ábrahám","doi":"10.1109/SYNASC.2016.014","DOIUrl":"https://doi.org/10.1109/SYNASC.2016.014","url":null,"abstract":"Satisfiability Checking is a relatively young research area, aiming at the development of efficient software technologies for checking the satisfiability of existentially quantified logical formulas. Besides the success story of SAT solving for propositional logic, SAT-modulo-theories (SMT) solvers offer sophisticated solutions for different theories. When targeting arithmetic theories, SMT solvers also make use of decision procedures rooted in Symbolic Computation. In this paper we give a brief introduction to SMT solving, discuss differences to Symbolic Computation, and illustrate the potentials and obstacles for embedding Symbolic Computation techniques in SMT solving on the example of the Cylindrical Algebraic Decomposition.","PeriodicalId":268635,"journal":{"name":"2016 18th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing (SYNASC)","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124055390","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This paper investigates the use of genetic algorithms in conjunction with the WRF - Weather Research and Forecast numerical weather prediction system in order to optimize the physical parametrization configuration and to improve the forecast of two important atmospheric parameters: 2 meter temperature and relative humidity. Our research showed good results in improving the average prediction error in limited amount of iterations and this could prove helpful in building GA optimized ensemble forecasts, especially when focusing on specific atmospheric parameters. The optimization process performed well in finding optimal physical configurations for humidity prediction, but showed poor results for temperature forecast, more experiments need to be conducted in order to have a clear view over the utility of using GA techniques for physical parametrization optimization.
本文研究了遗传算法与WRF - Weather Research and Forecast数值天气预报系统的结合，以优化物理参数化配置并改进对2米温度和相对湿度两个重要大气参数的预报。我们的研究表明，在有限的迭代次数下，平均预测误差得到了很好的改善，这对构建遗传算法优化的集合预测有帮助，特别是当关注特定的大气参数时。优化过程在寻找湿度预测的最佳物理配置方面表现良好，但在温度预测方面表现不佳，需要进行更多的实验以清楚地了解使用遗传算法进行物理参数优化的效用。
{"title":"Use of Genetic Algorithms in Numerical Weather Prediction","authors":"Liviu Oana, Adrian F. Spataru","doi":"10.1109/SYNASC.2016.075","DOIUrl":"https://doi.org/10.1109/SYNASC.2016.075","url":null,"abstract":"This paper investigates the use of genetic algorithms in conjunction with the WRF - Weather Research and Forecast numerical weather prediction system in order to optimize the physical parametrization configuration and to improve the forecast of two important atmospheric parameters: 2 meter temperature and relative humidity. Our research showed good results in improving the average prediction error in limited amount of iterations and this could prove helpful in building GA optimized ensemble forecasts, especially when focusing on specific atmospheric parameters. The optimization process performed well in finding optimal physical configurations for humidity prediction, but showed poor results for temperature forecast, more experiments need to be conducted in order to have a clear view over the utility of using GA techniques for physical parametrization optimization.","PeriodicalId":268635,"journal":{"name":"2016 18th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing (SYNASC)","volume":"39 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127921222","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Z. Marian, Ioan-Gabriel Mircea, I. Czibula, G. Czibula
Detecting defective entities from existing software systems is a problem of great importance for increasing both the software quality and the efficiency of software testing related activities. We introduce in this paper a novel approach for predicting software defects using fuzzy decision trees. Through the fuzzy approach we aim to better cope with noise and imprecise information. A fuzzy decision tree will be trained to identify if a software module is or not a defective one. Two open source software systems are used for experimentally evaluating our approach. The obtained results highlight that the fuzzy decision tree approach outperforms the non-fuzzy one on almost all case studies used for evaluation. Compared to the approaches used in the literature, the fuzzy decision tree classifier is shown to be more efficient than most of the other machine learning-based classifiers.
{"title":"A Novel Approach for Software Defect Prediction Using Fuzzy Decision Trees","authors":"Z. Marian, Ioan-Gabriel Mircea, I. Czibula, G. Czibula","doi":"10.1109/SYNASC.2016.046","DOIUrl":"https://doi.org/10.1109/SYNASC.2016.046","url":null,"abstract":"Detecting defective entities from existing software systems is a problem of great importance for increasing both the software quality and the efficiency of software testing related activities. We introduce in this paper a novel approach for predicting software defects using fuzzy decision trees. Through the fuzzy approach we aim to better cope with noise and imprecise information. A fuzzy decision tree will be trained to identify if a software module is or not a defective one. Two open source software systems are used for experimentally evaluating our approach. The obtained results highlight that the fuzzy decision tree approach outperforms the non-fuzzy one on almost all case studies used for evaluation. Compared to the approaches used in the literature, the fuzzy decision tree classifier is shown to be more efficient than most of the other machine learning-based classifiers.","PeriodicalId":268635,"journal":{"name":"2016 18th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing (SYNASC)","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132795771","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The development of search-based algorithms forautomatic test case generation is a key issue in the researcharea of software testing. Evolutionary algorithms have beenfrequently used for this purpose due to their ability to solvecomplex optimization problems. In this paper we introduce anovel approach to the automatic test-case generation problemfor reactive software systems. We build upon our previouswork where we defined a test generation framework based onparameterized executable environment models written in theLutin language. The main contribution of this paper is theapplication of a self-adaptive evolutionary algorithm, JADE inthe context of our test generation framework and the evaluationof its performance on a realistic reactive system written in Scade. Our preliminary results show that adaptive differential evolutioncan be used efficiently to increase the structural coverage of thesystem under test and is easier to use due to the fewer parametersthat require fine-tuning.
{"title":"Optimizing Test Input Generation for Reactive Systems with an Adaptive Differential Evolution","authors":"A. Szenkovits, Noémi Gaskó, Hunor Jakab","doi":"10.1109/SYNASC.2016.042","DOIUrl":"https://doi.org/10.1109/SYNASC.2016.042","url":null,"abstract":"The development of search-based algorithms forautomatic test case generation is a key issue in the researcharea of software testing. Evolutionary algorithms have beenfrequently used for this purpose due to their ability to solvecomplex optimization problems. In this paper we introduce anovel approach to the automatic test-case generation problemfor reactive software systems. We build upon our previouswork where we defined a test generation framework based onparameterized executable environment models written in theLutin language. The main contribution of this paper is theapplication of a self-adaptive evolutionary algorithm, JADE inthe context of our test generation framework and the evaluationof its performance on a realistic reactive system written in Scade. Our preliminary results show that adaptive differential evolutioncan be used efficiently to increase the structural coverage of thesystem under test and is easier to use due to the fewer parametersthat require fine-tuning.","PeriodicalId":268635,"journal":{"name":"2016 18th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing (SYNASC)","volume":"29 2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131415771","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
We provide a simple method, using Gröbner bases over modules, to compute multivariate polynomial greatest common divisors. The approach we show is flexible, adaptable to algebraic extensions of the rationals or prime fields, and is notably faster than prior methods that work with Gröbner bases. It can be used in situations where sparse interpolation might be difficult to implement, e.g. when there are few points for interpolation (small prime fields) or in the presence of non-numeric algebraic relations.
{"title":"Polynomial GCDs by Syzygies","authors":"Eliana Duarte, Daniel Lichtblau","doi":"10.1109/SYNASC.2016.021","DOIUrl":"https://doi.org/10.1109/SYNASC.2016.021","url":null,"abstract":"We provide a simple method, using Gröbner bases over modules, to compute multivariate polynomial greatest common divisors. The approach we show is flexible, adaptable to algebraic extensions of the rationals or prime fields, and is notably faster than prior methods that work with Gröbner bases. It can be used in situations where sparse interpolation might be difficult to implement, e.g. when there are few points for interpolation (small prime fields) or in the presence of non-numeric algebraic relations.","PeriodicalId":268635,"journal":{"name":"2016 18th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing (SYNASC)","volume":"58 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124436229","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The goal of this paper is to create a hybrid system based on a Multi-Agent Architecture that will investigate the evolution of some prediction strategies (Elliott Wave, Lucas, GANN) along with technical, fundamental and macro-economical analysis methods on stock market indexes and how this information influences the stock market behavior in order to improve the profitability on a short or medium time period investment. The proposed system correlates the results from Elliott Wave, GANN and Lucas methods in order to determine a better prediction of the stock price position on the trend and based on this to determine which will be its future direction. The system also finds correlations between the pattern recognition methods and technical and fundamental methods results in order to find the direction of the market trend, to predict the next day price of a stock and to trigger a useful buy/sell signal. In order to validate our model a prototype was developed and applied to the Bucharest Stock Exchange Market indexes.
{"title":"Behavioral Trading System - Detecting Crisis, Risk and Stability in Financial Markets","authors":"M. Tirea, V. Negru","doi":"10.1109/SYNASC.2016.051","DOIUrl":"https://doi.org/10.1109/SYNASC.2016.051","url":null,"abstract":"The goal of this paper is to create a hybrid system based on a Multi-Agent Architecture that will investigate the evolution of some prediction strategies (Elliott Wave, Lucas, GANN) along with technical, fundamental and macro-economical analysis methods on stock market indexes and how this information influences the stock market behavior in order to improve the profitability on a short or medium time period investment. The proposed system correlates the results from Elliott Wave, GANN and Lucas methods in order to determine a better prediction of the stock price position on the trend and based on this to determine which will be its future direction. The system also finds correlations between the pattern recognition methods and technical and fundamental methods results in order to find the direction of the market trend, to predict the next day price of a stock and to trigger a useful buy/sell signal. In order to validate our model a prototype was developed and applied to the Bucharest Stock Exchange Market indexes.","PeriodicalId":268635,"journal":{"name":"2016 18th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing (SYNASC)","volume":"2014 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128227487","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Dorinela Sirbu, Ana Secui, M. Dascalu, S. Crossley, Stefan Ruseti, Stefan Trausan-Matu
Opinion mining and sentiment analysis are a trending research domain in Natural Language Processing focused on automatically extracting subjective information, feelings, opinions, ideas or emotions from texts. Our study is centered on identifying sentiments and opinions, as well as other latent linguistic dimensions expressed in on-line game reviews. Over 9500 entertainment game reviews from Amazon were examined using a Principal Component Analysis applied to word-count indices derived from linguistic resources. Eight affective components were identified as being the most representative semantic and sentiment-oriented dimensions for our dataset. These components explained 51.2% of the variance of all reviews. A Multivariate Analysis of Variance showed that five of the eight components demonstrated significant differences between positive, negative and neutral game reviews. These five components used as predictors in a Discriminant Function Analysis, were able to classify game reviews into positive, negative and neutral ratings with a 55% accuracy.
观点挖掘和情感分析是自然语言处理领域的一个趋势研究领域，其重点是从文本中自动提取主观信息、感觉、观点、想法或情感。我们的研究集中于识别在线游戏评论中表达的情感和观点，以及其他潜在的语言维度。我们使用主成分分析(Principal Component Analysis)对来自亚马逊的9500多条娱乐游戏评论进行了分析，该分析应用于源自语言资源的单词计数指数。八个情感成分被确定为我们数据集中最具代表性的语义和情感导向维度。这些成分解释了所有评论中51.2%的差异。多元方差分析显示，8个成分中有5个在积极、消极和中立的游戏评价之间表现出显著差异。在判别函数分析(Discriminant Function Analysis)中，这5个成分能够以55%的准确率将游戏评论划分为正面、负面和中性评级。
{"title":"Extracting Gamers' Opinions from Reviews","authors":"Dorinela Sirbu, Ana Secui, M. Dascalu, S. Crossley, Stefan Ruseti, Stefan Trausan-Matu","doi":"10.1109/SYNASC.2016.044","DOIUrl":"https://doi.org/10.1109/SYNASC.2016.044","url":null,"abstract":"Opinion mining and sentiment analysis are a trending research domain in Natural Language Processing focused on automatically extracting subjective information, feelings, opinions, ideas or emotions from texts. Our study is centered on identifying sentiments and opinions, as well as other latent linguistic dimensions expressed in on-line game reviews. Over 9500 entertainment game reviews from Amazon were examined using a Principal Component Analysis applied to word-count indices derived from linguistic resources. Eight affective components were identified as being the most representative semantic and sentiment-oriented dimensions for our dataset. These components explained 51.2% of the variance of all reviews. A Multivariate Analysis of Variance showed that five of the eight components demonstrated significant differences between positive, negative and neutral game reviews. These five components used as predictors in a Discriminant Function Analysis, were able to classify game reviews into positive, negative and neutral ratings with a 55% accuracy.","PeriodicalId":268635,"journal":{"name":"2016 18th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing (SYNASC)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128607372","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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