Hardware and software stack complexity make programming GPGPUs difficult and limit application portability. This article first discusses challenges imposed by the current hardware and software model in GPGPU systems which relies heavily on the HOST device (CPU). We then identify system bottlenecks both in the hardware design and in the software stack and present two ideas to extend the HOST and DEVICE side of the OpenCL API with the aim to improve latency and device safety. As a first goal we target HOST side latency reduction using user synchronization directives. Our second goal was to improve on DEVICE side latency and add safety through a software layer which manages kernel execution. For both HOST and DEVICE side latency reduction we present concrete performance results.
{"title":"Extensions over OpenCL for Latency Reduction and Critical Applications","authors":"Grigore Lupescu, E. Slusanschi, N. Tapus","doi":"10.1109/SYNASC.2015.64","DOIUrl":"https://doi.org/10.1109/SYNASC.2015.64","url":null,"abstract":"Hardware and software stack complexity make programming GPGPUs difficult and limit application portability. This article first discusses challenges imposed by the current hardware and software model in GPGPU systems which relies heavily on the HOST device (CPU). We then identify system bottlenecks both in the hardware design and in the software stack and present two ideas to extend the HOST and DEVICE side of the OpenCL API with the aim to improve latency and device safety. As a first goal we target HOST side latency reduction using user synchronization directives. Our second goal was to improve on DEVICE side latency and add safety through a software layer which manages kernel execution. For both HOST and DEVICE side latency reduction we present concrete performance results.","PeriodicalId":6488,"journal":{"name":"2015 17th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing (SYNASC)","volume":"213 1","pages":"379-385"},"PeriodicalIF":0.0,"publicationDate":"2015-09-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"73113015","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}
Stock market prediction is influenced by manyinternal and external factors. One of these factors are the newsarticles and financial reports related to each listed company. This paper describes a system that is able to extract relevantinformation from this type of textual documents, correlate themwith the stock price movement and determine whether ornot a new released news can and in which proportion willinfluence the market behavior. Predefined ontologies are used forclassifying the news articles and automated ontology extractionfor classifying concepts and super - concepts, on an attempt tomake a semantic mining of the text news. The system is basedon a Multi-Agent Architecture that will investigate, extract andcorrelate the textual data message with the price evolution inorder to better determine buy/sell moments, the trend directionand optimize an investment portfolio. In order to validate ourmodel a prototype was developed and applied to the BucharestStock Exchange Market listed companies.
{"title":"Text Mining News System - Quantifying Certain Phenomena Effect on the Stock Market Behavior","authors":"M. Tirea, V. Negru","doi":"10.1109/SYNASC.2015.65","DOIUrl":"https://doi.org/10.1109/SYNASC.2015.65","url":null,"abstract":"Stock market prediction is influenced by manyinternal and external factors. One of these factors are the newsarticles and financial reports related to each listed company. This paper describes a system that is able to extract relevantinformation from this type of textual documents, correlate themwith the stock price movement and determine whether ornot a new released news can and in which proportion willinfluence the market behavior. Predefined ontologies are used forclassifying the news articles and automated ontology extractionfor classifying concepts and super - concepts, on an attempt tomake a semantic mining of the text news. The system is basedon a Multi-Agent Architecture that will investigate, extract andcorrelate the textual data message with the price evolution inorder to better determine buy/sell moments, the trend directionand optimize an investment portfolio. In order to validate ourmodel a prototype was developed and applied to the BucharestStock Exchange Market listed companies.","PeriodicalId":6488,"journal":{"name":"2015 17th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing (SYNASC)","volume":"5 1","pages":"391-398"},"PeriodicalIF":0.0,"publicationDate":"2015-09-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79319527","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}
Web applications are often vulnerable to code injection attacks and to attacks through buggy or malicious libraries. Unfortunately, the current protection mechanisms are frequently ad-hoc, as a response to attacks after the fact. This had lead to a plethora of specialized protection mechanisms that are often brittle and insufficient to guarantee security. This extended abstract accompanies a tutorial on web application security using JSFlow, an information-flow aware interpreter for full non-strict ECMA-262(v.5). In contrast to access control, which most current protection mechanisms apply, information-flow control focuses on what applications are allowed to do with the information they access. This removes the inherent trust that access control places on entities that are granted access. Dispensing with this trust is key for the protection to withstand bypassing in the presence of untrustworthy 3rd party code and code injection attacks. Based on two practical attacks against an example web application Hrafn, we demonstrate the power of JSFlow. The attacks model the scenario where the current standards protection mechanism are bypassed or not applicable. By using a simple and natural security policy, we show how both attacks are prevented byJSFlow. Although information-flow control has not been tailor made to preventthis kind of attacks, it offers a uniform line of defense against untrustworthyand malicious code and ensures confidentiality of sensitive data.
{"title":"Web Application Security Using JSFlow","authors":"Daniel Hedin, A. Sabelfeld","doi":"10.1109/SYNASC.2015.11","DOIUrl":"https://doi.org/10.1109/SYNASC.2015.11","url":null,"abstract":"Web applications are often vulnerable to code injection attacks and to attacks through buggy or malicious libraries. Unfortunately, the current protection mechanisms are frequently ad-hoc, as a response to attacks after the fact. This had lead to a plethora of specialized protection mechanisms that are often brittle and insufficient to guarantee security. This extended abstract accompanies a tutorial on web application security using JSFlow, an information-flow aware interpreter for full non-strict ECMA-262(v.5). In contrast to access control, which most current protection mechanisms apply, information-flow control focuses on what applications are allowed to do with the information they access. This removes the inherent trust that access control places on entities that are granted access. Dispensing with this trust is key for the protection to withstand bypassing in the presence of untrustworthy 3rd party code and code injection attacks. Based on two practical attacks against an example web application Hrafn, we demonstrate the power of JSFlow. The attacks model the scenario where the current standards protection mechanism are bypassed or not applicable. By using a simple and natural security policy, we show how both attacks are prevented byJSFlow. Although information-flow control has not been tailor made to preventthis kind of attacks, it offers a uniform line of defense against untrustworthyand malicious code and ensures confidentiality of sensitive data.","PeriodicalId":6488,"journal":{"name":"2015 17th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing (SYNASC)","volume":"30 1","pages":"16-19"},"PeriodicalIF":0.0,"publicationDate":"2015-09-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84467104","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}
W. Belkhir, N. Ratier, D. Nguyen, Bin Yang, M. Lenczner, F. Zamkotsian, Horatiu Cirstea
This paper reports recent advances in the development of a symbolic asymptotic modeling software package, called MEMSALab, which will be used for automatic generation of asymptotic models for arrays of micro and nanosystems. More precisely, a model is a partial differential equation and an asymptotic method approximate it by another partial differential equation which can be numerically simulated in a reasonable time. The challenge consists in taking into account a wide range of different physical features and geometries e.g. thin structures, periodic structures, multiple nested scales etc. The main purpose of this software is to construct models incrementally so that model features can be included step by step. This idea, conceptualized under the name "by-extension-combination", is presented for the first time. A user friendly language recently introduced is also shortly discussed. We illustrate the mathematical operations that need to be implemented in MEMSALab by an example of an asymptotic model for the stationary heat equation in a Micro-Mirror Array developed for astrophysics.
{"title":"Towards an Automatic Tool for Multi-scale Model Derivation Illustrated with a Micro-mirror Array","authors":"W. Belkhir, N. Ratier, D. Nguyen, Bin Yang, M. Lenczner, F. Zamkotsian, Horatiu Cirstea","doi":"10.1109/SYNASC.2015.17","DOIUrl":"https://doi.org/10.1109/SYNASC.2015.17","url":null,"abstract":"This paper reports recent advances in the development of a symbolic asymptotic modeling software package, called MEMSALab, which will be used for automatic generation of asymptotic models for arrays of micro and nanosystems. More precisely, a model is a partial differential equation and an asymptotic method approximate it by another partial differential equation which can be numerically simulated in a reasonable time. The challenge consists in taking into account a wide range of different physical features and geometries e.g. thin structures, periodic structures, multiple nested scales etc. The main purpose of this software is to construct models incrementally so that model features can be included step by step. This idea, conceptualized under the name \"by-extension-combination\", is presented for the first time. A user friendly language recently introduced is also shortly discussed. We illustrate the mathematical operations that need to be implemented in MEMSALab by an example of an asymptotic model for the stationary heat equation in a Micro-Mirror Array developed for astrophysics.","PeriodicalId":6488,"journal":{"name":"2015 17th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing (SYNASC)","volume":"10 1","pages":"47-54"},"PeriodicalIF":0.0,"publicationDate":"2015-09-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81339586","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}
By modelling a software project as a complex system, its internal structure can be analyzed in order to asses its design quality. As a software system is being developed, the quality of its internal structure is evolving too, not always for the better. Flaws in the internal structure are usually indicators of code that is hard to understand, maintain and, in many cases, they are pointers of accumulated technical debt. While there are already methods and tools that enable design flaw detection, they only look at a snapshot of the code, they do not analyze how the design flaw evolved over time. We propose an approach which enhances design flaw detection with history information, in order to: (i) find patterns in the evolution of a design flaw, which could then be used to predict future activity, (ii) improve detection by eliminating false negatives, (iii) improve the recommendation system to provide better refactoring advices and a better ranking of design flaws, in order to address the most critical first.
{"title":"Modeling Design Flaw Evolution Using Complex Systems","authors":"George Ganea, Radu Marinescu","doi":"10.1109/SYNASC.2015.70","DOIUrl":"https://doi.org/10.1109/SYNASC.2015.70","url":null,"abstract":"By modelling a software project as a complex system, its internal structure can be analyzed in order to asses its design quality. As a software system is being developed, the quality of its internal structure is evolving too, not always for the better. Flaws in the internal structure are usually indicators of code that is hard to understand, maintain and, in many cases, they are pointers of accumulated technical debt. While there are already methods and tools that enable design flaw detection, they only look at a snapshot of the code, they do not analyze how the design flaw evolved over time. We propose an approach which enhances design flaw detection with history information, in order to: (i) find patterns in the evolution of a design flaw, which could then be used to predict future activity, (ii) improve detection by eliminating false negatives, (iii) improve the recommendation system to provide better refactoring advices and a better ranking of design flaws, in order to address the most critical first.","PeriodicalId":6488,"journal":{"name":"2015 17th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing (SYNASC)","volume":"6 1","pages":"433-436"},"PeriodicalIF":0.0,"publicationDate":"2015-09-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81667054","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 presents a Multi-agent system that facilitates the remote monitoring of the elderly patients which are susceptible to mental disorder diseases. In order to find early signs of health condition depreciation we have assessed four of the most common mental disorder diseases to find which kind of sensors can detect specific symptoms with the main purpose of creating an early warning system. The diagnosis component is based on an ontology that defines the relations between sensors, symptoms and diseases. Based on these relationships a specialized agent can inform the medical personnel about the detected symptoms.
{"title":"A Multi-agent Architecture for Ontology-Based Diagnosis of Mental Disorders","authors":"Todor Ivascu, Bogdan Manate, V. Negru","doi":"10.1109/SYNASC.2015.69","DOIUrl":"https://doi.org/10.1109/SYNASC.2015.69","url":null,"abstract":"This paper presents a Multi-agent system that facilitates the remote monitoring of the elderly patients which are susceptible to mental disorder diseases. In order to find early signs of health condition depreciation we have assessed four of the most common mental disorder diseases to find which kind of sensors can detect specific symptoms with the main purpose of creating an early warning system. The diagnosis component is based on an ontology that defines the relations between sensors, symptoms and diseases. Based on these relationships a specialized agent can inform the medical personnel about the detected symptoms.","PeriodicalId":6488,"journal":{"name":"2015 17th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing (SYNASC)","volume":"26 1","pages":"423-430"},"PeriodicalIF":0.0,"publicationDate":"2015-09-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82264262","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}
When developing multi-agent systems, the initial choice of deployment platform has a long-term impact on the project, as it many times restricts the architecture of agents, the communication protocols used, and the available services. The goal of this paper is to present the architecture of tATAmI-2.5, a framework that is able to integrate agents deployed using different environments, and communicating using different communication platforms. This framework is based on the tATAmI-2 agent development and deployment framework, which allows agents to be deployed on various communication platforms without modifying the agent code. The details of the proposed architecture are presented, including insights into the bootstrap process and the routing of messages.
{"title":"A Framework for Integrating Heterogeneous Agent Communication Platforms","authors":"Andrei Olaru, A. Florea","doi":"10.1109/SYNASC.2015.66","DOIUrl":"https://doi.org/10.1109/SYNASC.2015.66","url":null,"abstract":"When developing multi-agent systems, the initial choice of deployment platform has a long-term impact on the project, as it many times restricts the architecture of agents, the communication protocols used, and the available services. The goal of this paper is to present the architecture of tATAmI-2.5, a framework that is able to integrate agents deployed using different environments, and communicating using different communication platforms. This framework is based on the tATAmI-2 agent development and deployment framework, which allows agents to be deployed on various communication platforms without modifying the agent code. The details of the proposed architecture are presented, including insights into the bootstrap process and the routing of messages.","PeriodicalId":6488,"journal":{"name":"2015 17th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing (SYNASC)","volume":"1 1","pages":"399-406"},"PeriodicalIF":0.0,"publicationDate":"2015-09-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82353774","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}
Cristina Vatamanu, Dragos Gavrilut, Razvan Benchea, H. Luchian
This paper extends the authors' previous research on a malware detection method, focusing on improving the accuracy of the perceptron based - One Side Class Perceptron algorithm via the use of Genetic Programming. We are concerned with finding a proper balance between the three basic requirements for malware detection algorithms: (a) that their training time on large datasets falls below acceptable upper limits; (b) that their false positive rate (clean/legitimate files/software wrongly classified as malware) is as close as possible to 0 and (c) that their detection rate is as close as possible to 1. When the first two requirements are set as objectives for the design of detection algorithms, it often happens that the third objective is missed: the detection rate is low. This study focuses on improving the detection rate while preserving the small training time and the low rate of false positives. Another concern is to use the perceptron-based algorithm's good performance on linearly separable data, by extracting features from existing ones. In order to keep the overall training time low, the huge search space of possible extracted features is efficiently explored in terms of time and memory foot-print using Genetic Programming; better separability is sought for. For experiments we used a dataset consisting of 350,000 executable files with an initial set of 300 Boolean features describing each of them. The feature-extraction algorithm is implemented in a parallel manner in order to cope with the size of the data set. We also tested different ways of controlling the growth in size of the variable-length chromosomes. The experimental results show that the features produced by this method are better than the best ones obtained through mapping allowing for an increase in detection rate.
{"title":"Feature Extraction Using Genetic Programming with Applications in Malware Detection","authors":"Cristina Vatamanu, Dragos Gavrilut, Razvan Benchea, H. Luchian","doi":"10.1109/SYNASC.2015.43","DOIUrl":"https://doi.org/10.1109/SYNASC.2015.43","url":null,"abstract":"This paper extends the authors' previous research on a malware detection method, focusing on improving the accuracy of the perceptron based - One Side Class Perceptron algorithm via the use of Genetic Programming. We are concerned with finding a proper balance between the three basic requirements for malware detection algorithms: (a) that their training time on large datasets falls below acceptable upper limits; (b) that their false positive rate (clean/legitimate files/software wrongly classified as malware) is as close as possible to 0 and (c) that their detection rate is as close as possible to 1. When the first two requirements are set as objectives for the design of detection algorithms, it often happens that the third objective is missed: the detection rate is low. This study focuses on improving the detection rate while preserving the small training time and the low rate of false positives. Another concern is to use the perceptron-based algorithm's good performance on linearly separable data, by extracting features from existing ones. In order to keep the overall training time low, the huge search space of possible extracted features is efficiently explored in terms of time and memory foot-print using Genetic Programming; better separability is sought for. For experiments we used a dataset consisting of 350,000 executable files with an initial set of 300 Boolean features describing each of them. The feature-extraction algorithm is implemented in a parallel manner in order to cope with the size of the data set. We also tested different ways of controlling the growth in size of the variable-length chromosomes. The experimental results show that the features produced by this method are better than the best ones obtained through mapping allowing for an increase in detection rate.","PeriodicalId":6488,"journal":{"name":"2015 17th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing (SYNASC)","volume":"157 1","pages":"224-231"},"PeriodicalIF":0.0,"publicationDate":"2015-09-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76432133","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}
Even-Odd Trees are a canonical tree-based number representation derived from a bijection between trees defined by the data type equation T = 1+T *T* +T *T* and positive natural numbers seen as iterated applications of o(x) = 2x and i(x) = 2x + 1 starting from 1. This paper introduces purely functional arithmetic algorithms for operations on Even-Odd Trees. While within constant factors from their traditional counterparts for their average case behavior, our algorithms make tractable important computations that are impossible with traditional number representations.
{"title":"The Arithmetic of Even-Odd Trees","authors":"Paul Tarau","doi":"10.1109/SYNASC.2015.23","DOIUrl":"https://doi.org/10.1109/SYNASC.2015.23","url":null,"abstract":"Even-Odd Trees are a canonical tree-based number representation derived from a bijection between trees defined by the data type equation T = 1+T *T* +T *T* and positive natural numbers seen as iterated applications of o(x) = 2x and i(x) = 2x + 1 starting from 1. This paper introduces purely functional arithmetic algorithms for operations on Even-Odd Trees. While within constant factors from their traditional counterparts for their average case behavior, our algorithms make tractable important computations that are impossible with traditional number representations.","PeriodicalId":6488,"journal":{"name":"2015 17th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing (SYNASC)","volume":"6 1","pages":"90-97"},"PeriodicalIF":0.0,"publicationDate":"2015-09-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90844512","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}
Andrew P. Smith, C. Muñoz, Anthony Narkawicz, Mantas Markevicius
Recursive branch and bound algorithms are often used, either rigorouslyor non-rigorously, to refine and isolate solutions to global optimizationproblems or systems of equations and inequalities involving nonlinearfunctions. The presented software library, Kodiak, integrates numericand symbolic computation into a generic framework for the solution of suchproblems over hyper-rectangular variable and parameter domains. Thecorrectness of both the generic branch and bound algorithm and the self-validating enclosure methods used, namely interval arithmetic and, for polynomials and rational functions, Bernstein expansion, has beenformally verified. The algorithm has three main instantiations, forsystems of equations and inequalities, for constrained global optimization, and for the computation of equilibria and bifurcation sets for systems ofordinary differential equations. For the latter category, and to enablethe computation of bisection heuristics to reduce the branching factor, advantage is taken of the partial derivatives of the constraint functions, which are symbolically manipulated. Pavings (unions of box subsets)for a continuum of solutions to underdetermined systems mayalso be produced. The capabilities of the software tool are outlined, andcomputational examples are presented.
{"title":"A Rigorous Generic Branch and Bound Solver for Nonlinear Problems","authors":"Andrew P. Smith, C. Muñoz, Anthony Narkawicz, Mantas Markevicius","doi":"10.1109/SYNASC.2015.20","DOIUrl":"https://doi.org/10.1109/SYNASC.2015.20","url":null,"abstract":"Recursive branch and bound algorithms are often used, either rigorouslyor non-rigorously, to refine and isolate solutions to global optimizationproblems or systems of equations and inequalities involving nonlinearfunctions. The presented software library, Kodiak, integrates numericand symbolic computation into a generic framework for the solution of suchproblems over hyper-rectangular variable and parameter domains. Thecorrectness of both the generic branch and bound algorithm and the self-validating enclosure methods used, namely interval arithmetic and, for polynomials and rational functions, Bernstein expansion, has beenformally verified. The algorithm has three main instantiations, forsystems of equations and inequalities, for constrained global optimization, and for the computation of equilibria and bifurcation sets for systems ofordinary differential equations. For the latter category, and to enablethe computation of bisection heuristics to reduce the branching factor, advantage is taken of the partial derivatives of the constraint functions, which are symbolically manipulated. Pavings (unions of box subsets)for a continuum of solutions to underdetermined systems mayalso be produced. The capabilities of the software tool are outlined, andcomputational examples are presented.","PeriodicalId":6488,"journal":{"name":"2015 17th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing (SYNASC)","volume":"480 1","pages":"71-78"},"PeriodicalIF":0.0,"publicationDate":"2015-09-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89649549","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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