{"title":"Lax-Like Stability for the Discretization of Pseudodifferential Operators through Gabor Multipliers and Spline-Type Spaces","authors":"D. Onchis, Simone Zappalá","doi":"10.1109/SYNASC.2018.00026","DOIUrl":"https://doi.org/10.1109/SYNASC.2018.00026","url":null,"abstract":"In this paper we study the stability of projection schemes for pseudodifferential operators defined over a locally compact Abelian (LCA) group G unto a space of generalized Gabor multipliers (GGM), also called time-frequency multipliers. The projection is reformulated as a projection of the symbol operator into the spline-type (ST) space generated by the Rihaczek distributions that characterize the selected space of multipliers and the related subgroup of the time-frequency space G×G. The symplectic nature of the time-frequency group is avoided, hence a constructive realizable algorithm can be performed on the LCA group G × G. Stability is defined as uniform boundedness of a sequence of projections induced by an automorphism over the group G. We will describe the automorphisms that generate a sequence of GGM spaces and the ones that characterize stability.","PeriodicalId":273805,"journal":{"name":"2018 20th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing (SYNASC)","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130694974","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}
{"title":"A Self Developing System for Medical Data Analysis","authors":"Adriana Dinis, Todor Ivascu, V. Negru","doi":"10.1109/SYNASC.2018.00058","DOIUrl":"https://doi.org/10.1109/SYNASC.2018.00058","url":null,"abstract":"In this paper we present a concept project for a self developing system based on agents built for a hospital. The system monitors patients during and after being released from hospitalization, with the aim of understanding patterns and predicting future problems. Due to its complexity and dynamism the agents must be automatically generated. They need to cooperate and \"compete\" with each other in order to get good results. By combining meta-heuristic algorithms with reinforcement and clustering techniques we target a large degree of autonomy in decision making.","PeriodicalId":273805,"journal":{"name":"2018 20th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing (SYNASC)","volume":"31 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128027144","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}
{"title":"Computation Results of the Riemann Zeta Search Project","authors":"Norbert Tihanyi, A. Kovács","doi":"10.1109/SYNASC.2018.00024","DOIUrl":"https://doi.org/10.1109/SYNASC.2018.00024","url":null,"abstract":"The paper summarizes the computation results of the Riemann Zeta Search Project. The aim of the project was to find extremely large values of the Riemann zeta function on the critical line. The computing method is based on the RS-PEAK algorithm which was presented in the 16th SYNASC conference in 2014. The computation environment was served by the SZTAKI Desktop Grid operated by the Laboratory of Parallel and Distributed Systems at the Hungarian Academy of Sciences. Applying the RS-Peak algorithm 5597001 candidates were found where large values of the Riemann-Siegel Z-function are expected. The largest known values are presented and published on the project website https://www.riemann-siegel.com.","PeriodicalId":273805,"journal":{"name":"2018 20th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing (SYNASC)","volume":"35 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123376218","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}
{"title":"Towards Compiling Region Types Into RTSJ-Compliant Java Code","authors":"Florin Craciun, Gabriel Glodean","doi":"10.1109/SYNASC.2018.00028","DOIUrl":"https://doi.org/10.1109/SYNASC.2018.00028","url":null,"abstract":"In the last decade, multiple Real-Time Specification for Java (RTSJ) compliant Java Virtual Machines have been developed and used in safety critical applications. Region-based memory management is a core feature of RTSJ. In this paper, we provide an automatic generation of RTSJ region-based memory management code. We start from a Java program annotated with region types and we apply three type-based analyses. The region types are provided either by our previous region type inference or by the programmers and verified by our previous region type checker. The first two analyses simplify the region type annotations, while the last analysis generates the code according to the RTSJ API.","PeriodicalId":273805,"journal":{"name":"2018 20th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing (SYNASC)","volume":"31 6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123185849","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}
{"title":"A four-Phase Meta-Heuristic Algorithm for Solving Large Scale Instances of the Shift Minimization Personnel Task Scheduling Problem","authors":"Sebastian Nechita, L. Dioşan","doi":"10.1109/SYNASC.2018.00067","DOIUrl":"https://doi.org/10.1109/SYNASC.2018.00067","url":null,"abstract":"The Shift minimization personnel task scheduling problem (SMPTSP) is a known NP-hard problem. The present paper introduces a novel four-phase meta-heuristic approach for solving the Shift minimization personnel task scheduling problem which consists of an optimal assignment of jobs to multi-skilled employees, such that a minimal number of employees is used and no job is left unassigned. The computational results show that the proposed approach is able to find very good solutions in a very short time. The approach was tested and validated on the benchmarks from existing literature, managing to find very good solutions.","PeriodicalId":273805,"journal":{"name":"2018 20th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing (SYNASC)","volume":"34 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125033114","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}
A. Cimatti, A. Griggio, A. Irfan, Marco Roveri, R. Sebastiani
{"title":"Incremental linearization: A practical approach to satisfiability modulo nonlinear arithmetic and transcendental functions","authors":"A. Cimatti, A. Griggio, A. Irfan, Marco Roveri, R. Sebastiani","doi":"10.1109/SYNASC.2018.00016","DOIUrl":"https://doi.org/10.1109/SYNASC.2018.00016","url":null,"abstract":"Satisfiability Modulo Theories (SMT) is the problem of deciding the satisfiability of a first-order formula with respect to some theory or combination of theories. In this paper, we overview our recent approach called Incremental Linearization, which successfully tackles the problems of SMT over the theories of nonlinear arithmetic over the reals (NRA), nonlinear arithmetic over the integers (NIA) and their combination, and of NRA augmented with transcendental (exponential and trigonometric) functions (NTA). Moreover, we showcase some of the experimental results and outline interesting future directions.","PeriodicalId":273805,"journal":{"name":"2018 20th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing (SYNASC)","volume":"71 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127380131","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}
C. Sánchez, M. Viñas, Coen Atens, A. Borràs, D. Gil
{"title":"Back to Front Architecture for Diagnosis as a Service","authors":"C. Sánchez, M. Viñas, Coen Atens, A. Borràs, D. Gil","doi":"10.1109/SYNASC.2018.00059","DOIUrl":"https://doi.org/10.1109/SYNASC.2018.00059","url":null,"abstract":"Software as a Service (SaaS) is a cloud computing model in which a provider hosts applications in a server that customers use via internet. Since SaaS does not require to install applications on customers' own computers, it allows the use by multiple users of highly specialized software without extra expenses for hardware acquisition or licensing. A SaaS tailored for clinical needs not only would alleviate licensing costs, but also would facilitate easy access to new methods for diagnosis assistance. This paper presents a SaaS client-server architecture for Diagnosis as a Service (DaaS). The server is based on docker technology in order to allow execution of softwares implemented in different languages with the highest portability and scalability. The client is a content management system allowing the design of websites with multimedia content and interactive visualization of results allowing user editing. We explain a usage case that uses our DaaS as crowdsourcing platform in a multicentric pilot study carried out to evaluate the clinical benefits of a software for assessment of central airway obstruction.","PeriodicalId":273805,"journal":{"name":"2018 20th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing (SYNASC)","volume":"78 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133214201","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}
{"title":"Modeling real estate dynamics using survival analysis","authors":"Diana Minzat, Mihaela Breaban, H. Luchian","doi":"10.1109/SYNASC.2018.00042","DOIUrl":"https://doi.org/10.1109/SYNASC.2018.00042","url":null,"abstract":"This article introduces an adapted version of survival analysis for predicting the period of time a property will stay on market from the listing date to the sale agreement. Survival analysis is a method developed for medical research, in which the dependent variable is the survival time of a patient. Generalizing, the method can be applied in most problems where the dependent variable is time - in our case, the time a property stays on market before selling. Experimental results show that survival analysis brings some advantages when compared to regression analysis on our problem, not only in terms of prediction accuracy: survival curves offer descriptive quantitative views on the influence specific house features have on the variable of interest - the time on market.","PeriodicalId":273805,"journal":{"name":"2018 20th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing (SYNASC)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130379247","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}
{"title":"Detecting Java Compiled Malware using Machine Learning Techniques","authors":"Gheorghe Balan, Adrian-Stefan Popescu","doi":"10.1109/SYNASC.2018.00073","DOIUrl":"https://doi.org/10.1109/SYNASC.2018.00073","url":null,"abstract":"Malicious software using Java Language in order to implement the attack evolved rapidly in the past years. Initially we were used to find malicious Applets and exploitation methods to escape the controlled environments and to gain access to victims. Nowadays, as a react to the security measurements implemented in browsers, it is common to distribute the malware through spear-phishing emails. This paper presents two methods to detect the Java malicious code. One method is using an unsupervised machine learning algorithm while the other is using the Perceptron algorithm in order to shape a detection model. Combining their capacities we obtained a very good solution to detect Java threats in a proactive manner and to make sure that the known malware variants are still detected. The detection is focused on the class files as a response to the Malware as a Service concept.","PeriodicalId":273805,"journal":{"name":"2018 20th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing (SYNASC)","volume":"34 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133273140","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}
{"title":"Real-Time Computation of Legendre-Sobolev Approximations","authors":"P. Alvandi, S. Watt","doi":"10.1109/SYNASC.2018.00023","DOIUrl":"https://doi.org/10.1109/SYNASC.2018.00023","url":null,"abstract":"The present work is motivated by the problem of mathematical handwriting recognition where symbols are represented as plane curves, (X(λ), Y(λ)) parameterized by arc length λ ε[0, L]. Earlier work has shown that approximating the coordinate functions as certain truncated orthogonal polynomial series yields fast and effective recognition. It has been previously shown how to compute Legendre series representation in real time, as the curve is being traced out. In this article we show how to compute Legendre-Sobolev series representation in real time. The idea is to numerically integrate the moments of the coordinate functions as the curve is being traced. We show how the Legendre-Sobolev coefficients may be constructed either from the Legendre series coefficients or directly from the moments. Computing via Legendre series coefficients requires two matrix vector products, while the direct method requires only one.","PeriodicalId":273805,"journal":{"name":"2018 20th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing (SYNASC)","volume":"55 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127493805","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}