2015 17th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing (SYNASC)最新文献_第6页

An Algebraic Petri Nets Emulator 代数Petri网仿真器

2015 17th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing (SYNASC) Pub Date : 2015-09-21 DOI: 10.1109/SYNASC.2015.19

L. Capra

引用次数: 4

Stock Market Trading Strategies Applying Risk and Decision Analysis Models for Detecting Financial Turbulence 运用风险和决策分析模型检测金融动荡的股票市场交易策略

2015 17th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing (SYNASC) Pub Date : 2015-09-21 DOI: 10.1109/SYNASC.2015.42

M. Tirea, V. Negru

{"title":"Stock Market Trading Strategies Applying Risk and Decision Analysis Models for Detecting Financial Turbulence","authors":"M. Tirea, V. Negru","doi":"10.1109/SYNASC.2015.42","DOIUrl":"https://doi.org/10.1109/SYNASC.2015.42","url":null,"abstract":"Risk handling and evaluation plays an importantrole in optimizing an investment portfolio. This paper's goal isto describe a system that determines, classifies and handles riskassociated to any type of investment based on sentiment analysis, price movement, information related to companies, certain characteristics, the traders confidence level, and by measuring thepotential loss over a certain period of time. This research impliesanalyzing trader's risk, market risk, risk associated to eachevaluated company or financial group, political and governmentalrisk. The system is able to create different types of portfoliooptions based on the investor/trader profile, which is build basedon the user's tolerance to risk (determined by the results froman interactive quiz that the user must complete when entering thesystem). We propose a multi-agent system that uses different typeof data(numerical, textual) in order to choose the appropriate mixof investments in order to minimize the risk and maximize thegain on a stock portfolio. In order to validate the result a systemwas constructed.","PeriodicalId":6488,"journal":{"name":"2015 17th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing (SYNASC)","volume":"1970 1","pages":"216-223"},"PeriodicalIF":0.0,"publicationDate":"2015-09-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87390575","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}

引用次数: 0

vanHelsing: A Fast Proof Checker for Debuggable Compiler Verification vanHelsing:用于可调试编译器验证的快速证明检查器

2015 17th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing (SYNASC) Pub Date : 2015-09-21 DOI: 10.1109/SYNASC.2015.34

Roland Lezuo, I. Drăgan, G. Barany, A. Krall

引用次数: 5

An Energy Efficient Intelligent Wireless Body Area Network for Real-Time Vital Signs Monitoring 用于实时生命体征监测的节能智能无线体域网络

2015 17th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing (SYNASC) Pub Date : 2015-09-21 DOI: 10.1109/SYNASC.2015.50

Todor Ivascu

引用次数: 1

Scalable and Fault Tolerant Monitoring of Security Parameters in the Cloud 云中安全参数的可扩展和容错监控

2015 17th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing (SYNASC) Pub Date : 2015-09-21 DOI: 10.1109/SYNASC.2015.53

Bogdan Irimie, D. Petcu

引用次数: 3

Improving Malware Detection Response Time with Behavior-Based Statistical Analysis Techniques 利用基于行为的统计分析技术改进恶意软件检测响应时间

2015 17th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing (SYNASC) Pub Date : 2015-09-21 DOI: 10.1109/SYNASC.2015.44

Dumitru-Bogdan Prelipcean, Adrian-Stefan Popescu, Dragos Gavrilut

{"title":"Improving Malware Detection Response Time with Behavior-Based Statistical Analysis Techniques","authors":"Dumitru-Bogdan Prelipcean, Adrian-Stefan Popescu, Dragos Gavrilut","doi":"10.1109/SYNASC.2015.44","DOIUrl":"https://doi.org/10.1109/SYNASC.2015.44","url":null,"abstract":"Detection of malicious software is a current problem which can be solved via several approaches. Among these are signature based detection, heuristic detection and behavioral analysis. In the last year the number of malicious files has increased exponentially. At the same time, automated obfuscation methods (used to generate malicious files with similar behavior but different aspect) have grown significantly. In response to these new obfuscation methods, many security vendors have introduced file reputation techniques to quickly find out potentially clean and malicious samples. In this paper we present a statistical based method that can be used to identify a specific dynamic behavior of a program. The main idea behind this solution is to analyze the execution flow of every file and to extract sequences of native system functions with a potential malign outcome. This technique is reliable against most forms of malware polymorphism and is intended to work as a filtering system for different automated detection systems. We use a database consisting of approximately 50.000 malicious files gathered over the last three months and almost 3.000.000 clean files collected for a period of 3 years. Our technique proved to be an effective filtering method and helped us improve our detection response time against the most prevalent malware families discovered in the last year.","PeriodicalId":6488,"journal":{"name":"2015 17th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing (SYNASC)","volume":"63 1","pages":"232-239"},"PeriodicalIF":0.0,"publicationDate":"2015-09-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"73521724","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}

引用次数: 11

Algorithmic Logic-Based Verification with SeaHorn 基于算法逻辑的SeaHorn验证

2015 17th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing (SYNASC) Pub Date : 2015-09-21 DOI: 10.1109/SYNASC.2015.10

A. Gurfinkel

引用次数: 1

Properties of Multisets Compared to Sets 多集相对于集合的性质

2015 17th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing (SYNASC) Pub Date : 2015-09-21 DOI: 10.1109/SYNASC.2015.37

Aurelian Radoaca

引用次数: 12

From Decision Procedures to Synthesis Procedures 从决策程序到综合程序

2015 17th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing (SYNASC) Pub Date : 2015-09-21 DOI: 10.1109/SYNASC.2015.78

R. Piskac

{"title":"From Decision Procedures to Synthesis Procedures","authors":"R. Piskac","doi":"10.1109/SYNASC.2015.78","DOIUrl":"https://doi.org/10.1109/SYNASC.2015.78","url":null,"abstract":"Software synthesis is a technique for automatically generating code from a given specification. The goal of software synthesis is to make software development easier while increasing both the productivity of the programmer and the correctness of the produced code. In this paper we present an approach to synthesis that relies on the use of automated reasoning and decision procedures. First we describe how to generalize decision procedures into predictable and complete synthesis procedures.Here completeness means that the procedure is guaranteed to find code that satisfies the given specification. We illustrate the process of turning a decision procedure into a synthesis procedure using linear integer arithmetic as an example.However, writing a complete specification can be a tedious task,sometimes even harder than writing the code itself. To over come this problem, ideally the user could provide a few input-output examples, and then the code should be automatically derived.We outline how to broaden usability and applications of current software synthesis techniques. We conclude with an outlook on possible future research directions and applications of synthesis procedures.","PeriodicalId":6488,"journal":{"name":"2015 17th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing (SYNASC)","volume":"91 1","pages":"3-10"},"PeriodicalIF":0.0,"publicationDate":"2015-09-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80397489","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}

引用次数: 0

Complex Network Analysis of a Tourism Content Sharing Network 旅游内容共享网络的复杂网络分析

2015 17th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing (SYNASC) Pub Date : 2015-09-21 DOI: 10.1109/SYNASC.2015.67

A. Becheru, C. Bǎdicǎ, Mihaita Antonie

引用次数: 0