发布求助
文献互助 智能选刊 最新文献

2022 24th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing (SYNASC)最新文献

筛选
英文 中文
Eye Detection For Drivers Using Convolutional Neural Networks With Automatically Generated Ground Truth Data 使用卷积神经网络自动生成地面真实数据的驾驶员眼睛检测
2022 24th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing (SYNASC) Pub Date : 2022-09-01 DOI: 10.1109/SYNASC57785.2022.00045
Sorin Valcan, Mihail Gaianu
{"title":"Eye Detection For Drivers Using Convolutional Neural Networks With Automatically Generated Ground Truth Data","authors":"Sorin Valcan, Mihail Gaianu","doi":"10.1109/SYNASC57785.2022.00045","DOIUrl":"https://doi.org/10.1109/SYNASC57785.2022.00045","url":null,"abstract":"Eye detection is an essential feature for driver monitoring systems acting as a base functionality for other algorithms like attention or drowsiness detection. Multiple methods for eye detection exist. The machine learning based methods involve a manual labeling process in order to generate training and testing datasets. This paper presents an eye detection algorithm based on convolutional neural networks trained using automatically generated ground truth data and proves that we can train very good machine learning models using automatically generated labels. Such approach reduces the effort needed for manual labeling and data preprocessing.","PeriodicalId":446065,"journal":{"name":"2022 24th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing (SYNASC)","volume":"42 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130123122","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: 1
Proof of Useful Work Based on Matrix Computation 基于矩阵计算的有用功证明
2022 24th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing (SYNASC) Pub Date : 2022-09-01 DOI: 10.1109/SYNASC57785.2022.00026
Cojocaru Dragos
{"title":"Proof of Useful Work Based on Matrix Computation","authors":"Cojocaru Dragos","doi":"10.1109/SYNASC57785.2022.00026","DOIUrl":"https://doi.org/10.1109/SYNASC57785.2022.00026","url":null,"abstract":"Due to the inherently wasteful nature of traditional proof of work mechanisms in blockchain networks, researchers are motivated to find alternatives that can make use of the computational power expended in the process. There are a number of such applications, however most of them target very specific problems, and few are proven to work in practice. This paper presents a proof of work mechanism based on matrix computation, serving a much wider range of applications while serving as the consensus mechanism of a blockchain network. I will cover the current research in the proof of useful work area, and focus on Proof of eXercise (PoX), another mechanism based on matrix computation. Proof of Computation (PoC), the consensus mechanism described in this paper, is a redesigned version of PoX. The mechanism is backed by a series of experiments that confirm the functionality of the protocol.","PeriodicalId":446065,"journal":{"name":"2022 24th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing (SYNASC)","volume":"211 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128623287","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
Using N-Gram Variations in Static Analysis for Malware Detection 在静态分析中使用N-Gram变量进行恶意软件检测
2022 24th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing (SYNASC) Pub Date : 2022-09-01 DOI: 10.1109/SYNASC57785.2022.00037
Marco Radovancovici, Darius Galis, Ciprian-Petrisor Pungila
{"title":"Using N-Gram Variations in Static Analysis for Malware Detection","authors":"Marco Radovancovici, Darius Galis, Ciprian-Petrisor Pungila","doi":"10.1109/SYNASC57785.2022.00037","DOIUrl":"https://doi.org/10.1109/SYNASC57785.2022.00037","url":null,"abstract":"Most of intrusion detection systems nowadays employ signature based analysis that often fails when newer or modified malware versions are brought into play. Intrusion detection systems working with cryptanalysis would offer some advantages against obfuscated code or newly derived viruses based on classic exploits. In this paper, we are applying an index of coincidence approach from cryptanalysis with a N-gram pattern-matching technique on recent binaries, to attempt classification of malicious code. Those characteristics are studied with the use of modern data mining methods, namely K-means, to discover interesting clusters for classification and properties of malicious behavior. The challenges of gathering, working with, learning from and classifying large amounts of virus datasets with different techniques are explored.","PeriodicalId":446065,"journal":{"name":"2022 24th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing (SYNASC)","volume":"50 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116945670","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
Balanced Dense Multivariate Multiplication: The General Case 平衡稠密多元乘法:一般情况
2022 24th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing (SYNASC) Pub Date : 2022-09-01 DOI: 10.1109/SYNASC57785.2022.00015
M. M. Maza, Haoze Yuan
{"title":"Balanced Dense Multivariate Multiplication: The General Case","authors":"M. M. Maza, Haoze Yuan","doi":"10.1109/SYNASC57785.2022.00015","DOIUrl":"https://doi.org/10.1109/SYNASC57785.2022.00015","url":null,"abstract":"We propose general preprocessing techniques to reshape dense multivariate polynomials over finite fields, in order to minimize the cost of memory accesses, while preserving sufficient parallelism, so as to reduce the running time of polynomial multiplication in multi-threaded implementations.","PeriodicalId":446065,"journal":{"name":"2022 24th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing (SYNASC)","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117021692","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
Quantitative Programming and Markov Decision Processes 定量规划与马尔可夫决策过程
2022 24th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing (SYNASC) Pub Date : 2022-09-01 DOI: 10.1109/SYNASC57785.2022.00027
E. Todoran
{"title":"Quantitative Programming and Markov Decision Processes","authors":"E. Todoran","doi":"10.1109/SYNASC57785.2022.00027","DOIUrl":"https://doi.org/10.1109/SYNASC57785.2022.00027","url":null,"abstract":"Quantitative programming (or performance evaluation programming) is a programming paradigm, which supports the formal verification of (bounded versions of) concurrent programs by using model checking techniques. By partitioning the state space of programs into bisimulation equivalence classes, this approach enables the formal verification of programs with large state spaces. The paradigm was introduced by us in previous works by developing an experimental concurrent language designed to facilitate the construction of probabilistic models that capture the behavior of programs and that can be verified by using probabilistic model checking techniques. The experimental language introduced in previous works is extended in this paper with constructions which enable the specification of behavioral equivalence classes. Concurrent programs are translated into corresponding probabilistic models, which are analyzed by using the PRISM probabilistic model checker. The programmer identifies bisimulation equivalence classes to enable the formal verification of programs with large state spaces. For formal verification, we employ Markov Decision Processes.","PeriodicalId":446065,"journal":{"name":"2022 24th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing (SYNASC)","volume":"43 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129512167","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
Homotopy Techniques for Analytic Combinatorics in Several Variables 多变量解析组合的同伦技术
2022 24th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing (SYNASC) Pub Date : 2022-08-09 DOI: 10.1109/SYNASC57785.2022.00014
Kisun Lee, S. Melczer, Joško Smolčić
{"title":"Homotopy Techniques for Analytic Combinatorics in Several Variables","authors":"Kisun Lee, S. Melczer, Joško Smolčić","doi":"10.1109/SYNASC57785.2022.00014","DOIUrl":"https://doi.org/10.1109/SYNASC57785.2022.00014","url":null,"abstract":"We combine tools from homotopy continuation solvers with the methods of analytic combinatorics in several variables to give the first practical algorithm and implementation for the asymptotics of multivariate rational generating functions not relying on a non-algorithmically checkable ‘combinatorial’ non-negativity assumption. Our homotopy implementation terminates on examples from the literature in three variables, and we additionally describe heuristic methods that terminate and correctly predict asymptotic behaviour in reasonable time on examples in even higher dimension. Our results are implemented in Julia, through the use of the HomotopyContinuation.jl package, and we provide a selection of examples and benchmarks.","PeriodicalId":446065,"journal":{"name":"2022 24th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing (SYNASC)","volume":"36 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-08-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121310749","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: 3
首页 上一页
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整，为了账户安全，请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
请完成安全验证×
相关产品
×
本文献相关产品
联系我们：info@booksci.cn Book学术提供免费学术资源搜索服务，方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号：604180095
Book学术官方微信