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

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FB-RO-Offense – A Romanian Dataset and Baseline Models for Detecting Offensive Language in Facebook Comments FB-RO-Offense -罗马尼亚数据集和基线模型，用于检测Facebook评论中的攻击性语言
2022 24th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing (SYNASC) Pub Date : 2022-09-01 DOI: 10.1109/SYNASC57785.2022.00029
Gabriel-Razvan Busuioc, Andrei Paraschiv, M. Dascalu
{"title":"FB-RO-Offense – A Romanian Dataset and Baseline Models for Detecting Offensive Language in Facebook Comments","authors":"Gabriel-Razvan Busuioc, Andrei Paraschiv, M. Dascalu","doi":"10.1109/SYNASC57785.2022.00029","DOIUrl":"https://doi.org/10.1109/SYNASC57785.2022.00029","url":null,"abstract":"In the past decade, social media platforms gained a lot of popularity amongst people all around the globe, some of them seizing this opportunity to proliferate offensive language and hate speech. In addition, platforms that choose not to consider text filtering techniques are being exploited by users who tend to use offensive and abusive language. This paper presents the creation and annotation of a novel Romanian language corpus for offensive language detection, FB-RO-Offense, an offensive speech dataset containing 4,455 organic generated comments from Facebook live broadcasts annotated not only for coarse-grained binary detection tasks but also fine-grained, based on the degree of the offense. We describe the data collection process and the annotation procedure and analyze the content of the corpus. Additionally, we present the results of automatic classification processes using state-of-the-art classification processes and establish a strong baseline for this new dataset including SVM, BERT-based, and CNN architectures, with results that show an F1-score of 0.83 for a four-way classification and an F1-score of 0.90 for the binary classification.","PeriodicalId":446065,"journal":{"name":"2022 24th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing (SYNASC)","volume":"1 4 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":"126144755","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
Prescriptive Analytics: When Data- and Simulation-based Models Interact in a Cooperative Way 规定性分析:当基于数据和模拟的模型以合作的方式交互时
2022 24th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing (SYNASC) Pub Date : 2022-09-01 DOI: 10.1109/SYNASC57785.2022.00009
M. Affenzeller, Michael Bögl, Lukas Fischer, F. Sobieczky, Kaifeng Yang, Jan Zenisek
{"title":"Prescriptive Analytics: When Data- and Simulation-based Models Interact in a Cooperative Way","authors":"M. Affenzeller, Michael Bögl, Lukas Fischer, F. Sobieczky, Kaifeng Yang, Jan Zenisek","doi":"10.1109/SYNASC57785.2022.00009","DOIUrl":"https://doi.org/10.1109/SYNASC57785.2022.00009","url":null,"abstract":"Business analytics is an extensive use of data acquired from diverse sources, statistical and quantitative analysis, explainable and predictive models, and fact-based management to make better strategic decisions for different stakeholders. To be able to model complex systems holistically in such a way that they can be fed into an efficient simulation-based optimization in the sense of prescriptive analytics, approaches and solutions that go beyond state-of-the-art are required. This paper introduces the basic technologies used in prescriptive analytics and proposes secure prescriptive analytics (SPA) that is based on component-based hierarchical modeling and dynamic optimization. Each element under the SPA framework is defined and illustrated by an example of production plan optimization.","PeriodicalId":446065,"journal":{"name":"2022 24th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing (SYNASC)","volume":"20 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":"122015156","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
An Ant Colony Optimisation Approach to the Densest k-Subgraph Problem* 最密集k子图问题的蚁群优化方法*
2022 24th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing (SYNASC) Pub Date : 2022-09-01 DOI: 10.1109/SYNASC57785.2022.00039
Zoltán Tasnádi, Noémi Gaskó
{"title":"An Ant Colony Optimisation Approach to the Densest k-Subgraph Problem*","authors":"Zoltán Tasnádi, Noémi Gaskó","doi":"10.1109/SYNASC57785.2022.00039","DOIUrl":"https://doi.org/10.1109/SYNASC57785.2022.00039","url":null,"abstract":"The densest k-subgraph problem is a relaxation of the well-known maximum clique problem and consists of finding a subgraph with exactly k nodes and a maximum number of edges. An ant colony optimisation-based approach is proposed to solve this combinatorial optimisation problem. Numerical experiments show the effectiveness and potential of the proposed approach.","PeriodicalId":446065,"journal":{"name":"2022 24th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing (SYNASC)","volume":"191 8 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":"115016380","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
Improving the Diagnostic of Contrast Enhanced Ultrasound Imaging using Optical Flow for Focal Liver Lesion Detection 提高超声造影光流对肝局灶性病变的诊断价值
2022 24th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing (SYNASC) Pub Date : 2022-09-01 DOI: 10.1109/SYNASC57785.2022.00048
Cristina Laura Sîrbu, G. Simion, C. Căleanu
{"title":"Improving the Diagnostic of Contrast Enhanced Ultrasound Imaging using Optical Flow for Focal Liver Lesion Detection","authors":"Cristina Laura Sîrbu, G. Simion, C. Căleanu","doi":"10.1109/SYNASC57785.2022.00048","DOIUrl":"https://doi.org/10.1109/SYNASC57785.2022.00048","url":null,"abstract":"Our proposal aims an automatic method used for obtaining the ultrasound image of a region of interest based on the optical flow computation. Combined with a kernel correlation filter tracking algorithm and a Xception deep convolutional neural network architecture, our solution provides state-of-the-art results (over 90% accuracy) in the automatic diagnosis of liver lesion using contrast enhanced ultrasound.","PeriodicalId":446065,"journal":{"name":"2022 24th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing (SYNASC)","volume":"4 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":"131412912","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
Artificial Conflict Sampling for Real Satisfiability Problems 真实可满足性问题的人工冲突抽样
2022 24th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing (SYNASC) Pub Date : 2022-09-01 DOI: 10.1109/SYNASC57785.2022.00018
J. Davenport, A. Uncu
{"title":"Artificial Conflict Sampling for Real Satisfiability Problems","authors":"J. Davenport, A. Uncu","doi":"10.1109/SYNASC57785.2022.00018","DOIUrl":"https://doi.org/10.1109/SYNASC57785.2022.00018","url":null,"abstract":"We outline some preliminary ideas on a guided theory assignment of variables in a real (QF_NRA) satisfiability problem. One objective of this approach is to mix the topdown approach of cylindric algebraic decomposition and the bottom-up approach of partial theory assignments of modern SAT/SMT solvers. We use equational constraints and a single strict inequality at a time to artificially create conflicting variable assignment traces, which can later be used in conflict resolution to enrich the constraints of the original satisfiability problem.","PeriodicalId":446065,"journal":{"name":"2022 24th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing (SYNASC)","volume":"72 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":"133415427","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
Fact-checking with explanations 有解释的事实核查
2022 24th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing (SYNASC) Pub Date : 2022-09-01 DOI: 10.1109/SYNASC57785.2022.00031
Adrian Groza, Áron Katona
{"title":"Fact-checking with explanations","authors":"Adrian Groza, Áron Katona","doi":"10.1109/SYNASC57785.2022.00031","DOIUrl":"https://doi.org/10.1109/SYNASC57785.2022.00031","url":null,"abstract":"We present an approach for automated fact-checking, given a trusted knowledge base and a natural language text. The FACE (FAct Checker with Explanations) system is capable of extracting the knowledge behind the sentences, and decide what is entailed in the trusted sources and what is in conflict with them, providing also explanations and counter speeches in English. The system also specifies the provenance of each of its argument, thus it can be traced back to the source of the information.Description logic representation of the input is obtained using the FRED machine reader, which is further improved by detecting and handling translation patterns. The obtained ontology is aligned to the knowledge base using the WordNet database in a custom algorithm, then entailment and conflict detection is performed with the Hermit reasoner, through which we obtain the explanations and counter speeches which are verbalized to Attempto Controlled English.The fact checker is demonstrated on Covid-19 related sentences, however it is domain independent, and can be used with other knowledge bases as well.","PeriodicalId":446065,"journal":{"name":"2022 24th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing (SYNASC)","volume":"16 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":"132135541","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
Learning networks hyper-parameter using multi-objective optimization of statistical performance metrics 学习网络超参数采用多目标优化统计性能指标
2022 24th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing (SYNASC) Pub Date : 2022-09-01 DOI: 10.1109/SYNASC57785.2022.00044
G. Torres, C. Sánchez, D. Gil
{"title":"Learning networks hyper-parameter using multi-objective optimization of statistical performance metrics","authors":"G. Torres, C. Sánchez, D. Gil","doi":"10.1109/SYNASC57785.2022.00044","DOIUrl":"https://doi.org/10.1109/SYNASC57785.2022.00044","url":null,"abstract":"Deep Learning has enabled remarkable progress over the last years on a several objectives, such as image and speech recognition, and machine translation. Deep neural architectures are a main contribution for this progress. Current architectures have mostly been developed manually by engineers, which is a time-consuming and error-prone process. Because of this, there is growing interest in automated neural architecture search methods. In this paper we present a strategy for the optimization of network hyper-parameters using a multi-objective Non-dominated Sorting Genetic Algorithm combined with a nested cross-validation to optimize statistical metrics of the performance of networks. In order to illustrate the proposed hyper-parameter optimization, we have applied it to a use case that uses transformers to map abstract radiomic features to specific radiological annotations. Results obtained with the LUNA16 public data base show generalization power of the proposed optimization strategy for hyper-parameter setting.","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":"130601580","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
Empirical evaluation of LZW-Compressed Multiple Pattern Matching Algorithms lzw压缩多模式匹配算法的实证评价
2022 24th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing (SYNASC) Pub Date : 2022-09-01 DOI: 10.1109/SYNASC57785.2022.00028
Mario Reja
{"title":"Empirical evaluation of LZW-Compressed Multiple Pattern Matching Algorithms","authors":"Mario Reja","doi":"10.1109/SYNASC57785.2022.00028","DOIUrl":"https://doi.org/10.1109/SYNASC57785.2022.00028","url":null,"abstract":"Data compression is used to reduce the cost of storing and transmitting increasingly large datasets in various domains ranging from bioinformatics to particle physics and general purpose computing. Most of these areas require the ability to scan the datasets for patterns like DNA sequences, malicious executable code or various other string queries, an operation that is hindered by the altered form of the data. In order to speed up the matching process, several compressed pattern matching algorithms have been previously proposed. This paper presents an overview of the state of the art in multiple pattern matching of Lempel-Ziv-Welch encoded archives, together with experimental results.","PeriodicalId":446065,"journal":{"name":"2022 24th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing (SYNASC)","volume":"1 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":"130959309","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
Accelerating heuristic convergence on the "Evolution of Mona Lisa" problem by including image-centric mutation operators 通过包含以图像为中心的突变算子加速“蒙娜丽莎的进化”问题的启发式收敛
2022 24th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing (SYNASC) Pub Date : 2022-09-01 DOI: 10.1109/SYNASC57785.2022.00030
Theodor-Alexandru Vlad, Eugen Croitoru
{"title":"Accelerating heuristic convergence on the \"Evolution of Mona Lisa\" problem by including image-centric mutation operators","authors":"Theodor-Alexandru Vlad, Eugen Croitoru","doi":"10.1109/SYNASC57785.2022.00030","DOIUrl":"https://doi.org/10.1109/SYNASC57785.2022.00030","url":null,"abstract":"The \"Evolution of Mona Lisa\" problem aims to approximate a target image by overlapping many semi-transparent polygons. The problem has been tackled in the past using multiple Nature-Inspired heuristics, and our main contribution is adding image-centric mutation operators (scaling, rotating and translating polygons).We compare Genetic Algorithms, Hill-Climbing and Simulated Annealing. A candidate solution has variable length (of, at most, 300 decagons) and, due to the variable opacity of polygons, order matters – resulting, in practice, in a pseudo-Messy GA. We use the same representation and mutation operators for the trajectory methods which, due to the focus on wall-clock time, outperform our GA implementation.We find that these methods retain good image approximation at good run times: 98.9-99.2% (mean on 30 images), with a time limit of 30 minutes, on images 500-pixels tall.","PeriodicalId":446065,"journal":{"name":"2022 24th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing (SYNASC)","volume":"90 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":"130971680","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
Identification of Discrete Non-Linear Dynamics of a Radio-Frequency Power Amplifier Circuit using Symbolic Regression 用符号回归辨识射频功率放大器电路的离散非线性动力学
2022 24th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing (SYNASC) Pub Date : 2022-09-01 DOI: 10.1109/SYNASC57785.2022.00054
M. Steiger, H. Brachtendorf, G. Kronberger
{"title":"Identification of Discrete Non-Linear Dynamics of a Radio-Frequency Power Amplifier Circuit using Symbolic Regression","authors":"M. Steiger, H. Brachtendorf, G. Kronberger","doi":"10.1109/SYNASC57785.2022.00054","DOIUrl":"https://doi.org/10.1109/SYNASC57785.2022.00054","url":null,"abstract":"The identification of non-linearities or undesirable dynamic behavior of electrical components is a common problem. Previous modeling forms are largely based on extensive physical knowledge at the semiconductor level, which has produced reliable solutions over the past decades. This however implies the measurement of physical prototypes in laboratories, which can be costly. It is therefore desirable to have reliable software models of the prototypes available to outsource this procedure to simulators. This paper presents a number of solutions from the field of empirical modeling including symbolic regression, which allow to parameterize such models from measured values. As an example we are utilizing time-domain data from a real radio-frequency power amplifier circuit. We compare a Hammerstein-Wiener model with two methods for symbolic regression, and find that the Hammerstein-Wiener model produces the best predictions but has many non-zero coefficients. Both symbolic regression methods produce short linear models with slightly higher prediction error than the HW model.","PeriodicalId":446065,"journal":{"name":"2022 24th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing (SYNASC)","volume":"76 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":"127696893","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
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