Proceedings of the 13th International Conference on Intelligent Systems: Theories and Applications最新文献

Multi Level interdependencies Management for resilience in Critical Infrastructures 关键基础设施弹性的多层次相互依赖管理

Proceedings of the 13th International Conference on Intelligent Systems: Theories and Applications Pub Date : 2020-09-23 DOI: 10.1145/3419604.3419791

Ouafae Kasmi, Amine Baïna, M. Bellafkih

{"title":"Multi Level interdependencies Management for resilience in Critical Infrastructures","authors":"Ouafae Kasmi, Amine Baïna, M. Bellafkih","doi":"10.1145/3419604.3419791","DOIUrl":"https://doi.org/10.1145/3419604.3419791","url":null,"abstract":"Modeling resilience of interdependent critical infrastructure is recently an important task in literature researches. The guard of these critical infrastructures (CI) is fundamental for the efficient functioning of society in particular and nations in general. The CI is composed of several entities that have highly interconnected and collaborated with other organizations to accomplish services according to mutual interdependencies and interconnections. These interdependencies reinforce the systems to be more resilient in case of vulnerabilities and failures. In this sense, sophisticated management is required to improve the protection of these infrastructures and ensure their safety, and continuous operation in cases of failures and disruptions of services. In this paper, we propose a new approach of resilience to manage disruptions and failures in critical infrastructure using multi-level interdependencies. The aim of this paper is threefold: first, we propose a road map for modeling multilevel interdependencies. Second, we introduce a new paradigm of nodes classification using a convolutional neural network. Third, we propose agents to each CI to have a global view of the resilience policy of the others using multi-levels interdependencies. Simulations results show that by adopting our proposed approach using multi-level interdependencies, improved management for resilience is gained in these CIs.","PeriodicalId":250715,"journal":{"name":"Proceedings of the 13th International Conference on Intelligent Systems: Theories and Applications","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122065040","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

Towards Mining Semantically Enriched Configurable Process Models 面向挖掘语义丰富的可配置过程模型

Proceedings of the 13th International Conference on Intelligent Systems: Theories and Applications Pub Date : 2020-09-23 DOI: 10.1145/3419604.3419797

Aicha Khannat, Hanae Sbaï, L. Kjiri

{"title":"Towards Mining Semantically Enriched Configurable Process Models","authors":"Aicha Khannat, Hanae Sbaï, L. Kjiri","doi":"10.1145/3419604.3419797","DOIUrl":"https://doi.org/10.1145/3419604.3419797","url":null,"abstract":"Providing configurable process model with high quality is a primary objective to derive process variants with better accuracy and facilitate process model reuse. For this purpose, many research works have been interested in configurable process mining techniques to discover and configure processes from event logs. Moreover, to use the knowledge captured by event logs when mining processes, the concept of semantic process mining is introduced. It allows for combining semantic technologies with process mining. Despite the diversity of works in mining and customizing configurable process models, the application of these techniques is still limited to use semantics in minimizing the complexity of discovered processes. However, it seems to be pertinent to discover semantically enriched configurable process models directly from event logs. Consequently, this can facilitate using semantic in configuring, verifying conformance or enhancing discovered configurable processes. In this paper, we present a comparative study of existing works that focus on mining configurable process models with respect to semantic technologies. Our aim is to propose a new framework to automatically discover semantically enriched configurable processes.","PeriodicalId":250715,"journal":{"name":"Proceedings of the 13th International Conference on Intelligent Systems: Theories and Applications","volume":"36 12","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114117410","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

An Efficient Lightweight Algorithm for Automatic Meters Identification and Error Management in Arabic Poetry 一种高效轻量级的阿拉伯诗歌仪表自动识别与误差管理算法

Proceedings of the 13th International Conference on Intelligent Systems: Theories and Applications Pub Date : 2020-09-23 DOI: 10.1145/3419604.3419781

Karim Baïna, Hamza Moutassaref

引用次数: 1

A Qualitative-Driven Study of Irreversible Data Anonymizing Techniques in Databases 数据库中不可逆数据匿名化技术的定性研究

Proceedings of the 13th International Conference on Intelligent Systems: Theories and Applications Pub Date : 2020-09-23 DOI: 10.1145/3419604.3419788

Siham Arfaoui, A. Belmekki, Abdellatif Mezrioui

引用次数: 1

Evaluation of Classical Descriptors coupled to Support Vector Machine Classifier for Phosphate ore Screening monitoring 经典描述符与支持向量机分类器耦合的磷矿筛分监测评价

Proceedings of the 13th International Conference on Intelligent Systems: Theories and Applications Pub Date : 2020-09-23 DOI: 10.1145/3419604.3419785

Laila El hiouile, A. Errami, N. Azami, R. Majdoul, L. Deshayes

{"title":"Evaluation of Classical Descriptors coupled to Support Vector Machine Classifier for Phosphate ore Screening monitoring","authors":"Laila El hiouile, A. Errami, N. Azami, R. Majdoul, L. Deshayes","doi":"10.1145/3419604.3419785","DOIUrl":"https://doi.org/10.1145/3419604.3419785","url":null,"abstract":"Phosphorus is an important and finite resource that is utilized mainly to produce phosphate fertilizers that assist in crop production. From phosphate ore to phosphate a process of beneficiation is required to remove the unnecessary minerals contains in the phosphate ore and to increase the grade concentration of mining product. The screening unit is a very important and critical step in this process. However, during this stage, many dysfunctions and anomalies can occur which impact the yield and quality of the product. Hence, it is essential to be monitored for real-time quality control. The purpose of this work is to automate surveillance and anomaly detection on the screening unit by using artificial vision techniques. Classical and supervised image classification approach has been used based on tree manual descriptors; HOG, SIFT, and LBP combined each with the support vector machine classifier. The evaluation of the three combinations shows that the HOG-SVM combination has the best trade-off between both accuracy and runtime.","PeriodicalId":250715,"journal":{"name":"Proceedings of the 13th International Conference on Intelligent Systems: Theories and Applications","volume":"159 3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125932929","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

State of the art of Fairness, Interpretability and Explainability in Machine Learning: Case of PRIM 机器学习中的公平性、可解释性和可解释性:以PRIM为例

Proceedings of the 13th International Conference on Intelligent Systems: Theories and Applications Pub Date : 2020-09-23 DOI: 10.1145/3419604.3419776

Rym Nassih, A. Berrado

引用次数: 7

A Frequency-Category Based Feature Selection in Big Data for Text Classification 基于频率分类的大数据文本分类特征选择

Proceedings of the 13th International Conference on Intelligent Systems: Theories and Applications Pub Date : 2020-09-23 DOI: 10.1145/3419604.3419620

Houda Amazal, M. Ramdani, M. Kissi

引用次数: 0

ARG-RPL: Arrangement Graph-, Region-Based Routing Protocol for Internet of Things ARG-RPL:物联网基于区域的排列图路由协议

Proceedings of the 13th International Conference on Intelligent Systems: Theories and Applications Pub Date : 2020-09-23 DOI: 10.1145/3419604.3419761

Abdellatif Serhani, N. Naja, A. Jamali

{"title":"ARG-RPL: Arrangement Graph-, Region-Based Routing Protocol for Internet of Things","authors":"Abdellatif Serhani, N. Naja, A. Jamali","doi":"10.1145/3419604.3419761","DOIUrl":"https://doi.org/10.1145/3419604.3419761","url":null,"abstract":"Internet of Things, is an innovative technology which allows the connection of physical things with the digital world through the use of heterogeneous networks and communication technologies. The Routing Protocol for low power and Lossy networks (RPL) is standardized as a routing protocol for LLNs. However, more and more of experimental results demonstrate that RPL performs poorly in throughput and adaptability to network dynamics. In this study, we applied properties of arrangement graphs to design a newly structured routing protocol, extension of RPL, named as Arrangement Graph based Adaptive routing protocol ARG-RPL that enhances the supports of high throughput, adaptivity and mobility for RPL without any modification or assumption on the OFs. In such protocol, the IDs between the two adjacent nodes differ only one digit and thus, self configuration and self optimization in LLNs networks are easy while keeping the low maintenance cost. Distributed algorithms have been developed, consisting of two stages: initialization stage and reactive routing discovery stage. We implement ARG-RPL on the Contiki operating system, and construct extensive evaluation using a large-scale simulations on Cooja. Analysis of experimental results show that the establishment of the system and the routing processing could achieve better performance than those obtained in the RPL and ER-RPL.","PeriodicalId":250715,"journal":{"name":"Proceedings of the 13th International Conference on Intelligent Systems: Theories and Applications","volume":"32 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126930415","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

Customer Segmentation With Machine Learning: New Strategy For Targeted Actions 用机器学习进行客户细分:目标行动的新策略

Proceedings of the 13th International Conference on Intelligent Systems: Theories and Applications Pub Date : 2020-09-23 DOI: 10.1145/3419604.3419794

Lahcen Abidar, Dounia Zaidouni, Abdeslam Ennouaary

引用次数: 5

ECG-based Arrhythmia Classification & Clinical Suggestions: An Incremental Approach of Hyperparameter Tuning 基于心电图的心律失常分类及临床建议:一种超参数调整的增量方法

Proceedings of the 13th International Conference on Intelligent Systems: Theories and Applications Pub Date : 2020-09-23 DOI: 10.1145/3419604.3419787

M. Serhani, A. Navaz, Hany Al Ashwal, N. Al-Qirim

{"title":"ECG-based Arrhythmia Classification & Clinical Suggestions: An Incremental Approach of Hyperparameter Tuning","authors":"M. Serhani, A. Navaz, Hany Al Ashwal, N. Al-Qirim","doi":"10.1145/3419604.3419787","DOIUrl":"https://doi.org/10.1145/3419604.3419787","url":null,"abstract":"Cardiovascular diseases (CVD) are the principal cause of death globally. Electrocardiography (ECG) is a widely adopted tool to quantify heart activities to detect any heart abnormalities. Arrhythmia is one of these CVDs that heavily relies on continuous ECG recordings in order to detect and predict irregularities in the heart rhythms. Various Deep Learning (DL) approaches has been heavily used to classify and predict different heart rhythms. However, most of the proposed works do not consider the various hyperparameter optimization and tuning to get the full potential of the DL model and achieve higher accuracy. Besides, very few works implemented the full monitoring cycle and close the loop to propose some clinical and non-clinical recommendations. Therefore, in this paper, we adopt the Convolutional Neural Network (CNN) model and we apply various parameter optimization to capture various properties of the data, the training, and the model. We also close the monitoring loop and suggest tailored recommendations for each category of arrhythmia that go beyond simple to more deeper diagnosis using the Global Registry of Acute Coronary Events (GRACE), and the European Guidelines on CVDs prevention in clinical practice (ESC/EAS 2016). We conducted a set of experiments to evaluate our model and the set of hyperparameter optimization we have experienced and the results we have obtained showed significant improvement in the prediction accuracy after a couple of optimization iterations.","PeriodicalId":250715,"journal":{"name":"Proceedings of the 13th International Conference on Intelligent Systems: Theories and Applications","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129009624","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: 4