2022 4th International Conference on Pattern Analysis and Intelligent Systems (PAIS)最新文献_第4页

DeepD_DrugC: Deep and distributed workflow to predict drug- candidates 深度和分布式工作流程预测候选药物

2022 4th International Conference on Pattern Analysis and Intelligent Systems (PAIS) Pub Date : 2022-10-12 DOI: 10.1109/PAIS56586.2022.9946898

Karima Sid, Soumia Zertal, Chaker Mezioud

{"title":"DeepD_DrugC: Deep and distributed workflow to predict drug- candidates","authors":"Karima Sid, Soumia Zertal, Chaker Mezioud","doi":"10.1109/PAIS56586.2022.9946898","DOIUrl":"https://doi.org/10.1109/PAIS56586.2022.9946898","url":null,"abstract":"The applications of computational tools at various stages of drug discovery is one of the most active axes of research. Virtual Screening (VS) is a very common application, which aims to screen and analyze large chemical libraries using algorithms and models to extract drug-candidates that can bind to therapeutic targets. Machine learning (ML) techniques are widely applied as a tool to analyze the chemical libraries in ligand-based virtual screening (LBVS). Deep learning (DL) is a novel mode of machine learning that provides several new architectures primarily based on classical Artificial Neural Network algorithms, but with many hidden layers to learn features with multiple levels of abstraction. Recently, chemical libraries are identified as Big Data, due to their huge size, the variety of data, and the speed at which they are created, streamed and aggregated. In this context, we need advanced tools to handle and treat this type of data. Apache Spark is the most widely used engine for big data processing, with many improvements that make it more suitable for virtual screening analysis. In this work, we propose a novel workflow named DeepD_ DrugC based on Spark and Deep Neural Network model implemented with Deeplearning4j (DL4J) to improve the prediction results in LBVS. To evaluate the workflow, we suggest a process to create training datasets using the PubChem Bioassay database for cancer disease. The evaluation results show a good precision more than 93%, with acceptable scaling behavior.","PeriodicalId":266229,"journal":{"name":"2022 4th International Conference on Pattern Analysis and Intelligent Systems (PAIS)","volume":"127 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122905952","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

A Virtual Clustering for Data Dissemination in Vehicular Fog Computing 车辆雾计算中数据传播的虚拟聚类

2022 4th International Conference on Pattern Analysis and Intelligent Systems (PAIS) Pub Date : 2022-10-12 DOI: 10.1109/PAIS56586.2022.9946907

Sahraoui Abdelatif, Abdelhak Ghozlane, P. Roose

引用次数: 0

Testing Cyber-Physical Production System: Test Methods Categorization and dataset 测试网络物理生产系统:测试方法、分类和数据集

2022 4th International Conference on Pattern Analysis and Intelligent Systems (PAIS) Pub Date : 2022-10-12 DOI: 10.1109/PAIS56586.2022.9946868

Zina Oudina, M. Derdour, Mohammed Mounir Bouhamed

引用次数: 3

Keeping the Privacy and the Security of the Knowledge Graph Completion Using Blockchain Technology 利用区块链技术保护知识图谱完成的隐私和安全性

2022 4th International Conference on Pattern Analysis and Intelligent Systems (PAIS) Pub Date : 2022-10-12 DOI: 10.1109/PAIS56586.2022.9946869

A. Djeddai, Rofaida Khemaissia

引用次数: 1

A survey of parallel clustering algorithms based on vertical scaling platforms for big data 基于垂直尺度平台的大数据并行聚类算法研究

2022 4th International Conference on Pattern Analysis and Intelligent Systems (PAIS) Pub Date : 2022-10-12 DOI: 10.1109/PAIS56586.2022.9946663

Hadjir Zemmouri, Said Labed, Akram Kout

{"title":"A survey of parallel clustering algorithms based on vertical scaling platforms for big data","authors":"Hadjir Zemmouri, Said Labed, Akram Kout","doi":"10.1109/PAIS56586.2022.9946663","DOIUrl":"https://doi.org/10.1109/PAIS56586.2022.9946663","url":null,"abstract":"Clustering, or cluster analysis, is an important unsupervised task in machine learning that determines how the observed data naturally clusters. Many efficient traditional clustering methods based on different behaviours, such as partitioning’ hierarchical, grid, model, and density based, have been proposed in recent decades. However, clustering itself is considered an NP-hard problem, and it becomes more challenging when the clustered data is large. The classical clustering techniques cannot handle big data problems due to their large volume, fast generation, significant heterogeneity and complexity. Therefore, more effective, flexible, and efficient clustering approaches are required. Recently, the parallel and distributed computing concepts gives birth to the parallel clustering algorithms. Nowadays, the researches focus on scalable clustering methods based on different acceleration platforms to deal with big data problems. The acceleration platforms can be classified into horizontal and vertical-scaling platforms. In this paper we present a recent overview of the latest parallel and distributed clustering algorithms based on vertical scaling platforms. Otherwise, the paper gives a discussion that will be useful for researchers to propose more effective and efficient algorithms for Big Data clustering.","PeriodicalId":266229,"journal":{"name":"2022 4th International Conference on Pattern Analysis and Intelligent Systems (PAIS)","volume":"40 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127089179","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

Development of a biometric authentication platform using voice recognition 基于语音识别的生物识别认证平台的开发

2022 4th International Conference on Pattern Analysis and Intelligent Systems (PAIS) Pub Date : 2022-10-12 DOI: 10.1109/PAIS56586.2022.9946890

Abdelmadjid Benmachiche, Bouzata Hadjar, Ines Boutabia, Ali Abdelatif Betouil, Majda Maâtallah, Amina Makhlouf

{"title":"Development of a biometric authentication platform using voice recognition","authors":"Abdelmadjid Benmachiche, Bouzata Hadjar, Ines Boutabia, Ali Abdelatif Betouil, Majda Maâtallah, Amina Makhlouf","doi":"10.1109/PAIS56586.2022.9946890","DOIUrl":"https://doi.org/10.1109/PAIS56586.2022.9946890","url":null,"abstract":"Nowadays, several areas have turned to speech recognition, as they have witnessed its efficiency in maintaining the privacy of users and facilitating access and use of numerous applications, systems even establishments. Our work revolves around recognizing a form of speech from a single word, where the main objective is to identify as accurately as possible a set of predefined words from brief audio clips. a Speech Commands dataset consisting of 65 000 one-second-long statements of 30 short term, is applied. We use a Convolutional Neural Network (CNN) to classify representatives with two-dimensional convolutions on the audio waveform. Unlike many classic techniques with critical feature engineering, we benefit from the power of deep learning to comprehend the feature representation while training. The prototype achieves an acceptable accuracy rate on the validation set. Our model has provided satisfactory results during training with high accuracy compared to its pre-descendants. Still, room for errors exists in words exceeding the range of the training data and especially noisy samples.","PeriodicalId":266229,"journal":{"name":"2022 4th International Conference on Pattern Analysis and Intelligent Systems (PAIS)","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127126010","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

RFID and NFC authentication protocol for securing a payment transaction 用于确保支付交易安全的RFID和NFC认证协议

2022 4th International Conference on Pattern Analysis and Intelligent Systems (PAIS) Pub Date : 2022-10-12 DOI: 10.1109/PAIS56586.2022.9946661

Samir Chabbi, Chaouki Araar

{"title":"RFID and NFC authentication protocol for securing a payment transaction","authors":"Samir Chabbi, Chaouki Araar","doi":"10.1109/PAIS56586.2022.9946661","DOIUrl":"https://doi.org/10.1109/PAIS56586.2022.9946661","url":null,"abstract":"RFID (Radio Frequency Identification) is a technology that permits to identify objects with a radio frequency field for few meters distance. It is applied in several fields such as traceability, logistics, military, security, healthcare, library, etc. Its successor NFC (Near Field Communication)), on the contrary, is used to transmit messages at a short distance (less than 10 Cent.). Recently, NFC is frequently used for payment transaction using ATM and smartphone both equipped of this technology. Unfortunately, the information transferred with this technology during a payment transaction can be an objectif for threads to steale personal and privacy data that concern a user. This paper introduces a new method for payment transaction that combines RFID and NFC. This process which uses an authentication protocol is proposed in order to (1) secure the payment transaction using an Automated Teller Machine (ATM) and a smartphone both equipped with these two technologies, (2) minimize the waiting chain in front of the ATM for agents using NFC by minimizing the transaction time. To evaluate the performance of our proposal, we tested its security against few attacks. A security and performance comparison of our technique with few recent and important methods is performed and shows the effectiveness of the solution.","PeriodicalId":266229,"journal":{"name":"2022 4th International Conference on Pattern Analysis and Intelligent Systems (PAIS)","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126976551","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

Smart Virtual Environment To Support Collaborative Medical Diagnosis 支持协同医疗诊断的智能虚拟环境

2022 4th International Conference on Pattern Analysis and Intelligent Systems (PAIS) Pub Date : 2022-10-12 DOI: 10.1109/PAIS56586.2022.9946910

Asma Merabet, Mohamed Abderraouf Ferradji

引用次数: 0

Machine learning based cryptanalysis techniques: perspectives, challenges and future directions 基于机器学习的密码分析技术:观点、挑战和未来方向

2022 4th International Conference on Pattern Analysis and Intelligent Systems (PAIS) Pub Date : 2022-10-12 DOI: 10.1109/PAIS56586.2022.9946889

Zakaria Tolba, M. Derdour, N. H. Dehimi

引用次数: 0

Study of the influence of RGB and Lab color spaces on the performance of multifocus image fusion techniques RGB和Lab色彩空间对多聚焦图像融合技术性能影响的研究

2022 4th International Conference on Pattern Analysis and Intelligent Systems (PAIS) Pub Date : 2022-10-12 DOI: 10.1109/PAIS56586.2022.9946904

Sarra Babahenini, F. Charif, A. Taleb-Ahmed

{"title":"Study of the influence of RGB and Lab color spaces on the performance of multifocus image fusion techniques","authors":"Sarra Babahenini, F. Charif, A. Taleb-Ahmed","doi":"10.1109/PAIS56586.2022.9946904","DOIUrl":"https://doi.org/10.1109/PAIS56586.2022.9946904","url":null,"abstract":"In order to create a single image, multifocus image fusion brings together the important details and focused areas of the input multifocus images. Diverse camera depths of the field are used to capture these multi-focus images. Spatial domain focusing measurement has been used to introduce various multifocus image fusion algorithms. In this paper, we focus on the implementation of three multifocus color image fusion techniques: salience detection based multifocus image fusion (SDMF), salience detection using the technique of contourlet transformation (CT) and multi-scale guided filter (MGF) based fusion technique, using various color space models to improve the fusion result. The main objective is to examine whether the effects of R.G.B and L.A.B spaces have an influence on their recognition rate. We evaluated the performance of these techniques based on SSIM metrics, $mathbf{Q}^{(mathbf{AB} / mathbf{F})}, mathbf{L}^{(mathbf{AB} / mathbf{F})} mathbf{N}^{(mathbf{AB} / mathbf{F})}$ and FMI. The experimental results on the test set show that the RGB space performs better than the LAB space.","PeriodicalId":266229,"journal":{"name":"2022 4th International Conference on Pattern Analysis and Intelligent Systems (PAIS)","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116244258","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