2021 26th International Computer Conference, Computer Society of Iran (CSICC)最新文献

Static Detection of Ransomware Using LSTM Network and PE Header 基于LSTM网络和PE头的勒索软件静态检测

2021 26th International Computer Conference, Computer Society of Iran (CSICC) Pub Date : 2021-03-03 DOI: 10.1109/CSICC52343.2021.9420580

F. Manavi, A. Hamzeh

引用次数: 4

Click-Through Rate Prediction Using Feature Engineered Boosting Algorithms 使用特征工程增强算法的点击率预测

2021 26th International Computer Conference, Computer Society of Iran (CSICC) Pub Date : 2021-03-03 DOI: 10.1109/CSICC52343.2021.9420546

Mohamadreza Bakhtyari, S. Mirzaei

{"title":"Click-Through Rate Prediction Using Feature Engineered Boosting Algorithms","authors":"Mohamadreza Bakhtyari, S. Mirzaei","doi":"10.1109/CSICC52343.2021.9420546","DOIUrl":"https://doi.org/10.1109/CSICC52343.2021.9420546","url":null,"abstract":"Click-Through Rate (CTR) prediction plays a critical role in online advertisement campaigns and recommendation systems. Most of the state-of-the-art models are based on Factorization Machines and some of these models try to feed mapped field features to a deep learning component for learning users’ interests by modelling feature interactions. Deploying a model for CTR is an online task and should be able to perform well with a limited amount of data and time. While these models are very good at prediction inferences and learning feature interactions, their deep component needs a vast amount of data and time and does not perform well in limited situations.In a recent article, a combination of boosting algorithms with deep factorization machines (XDBoost algorithm) has been proposed. In this paper, we use a boosting algorithm for prediction inference with limited raw data and time. We show that with an appropriate feature engineering and fine parameter tuning for a raw boosting model, we can outperform XDBoost method and get better results. We will use exploratory data analysis to extract the main characteristics of the dataset and eliminate the redundant data. Then, by applying grid search scheme, we select the best values for the hyperparameters of our model.","PeriodicalId":374593,"journal":{"name":"2021 26th International Computer Conference, Computer Society of Iran (CSICC)","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-03-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134497037","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: 2

Polarimetric SAR Classification Using Ridge Regression-Based Polarimetric-Spatial Feature Extraction 基于岭回归的极化空间特征提取的极化SAR分类

2021 26th International Computer Conference, Computer Society of Iran (CSICC) Pub Date : 2021-03-03 DOI: 10.1109/CSICC52343.2021.9420603

M. Imani

引用次数: 4

Zero-Shot Estimation of Base Models’ Weights in Ensemble of Machine Reading Comprehension Systems for Robust Generalization 基于鲁棒泛化的机器阅读理解系统集成中基本模型权值的零射击估计

2021 26th International Computer Conference, Computer Society of Iran (CSICC) Pub Date : 2021-03-03 DOI: 10.1109/CSICC52343.2021.9420549

Razieh Baradaran, Hossein Amirkhani

引用次数: 1

Implementing a Scalable Data Management System for Collected Data by Smart Meters 智能电表采集数据的可扩展数据管理系统的实现

2021 26th International Computer Conference, Computer Society of Iran (CSICC) Pub Date : 2021-03-03 DOI: 10.1109/CSICC52343.2021.9420619

F. Farahani, F. Rezaei

引用次数: 1

A practical system based on CNN-BLSTM network for accurate classification of ECG heartbeats of MIT-BIH imbalanced dataset 基于CNN-BLSTM网络的MIT-BIH不平衡数据集心电心跳准确分类实用系统

2021 26th International Computer Conference, Computer Society of Iran (CSICC) Pub Date : 2021-03-03 DOI: 10.1109/CSICC52343.2021.9420620

Armin Shoughi, M. B. Dowlatshahi

{"title":"A practical system based on CNN-BLSTM network for accurate classification of ECG heartbeats of MIT-BIH imbalanced dataset","authors":"Armin Shoughi, M. B. Dowlatshahi","doi":"10.1109/CSICC52343.2021.9420620","DOIUrl":"https://doi.org/10.1109/CSICC52343.2021.9420620","url":null,"abstract":"ECG beats have a key role in the reduction of fatality rate arising from cardiovascular diseases (CVDs) by using Arrhythmia diagnosis computer-aided systems and get the important information from patient cardiac conditions to the specialist. However, the accuracy and speed of arrhythmia diagnosis are challenging in ECG classification systems, and the existence of noise, instability nature, and imbalance in heartbeats challenged these systems. Accurate and on-time diagnosis of CVDs is a vital and important factor. So it has a significant effect on the treatment and recovery of patients. In this study, with the aim of accurate diagnosis of CVDs types, according to arrhythmia in ECG heartbeats, we implement an automatic ECG heartbeats classification by using discrete wavelet transformation on db2 mother wavelet and SMOTE oversampling algorithm as pre-processing level, and a classifier that consists of Convolutional neural network and BLSTM network. Then evaluate the proposed system on MIT-BIH imbalanced dataset, according to AAMI standards. The evaluations results show this approach with 50 epoch training achieved 99.78% accuracy for category F, 98.85% accuracy for category N, 99.43% accuracy for category S, 99.49% accuracy for category V, 99.87% accuracy for category Q. The source code is available at https://gitlab.com/arminshoughi/cnnlstmecg-classification. Our proposed classification system can be used as a tool for the automatic diagnosis of arrhythmia for CVDs specialists with the aim of primary screening of patients with heart arrhythmia.","PeriodicalId":374593,"journal":{"name":"2021 26th International Computer Conference, Computer Society of Iran (CSICC)","volume":"54 23","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-03-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131875044","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: 7

User recommendation based on Hybrid filtering in Telegram messenger 基于混合过滤的Telegram messenger用户推荐

2021 26th International Computer Conference, Computer Society of Iran (CSICC) Pub Date : 2021-03-03 DOI: 10.1109/CSICC52343.2021.9420562

Davod Karimpour, M. Z. Chahooki, Ali Hashemi

{"title":"User recommendation based on Hybrid filtering in Telegram messenger","authors":"Davod Karimpour, M. Z. Chahooki, Ali Hashemi","doi":"10.1109/CSICC52343.2021.9420562","DOIUrl":"https://doi.org/10.1109/CSICC52343.2021.9420562","url":null,"abstract":"Over the past decade, social networks and messengers have found a special place in the creation and development of businesses. User recommendation is a very important feature in social networks that has attracted the attention of many users to these environments. Using this system in an instant messenger environment is very useful. Telegram is a cloud-based messenger with more than 400 million monthly active users. Telegram is used as a social network in Iran, but does not offer the most widely used features of social networks, such as recommending users. This feature is important for marketers to find target audience. This paper presents a hybrid filtering-based algorithm to recommend Telegram users. This method combines the membership graph of users with the profile of groups. The membership graph, models users based on their membership in groups. Also, the profile of each group includes the name and description of the group. We have created a bag of words for each group based on natural language processing methods to combine it with the membership graph. After combination process, users are recommended based on the list of groups obtained. The data used in this study is the information of more than 120 million users and 900,000 supergroups in Telegram. This data is obtained through Telegram API by Idekav system. The evaluation of the proposed method has been done separately on two categories of specialized supergroups. Each category includes 25 specialized supergroups in Telegram. Selected supergroups for evaluation have between 2,000 and 10,000 members. Experimental results show the integrity of the model and error reduction in RMSE.","PeriodicalId":374593,"journal":{"name":"2021 26th International Computer Conference, Computer Society of Iran (CSICC)","volume":"245 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-03-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127748794","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: 2

On the Possibility of Creating Smart Contracts on Bitcoin by MPC-based Approaches 基于mpc的方法在比特币上创建智能合约的可能性

2021 26th International Computer Conference, Computer Society of Iran (CSICC) Pub Date : 2021-03-03 DOI: 10.1109/CSICC52343.2021.9420558

Ahmad Jahanbin, M. S. Haghighi

{"title":"On the Possibility of Creating Smart Contracts on Bitcoin by MPC-based Approaches","authors":"Ahmad Jahanbin, M. S. Haghighi","doi":"10.1109/CSICC52343.2021.9420558","DOIUrl":"https://doi.org/10.1109/CSICC52343.2021.9420558","url":null,"abstract":"Bitcoin, as the first and the most adopted cryptocurrency, offers many features one of which is contingent payment, that is, the owner of money can programmatically describe the condition upon which his/her money is spent. The condition is determined using a set of instructions written in the Bitcoin scripting language. Unfortunately, this scripting language is not sophisticated enough to create complex conditions or smart contracts in general. Many admirable efforts have been made to build a smart contract infrastructure on top of the Bitcoin platform. In this paper, given the inherent limitations of the Bitcoin scripting language, we critically analyze the practical effectiveness of these methods. Afterwards, we formally define what a smart contract is and introduce seven requirements that if are satisfied, can make creation of smart contracts for Bitcoin possible. Based on the introduced requirements, we examine the ability of the current methods that use secure Multi-party Computation (MPC) to create smart contracts for Bitcoin and show where they fall short. We additionally compare their pros and cons and give clues on how a comprehensive smart contract platform can be possibly built for Bitcoin.","PeriodicalId":374593,"journal":{"name":"2021 26th International Computer Conference, Computer Society of Iran (CSICC)","volume":"47 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-03-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128718645","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 Hierarchical Method for Kannada-MNIST Classification Based on Convolutional Neural Networks 基于卷积神经网络的Kannada-MNIST分类分层方法

2021 26th International Computer Conference, Computer Society of Iran (CSICC) Pub Date : 2021-03-03 DOI: 10.1109/CSICC52343.2021.9420604

Ali Beikmohammadi, N. Zahabi

引用次数: 7

A practical resource management prototype for mobile networks 一个实用的移动网络资源管理原型

2021 26th International Computer Conference, Computer Society of Iran (CSICC) Pub Date : 2021-03-03 DOI: 10.1109/CSICC52343.2021.9420609

M. A. Nourian, A. Kusedghi, A. Akbari

{"title":"A practical resource management prototype for mobile networks","authors":"M. A. Nourian, A. Kusedghi, A. Akbari","doi":"10.1109/CSICC52343.2021.9420609","DOIUrl":"https://doi.org/10.1109/CSICC52343.2021.9420609","url":null,"abstract":"Network slicing is a promising approach to meet the diverse requirements of the various use cases in the 5G networks. Hence, the mobile operators are moving forward to leveraging network slicing in order to measure up with the individual service expectations in their networks. Deploying different network slice types requires the global view of the network and the automated orchestration and management of the underlying resources. This is facilitated by utilizing software-defined networking and network function virtualization as the 5G key-enabler technologies. In this paper, we propose a practical network slicing resource management scheme which is comprised of a dynamic, priority-based resource allocation cooperating with an admission control unit. Adopting the proposed dynamic resource allocation would allow the admission control to comply with more NS requests while ensuring the desired requirements of the existing network slices. To validate the effectiveness of such a mechanism in a real environment, we take advantage of the features provided by OpenAirInterface and FlexRAN to efficiently manage multiple isolated network slices. In particular, we evaluate the significance of the network slicing, the isolation degree among created slices, and the effectiveness of the proposed scheme through several practical scenarios.","PeriodicalId":374593,"journal":{"name":"2021 26th International Computer Conference, Computer Society of Iran (CSICC)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-03-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132628987","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