2021 26th International Computer Conference, Computer Society of Iran (CSICC)最新文献_第7页

A Novel Design of Quantum 3:8 Decoder Circuit using Reversible Logic for Improvement in Key Quantum Circuit Design Parameters 一种基于可逆逻辑的量子3:8译码电路设计，改进了量子电路的关键设计参数

2021 26th International Computer Conference, Computer Society of Iran (CSICC) Pub Date : 2021-03-03 DOI: 10.1109/CSICC52343.2021.9420575

Seyyed Mohammad Amir Mirizadeh, Mohammad Mahdi Emadi Kouchak, Mohammad Mahdi Panahi

引用次数: 0

A Method for Rate-Distortion-Complexity Optimization in Versatile Video Coding Standard 通用视频编码标准中率失真复杂度优化方法

2021 26th International Computer Conference, Computer Society of Iran (CSICC) Pub Date : 2021-03-03 DOI: 10.1109/CSICC52343.2021.9420608

A. Rezaeieh, Hoda Roodaki

{"title":"A Method for Rate-Distortion-Complexity Optimization in Versatile Video Coding Standard","authors":"A. Rezaeieh, Hoda Roodaki","doi":"10.1109/CSICC52343.2021.9420608","DOIUrl":"https://doi.org/10.1109/CSICC52343.2021.9420608","url":null,"abstract":"The most recent video coding standard, named Versatile Video Coding (VVC), greatly improved the compression rate compared to its predecessor, High Efficiency Video Coding (HEVC) using some new coding tools. Though these new option provide appreciable coding gain, its computational complexity is relatively high since the performance of these coding tools need to be evaluated for each Coding Tree Units (CTU) through the Rate-Distortion Optimization (RDO) process. To address this issue, in this paper, first, the effectiveness of the coding tools in various parts of the frame, such as the borderline and central CTU, is investigated. The results of this study show that the coding efficiency of some of these coding tools is much higher for the borderline CTUs due to their specific features. Hence, these coding tools would be only considered enable for the borderline CTUs in rate-distortion process to decrease the computational complexity, without affecting the coding gain considerably. Simulation results show that using this method, the compression efficiency decreased only by 0.64% in average, but the computational complexity is reduced considerably, by 28.31%, in average.","PeriodicalId":374593,"journal":{"name":"2021 26th International Computer Conference, Computer Society of Iran (CSICC)","volume":"29 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":"116856713","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

Design of an IoT-based Flood Early Detection System using Machine Learning 基于机器学习的物联网洪水早期检测系统设计

2021 26th International Computer Conference, Computer Society of Iran (CSICC) Pub Date : 2021-03-03 DOI: 10.1109/CSICC52343.2021.9420594

Fatereh Sadat Mousavi, S. Yousefi, H. Abghari, Ardalan Ghasemzadeh

{"title":"Design of an IoT-based Flood Early Detection System using Machine Learning","authors":"Fatereh Sadat Mousavi, S. Yousefi, H. Abghari, Ardalan Ghasemzadeh","doi":"10.1109/CSICC52343.2021.9420594","DOIUrl":"https://doi.org/10.1109/CSICC52343.2021.9420594","url":null,"abstract":"Floods are a complex phenomenon that is difficult to predict because of their non-linear and dynamic nature. Gauging stations that transmit measured data to the server are often placed in very harsh and far environments that make the risk of missing data so high. The purpose of this study is to develop a real-time reliable flood monitoring and detection system using deep learning. This paper proposed an Internet of Things (IoT) approach for utilizing LoRaWAN as a reliable, low power, wide area communication technology by considering the effect of radius and transmission rate on packet loss. Besides, we evaluate an artificial neural network (ANN), Long Short-Term Memory (LSTM), and Gated Recurrent Unit (GRU) neural network models for flood forecasting. The data from 2013 to 2019 were collected from four gauging stations at Brandywine-Christina watershed, Pennsylvania. Our results show that the deep learning models are more accurate than the physical and statistical models. These results can help to provide and implement flood detection systems that would be able to predict floods at rescue time and reduce financial, human, and infrastructural damage.","PeriodicalId":374593,"journal":{"name":"2021 26th International Computer Conference, Computer Society of Iran (CSICC)","volume":"21 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":"115091335","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

DPSA: A Brief Review for Design Pattern Selection Approaches DPSA:设计模式选择方法综述

2021 26th International Computer Conference, Computer Society of Iran (CSICC) Pub Date : 2021-03-03 DOI: 10.1109/CSICC52343.2021.9420629

Amene Naghdipour, S. Hasheminejad, M. Keyvanpour

引用次数: 3

Topology-Aware Graph Signal Sampling for Pooling in Graph Neural Networks 面向图神经网络池化的拓扑感知图信号采样

2021 26th International Computer Conference, Computer Society of Iran (CSICC) Pub Date : 2021-03-03 DOI: 10.1109/CSICC52343.2021.9420547

Amirhossein Nouranizadeh, Mohammadjavad Matinkia, M. Rahmati

引用次数: 3

Reusability Metrics in Search-Based Testing of Software Product Lines: An Experimentation 基于搜索的软件产品线测试中的可重用性度量:一个实验

2021 26th International Computer Conference, Computer Society of Iran (CSICC) Pub Date : 2021-03-03 DOI: 10.1109/CSICC52343.2021.9420583

Masoud Fathi, S. Khoshnevis

{"title":"Reusability Metrics in Search-Based Testing of Software Product Lines: An Experimentation","authors":"Masoud Fathi, S. Khoshnevis","doi":"10.1109/CSICC52343.2021.9420583","DOIUrl":"https://doi.org/10.1109/CSICC52343.2021.9420583","url":null,"abstract":"Reusability is one of the most important objectives in software development and especially, in software product line (SPL) engineering, involving analysis, design, implementation, testing, and maintenance activities. Therefore, in software product line testing, as well as other activities, it is crucial that we pay special attention to reusability. In SPL testing, reusability can be defined and measured in different ways. In this paper, we first introduce four different reusability metrics for SPL testing (SPLT); and then, as a first step toward improving reusability in SPLT, we experimentally examine how a search-based software testing (SBST) approach for optimizing an existing SPL domain test suite can affect (improve) two of the proposed reusability metrics. The results of the experimentation on 20 SPL feature models of size 5000 showed a significant improvement in the two selected test reusability metrics, namely, TSRR (test suite reusability regarding test requirements) and TCRR (test case reusability regarding test requirements) in optimized solutions compared with non-optimized solutions.","PeriodicalId":374593,"journal":{"name":"2021 26th International Computer Conference, Computer Society of Iran (CSICC)","volume":"26 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":"126052620","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

Telegram group recommendation based on users' migration 基于用户迁移的Telegram群组推荐

2021 26th International Computer Conference, Computer Society of Iran (CSICC) Pub Date : 2021-03-03 DOI: 10.1109/CSICC52343.2021.9420581

Davod Karimpour, M. Z. Chahooki, Ali Hashemi

{"title":"Telegram group recommendation based on users' migration","authors":"Davod Karimpour, M. Z. Chahooki, Ali Hashemi","doi":"10.1109/CSICC52343.2021.9420581","DOIUrl":"https://doi.org/10.1109/CSICC52343.2021.9420581","url":null,"abstract":"Today, social networks and messengers have attracted the attention of many different businesses. Every day, a lot of information is produced in these environments. Analyzing this information is very useful for connecting different businesses. This information is very valuable for marketers to find the target community. Telegram is a messenger based on cloud computing. This messenger is used as a social network in some countries, including Iran. Telegram, while used as a social network, does not offer all the capabilities of a social network. The capabilities provided in this messenger include creating a channel, group, and bot. The shortfall in most messengers, such as Telegram, is the limited search service of groups and a community of users. In this paper, we have recommended groups according to the users ' interests, using the graph of users' membership and analyzing their membership records. The proposed method, considering the users' status, models their records in each group. We obtained users’ migration by analyzing their records in each group. Users' migration is analyzed based on the maximum number of users leaving each group and entering another group. In this study, information about 70 million users and 700,000 Telegram supergroups have been used. The evaluation of the proposed model has been done on 30 high-quality groups in Telegram. Selected groups had between 5,000 and 15,000 members. The proposed method showed an error reduction of 0.0237 in RMSE compared to a base method.","PeriodicalId":374593,"journal":{"name":"2021 26th International Computer Conference, Computer Society of Iran (CSICC)","volume":"18 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":"114970974","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

Attribute-Image Similarity Measure for Multimodal Attention Mechanism 多模态注意机制的属性-图像相似性度量

2021 26th International Computer Conference, Computer Society of Iran (CSICC) Pub Date : 2021-03-03 DOI: 10.1109/CSICC52343.2021.9420626

Ali Salehi Najafabadi, A. Ghomsheh

引用次数: 0

A 3D Deep Learning Approach for Classification of Gait Abnormalities Using Microsoft Kinect V2 Sensor 基于Microsoft Kinect V2传感器的步态异常分类的3D深度学习方法

2021 26th International Computer Conference, Computer Society of Iran (CSICC) Pub Date : 2021-03-03 DOI: 10.1109/CSICC52343.2021.9420611

Milad Shoryabi, A. Foroutannia, A. Rowhanimanesh

{"title":"A 3D Deep Learning Approach for Classification of Gait Abnormalities Using Microsoft Kinect V2 Sensor","authors":"Milad Shoryabi, A. Foroutannia, A. Rowhanimanesh","doi":"10.1109/CSICC52343.2021.9420611","DOIUrl":"https://doi.org/10.1109/CSICC52343.2021.9420611","url":null,"abstract":"In this paper, a deep learning approach is proposed based on a 3D Convolutional Neural Network for the classification of gait abnormalities. Six gait classes are considered, including Trendelenburg, Steppage, Stiff-legged, Lurching, and Antalgic gait abnormalities as well as normal gait. The proposed scheme is applied to a recently-published dataset from the literature. This dataset consists of the gait data recorded by multiple Microsoft Kinect v2 sensor from 25 joints of a person during walking on a specified walkway. In this dataset, for each of the 6 gait classes, ten people have attended the data collection procedure; and for each participant, 120 walking instances have been recorded. Each instance includes the spatial and temporal information of the walking, and it is converted to two 3D images, which respectively display the changes of the Coronal (X-Z) and Sagittal (Y-Z) views of the originally captured data over time. These two 3D images are used as the input of the proposed 3D convolutional neural network. There are a total of 14400 3D images in this dataset. In order to demonstrate the accuracy of the proposed approach, it is compared with four well-known neural classifiers from the literature.","PeriodicalId":374593,"journal":{"name":"2021 26th International Computer Conference, Computer Society of Iran (CSICC)","volume":"14 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":"127705262","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

The improved greedy gang scheduling by minimizing context switch condition 最小化上下文切换条件的改进贪婪组调度

2021 26th International Computer Conference, Computer Society of Iran (CSICC) Pub Date : 2021-03-03 DOI: 10.1109/CSICC52343.2021.9420557

Maryam Sadat Mastoori, Ghazal Rahmanian

引用次数: 0