2021 7th International Conference on Web Research (ICWR)最新文献_第6页

IoT Based Smart Greenhouse Design with an Intelligent Supervisory Fuzzy Optimized Controller 基于物联网的智能温室设计与智能监控模糊优化控制器

2021 7th International Conference on Web Research (ICWR) Pub Date : 2021-05-19 DOI: 10.1109/ICWR51868.2021.9443022

Mh. Aghaseyedabdollah, Y. Alaviyan, A. Yazdizadeh

引用次数: 3

A Containerized Integrated Fast IoT Platform for Low Energy Power Management 面向低能耗电源管理的集装箱化集成快速物联网平台

2021 7th International Conference on Web Research (ICWR) Pub Date : 2021-05-19 DOI: 10.1109/ICWR51868.2021.9443141

Mohammadreza Parvizimosaed, M. Noei, Mohammadmostafa Yalpanian, Javad Bahrami

{"title":"A Containerized Integrated Fast IoT Platform for Low Energy Power Management","authors":"Mohammadreza Parvizimosaed, M. Noei, Mohammadmostafa Yalpanian, Javad Bahrami","doi":"10.1109/ICWR51868.2021.9443141","DOIUrl":"https://doi.org/10.1109/ICWR51868.2021.9443141","url":null,"abstract":"Internet of Things (IoT) includes technologies that fit applications and smart devices together to build an ecosystem. IoT has influenced the communication and information world. A large number of connected devices, connected devices heterogeneity, latency, high availability, the security of communication, and latency are IoT challenges. IoT platforms integrate devices, users, and applications to tackle these challenges. In this paper, we design an IoT platform and compare it to the related work based on throughput, memory and CPU usage, and response time. The architecture of the proposed method is modular. Thus, flexibility and scalability will be increased because each module can be removed or added to the architecture. Public cloud proposes general services, but the proposed method is application-specific based on what the customers need. The proposed method’s novelty is using device management and user management in the system as the module. Another novelty of the proposed method is using TDengine as the database for the platform. Thus, by using TDengine as a database and using user management and device management in the system, latency will be reduced as latency is an important challenge in power energy. As we make the platform, it can be used in the edge layer because we can add each module needed. The platform is tested and deployed on different scenarios, and the implementation shows that our method’s resource usage and performance are better than the related work.","PeriodicalId":377597,"journal":{"name":"2021 7th International Conference on Web Research (ICWR)","volume":"125 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-05-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133977059","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: 5

Adaptive Genetic Algorithm Based on Mutation and Crossover and Selection Probabilities 基于变异、交叉和选择概率的自适应遗传算法

2021 7th International Conference on Web Research (ICWR) Pub Date : 2021-05-19 DOI: 10.1109/ICWR51868.2021.9443124

A. Damia, M. Esnaashari, Mohammadreza Parvizimosaed

{"title":"Adaptive Genetic Algorithm Based on Mutation and Crossover and Selection Probabilities","authors":"A. Damia, M. Esnaashari, Mohammadreza Parvizimosaed","doi":"10.1109/ICWR51868.2021.9443124","DOIUrl":"https://doi.org/10.1109/ICWR51868.2021.9443124","url":null,"abstract":"The Genetic Algorithm (GA) is an explore technique used to solve issues in many different applications. The genetic algorithm has some parameters, including crossover probability, selection mechanism, and mutation probability. In GA, parameter adaptation is an important research topic. This paper proposes a Probabilistic Adaptive Genetic Algorithm in which the mutation and crossover probabilities, as well as the selection mechanism are dynamically adapted throughout the running of the algorithm. A new set of rates is generated for the next iteration based on the differences between fitness values and individual, enhancing the searching global optimum exploitation. We have compared the proposed algorithm with some common and state-of-the-art adaptive strategies such as dynamic adaptive, dynamic deterministic, dynamic self-adaptive, and static on a set of several functions with varying degrees of complexity. Experimental results on several popular test functions have shown that the results of the proposed algorithm are significantly better than these methods on both convergence speed and the solutions' quality.The reason that the proposed method has better results than other methods is the adaptation of each parameter of the genetic algorithm.","PeriodicalId":377597,"journal":{"name":"2021 7th International Conference on Web Research (ICWR)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-05-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130313800","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: 5

Designing a Deep Neural Network Model for Finding Semantic Similarity Between Short Persian Texts Using a Parallel Corpus 基于并行语料库的波斯语短文本语义相似度深度神经网络模型设计

2021 7th International Conference on Web Research (ICWR) Pub Date : 2021-05-19 DOI: 10.1109/ICWR51868.2021.9443108

Zahra Sadat Hosseini Moghadam Emami, Shohreh Tabatabayiseifi, M. Izadi, Mohammad Tavakoli

{"title":"Designing a Deep Neural Network Model for Finding Semantic Similarity Between Short Persian Texts Using a Parallel Corpus","authors":"Zahra Sadat Hosseini Moghadam Emami, Shohreh Tabatabayiseifi, M. Izadi, Mohammad Tavakoli","doi":"10.1109/ICWR51868.2021.9443108","DOIUrl":"https://doi.org/10.1109/ICWR51868.2021.9443108","url":null,"abstract":"Text processing, as one of the main issues in the field of artificial intelligence, has received a lot of attention in recent decades. Numerous methods and algorithms are proposed to address the task of semantic textual similarity which is one of the sub-branches of text processing. Due to the special features of the Persian language and its non-standard writing system, finding semantic similarity is an even more challenging task in Persian. On the other hand, producing a proper corpus that can be used for training a model for finding semantic similarities, is of great importance. In this study, the main purpose is to propose a method for measuring the semantic similarity between short Persian texts. To do so, first, we try to build an appropriate corpus, and then propose an efficient approach based on neural networks. The proposed method involves three steps. The first step is data collection and building a parallel corpus. In the next step, namely the pre-processing step, the data is normalized. Finally, Semantic similarity recognition is done by the neural network using vector representations of the words. The suggested model is built upon the produced corpus made of movie and tv show subtitles containing 35266 sentence pairs. The F-measure of the proposed approach on PAN2016 is 75.98% with 4 tags and 98.87% with 2 tags. We also achieved an F-measure of 98.86% for our model tested on the parallel corpus with 2 tags.","PeriodicalId":377597,"journal":{"name":"2021 7th International Conference on Web Research (ICWR)","volume":"56 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-05-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121375094","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

Exploiting BERT to Improve Aspect-Based Sentiment Analysis Performance on Persian Language 利用BERT提高波斯语基于方面的情感分析性能

2021 7th International Conference on Web Research (ICWR) Pub Date : 2020-12-02 DOI: 10.1109/ICWR51868.2021.9443131

H. Jafarian, Amirhosein Taghavi, Alireza Javaheri, Reza Rawassizadeh

引用次数: 9