2020 10th International Conference on Computer and Knowledge Engineering (ICCKE)最新文献_第3页

Knowledge Based Word Sense Disambiguation with Distributional Semantic Expansion for the Persian Language 基于知识的波斯语分布式语义扩展词义消歧

2020 10th International Conference on Computer and Knowledge Engineering (ICCKE) Pub Date : 2020-10-29 DOI: 10.1109/ICCKE50421.2020.9303675

H. Rouhizadeh, M. Shamsfard, Masoud Rouhizadeh

引用次数: 4

Semi-deterministic Broadcast Channel With Side Information: A Secrecy Capacity Outer Bound 带边信息的半确定性广播信道:一种保密能力的外界

2020 10th International Conference on Computer and Knowledge Engineering (ICCKE) Pub Date : 2020-10-29 DOI: 10.1109/ICCKE50421.2020.9303628

S. Pakravan, G. Hodtani

引用次数: 0

A Comprehensive Blockchain-based solution For Academic Certificates Management Using Smart Contracts 一个全面的基于区块链的解决方案，用于使用智能合约进行学术证书管理

2020 10th International Conference on Computer and Knowledge Engineering (ICCKE) Pub Date : 2020-10-29 DOI: 10.1109/ICCKE50421.2020.9303656

Masoomeh Bahrami, Alireza Movahedian, A. Deldari

引用次数: 9

Unsupervised aspect-based Sentiment Analysis in the Persian language: Extracting and clustering aspects 波斯语中基于方面的无监督情感分析:方面的提取和聚类

2020 10th International Conference on Computer and Knowledge Engineering (ICCKE) Pub Date : 2020-10-29 DOI: 10.1109/ICCKE50421.2020.9303651

Reza Akhoundzade, Kourosh Hashemi Devin

{"title":"Unsupervised aspect-based Sentiment Analysis in the Persian language: Extracting and clustering aspects","authors":"Reza Akhoundzade, Kourosh Hashemi Devin","doi":"10.1109/ICCKE50421.2020.9303651","DOIUrl":"https://doi.org/10.1109/ICCKE50421.2020.9303651","url":null,"abstract":"Sentiment analysis is the field of natural language processing to analyze user feedback, preferences, and evaluations from the text. Different organizations in most social scopes use this context as an appropriate tool to find their strengths and weaknesses. In this field of research, the objective is to determine the positive or negative orientations of users towards the features of a product or commodity. Solving this problem consists of two main steps: aspect extraction and identifying the positive or negative tendencies of users towards those aspects. Two of the most critical issues of sentiment analysis in the Persian language are the lack of comprehensive labeled data and the significant difference between colloquial and formal sentences in Persian. One of the most important methods to confront the first problem is to apply unsupervised methods. In this research, a system for aspect-based sentiment analysis in the Persian language is proposed using unsupervised methods. The Sentiment words extraction step is done in another article [1]. The aspect extraction and clustering steps are done using topic modeling methods and neural networks and taking benefit of rule-based methods. This system has been evaluated using precision and recall criteria. The F1 criterion for extracting aspect words in the proposed system was 0.766.","PeriodicalId":402043,"journal":{"name":"2020 10th International Conference on Computer and Knowledge Engineering (ICCKE)","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122722358","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: 3

Rainfall Data Analysis of Iran using Complex Networks View 利用复杂网络视图分析伊朗降雨数据

2020 10th International Conference on Computer and Knowledge Engineering (ICCKE) Pub Date : 2020-10-29 DOI: 10.1109/ICCKE50421.2020.9303665

Ehsan Baratnezhad, M. Rezghi

{"title":"Rainfall Data Analysis of Iran using Complex Networks View","authors":"Ehsan Baratnezhad, M. Rezghi","doi":"10.1109/ICCKE50421.2020.9303665","DOIUrl":"https://doi.org/10.1109/ICCKE50421.2020.9303665","url":null,"abstract":"Rainfall Zoning is one of the most significant applications in hydro-climatic science. The investigation of these regions helps us to better interpret the functional mechanism of the climatology. A popular way to detect these regions is to use a typical clustering algorithm like K-means on spatial features of the data, But it’s better to detect the zones based on the rainfall data because temporal features of rainfall data, unlike its spatial features, can cause a better result in clustering these data types. The most challenging part while using temporal data is to apply them in the presence of missing values. Here, applying a typical clustering method due to high missing values as a whole block on these data is not proper or maybe even impossible. We implemented a clustering on Iran’s rainfall dataset and one of the most disturbing facts about this dataset was its missing values and to carry out these missing data we demanded to change the data type. To overcome this missing value problem in data, we used a method named \"Event synchronization\" that could give appropriate similarity for temporal data with high missing values. By this approach, the data with high missing value could be converted to a network. Then by adopting the state-of-the-art community detection algorithm we detected the most related points to each other as rainfall clusters, and we’ll see the promising results at the end. The nature of our real-world data can prove the results.","PeriodicalId":402043,"journal":{"name":"2020 10th International Conference on Computer and Knowledge Engineering (ICCKE)","volume":"57 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121864402","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

Texture based blur estimation in a single defocused image 在单个散焦图像中基于纹理的模糊估计

2020 10th International Conference on Computer and Knowledge Engineering (ICCKE) Pub Date : 2020-10-29 DOI: 10.1109/ICCKE50421.2020.9303719

M. Masoudifar, H. Pourreza

引用次数: 0

Improving the Performance of Intrusion Detection Systems Using the Development of Deep Neural Network Parameters 基于深度神经网络参数的入侵检测系统性能改进

2020 10th International Conference on Computer and Knowledge Engineering (ICCKE) Pub Date : 2020-10-29 DOI: 10.1109/ICCKE50421.2020.9303701

Amin Rezaeipanah, Esmat Afsoon, Gholamreza Ahmadi

{"title":"Improving the Performance of Intrusion Detection Systems Using the Development of Deep Neural Network Parameters","authors":"Amin Rezaeipanah, Esmat Afsoon, Gholamreza Ahmadi","doi":"10.1109/ICCKE50421.2020.9303701","DOIUrl":"https://doi.org/10.1109/ICCKE50421.2020.9303701","url":null,"abstract":"One of the solutions used to create security in computer networks is the use of intrusion detection systems. Today’s architectures detecting intrusion have made it difficult for the designers of these systems to select an efficient architecture that can be more reliable in detecting intrusions. One of the solutions that has been developed to secure computer systems and networks is the emergence of intrusion detection systems. In the present study, a method for combining deep learning and observer learning in detecting intrusion patterns is presented with the aim of increasing the security of computer networks. Observer learning is provided to teach the parameters of a deep neural network algorithm that uses linear combinations and representations of effective features. This method is based on a learning algorithm with supervision and a deep neural network that optimizes the appropriate number of hidden layers and the number of neurons in each layer according to a threshold value. The results of experiments on NSL-KDD data set show the superiority of the proposed method with 97.64% accuracy over MARS and DLNN methods.","PeriodicalId":402043,"journal":{"name":"2020 10th International Conference on Computer and Knowledge Engineering (ICCKE)","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127818819","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

AAS: Address Aware Scheduler for Enhancing the Performance of NVMe SSDs in IoT Applications AAS:地址感知调度器，用于增强物联网应用中NVMe ssd的性能

2020 10th International Conference on Computer and Knowledge Engineering (ICCKE) Pub Date : 2020-10-29 DOI: 10.1109/ICCKE50421.2020.9303663

Sara Talebpour, Saeideh Alinezhad

{"title":"AAS: Address Aware Scheduler for Enhancing the Performance of NVMe SSDs in IoT Applications","authors":"Sara Talebpour, Saeideh Alinezhad","doi":"10.1109/ICCKE50421.2020.9303663","DOIUrl":"https://doi.org/10.1109/ICCKE50421.2020.9303663","url":null,"abstract":"The use of NVMe SSDs have been growing in many applications as well in IoT due to their high-performance features as compared with the traditional SATA SSDs. Although, NVMe SSDs provide higher performance due to their multi-Queues feature, but this feature may not be employed efficiently due to the wrong configuration as well as weak scheduling. The scheduler plays a key role in handling the requests to separate among multi queues. Traditional schedulers usually fulfill the queues of SSDs with aim of providing parallel processing. While, in some conditions, especially in IoT applications, many useless repeated writes have been issued to the memory which may degrade the performance. In this paper, we first investigate the main parameters which affect the performance of NVMe SSDs; then, we proposed an address aware scheduler caller AAS, which improves the performance of SSDs by mitigating the useless writes. The results of evaluation on MQSim shows that the enhanced performance of NVMe SSDs will be achieved in specific configuration when running simulator. By considering those configurations, we evaluate the performance of SSDs when using proposed AAS scheduler, the results show that the proposed method enhances the performance significantly (up to 111%) especially in the cases with high percent of repeated data.","PeriodicalId":402043,"journal":{"name":"2020 10th International Conference on Computer and Knowledge Engineering (ICCKE)","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114194460","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 Greedy Virtual Force Algorithm for Target Coverage in Distributed Sensor Networks 分布式传感器网络中目标覆盖的贪婪虚力算法

2020 10th International Conference on Computer and Knowledge Engineering (ICCKE) Pub Date : 2020-10-29 DOI: 10.1109/ICCKE50421.2020.9303642

V. Kiani

引用次数: 3

Lightweight Authentication for Remote Healthcare Systems in Cloud-IoT 云-物联网中远程医疗系统的轻量级身份验证

2020 10th International Conference on Computer and Knowledge Engineering (ICCKE) Pub Date : 2020-10-29 DOI: 10.1109/ICCKE50421.2020.9303671

Mahdi Nikooghadam, H. Amintoosi, N. Bagheri

{"title":"Lightweight Authentication for Remote Healthcare Systems in Cloud-IoT","authors":"Mahdi Nikooghadam, H. Amintoosi, N. Bagheri","doi":"10.1109/ICCKE50421.2020.9303671","DOIUrl":"https://doi.org/10.1109/ICCKE50421.2020.9303671","url":null,"abstract":"The recent developments in Cloud-IoT has paved the way to the emergence of remote real-time health monitoring systems, where wearable sensors collect patient’s health data and transfer it to the cloud server. The server then provides data access for specialists and doctors for further medical treatment. Due to the high sensitivity of health-related data, establishing a secure and privacy-preserving data access and communication is a major challenge in the success of remote healthcare systems. In other words, there needs to be an efficient authentication scheme that enables authorized parties to agree on a shared key and communicate in a secure manner. Moreover, due to the limited storage and computation capacity of sensor devices, the scheme should be lightweight in terms of incurring minimum computation overhead. Lately, Alzahrani et al. proposed a remote patient monitoring authentication protocol. In this article, we demonstrate that their scheme is not robust to the stolen verifier attack and lacks the provision of perfect forward secrecy. In view of those limitations, we design a lightweight and secure authentication protocol for remote health monitoring and prove its security in resisting various security attacks and satisfying essential security requirements. We also formally prove the security of the scheme through using the Scyther tool. Moreover, we compare the performance of the proposed protocol with the related articles regarding the computation overhead, and demonstrate that the scheme obtains minimum computation complexity, making it appropriate for limited-capacity IoT devices.","PeriodicalId":402043,"journal":{"name":"2020 10th International Conference on Computer and Knowledge Engineering (ICCKE)","volume":"266 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123263594","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