2020 International Conference on Advanced Information Technologies (ICAIT)最新文献_第3页

Blockchain based Digital Identity Management System: A Case Study of Myanmar 基于区块链的数字身份管理系统:缅甸案例研究

2020 International Conference on Advanced Information Technologies (ICAIT) Pub Date : 2020-11-04 DOI: 10.1109/ICAIT51105.2020.9261785

May Htet, P. Yee, Jay Rajasekera

{"title":"Blockchain based Digital Identity Management System: A Case Study of Myanmar","authors":"May Htet, P. Yee, Jay Rajasekera","doi":"10.1109/ICAIT51105.2020.9261785","DOIUrl":"https://doi.org/10.1109/ICAIT51105.2020.9261785","url":null,"abstract":"Although Blockchain technology is formerly invented for digital currencies such as Bitcoin, its applications have extended into such areas as fair voting, healthcare, banking, and digital identity. A blockchain ‘s data is cryptographically connected and distributed across multiple computers, making them nearly impossible to temper with. Hence, this paper considers the possible use of introducing blockchain technology for digital identity management system for the issue of digital identity (passport) in Myanmar. Through blockchain technology, all the passport offices in Myanmar will be connected to each other in decentralized environment and enough passport information of a person can be securely shared within peers. Therefore, the proposed system can hinder the illegal duplication of passports (different types) since a valid passport can be issued only once to a person (except passport loss, renewal and expired) and it is impossible for a person to apply more than one passport type in the decentralized system. In addition, in the proposed system, the authenticity of passport can also be verified after granting permission for international travel. Therefore, the proposed system can be effectively applied for the passport offices in Myanmar for verifying the passport application and its data authentication.","PeriodicalId":173291,"journal":{"name":"2020 International Conference on Advanced Information Technologies (ICAIT)","volume":"37 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114530962","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: 6

Analysis of Single-Agent Game: Case Study using Minesweeper 单智能体博弈分析:以扫雷为例

2020 International Conference on Advanced Information Technologies (ICAIT) Pub Date : 2020-11-04 DOI: 10.1109/ICAIT51105.2020.9261782

Wu Tingting, Huang Shunqi, Htung Pa Pa Aung, Mohd Nor Akmal Khalid, H. Iida

引用次数: 2

Improved Job Scheduling for Achieving Fairness on Apache Hadoop YARN 改进的作业调度在Apache Hadoop YARN上实现公平性

2020 International Conference on Advanced Information Technologies (ICAIT) Pub Date : 2020-11-04 DOI: 10.1109/ICAIT51105.2020.9261793

Thet Hsu Aung, W. Zaw

{"title":"Improved Job Scheduling for Achieving Fairness on Apache Hadoop YARN","authors":"Thet Hsu Aung, W. Zaw","doi":"10.1109/ICAIT51105.2020.9261793","DOIUrl":"https://doi.org/10.1109/ICAIT51105.2020.9261793","url":null,"abstract":"Enormous amounts of data are gathered from social media sites, mobile and other business environment. Analyzing the enormous amounts of big data becomes large workloads with distributed applications and the resources of a single machine are insufficient for this application. Hadoop YARN (Yet Another Resource Negotiator) enables running multiple applications over hadoop cluster to utilize the resources efficiently and provide the data parallel programming model. Hadoop YARN breaks up the performance of open source framework for distributed applications and performs job scheduling and monitoring together with storage, processing and analysis of big data on commodity hardware. Apache Hadoop provides for over 200 default parameter configuration settings for all type of clusters and applications. Of If the available parameters misconfigure, the one or more machines in the cluster may decrease the system performance. Appropriate tuning parameters configuration can increase the system performance. Tuning parameter configuration becomes the challenge of Apache Hadoop Framework for utilization of system resources efficiently. In this paper, YARN parameters tuning is done for improving the execution time and efficient job scheduling.","PeriodicalId":173291,"journal":{"name":"2020 International Conference on Advanced Information Technologies (ICAIT)","volume":"71 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121992740","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

Prediction of Natural Gas Final Consumption using Artificial Neural Networks 基于人工神经网络的天然气最终消费量预测

2020 International Conference on Advanced Information Technologies (ICAIT) Pub Date : 2020-11-04 DOI: 10.1109/ICAIT51105.2020.9261813

K. S. Yin, S. S. Htay

{"title":"Prediction of Natural Gas Final Consumption using Artificial Neural Networks","authors":"K. S. Yin, S. S. Htay","doi":"10.1109/ICAIT51105.2020.9261813","DOIUrl":"https://doi.org/10.1109/ICAIT51105.2020.9261813","url":null,"abstract":"Natural gas is a kind of fossil fuel and itself is more suitable for reducing environmental pollution than the refined fuel oils such as gasoline(petrol) and diesel. Natural gas consumption is eco-friendly and is useful to fulfill energy demand for industries, transportation and other purposes. Myanmar is natural gas main producer in Asia and the majority of natural gas is exported to Thailand and China. In the near future, it is important to know the total consumption of natural gas for a country to fulfill the demand of country's needs. In this paper, Myanmar's natural gas final consumption will be predicted using Artificial Neural Networks(ANN). To predict natural gas final consumption for the coming years, actual recorded consumption data of Myanmar 1990–2015 are used. The last five years' data (2011–2015) are applied for testing and the previous years' data (1990–2010) are used for training. Population, gross domestic product(GDP), and other factors that affect natural gas final consumption are used as input for model building. The training model is strong with a minimum error rate of 0.005 Mean Squared Error (MSE). The developed ANN model is applied for the prediction of future natural gas consumption of Myanmar year by year. The proposed method is effective to predict Myanmar's natural gas final consumption and is useful in the studies of energy policy and ecological quality.","PeriodicalId":173291,"journal":{"name":"2020 International Conference on Advanced Information Technologies (ICAIT)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131150342","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

An Enhanced RSS Fingerprinting-based Wireless Indoor Positioning using Random Forest Classifier 基于随机森林分类器的增强型RSS指纹无线室内定位

2020 International Conference on Advanced Information Technologies (ICAIT) Pub Date : 2020-11-04 DOI: 10.1109/ICAIT51105.2020.9261776

Nyein Aye Maung Maung, Baby Yaw Lwi, Soe Thida.

{"title":"An Enhanced RSS Fingerprinting-based Wireless Indoor Positioning using Random Forest Classifier","authors":"Nyein Aye Maung Maung, Baby Yaw Lwi, Soe Thida.","doi":"10.1109/ICAIT51105.2020.9261776","DOIUrl":"https://doi.org/10.1109/ICAIT51105.2020.9261776","url":null,"abstract":"Fingerprinting-based wireless indoor positioning which utilizes Received Signal Strength (RSS) data achieves increasing attention for modern location-based services due to its benefits of cost effectiveness and ease of deployment. Recent research works in RSS fingerprinting based wireless indoor positioning employed Random Forest (RF) classifier, which is one of the most popular machine learning techniques, to achieve outstanding localization performance. However, there are still some shortcomings in the existing works due to high RSS variability and multipath fading effects in indoor environments. To further improve the performance of existing works, an efficient RSS fingerprinting wireless indoor positioning using Random Forest classifier is proposed, in which RSS data from two different frequency bands: 2.4 GHz and 5GHz are deployed in building the fingerprinting database. In addition, RSS readings are taken with four different antenna orientations at each reference point to improve positioning accuracy and mitigate effect of radio irregularity. Experiments are conducted in a real- world test-bed and results indicate that the proposed Random Forest (RF) based wireless indoor positioning system achieves 1.69-meter precision with improved positioning accuracy than existing RF based approaches.","PeriodicalId":173291,"journal":{"name":"2020 International Conference on Advanced Information Technologies (ICAIT)","volume":"25 2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123263245","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: 11

Performance Evaluation of M/D/1 Queuing Model on Hyperledger Fabric 超级账本结构上M/D/1排队模型的性能评价

2020 International Conference on Advanced Information Technologies (ICAIT) Pub Date : 2020-11-04 DOI: 10.1109/ICAIT51105.2020.9261808

Khin Su Su Wai, Ei Chaw Htoon, Nwe Nwe Myint Thein

引用次数: 0

Increasing SMT and NMT Performance by Corpus Extension with Free Online Machine Translation Services 利用免费在线机器翻译服务的语料库扩展提高SMT和NMT的性能

2020 International Conference on Advanced Information Technologies (ICAIT) Pub Date : 2020-11-04 DOI: 10.1109/ICAIT51105.2020.9261772

Zar Zar Hlaing, Ye Kyaw Thu, T. Supnithi, P. Netisopakul

引用次数: 1

Feature Based Human Activity Recognition using Neural Network 基于特征的神经网络人体活动识别

2020 International Conference on Advanced Information Technologies (ICAIT) Pub Date : 2020-11-04 DOI: 10.1109/ICAIT51105.2020.9261774

Win Myat Oo, Bawin Aye, Myo Min Hein

引用次数: 1

An Improvement of Apriori Mining Algorithm using Linked List Based Hash Table 基于链表哈希表的Apriori挖掘算法改进

2020 International Conference on Advanced Information Technologies (ICAIT) Pub Date : 2020-11-04 DOI: 10.1109/ICAIT51105.2020.9261804

Zin Mar, Khine Khine Oo

{"title":"An Improvement of Apriori Mining Algorithm using Linked List Based Hash Table","authors":"Zin Mar, Khine Khine Oo","doi":"10.1109/ICAIT51105.2020.9261804","DOIUrl":"https://doi.org/10.1109/ICAIT51105.2020.9261804","url":null,"abstract":"Today, the huge amount of data was using in organizations around the world. This huge amount of data needs to process so that we can acquire useful information. Consequently, a number of industry enterprises discovered great information from shopper purchases found in any respect times. In data mining, the most important algorithms for find frequent item sets from large database is Apriori algorithm and discover the knowledge using the association rule. Apriori algorithm was wasted times for scanning the whole database and searching the frequent item sets and inefficient of memory requirement when large numbers of transactions are in consideration. The improved Apriori algorithm is adding and calculating third threshold may increase the overhead. So, in the aims of proposed research, Improved Apriori algorithm with LinkedList and hash tabled is used to mine frequent item sets from the transaction large amount of database. This method includes database is scanning with Improved Apriori algorithm and frequent 1-item sets counts with using the hash table. Then, in the linked list saved the next frequent item sets and scanning the database. The hash table used to produce the frequent 2-item sets Therefore, the database scans the only two times and necessary less processing time and memory space.","PeriodicalId":173291,"journal":{"name":"2020 International Conference on Advanced Information Technologies (ICAIT)","volume":"35 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123548709","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

Trend Extraction from High Dimensional Stock News based on Markov Chain 基于马尔可夫链的高维股票新闻趋势提取

2020 International Conference on Advanced Information Technologies (ICAIT) Pub Date : 2020-11-04 DOI: 10.1109/ICAIT51105.2020.9261802

Ei Thwe Khaing, M. Thein, M. Lwin

引用次数: 0