2019 International Conference on Advanced Information Technologies (ICAIT)最新文献_第5页

Simulation of Multiple Light Scattering in Intraocular lens with glistenings by T-Matrix 含闪烁的人工晶状体内多次光散射的t矩阵模拟

2019 International Conference on Advanced Information Technologies (ICAIT) Pub Date : 2019-11-01 DOI: 10.1109/AITC.2019.8920838

Kay Thwe Min Han, Kotani Kazunori, Prarinya Siritanawan, W. Kongprawechnon, C. Sinthanayothin

引用次数: 1

Evolution of Games Towards The Discovery of Noble Uncertainty 从游戏进化到发现不确定性

2019 International Conference on Advanced Information Technologies (ICAIT) Pub Date : 2019-11-01 DOI: 10.1109/AITC.2019.8921061

Wu Yicong, H. Aung, M. Khalid, H. Iida

引用次数: 10

Towards a fairness solution of Scrabble with Komi system 基于Komi系统的拼字游戏公平性解决方案

2019 International Conference on Advanced Information Technologies (ICAIT) Pub Date : 2019-11-01 DOI: 10.1109/AITC.2019.8921355

H. Aung, M. Khalid, H. Iida

引用次数: 1

Flow Path Computing in Software Defined Networking 软件定义网络中的流路径计算

2019 International Conference on Advanced Information Technologies (ICAIT) Pub Date : 2019-11-01 DOI: 10.1109/AITC.2019.8921370

Ohmmar Min Mon, M. Mon

引用次数: 2

Applying Deep Learning Approach to Targeted Aspect-based Sentiment Analysis for Restaurant Domain 将深度学习方法应用于餐馆领域的基于方面的情感分析

2019 International Conference on Advanced Information Technologies (ICAIT) Pub Date : 2019-11-01 DOI: 10.1109/AITC.2019.8920880

Win Lei Kay Khine, Nyein Thwet Thwet Aung

{"title":"Applying Deep Learning Approach to Targeted Aspect-based Sentiment Analysis for Restaurant Domain","authors":"Win Lei Kay Khine, Nyein Thwet Thwet Aung","doi":"10.1109/AITC.2019.8920880","DOIUrl":"https://doi.org/10.1109/AITC.2019.8920880","url":null,"abstract":"Sentiment analysis is a well-studied topic in social media analysis and it becomes an important decision-making tool to classify the opinion of user on the Web. In a few years ago, there are so many research works for sentiment analysis using machine learning. Nowadays, deep learning models are implemented in AI applications to gain better performance. This paper proposes to extend the traditional LSTM approach by adding the external knowledge. LSTM is a kind of recurrent neural network (RNN) and it can learn the past and future information. Unlike traditional RNN, it can capture the long sequence of text. With the LSTM cell, SenticNet is used as an external knowledge, to improve the accuracy in classification. We termed SenticNet multi-attentive LSTM (MA-LSTM). The results from the SenticNet MA-LSTM are classified as positive, negative or neutral and finally, compare the results with other state-of-the-art LSTM methods: standard LSTM, TD-LSTM, TC-LSTM, AE-LSTM, and ATAE-LSTM. To our knowledge, this is the first work for using multi-attention LSTM with external knowledge in targeted aspect-based sentiment analysis task.","PeriodicalId":388642,"journal":{"name":"2019 International Conference on Advanced Information Technologies (ICAIT)","volume":"27 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126503980","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

Child Face Recognition with Deep Learning 儿童面部识别与深度学习

2019 International Conference on Advanced Information Technologies (ICAIT) Pub Date : 2019-11-01 DOI: 10.1109/AITC.2019.8921152

Shun Lei Myat Oo, Aung Nway Oo

引用次数: 7

Network Traffic Anomaly Detection based on Apache Spark 基于Apache Spark的网络流量异常检测

2019 International Conference on Advanced Information Technologies (ICAIT) Pub Date : 2019-11-01 DOI: 10.1109/AITC.2019.8920897

P. H. Pwint, T. Shwe

{"title":"Network Traffic Anomaly Detection based on Apache Spark","authors":"P. H. Pwint, T. Shwe","doi":"10.1109/AITC.2019.8920897","DOIUrl":"https://doi.org/10.1109/AITC.2019.8920897","url":null,"abstract":"With the growing amount of internet and IoT traffic across the network, network anomaly detection system has become a popular and useful strategy to detect anomalies, attacks and intrusions. With machine learning technique, network traffic anomalies can be detected with reasonable prediction accuracy. However, most of the previous work has been focused on detecting anomalies using traditional machine learning environment. Because of ever increasing amount of data and high speed networks, traditional machine learning environment becomes infeasible to cope with the current condition. In this paper, we investigate the feasibility of the applying one of the big data technologies, Apache Spark, to classify different attacks rather than detecting anomalies. We employ traditional machine learning algorithms, namely, Multinomial Logistic Regression, Decision Tree, Random Forest, Multi-layer perceptron and Naïve Bayes using generated dataset of MAWILab gold standard and classify 15 different attack types. In addition, we investigate the efficiency of Apache Spark in terms of accuracy and speed under varied configuration setting of Spark. Our results demonstrate that employing big data technologies adds more benefits to network traffic anomaly detector than traditional machine learning environment in terms of prediction accuracy and execution time.","PeriodicalId":388642,"journal":{"name":"2019 International Conference on Advanced Information Technologies (ICAIT)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131207844","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

Inferring User Preferences Using Reviews for Rating Prediction 使用评论推断用户偏好进行评级预测

2019 International Conference on Advanced Information Technologies (ICAIT) Pub Date : 2019-11-01 DOI: 10.1109/AITC.2019.8921179

Nyein Ei Ei Kyaw, T. T. Wai

{"title":"Inferring User Preferences Using Reviews for Rating Prediction","authors":"Nyein Ei Ei Kyaw, T. T. Wai","doi":"10.1109/AITC.2019.8921179","DOIUrl":"https://doi.org/10.1109/AITC.2019.8921179","url":null,"abstract":"Nowadays, E-commerce websites have been developed and are very popular among online users. Users deal with the problems to choose the right items that meet with their needs. Recommender systems try to suggest the right items to the user by applying different recommendation approaches. Collaborative Filtering recommendation (CF) approach makes recommendations to users using the user-item matrix which has the ratings on each item given by users. Data sparsity problems may occur when a user-item matrix is built based on the ratings of users (one to five stars). User reviews on the products contain more information and opinions than user ratings. This paper proposes the rating prediction approach that infers the user preferences from textual reviews of hotels by performing sentiment analysis. The preference scores obtained from the sentiment analysis are integrated into the rating prediction process which applies two approaches named memory-based CF and model-based CF. The performance of the proposed system is tested on the Myanmar hotel reviews which are crawled from TripAdvisor site and hotel reviews which are downloaded from the Kaggle site. The resulted rating prediction accuracy of two approaches on two data sets is compared by using Root Mean Square Error (RMSE).","PeriodicalId":388642,"journal":{"name":"2019 International Conference on Advanced Information Technologies (ICAIT)","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125564464","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

Electricity Billing System using Ethereum and Firebase 使用以太坊和Firebase的电费计费系统

2019 International Conference on Advanced Information Technologies (ICAIT) Pub Date : 2019-11-01 DOI: 10.1109/AITC.2019.8920931

Kyawt May Hlaing, Dim En Nyaung

引用次数: 4

Coordinate Checkpoint Mechanism on Real-Time Messaging System in Kafka Pipeline Architecture Kafka管道架构中实时消息系统的坐标检查点机制

2019 International Conference on Advanced Information Technologies (ICAIT) Pub Date : 2019-11-01 DOI: 10.1109/AITC.2019.8921392

Thandar Aung, Hla Yin Min, A. Maw

{"title":"Coordinate Checkpoint Mechanism on Real-Time Messaging System in Kafka Pipeline Architecture","authors":"Thandar Aung, Hla Yin Min, A. Maw","doi":"10.1109/AITC.2019.8921392","DOIUrl":"https://doi.org/10.1109/AITC.2019.8921392","url":null,"abstract":"The real-time messaging system is the critical thing in computing based on time-critical decision making in many organizations. In the real-time messaging system, fault tolerance is the key challenge of developing reliability requirements. Apache Kafka is a popular framework for consuming data stream into the processing platforms. However, there are many challenges in the replication process because of a server failure in Apache Kafka. To develop fault tolerance in Apache Kafka, this paper focuses on defining a fixed checkpoint interval to reduce the recovery time and lost messages in server failure. Then, we measure the cost of checkpointing, cost of rollback and total time cost of overheads due to the fixed checkpointing intervals. The system shows the drawback of real-time processing depend on the number of lost messages on various partitions and server failure processes. The experimental results emphasize the checkpoint interval method to reduce recovery time and lost messages. Conforming to the experimental results, the performance of the total time cost with checkpoint interval saves time approximately 30% than without checkpoint interval.","PeriodicalId":388642,"journal":{"name":"2019 International Conference on Advanced Information Technologies (ICAIT)","volume":"37 6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126100944","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