2016 International Workshop on Big Data and Information Security (IWBIS)最新文献

Generalized learning vector quantization particle swarm optimization (GLVQ-PSO) FPGA implementation for real-time electrocardiogram 基于广义学习向量量化粒子群优化(GLVQ-PSO)的实时心电图FPGA实现

2016 International Workshop on Big Data and Information Security (IWBIS) Pub Date : 2016-10-01 DOI: 10.1109/IWBIS.2016.7872897

Yulistiyan Wardhana, W. Jatmiko, M. F. Rachmadi

引用次数: 1

The power of big data and algorithms for advertising and customer communication 大数据和算法在广告和客户沟通方面的力量

2016 International Workshop on Big Data and Information Security (IWBIS) Pub Date : 2016-10-01 DOI: 10.1109/IWBIS.2016.7872882

Nico Neumann

引用次数: 4

Overview of research center for information technology innovation in Taiwan Academia Sinica 台湾中央研究院资讯科技创新研究中心概况

2016 International Workshop on Big Data and Information Security (IWBIS) Pub Date : 2016-10-01 DOI: 10.1109/IWBIS.2016.7872881

Yennun Huang, Szu-Chuang Li

{"title":"Overview of research center for information technology innovation in Taiwan Academia Sinica","authors":"Yennun Huang, Szu-Chuang Li","doi":"10.1109/IWBIS.2016.7872881","DOIUrl":"https://doi.org/10.1109/IWBIS.2016.7872881","url":null,"abstract":"Founded in February 2007, the aim of the Research Center for Information Technology Innovation (CITI) at Academia Sinica is to integrate research and development efforts in information technologies by various organizations in Academia Sinica, and also to facilitate and leverage IT-related multidisciplinary research. As a integral part of CITI, Taiwan Information Security Center (TWISC) to conduct researches on security with funding support from Ministry of Science and Technology. TWISC serves as a platform for security experts from universities, research institutes and private sector to share information and to explore opportunities to collaborate. Its aim is to boost research and development activities and promote public awareness regarding information security. Its research topics cover data/ software/ hardware/ network security and security management. TWISC has become the hub of security research in Taiwan and have been making significant impact through publishing and creating of toolkits. Recently privacy also becomes one of the main focuses of TWISC. The research team at CITI, Academia has been working on a viable way to assess the disclosure risk of synthetic dataset. Preliminary research result will be presented in this paper.","PeriodicalId":193821,"journal":{"name":"2016 International Workshop on Big Data and Information Security (IWBIS)","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116478668","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 and implementation of merchant acquirer data warehouse at PT. XYZ 在PT. XYZ上设计和实现商户收单数据仓库

2016 International Workshop on Big Data and Information Security (IWBIS) Pub Date : 2016-10-01 DOI: 10.1109/IWBIS.2016.7872888

Y. Ruldeviyani, Bofandra Mohammad

引用次数: 2

Design DDoS attack detector using NTOPNG 利用NTOPNG设计DDoS攻击检测器

2016 International Workshop on Big Data and Information Security (IWBIS) Pub Date : 2016-10-01 DOI: 10.1109/IWBIS.2016.7872903

G. Jati, Budi Hartadi, A. Putra, Fahri Nurul, M. Iqbal, S. Yazid

引用次数: 3

Enhanced tele ECG system using Hadoop framework to deal with big data processing 增强远程心电系统采用Hadoop框架进行大数据处理

2016 International Workshop on Big Data and Information Security (IWBIS) Pub Date : 2016-10-01 DOI: 10.1109/IWBIS.2016.7872900

M. A. Ma'sum, W. Jatmiko, H. Suhartanto

引用次数: 7

Big sensor-generated data streaming using Kafka and Impala for data storage in Wireless Sensor Network for CO2 monitoring 大传感器生成的数据流使用Kafka和Impala在无线传感器网络中存储数据，用于二氧化碳监测

2016 International Workshop on Big Data and Information Security (IWBIS) Pub Date : 2016-10-01 DOI: 10.1109/IWBIS.2016.7872896

Rindra Wiska, Novian Habibie, A. Wibisono, W. S. Nugroho, P. Mursanto

引用次数: 13

Dimensionality reduction using deep belief network in big data case study: Hyperspectral image classification 基于深度信念网络的大数据降维研究:高光谱图像分类

2016 International Workshop on Big Data and Information Security (IWBIS) Pub Date : 2016-10-01 DOI: 10.1109/IWBIS.2016.7872892

D. M. S. Arsa, G. Jati, Aprinaldi Jasa Mantau, Ito Wasito

引用次数: 15

Spatial data mining for predicting of unobserved zinc pollutant using ordinary point Kriging 常点克里格法预测未观测锌污染物的空间数据挖掘

2016 International Workshop on Big Data and Information Security (IWBIS) Pub Date : 2016-10-01 DOI: 10.1109/IWBIS.2016.7872894

A. A. Gunawan, A. N. Falah, Alfensi Faruk, D. S. Lutero, B. N. Ruchjana, A. S. Abdullah

{"title":"Spatial data mining for predicting of unobserved zinc pollutant using ordinary point Kriging","authors":"A. A. Gunawan, A. N. Falah, Alfensi Faruk, D. S. Lutero, B. N. Ruchjana, A. S. Abdullah","doi":"10.1109/IWBIS.2016.7872894","DOIUrl":"https://doi.org/10.1109/IWBIS.2016.7872894","url":null,"abstract":"Due to pollution over many years, large amounts of heavy metal pollutant can be accumulated in the rivers. In the research, we would like to predict the dangerous region around the river. For study case, we use the Meuse river floodplains which are contaminated with zinc (Zn). Large zinc concentrations can cause many health problems, for example vomiting, skin irritations, stomach cramps, and anaemia. However there is only few sample data about the zinc concentration of Meuse river, thus the missing data in unknown regions need to be generated. The aim of this research is to study and to apply spatial data mining to predict unobserved zinc pollutant by using ordinary point Kriging. By mean of semivariogram, the variability pattern of zinc can be captured. This captured model will be interpolated to predict the unknown regions by using Kriging method. In our experiments, we propose ordinary point Kriging and employ several semivariogram: Gaussian, Exponential and Spherical models. The experimental results show that: (i) by calculating the minimum error sum of squares, the fittest theoretical semivariogram models is exponential model (ii) the accuracy of the predictions can be confirmed visually by projecting the results to the map.","PeriodicalId":193821,"journal":{"name":"2016 International Workshop on Big Data and Information Security (IWBIS)","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121116694","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: 7

The application of big data using MongoDB: Case study with SCeLE Fasilkom UI forum data MongoDB的大数据应用:以SCeLE Fasilkom UI论坛数据为例

2016 International Workshop on Big Data and Information Security (IWBIS) Pub Date : 2016-10-01 DOI: 10.1109/IWBIS.2016.7872889

Argianto Rahartomo, R. F. Aji, Y. Ruldeviyani

引用次数: 1