2015 International Conference on Advanced Computer Science and Information Systems (ICACSIS)最新文献

Road detection system based on RGB histogram filterization and boundary classifier 基于RGB直方图滤波和边界分类器的道路检测系统

2015 International Conference on Advanced Computer Science and Information Systems (ICACSIS) Pub Date : 2015-10-01 DOI: 10.1109/ICACSIS.2015.7415163

M. D. Enjat Munajat, D. H. Widyantoro, R. Munir

{"title":"Road detection system based on RGB histogram filterization and boundary classifier","authors":"M. D. Enjat Munajat, D. H. Widyantoro, R. Munir","doi":"10.1109/ICACSIS.2015.7415163","DOIUrl":"https://doi.org/10.1109/ICACSIS.2015.7415163","url":null,"abstract":"The purpose of this paper is to describe a new approach in road detection. This research uses two detection processes approaches: RGB histogram Filterization and Boundary Classifer, which is different from previous works on road detection. RGB Histogram Filterization processes the reading from the camera in greyscale form and afterward processes them by color segmentation. The last step for this process is determining area between the slopes, which is considered to be the road area. Boundary classification process then employs the RGB indexing on slope ranges, and mapping them into real pictures of roads and its environments. The next process is specifically looking for line boundaries by using Hough-Transform and Canny Edge Detection, and transforms them into binary numbers of `0' and `1'. `1' represents road boundaries while `0' represents surrounding area. The coordinate of `1', then mapped by cubic spline to produce connecting line between point `1' coordinates, which in the end produce sharp images on boundaries between road and non-road. This model has proven to be able to detect road conditions and distinguish roads from non-road in a precise way. A test is already conducted for the system by using real-time roads in Bandung, Indonesia. The results are really promising for the road condition on both straight and curved road area.","PeriodicalId":325539,"journal":{"name":"2015 International Conference on Advanced Computer Science and Information Systems (ICACSIS)","volume":"2004 7","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114129040","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: 13

Dynamic, auto-adaptive software product lines using the ABS language 采用ABS语言的动态、自适应软件产品线

2015 International Conference on Advanced Computer Science and Information Systems (ICACSIS) Pub Date : 2015-10-01 DOI: 10.1109/ICACSIS.2015.7415195

Radu Muschevici

引用次数: 0

A classification system for jamu efficacy based on formula using support vector machine and k-means algorithm as a feature selection 采用支持向量机和k-means算法作为特征选择，建立了基于公式的果酱功效分类系统

2015 International Conference on Advanced Computer Science and Information Systems (ICACSIS) Pub Date : 2015-10-01 DOI: 10.1109/ICACSIS.2015.7415176

M. N. Puspita, W. Kusuma, A. Kustiyo, R. Heryanto

引用次数: 6

ECG signal compression by predictive coding and Set Partitioning in Hierarchical Trees (SPIHT) 基于预测编码和分层树集分割的心电信号压缩

2015 International Conference on Advanced Computer Science and Information Systems (ICACSIS) Pub Date : 2015-10-01 DOI: 10.1109/ICACSIS.2015.7415191

G. Jati, Aprinaldi, S. M. Isa, W. Jatmiko

引用次数: 4

Application of hierarchical clustering ordered partitioning and collapsing hybrid in Ebola Virus phylogenetic analysis 层次聚类、有序划分和崩溃杂交在埃博拉病毒系统发育分析中的应用

2015 International Conference on Advanced Computer Science and Information Systems (ICACSIS) Pub Date : 2015-10-01 DOI: 10.1109/ICACSIS.2015.7415183

Hengki Muradi, A. Bustamam, D. Lestari

{"title":"Application of hierarchical clustering ordered partitioning and collapsing hybrid in Ebola Virus phylogenetic analysis","authors":"Hengki Muradi, A. Bustamam, D. Lestari","doi":"10.1109/ICACSIS.2015.7415183","DOIUrl":"https://doi.org/10.1109/ICACSIS.2015.7415183","url":null,"abstract":"Gene clustering can be achieved through hierarchical or partition method. Both clustering methods can be combined by processing the partition and hierarchical phases alternately. This method is known as a hierarchical clustering ordered partitioning and collapsing hybrid (HOPACH) method. The Partitioning phase can be done by using PAM, SOM, or K-Means methods. The partition process is continued with the ordered process, and then it is corrected with agglomerative process, in order to have more accurate clustering results. Furthermore, the main clusters are determined by using MSS (Median Split Silhouette) value. We selected the clustering results which minimize the MSS value. In this work, we conduct the clustering on 136 Ebola Virus DNA sequences data from GenBank. The global alignment process is initially performed, followed by genetic distance calculation using Jukes-Cantor correction. In our implementation, we applied global alignment process and used the combination of HOPACH-PAM clustering using the R open source programming tool. In our results, we obtained maximum genetic distance is 0.6153407; meanwhile the minimum genetic distance is 0. Furthermore, genetic distance matrix can be used as a basis for sequences clustering and phylogenetic analysis. In our HOPACH-PAM clustering results, we obtained 10 main clusters with MSS value is 0.8873843. Ebola virus clusters can be identified by species and virus epidemic year.","PeriodicalId":325539,"journal":{"name":"2015 International Conference on Advanced Computer Science and Information Systems (ICACSIS)","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124083428","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: 18

Segmenting and targeting customers through clusters selection & analysis 通过集群选择和分析来细分和定位客户

2015 International Conference on Advanced Computer Science and Information Systems (ICACSIS) Pub Date : 2015-10-01 DOI: 10.1109/ICACSIS.2015.7415187

I. Pranata, G. Skinner

引用次数: 9

Gestalt geometric CAPTCHA 格式塔几何验证码

2015 International Conference on Advanced Computer Science and Information Systems (ICACSIS) Pub Date : 2015-10-01 DOI: 10.1109/ICACSIS.2015.7415185

Nuttanont Hongwarittorrn, Suttikiat Meelap

引用次数: 0

Spark-gram: Mining frequent N-grams using parallel processing in Spark Spark-gram:在Spark中使用并行处理挖掘频繁的n -gram

2015 International Conference on Advanced Computer Science and Information Systems (ICACSIS) Pub Date : 2015-10-01 DOI: 10.1109/ICACSIS.2015.7415169

Prasetya Ajie Utama, Bayu Distiawan

引用次数: 2

Developing smart telehealth system in Indonesia: Progress and challenge 在印度尼西亚发展智能远程医疗系统:进展与挑战

2015 International Conference on Advanced Computer Science and Information Systems (ICACSIS) Pub Date : 2015-10-01 DOI: 10.1109/ICACSIS.2015.7415199

W. Jatmiko, M. A. Ma'sum, S. M. Isa, E. Imah, R. Rahmatullah, B. Wiweko

{"title":"Developing smart telehealth system in Indonesia: Progress and challenge","authors":"W. Jatmiko, M. A. Ma'sum, S. M. Isa, E. Imah, R. Rahmatullah, B. Wiweko","doi":"10.1109/ICACSIS.2015.7415199","DOIUrl":"https://doi.org/10.1109/ICACSIS.2015.7415199","url":null,"abstract":"Indonesia is developing country with high population. There are more than 200 million residents living in the country. As a developing country, Indonesia has several health problems. First, Indonesia has a high value of mortality caused by heart and cardio vascular diseases. One of the major cause is the lack of medical checkup especially for heart monitoring. It is caused by limited number of medical instrumentation e.g. ECG in hospital and public health center. The supporting factor is the small number of cardiologist in Indonesia. There are 365 cardiologists across the country, which is a very small number compared to the 200 million of Indonesia population. Furthermore, they are not distributed evenly in all provinces, but only centered in Jakarta and other capital cities. Therefore, it is difficult for residents to get appropriate heart monitoring. Second, the mortality rate of mother and baby during delivery of the baby in Indonesia is also high. One way to solve this problem is to devise a system where the health clinics in rural areas can perform fetal biometry detection before consulting the results to the expert physicians from other areas. The proposed system will be equipped with algorithms for automatic fetal detection and biometry measurement. By the end of this development, we have several results, the first is a classifier to automatic heartbeat disease prediction with accuracy more than 95%, the second is compression method based on wavelet decompositon, and the third is detection and approximation a fetus in an ultrasound image with hit rate more than 93%.","PeriodicalId":325539,"journal":{"name":"2015 International Conference on Advanced Computer Science and Information Systems (ICACSIS)","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114168060","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: 21

Weather forecasting using deep learning techniques 使用深度学习技术进行天气预报

2015 International Conference on Advanced Computer Science and Information Systems (ICACSIS) Pub Date : 2015-10-01 DOI: 10.1109/ICACSIS.2015.7415154

A. G. Salman, Bayu Kanigoro, Y. Heryadi

{"title":"Weather forecasting using deep learning techniques","authors":"A. G. Salman, Bayu Kanigoro, Y. Heryadi","doi":"10.1109/ICACSIS.2015.7415154","DOIUrl":"https://doi.org/10.1109/ICACSIS.2015.7415154","url":null,"abstract":"Weather forecasting has gained attention many researchers from various research communities due to its effect to the global human life. The emerging deep learning techniques in the last decade coupled with the wide availability of massive weather observation data and the advent of information and computer technology have motivated many researches to explore hidden hierarchical pattern in the large volume of weather dataset for weather forecasting. This study investigates deep learning techniques for weather forecasting. In particular, this study will compare prediction performance of Recurrence Neural Network (RNN), Conditional Restricted Boltzmann Machine (CRBM), and Convolutional Network (CN) models. Those models are tested using weather dataset provided by BMKG (Indonesian Agency for Meteorology, Climatology, and Geophysics) which are collected from a number of weather stations in Aceh area from 1973 to 2009 and El-Nino Southern Oscilation (ENSO) data set provided by International Institution such as National Weather Service Center for Environmental Prediction Climate (NOAA). Forecasting accuracy of each model is evaluated using Frobenius norm. The result of this study expected to contribute to weather forecasting for wide application domains including flight navigation to agriculture and tourism.","PeriodicalId":325539,"journal":{"name":"2015 International Conference on Advanced Computer Science and Information Systems (ICACSIS)","volume":"190 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131911583","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: 130