2016 2nd International Conference on Science and Technology-Computer (ICST)最新文献_第3页

State of charge estimation of Lithium Polymer battery using ANFIS and IT2FLS 基于ANFIS和IT2FLS的聚合物锂电池充电状态估计

2016 2nd International Conference on Science and Technology-Computer (ICST) Pub Date : 2016-10-01 DOI: 10.1109/ICSTC.2016.7877346

Wahyuni Eka Sari, O. Wahyunggoro, S. Fauziati, A. Cahyadi

引用次数: 2

Palm oil plantation area clusterization for monitoring 棕榈油种植区集群化监测

2016 2nd International Conference on Science and Technology-Computer (ICST) Pub Date : 2016-10-01 DOI: 10.1109/ICSTC.2016.7877364

A. Frisky, A. Harjoko

{"title":"Palm oil plantation area clusterization for monitoring","authors":"A. Frisky, A. Harjoko","doi":"10.1109/ICSTC.2016.7877364","DOIUrl":"https://doi.org/10.1109/ICSTC.2016.7877364","url":null,"abstract":"This paper discusses the use of the clusterization to group palm trees in plantation areas using three categories, i.e. healthy, unhealthy, and non-plantation. Here, overhead images taken by an Unmanned Aerial Vehicle (UAV) were used to view a wider area. Images were divided into several smaller images using sliding windows and extracted using three color feature extraction techniques, i.e. 2D Wavelet Decomposition Color Energy, Principal Component Analysis, and t-Distributed Stochastic Neighbor Embedding (t-SNE). Texture feature extraction techniques used were Local Binary Pattern, Gray Level Co-occurrence Matrix and Segmentation-based Fractal Texture Analysis. Cluster results using the different techniques were compared to determine the optimal feature. Sliding windows were first implemented, and then cropped into small images with the same size as the windows. During clusterization, the K-Means clustering method was used to divide all smaller images into groups with high degrees of similarity. Feature extraction techniques were used individually to divide areas into three categories. The ground truth of the dataset was determined in advance, and results were compared to determine recognition rate. The study shows that dimensionality reduction using t-SNE in RGB color obtained the best clusterization results with 1135 correct patches.","PeriodicalId":228650,"journal":{"name":"2016 2nd International Conference on Science and Technology-Computer (ICST)","volume":"1 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":"124993497","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

Block-based Tchebichef image watermarking scheme using psychovisual threshold 基于块的视觉心理阈值的切切夫图像水印方案

2016 2nd International Conference on Science and Technology-Computer (ICST) Pub Date : 2016-10-01 DOI: 10.1109/ICSTC.2016.7877339

F. Ernawan, M. Kabir, M. Fadli, Z. Mustaffa

引用次数: 16

Combat aircraft effectiveness assessment using hybrid multi-criteria decision making methodology 基于混合多准则决策方法的作战飞机效能评估

2016 2nd International Conference on Science and Technology-Computer (ICST) Pub Date : 2016-10-01 DOI: 10.1109/ICSTC.2016.7877358

Agus Suryo Wibowo, A. E. Permanasari, S. Fauziati

引用次数: 5

Convolutional Neural Network implementation for image-based Salak sortation 基于图像的Salak排序的卷积神经网络实现

2016 2nd International Conference on Science and Technology-Computer (ICST) Pub Date : 2016-10-01 DOI: 10.1109/ICSTC.2016.7877351

Rismiyati, Sn Azhari

{"title":"Convolutional Neural Network implementation for image-based Salak sortation","authors":"Rismiyati, Sn Azhari","doi":"10.1109/ICSTC.2016.7877351","DOIUrl":"https://doi.org/10.1109/ICSTC.2016.7877351","url":null,"abstract":"Salak is one of potential export commodities from Indonesia. However, the main obstacle to perform Salak export is transportation which requires rigorous selection of the fruit. In the current packaging process, this sortation is done manually. In this study, convolution neural network (CNN) is applied to automatically distinguish quality of Salak. Input used in this study is the image of salak. The process involved in this study is data collection, preprocessing, classification and testing. Preprocessing is done by cutting a region of interest (ROI) containing only salak image. Classification is done by CNN, for which to get the best accuracy of the model, existing parameters should be tested and evaluated. Testing is done for two types of model, 2-class models and 4-class models. The experiments result showed that the best accuracy obtained for 2-class model is 81.45% by using learning rate of 0.0001, a single layer convolution with fifteen filters and 100 neurons in the hidden layer. The filters' size is 3×3×3. While 4-class model obtained best accuracy of 70.71% with two convolutional layers. The numbers of filter in each layer are 6 filters with the size of 3×5×5 in the first layer and 18 filters with the size of 6×3×3 in the second layer.","PeriodicalId":228650,"journal":{"name":"2016 2nd International Conference on Science and Technology-Computer (ICST)","volume":"26 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":"129601463","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: 9

Stereo camera — Based 3D object reconstruction utilizing Semi-Global Matching Algorithm 基于半全局匹配算法的立体相机三维物体重建

2016 2nd International Conference on Science and Technology-Computer (ICST) Pub Date : 2016-10-01 DOI: 10.1109/ICSTC.2016.7877373

M. S. H. Achmad, Widya Setia Findari, Nurnajmin Qasrina Ann, Dwi Pebrianti, M. R. Daud

引用次数: 6

Infant's cry sound classification using Mel-Frequency Cepstrum Coefficients feature extraction and Backpropagation Neural Network 基于mel -频倒谱系数特征提取和反向传播神经网络的婴儿哭声声音分类

2016 2nd International Conference on Science and Technology-Computer (ICST) Pub Date : 2016-10-01 DOI: 10.1109/ICSTC.2016.7877367

Yesy Diah Rosita, Hartarto Junaedi

引用次数: 7

Optimal cell selection scheme in Femtocell networks using bacterial foraging optimization algorithm 基于细菌觅食优化算法的Femtocell网络细胞选择优化方案

2016 2nd International Conference on Science and Technology-Computer (ICST) Pub Date : 2016-10-01 DOI: 10.1109/ICSTC.2016.7877366

Sahirul Alam, I. Mustika, Selo, Heng Lalin

引用次数: 3

Implementation of multi-criteria collaborative filtering on cluster using Apache Spark 基于Apache Spark的集群多准则协同过滤的实现

2016 2nd International Conference on Science and Technology-Computer (ICST) Pub Date : 2016-10-01 DOI: 10.1109/ICSTC.2016.7877370

A. Wijayanto, E. Winarko

{"title":"Implementation of multi-criteria collaborative filtering on cluster using Apache Spark","authors":"A. Wijayanto, E. Winarko","doi":"10.1109/ICSTC.2016.7877370","DOIUrl":"https://doi.org/10.1109/ICSTC.2016.7877370","url":null,"abstract":"Scalability is a problem commonly faced by a recommendation system that uses collaborative filtering methods. Multi-criteria collaborative filtering recommender system has the exact same problem. The performance of multi-criteria collaborative filtering is reduced when the amount of data processed by recommender system is increasing too high. This research aims to complement previous research which is to improve the scalability of multi-criteria collaborative filtering recommender system by applying scale-out approach or adding computer node to run the recommender system. The process of generating a recommendation on multi-criteria collaborative filtering recommender system will be done on multiple nodes of computer network inside a cluster using Apache Spark framework. To measure system scalability, the running time of multi-criteria collaborative filtering recommender system that are implemented as a recommender program on Apache Spark cluster will be compared in the form of speedup value. Based on test results, it is known that multi-criteria collaborative filtering on Apache Spark cluster has better running time than its sequential counterpart. Unfortunately, as the numbers of nodes inside cluster are increased, multi-criteria collaborative filtering recommender system on Apache Spark cluster does not gain ideal speedup.","PeriodicalId":228650,"journal":{"name":"2016 2nd International Conference on Science and Technology-Computer (ICST)","volume":"20 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":"128092267","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

Simulation and experiment based optimization of calligraphy manufacturing using a 5-axis CNC Milling Machine 基于仿真和实验的五轴数控铣床书法加工优化

2016 2nd International Conference on Science and Technology-Computer (ICST) Pub Date : 2016-10-01 DOI: 10.1109/ICSTC.2016.7877355

M. Muflikhun, M. Mahardika, Subarmono, H. Rochardjo

引用次数: 0