2015 International Conference on Advanced Computer Science and Information Systems (ICACSIS)最新文献_第2页

Evolutionary segment selection for higher-order conditional random fields in semantic image segmentation 语义图像分割中高阶条件随机场的进化段选择

2015 International Conference on Advanced Computer Science and Information Systems (ICACSIS) Pub Date : 2015-10-01 DOI: 10.1109/ICACSIS.2015.7415150

Novian Habibie, Vektor Dewanto, Jogie Chandra, Fariz Ikhwantri, H. Santoso, W. Jatmiko

{"title":"Evolutionary segment selection for higher-order conditional random fields in semantic image segmentation","authors":"Novian Habibie, Vektor Dewanto, Jogie Chandra, Fariz Ikhwantri, H. Santoso, W. Jatmiko","doi":"10.1109/ICACSIS.2015.7415150","DOIUrl":"https://doi.org/10.1109/ICACSIS.2015.7415150","url":null,"abstract":"One promising approach for pixel-wise semantic segmentation is based on higher-order Conditional Random Fields (CRFs). We aim to selectively choose segments for the higher-order CRFs in semantic segmentation. To this end, we formulate the selection as an optimization problem. We propose three optimization criteria in relation to the selected segments, namely: a) averaged goodness, b) coverage area and c) non-overlapped area. Essentially, we desire to have best segments with maximum coverage area and maximum non-overlapped area. We apply two evolutionary optimization algorithms, namely: the genetic algorithm (GA) and the particle swarm optimization (PSO). The goodness of segments is estimated using the Latent Dirichlet Allocation approach. Experiment results show that semantic segmentation with GA-or-PSO-selected segments yields competitive semantic segmentation accuracy in comparison to that of naively using all segments. Moreover, the fewer number of segments used in semantic segmentation speeds up its computation time up to six times faster.","PeriodicalId":325539,"journal":{"name":"2015 International Conference on Advanced Computer Science and Information Systems (ICACSIS)","volume":"49 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":"114369770","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

Online marginalized linear stacked denoising autoencoders for learning from big data stream 面向大数据流学习的在线边缘线性堆叠去噪自编码器

2015 International Conference on Advanced Computer Science and Information Systems (ICACSIS) Pub Date : 2015-10-01 DOI: 10.1109/ICACSIS.2015.7415181

Arif Budiman, M. I. Fanany, Chan Basaruddin

{"title":"Online marginalized linear stacked denoising autoencoders for learning from big data stream","authors":"Arif Budiman, M. I. Fanany, Chan Basaruddin","doi":"10.1109/ICACSIS.2015.7415181","DOIUrl":"https://doi.org/10.1109/ICACSIS.2015.7415181","url":null,"abstract":"Big non-stationary data, which comes in gradual fashion or stream, is one important issue in the application of big data to train deep learning machines. In this paper, we focused on a unique variant of traditional autoencoder, which is called Marginalized Linear Stacked Denoising Autoencoder (MLSDA). MLSDA uses a simple linear model. It is faster and uses less number of parameters than the traditional SDA. It also takes advantages of convex optimization. It has better improvement in the bag of words feature representation. However, the traditional SDA with stochastic gradient descent has been more widely accepted in many applications. The stochastic gradient descent is naturally an online learning. It makes the traditional SDA more scalable for streaming big data. This paper proposes a simple modification of MLSDA. Our modification uses matrix multiplication concept for online learning. The experiment result showed the similar accuracy level compared with a batch version of MLSDA and using lower computation resources. The online MLSDA will improve the scalability of MLSDA for handling streaming big data that representing bag of words features for natural language processing, information retrieval, and computer vision.","PeriodicalId":325539,"journal":{"name":"2015 International Conference on Advanced Computer Science and Information Systems (ICACSIS)","volume":"49 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":"129971195","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

Phrase-based clause extraction for open information extraction system 面向开放信息抽取系统的基于短语的子句抽取

2015 International Conference on Advanced Computer Science and Information Systems (ICACSIS) Pub Date : 2015-10-01 DOI: 10.1109/ICACSIS.2015.7415184

A. Romadhony, D. H. Widyantoro, A. Purwarianti

引用次数: 4

Personal traits as antecedents towards intention to use: A perspective of a government EDMS adoption in Indonesia 个人特质对使用意愿的影响:印尼政府采用电子数据管理系统的视角

2015 International Conference on Advanced Computer Science and Information Systems (ICACSIS) Pub Date : 2015-10-01 DOI: 10.1109/ICACSIS.2015.7415170

Karyanto Wijaya, B. Purwandari, M. R. Shihab

引用次数: 8

An adaptive selective background learning-hole filling algorithm to improve vehicle detection 一种改进车辆检测的自适应选择性背景学习-孔填充算法

2015 International Conference on Advanced Computer Science and Information Systems (ICACSIS) Pub Date : 2015-10-01 DOI: 10.1109/ICACSIS.2015.7415188

M. Alhamidi, Qurrotin A’yunina, A. Wibisono, P. Mursanto, W. Jatmiko

{"title":"An adaptive selective background learning-hole filling algorithm to improve vehicle detection","authors":"M. Alhamidi, Qurrotin A’yunina, A. Wibisono, P. Mursanto, W. Jatmiko","doi":"10.1109/ICACSIS.2015.7415188","DOIUrl":"https://doi.org/10.1109/ICACSIS.2015.7415188","url":null,"abstract":"Transportation plays an important role in urban development However, the vehicle growth in Indonesia is not supported by the number of road. Due to this fact, traffic congestion is easily occurred, especially in big cities. Intelligent Transportation System (ITS) has huge contribution to decrease the traffic congestion. In ITS, vehicle detection is one of challenging issue for traffic surveillance. In this paper, adaptive selective background learning and hole filling algorithm are applied to improve the vehicle detection. The validity of the proposed method is tested by using three scenarios and two parameters. The scenarios are bad weather close range (BW-CR), normal weather close range (NW-CR) and normal weather wide range (NW-WR). While, the parameters are the time duration of stopped vehicle detection and the pixel accuracy. Then, the proposed method (Adaptive Selective Background Learning-Hole Filling algorithm) is compared by another previous vehicle detection method. Generally, the result shows that the proposed method yields a significant improvement in vehicle detection. ASBL-HF can detect the stopped and moved vehicle with free noises. Moreover, ASBL-HF has the best accuracy. The accuracy value is about 98.2%.","PeriodicalId":325539,"journal":{"name":"2015 International Conference on Advanced Computer Science and Information Systems (ICACSIS)","volume":"17 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":"115399155","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: 2

Information quality assessment for user perception on Indonesia Kreatif web portal 印度尼西亚Kreatif门户网站用户感知的信息质量评估

2015 International Conference on Advanced Computer Science and Information Systems (ICACSIS) Pub Date : 2015-10-01 DOI: 10.1109/ICACSIS.2015.7415182

Arfive Gandhi, M. R. Shihab, S. Yudhoatmojo, A. Hidayanto

引用次数: 5

Indonesian-Japanese term extraction from bilingual corpora using machine learning 使用机器学习从双语语料库中提取印尼语-日语术语

2015 International Conference on Advanced Computer Science and Information Systems (ICACSIS) Pub Date : 2015-10-01 DOI: 10.1109/ICACSIS.2015.7415180

Muhammad Nassirudin, A. Purwarianti

{"title":"Indonesian-Japanese term extraction from bilingual corpora using machine learning","authors":"Muhammad Nassirudin, A. Purwarianti","doi":"10.1109/ICACSIS.2015.7415180","DOIUrl":"https://doi.org/10.1109/ICACSIS.2015.7415180","url":null,"abstract":"As bilateral relation between Indonesia and Japan strengthens, the need of consistent term usage for both languages becomes important. In this paper, a new method for Indonesian-Japanese term extraction is presented. In general, this is done in 3 steps: (1) n-gram extraction for each language, (2) n-gram cross-pairing between both languages, and (3) classification. This method is aimed to be able to handle term extraction from both parallel corpora and comparable corpora. In order to use this method, we have to build a classification model first using machine learning. There are 4 types of feature we take into consideration. They are dictionary based features, cognate based features, combined features, and statistic features. The first three features are linguistic features. Dictionary based features consider word-pair existence in a predefined dictionary, cognate based features consider morpheme level similarity, combined features consider both dictionary and cognate based features altogether, and statistic features is used in case the first 3 features fail. The only statistic feature we use is context heterogeneity similarity, which consider the variety of words that can precede or follow a term. For learning algorithm, we use SVM (Support Vector Machine). In the experiment, we compared several scenarios: only linguistic features, only statistic features, or both features combined. The classification model was built from parallel corpora since plenty of term pairs can be extracted from parallel corpora. The size of training data was 5,000 term pairs. The best result was achieved by using only linguistic features and without the preprocessing step. The accuracy was up to 90.98% and recall 92.14%. A testing from comparable corpora was also done with size of 37,392 term pairs where 94 were equivalent translation and 37,298 were not. Evaluation using test set gave accuracy of 98.63% precision, but with low recall score of 24.47%.","PeriodicalId":325539,"journal":{"name":"2015 International Conference on Advanced Computer Science and Information Systems (ICACSIS)","volume":"10 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":"122729315","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

Agent-based modeling for developing pervasive persuasive systems 开发普遍说服系统的基于主体的建模

2015 International Conference on Advanced Computer Science and Information Systems (ICACSIS) Pub Date : 2015-10-01 DOI: 10.1109/ICACSIS.2015.7415198

Budhitama Subagdja

引用次数: 1

Ontology development based on generic object oriented smart home model 基于通用面向对象智能家居模型的本体开发

2015 International Conference on Advanced Computer Science and Information Systems (ICACSIS) Pub Date : 2015-10-01 DOI: 10.1109/ICACSIS.2015.7415186

Yulistiyan Wardhana, B. Hardian, G. Guarddin

{"title":"Ontology development based on generic object oriented smart home model","authors":"Yulistiyan Wardhana, B. Hardian, G. Guarddin","doi":"10.1109/ICACSIS.2015.7415186","DOIUrl":"https://doi.org/10.1109/ICACSIS.2015.7415186","url":null,"abstract":"Smart home development has many methods that cause the rise of various smart home systems which has its own uniqueness on every system. Nevertheless, those systems could not accommodate their communication and information sharing. It causes the difficulties of collaboration on a system to another, and it makes hard to implement an existing models on a new system. One of solution to answer this problem is to implement ontology. Ontology allows the preparation of structured system that corresponds to a specific character in accordance with the needs of the system. Ontology implementations in Smart Home are expected to ease in managing information and using information. In this research, an ontology is built. The ontology would be mapped from the smart-home object based generic design. We developed a simple system by utilizing the ontology that has been built. Based on the experiment has been done, the ontology has had a consistent structure and appropriate with the smart home system design requirement. Based on tests that we have done, the ontology is easy to be implemented into a system. Besides, with a limited instance, the ontology has been successfully delivered 81.027 % appropriate response with 0.0146 second average response time to the residents activity in the smart home environment.","PeriodicalId":325539,"journal":{"name":"2015 International Conference on Advanced Computer Science and Information Systems (ICACSIS)","volume":"42 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":"132524350","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

An automatic health surveillance chart interpretation system based on Indonesian language 基于印尼语的健康监测图表自动翻译系统

2015 International Conference on Advanced Computer Science and Information Systems (ICACSIS) Pub Date : 2015-10-01 DOI: 10.1109/ICACSIS.2015.7415165

I. Aulia, A. Barmawi

{"title":"An automatic health surveillance chart interpretation system based on Indonesian language","authors":"I. Aulia, A. Barmawi","doi":"10.1109/ICACSIS.2015.7415165","DOIUrl":"https://doi.org/10.1109/ICACSIS.2015.7415165","url":null,"abstract":"The Indonesian communities have the difficulties for interpreting the chart image, especially the health surveillance chart image. This condition is impacted on late awareness of disease threat. In Indonesia, the chart interpreter system based on Indonesian language is available, but it still has the limitation in generating the textual representation (i.e the health surveillance summaries) in the case of the user involvement. This paper proposed the automatic chart interpreter system as the Natural Language Generation (NLG) system adopting Data-to-Text architecture for overcoming the intended problem. In other words, it emphasizes on the automation system, where the automation system refers to the ability of system for determining the related events and the inference of the related events as well as to generating the related summaries without requiring the manual input from the users. Based on the experiment result, the proposed system (HS-CISys) can perform the automation with involving Data Interpretation and Micro Planning. Therefore, Data Interpretation and Micro Planning ensure that the proposed system can generate the health surveillance summaries fully automatic without relying on the manual input from the users.","PeriodicalId":325539,"journal":{"name":"2015 International Conference on Advanced Computer Science and Information Systems (ICACSIS)","volume":"47 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":"114056806","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: 3