2018 10th International Conference on Information Technology and Electrical Engineering (ICITEE)最新文献_第2页

Consensus of Uncertain Second-Order Multi-Agent Systems Using Interval Type-2 Fuzzy System and Minimal Learning Parameter Algorithm 基于区间2型模糊系统和最小学习参数算法的不确定二阶多智能体系统一致性

2018 10th International Conference on Information Technology and Electrical Engineering (ICITEE) Pub Date : 2018-07-01 DOI: 10.1109/ICITEED.2018.8534863

Maedeh Taj, M. Shahriari-kahkeshi

引用次数: 1

Investigation of 150/66 kV 100 MVA Transformer Internal Failure 150/66 kV 100mva变压器内部故障调查

2018 10th International Conference on Information Technology and Electrical Engineering (ICITEE) Pub Date : 2018-07-01 DOI: 10.1109/ICITEED.2018.8534796

B. Harsono, A. A. Kusuma, B. S. Munir, N. W. Priambodo

{"title":"Investigation of 150/66 kV 100 MVA Transformer Internal Failure","authors":"B. Harsono, A. A. Kusuma, B. S. Munir, N. W. Priambodo","doi":"10.1109/ICITEED.2018.8534796","DOIUrl":"https://doi.org/10.1109/ICITEED.2018.8534796","url":null,"abstract":"An investigation was performed upon the failure of a 150/66 kV 100 MVA power transformer and nearby 66 kV arrester during heavy rain. To verify the possible cause of the failure, an evaluation was conducted by performing visual inspection on the transformer and the arrester after breakdown, analyzing related historical assessment and maintenance data, evaluating recorded lightning activity data from lightning detection system and generating relevant simulation using transformer nameplate and actual configuration. Majority of the historical assessment and maintenance data results showed no indication of transformer early breakdown, but the sweep frequency response analysis (SFRA) test result showed severe deformation on primary and secondary winding. According to the simulation using 20 kA 1.2/$50~mu $ s lightning strike on 66 kV transmission line connected to the transformer, overvoltage on the transformer reached 1.69 p.u. for primary winding and 8.47 p.u for secondary winding. However, according to recorded lightning data during time of failure, there's no nearby lightning strike around the transformer or the transmission lines connected to it. Moreover, lightning overvoltage would initially shatter the transformer's bushing rather than directly deforming the transformer tank. The simulation result for short circuit between primary winding phase R to ground showed identical current and voltage waveform with digital fault recorder data during breakdown. According to data and simulation result analysis, lightning activity has no contribution toward the failure of the 150/66 kV 100 MVA transformer. The possible cause of transformer breakdown was internal failure in form of arcing between primary winding phase R to ground.","PeriodicalId":142523,"journal":{"name":"2018 10th International Conference on Information Technology and Electrical Engineering (ICITEE)","volume":"9 23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117255496","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

Comparison of Three Auditory Frequency Scales in Feature Extraction on Myanmar Digits Recognition 三种听觉频率尺度在缅甸数字识别特征提取中的比较

2018 10th International Conference on Information Technology and Electrical Engineering (ICITEE) Pub Date : 2018-07-01 DOI: 10.1109/ICITEED.2018.8534768

Hay Mar Soe Naing, Risanuri Hidayat, Bondhan Winduratna, Y. Miyanaga

{"title":"Comparison of Three Auditory Frequency Scales in Feature Extraction on Myanmar Digits Recognition","authors":"Hay Mar Soe Naing, Risanuri Hidayat, Bondhan Winduratna, Y. Miyanaga","doi":"10.1109/ICITEED.2018.8534768","DOIUrl":"https://doi.org/10.1109/ICITEED.2018.8534768","url":null,"abstract":"With the rapidly growth of digital computers, there has been an increasing demand to communicate with machines in efficient spoken manner. Speech recognition is the process of translating fromspoken words into readable text. To get the robust and reliable transcription text from recognizer,proper feature extraction methods are needed. This paper is concerned to an approach of features extraction on spoken Myanmar digits recognition. In this study, the recognition performances of Fast Fourier Transform (FFT), Mel Frequency Cepstrum Coefficients (MFCC), Linear Predictive Coding (LPC)and Linear Prediction Cepstral Coefficients (LPCC) methods will be compared. Even though the frequency spacing with Mel scale is extensively used in Automatic Speech Recognition (ASR), this paper demonstrates another scale of auditory frequency spectrum namely, Bark and Equivalent Rectangular Bandwidth (ERB) scales. The results have achieved the better performance than the Mel scale. The k-Nearest Neighbor (KNN) is employed as the classifier and ten digits of Myanmar language from twelve speakers are collected. According to these experiments, the results show the best recognition rates of 88.6% with the used of feature extraction based on ERB scale band pass filter.","PeriodicalId":142523,"journal":{"name":"2018 10th International Conference on Information Technology and Electrical Engineering (ICITEE)","volume":" 24","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"120829964","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

Performance Evaluation of n-Grams Ratio Features in Solving Multi-Classes Classification Problems n-Grams比率特征在求解多类分类问题中的性能评价

2018 10th International Conference on Information Technology and Electrical Engineering (ICITEE) Pub Date : 2018-07-01 DOI: 10.1109/ICITEED.2018.8534773

T. Abidin, Nur Ratna Sari, Ahmad Zuhri Ramadhan, Irvanizam, R. P. F. Afidh

{"title":"Performance Evaluation of n-Grams Ratio Features in Solving Multi-Classes Classification Problems","authors":"T. Abidin, Nur Ratna Sari, Ahmad Zuhri Ramadhan, Irvanizam, R. P. F. Afidh","doi":"10.1109/ICITEED.2018.8534773","DOIUrl":"https://doi.org/10.1109/ICITEED.2018.8534773","url":null,"abstract":"We present experimental results that compare k-Nearest Neighbors (k-NN) and Support Vector Machines (SVM) algorithms to classifythe natural disasters multi-classes problem when n-grams ratio is used as the numerical features and compare three SVM approaches to classify the transportation accidents multi-classes problem when the same n-grams ratio is used as the features. In the former problem, we would like to investigate which of the two prominent algorithms have a better accuracy, while in thelatter problem, we would like to compare which of the three well-known SVM approaches for solving multi-classes problem performs best.In the natural disasters problem, the class labels are earthquakes, volcanic eruptions, flooding, landslides, and others, while in the transportation accidents problem, the categories are traffic collisions, maritime accidents, aviation accidents, and others. n-grams dictionaries of each category are used as the references in creating numerical features of the news articles. The results show that for the natural disasters problem, k-NN performs better than SVM and for the transportation accidents problem, DAGSVMoutperforms the other two SVM binary classification approaches.","PeriodicalId":142523,"journal":{"name":"2018 10th International Conference on Information Technology and Electrical Engineering (ICITEE)","volume":"755 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116409492","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

Natural Language Processing and Lexical Approach for Depression Symptoms Screening of Indonesian Twitter User 印尼Twitter用户抑郁症状筛选的自然语言处理和词汇方法

2018 10th International Conference on Information Technology and Electrical Engineering (ICITEE) Pub Date : 2018-07-01 DOI: 10.1109/ICITEED.2018.8534929

Irwan Oyong, Ema Utami, E. T. Luthfi

{"title":"Natural Language Processing and Lexical Approach for Depression Symptoms Screening of Indonesian Twitter User","authors":"Irwan Oyong, Ema Utami, E. T. Luthfi","doi":"10.1109/ICITEED.2018.8534929","DOIUrl":"https://doi.org/10.1109/ICITEED.2018.8534929","url":null,"abstract":"The shame and disgrace of depression cause people not to seek help for the problem. Contemporary social media technologies such as Twitter provide an opportunity for people to be able to express their feelings in an anonymous and confidential environment. In this study symptoms lexicon terms are used with the frequency lexicon for weighting and perform depression score calculations from text materials that have undergone Natural Language Processing. Through the scraping process, 55 relevant users were found who netted depression-related keywords. For each user, a data search is made for a week before and after the initial tweet. Tweet extensions generate a total of 6055 tweets from 55 users in question. The sum of the scores becomes the label determinant of user depression, which is then compared to the labels that have been given manually by psychologists based on clinical screening standards. Based on comparative and evaluation results, the same F1 score of 0.47 is obtained for standard text processing and text-specific processing for Twitter, and a Sensitivity value of 0.89 at the threshold value of 0.5. A slightly better F1 Score value of 0.50 is obtained by text-specific processing on the threshold value of 0.8. Research shows differences in minor results between standard text processing and text-specific processing of Twitter. Seen some of the advantages of text-specific Twitter processing when handling non-standard text, thereby enhancing the fmdings of the Part-of-Speech tagging process.","PeriodicalId":142523,"journal":{"name":"2018 10th International Conference on Information Technology and Electrical Engineering (ICITEE)","volume":"150 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123213005","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: 15

Indonesian Traditional Shadow Puppet Image Classification: A Deep Learning Approach 印尼传统皮影图像分类:一种深度学习方法

2018 10th International Conference on Information Technology and Electrical Engineering (ICITEE) Pub Date : 2018-07-01 DOI: 10.1109/ICITEED.2018.8534776

Ida Bagus Kresna Sudiatmika, Pranowo, Suyoto

引用次数: 1

Design of Data Collection Form to Ensure Consistency in AHP 确保AHP一致性的数据收集表设计

2018 10th International Conference on Information Technology and Electrical Engineering (ICITEE) Pub Date : 2018-07-01 DOI: 10.1109/ICITEED.2018.8534751

A. Wadjdi, E. Sianturi, Nina Ruslinawaty

引用次数: 0

Optimal Distribution Route Planning based on Collaboration of Dijkstra and Sweep Algorithm 基于Dijkstra和扫描算法协同的最优配送路径规划

2018 10th International Conference on Information Technology and Electrical Engineering (ICITEE) Pub Date : 2018-07-01 DOI: 10.1109/ICITEED.2018.8534753

L. Zulfiqar, R. Isnanto, O. Nurhayati

引用次数: 5

Evidence Data Collection with ANDROSICS Tool for Android Forensics 证据数据收集与ANDROSICS工具安卓取证

2018 10th International Conference on Information Technology and Electrical Engineering (ICITEE) Pub Date : 2018-07-01 DOI: 10.1109/ICITEED.2018.8534760

Naing Linn Htun, M. Thwin, C. C. San

引用次数: 4

Self Monitoring, Failure-Detection and Decision-Making System to Support E-TrashBot (EEPIS Trash Bin Robot) Operations: Preliminary Report 支持E-TrashBot (EEPIS垃圾桶机器人)运行的自我监测、故障检测和决策系统:初步报告

2018 10th International Conference on Information Technology and Electrical Engineering (ICITEE) Pub Date : 2018-07-01 DOI: 10.1109/ICITEED.2018.8534932

Kisron, B. S. B. Dewantara, Fernando Ardilla

引用次数: 7