2016 IEEE International Conference on Automatic Control and Intelligent Systems (I2CACIS)最新文献

Fuzzy logic controller design for intelligent drilling system 智能钻井系统的模糊控制器设计

2016 IEEE International Conference on Automatic Control and Intelligent Systems (I2CACIS) Pub Date : 2016-10-22 DOI: 10.1109/I2CACIS.2016.7885316

N. Ahamed, Z. Yusof, Z. Hamedon, M. Rabbi, Tasriva Sikandar, R. Palaniappan, Md. Asraf Ali, S. M. Rahman, K. Sundaraj

引用次数: 6

Development of fuzzy inference system for automatic tea making 自动泡茶模糊推理系统的开发

2016 IEEE International Conference on Automatic Control and Intelligent Systems (I2CACIS) Pub Date : 2016-10-01 DOI: 10.1109/I2CACIS.2016.7885314

N. Ahamed, Z. Taha, I. Khairuddin, M. Rabbi, Tasriva Sikandar, R. Palaniappan, Md. Asraf Ali, S. M. Rahman, K. Sundaraj

引用次数: 1

The comparison between listening to Surah Al-Mulk and Surah Al-Hasyr using EEG 用脑电图听《穆尔克苏拉》和《哈西尔苏拉》的比较

2016 IEEE International Conference on Automatic Control and Intelligent Systems (I2CACIS) Pub Date : 2016-10-01 DOI: 10.1109/I2CACIS.2016.7885284

Nurul Fadhilah Binti Ismail, Z. Sharif

引用次数: 1

Fault detection and identification in Quadrotor system (Quadrotor robot) 四旋翼系统(四旋翼机器人)故障检测与识别

2016 IEEE International Conference on Automatic Control and Intelligent Systems (I2CACIS) Pub Date : 2016-10-01 DOI: 10.1109/I2CACIS.2016.7885281

C. Jing, Dwi Pebrianti

{"title":"Fault detection and identification in Quadrotor system (Quadrotor robot)","authors":"C. Jing, Dwi Pebrianti","doi":"10.1109/I2CACIS.2016.7885281","DOIUrl":"https://doi.org/10.1109/I2CACIS.2016.7885281","url":null,"abstract":"Fault Detection and Identification (FDI) monitor, identify, and pinpoint the type and location of system fault in a complex multiple input multiple output (MIMO) non-linear system. A Quadrotor robot is used to represent a complex system in this study. The aim of the research is to construct and design a Fault Detection and Isolation algorithm. This dynamic model is based on the first principles of the Quadrotor: Propeller model and its force as well as moments generation. The Quadrotor controller is designed such that it can be controlled using both the attitude control (inner loop) and position control (outer loop). PD controller used the Phi, Theta, Psi, x, y and z as a reference to adjust the attitude and position of the Quadrotor. The proposed method for the fault identification is a hybrid technique which combined both the Kalman filter and Artificial Neural Network (ANN). Kalman filter recognized data from the system sensors and can indicate the fault of the system in the sensor reading. Error prediction is based on the fault magnitude and the time occurrence of fault. The information will then be fed to Artificial Neural Network (ANN), which consist of a bank of parameter estimation that generates the failure state. This Artificial Neural Network (ANN) is an algorithm that is used to determine the type of fault and the severity level as well as isolate the fault from the system. The ANN is designed based on the back-propagation technique so that it can be trained to generate output based on the data. Based on the result comparison of the residual signal before filter and after filter, the algorithm of FDI is able to identify parts of the system that experience failure and the fault can be solved immediately allowing the Quadrotor to be back to its normal operation. It is also capable to acknowledge the user on the parts of the system which experienced failure and can provide user with the best instructions or solutions for the situation. It is also capable to cater a safe landing.","PeriodicalId":399080,"journal":{"name":"2016 IEEE International Conference on Automatic Control and Intelligent Systems (I2CACIS)","volume":"35 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":"125808350","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

Enhancing vehicle ride comfort through intelligent based control 通过智能控制增强车辆乘坐舒适性

2016 IEEE International Conference on Automatic Control and Intelligent Systems (I2CACIS) Pub Date : 2016-10-01 DOI: 10.1109/I2CACIS.2016.7885291

F. Yakub, P. Muhamad, H. T. Toh, N. Fawazi, S. Sarip, Mohamed Sukri Mat Ali, S. A. Zaki

引用次数: 9

Sliding mode control parameter tuning using ant colony optimization for a 2-DOF hydraulic servo system 基于蚁群优化的二自由度液压伺服系统滑模控制参数整定

2016 IEEE International Conference on Automatic Control and Intelligent Systems (I2CACIS) Pub Date : 2016-10-01 DOI: 10.1109/I2CACIS.2016.7885322

Lindokuhle J. Mpanza, J. Pedro

引用次数: 2

Speech semantic recognition system for an assistive robotic application 语音语义识别系统的一种辅助机器人应用

2016 IEEE International Conference on Automatic Control and Intelligent Systems (I2CACIS) Pub Date : 2016-10-01 DOI: 10.1109/I2CACIS.2016.7885295

S. Mohamad, A. A. Jamaludin, K. Isa

{"title":"Speech semantic recognition system for an assistive robotic application","authors":"S. Mohamad, A. A. Jamaludin, K. Isa","doi":"10.1109/I2CACIS.2016.7885295","DOIUrl":"https://doi.org/10.1109/I2CACIS.2016.7885295","url":null,"abstract":"This project creates a speech semantic recognition system that can be applied in the assistive robotic application by using the meaning of speech for people who suffer a permanent disability that cannot move around normally. The user interface of this speech semantic recognition system of this project are capable to receive the speech input of the user and an application interface transfers the input content of the user to an application. This speech semantic recognition system consists of input part that is speech signal. Based on the input of speech signal, the speech recognizer is used to recognize a corresponding word, the word semantic model representing the connection between a semantic database with the meaning of a word and a registered word belonging to a speech recognizer. The speech signal is recognized the word by using speech recognizer then is converted to the corresponding word-semantic model by the feature extraction approach. The converted word-semantic model is stored in the database and trained. The speech recognizer will recognize the speech signal again and notified to the application via comparing with the word-semantic model stored in the database based on feature matching method before send to the application interface.","PeriodicalId":399080,"journal":{"name":"2016 IEEE International Conference on Automatic Control and Intelligent Systems (I2CACIS)","volume":"29 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":"127194584","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

Unsupervised floating platform for environmental monitoring 无监督环境监测浮动平台

2016 IEEE International Conference on Automatic Control and Intelligent Systems (I2CACIS) Pub Date : 2016-10-01 DOI: 10.1109/I2CACIS.2016.7885294

Nurliyana Kafli, M. Z. Othman, K. Isa

{"title":"Unsupervised floating platform for environmental monitoring","authors":"Nurliyana Kafli, M. Z. Othman, K. Isa","doi":"10.1109/I2CACIS.2016.7885294","DOIUrl":"https://doi.org/10.1109/I2CACIS.2016.7885294","url":null,"abstract":"Environmental monitoring plays an important role in human life, so this project aims to provide a spatial-temporal resolution of data collected inland water storages and lakes through the development of a unique floating platform. Several challenges in monitoring environment especially the accessibility to the site and representativesness of data cause the quality of water and air become worse. Hence, an unsupervised floating platform was developed in order to monitor the environment. The system focused on doing a precision measurement of water quality and air quality. With the help of several sensors that act as an input that is Real-Time Clock, Global Positioning System (GPS) sensor, humidity and temperature sensor, pH sensor and carbon monoxide sensor. Through this sensor, the floating platform collects the data and save it for every 10 minutes to perform real-time data collection. The data are saved into SD card, which consists of time, date, longitude, latitude, carbon monoxide, water pH value, temperature, and humidity. The results obtained then used to evaluate the quality of the air and water of the lake.","PeriodicalId":399080,"journal":{"name":"2016 IEEE International Conference on Automatic Control and Intelligent Systems (I2CACIS)","volume":"154 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":"127338962","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

Sharpening based image enhancement algorithms in reducing the disagreement of medical images subjective evaluation 基于锐化的图像增强算法在减少医学图像主观评价差异中的应用

2016 IEEE International Conference on Automatic Control and Intelligent Systems (I2CACIS) Pub Date : 2016-10-01 DOI: 10.1109/I2CACIS.2016.7885283

Siti Arpah Ahmad, N. Khalid, M. Taib, H. Taib

{"title":"Sharpening based image enhancement algorithms in reducing the disagreement of medical images subjective evaluation","authors":"Siti Arpah Ahmad, N. Khalid, M. Taib, H. Taib","doi":"10.1109/I2CACIS.2016.7885283","DOIUrl":"https://doi.org/10.1109/I2CACIS.2016.7885283","url":null,"abstract":"Subjective evaluation of the abnormalities in dental images faces a few challenges such as low contrast. The problem arises due to the fix regulation of small X-ray dosage. Thus there are applications of image enhancement on the dental images and it is an acceptable technique to improve image quality and better diagnosis. Low contrast images could hinder the subjective evaluation and contribute to disagreement between the evaluators. This work investigates the performance of original and enhanced dental images towards the disagreement issues of evaluating image quality and detecting dental abnormalities. The abnormalities of interest are periapical radiolucency (PA), widen periodontal ligament space (widen PDLs) and loss of lamina dura (Loss of LD). The work begins with collecting the raw intra-oral dental images. Then sharpening based contrast image enhancement algorithms were applied to the images. After that, the images were evaluated by dentists towards the image quality and the abnormalities mentioned. The disagreements among the evaluators were determined using standard deviation formula. Results show that disagreement issue among the evaluators do exists to the extent of above 90%. Comparing to the original images show that enhanced images are able to slightly reduced the subjective evaluation disagreement in image quality and abnormalities.","PeriodicalId":399080,"journal":{"name":"2016 IEEE International Conference on Automatic Control and Intelligent Systems (I2CACIS)","volume":"85 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":"122631583","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

Vision system for detection of white root disease infection based on capacitance properties 基于电容特性的白根病感染视觉检测系统

2016 IEEE International Conference on Automatic Control and Intelligent Systems (I2CACIS) Pub Date : 2016-10-01 DOI: 10.1109/I2CACIS.2016.7885312

A. F. M. Sampian, H. Hashim, M. Kamal, N. E. Abdullah, Ummu Raihan Yussuf, N. A. Khairuzzaman, A. F. M. Azmi

引用次数: 1