2021 IEEE International Conference on Automatic Control & Intelligent Systems (I2CACIS)最新文献_第6页

Supervised and Unsupervised Machine Learning for Cancer Classification: Recent Development 癌症分类的监督和非监督机器学习:最新进展

2021 IEEE International Conference on Automatic Control & Intelligent Systems (I2CACIS) Pub Date : 2021-06-26 DOI: 10.1109/I2CACIS52118.2021.9495888

Aina Umairah Mazlan, N. A. Sahabudin, Muhammad Akmal bin Remli, N. N. Ismail, M. S. Mohamad, Nor Bakiah Abd Warif

{"title":"Supervised and Unsupervised Machine Learning for Cancer Classification: Recent Development","authors":"Aina Umairah Mazlan, N. A. Sahabudin, Muhammad Akmal bin Remli, N. N. Ismail, M. S. Mohamad, Nor Bakiah Abd Warif","doi":"10.1109/I2CACIS52118.2021.9495888","DOIUrl":"https://doi.org/10.1109/I2CACIS52118.2021.9495888","url":null,"abstract":"This is models with the ability to detect and classify cancer is important in the industrial of healthcare. The most difficult aspect for such model is the classification of cancer, which can be addressed using machine learning methods. The methods are used to improve classification accuracy between system output and test data. The classification process becomes more difficult due to vast data information. This paper presents an overview on current development of cancer classification techniques using machine learning methods, which have received increasing attention within the area of healthcare. This review will mainly focus on the development of machine learning methods for classification of cancer diseases. Recently, there are various researchers proposed different kinds of methods for cancer classification. The results show that the successful of cancer classification is dependent on the machine learning models. Besides, various types of healthcare data used in the experiments would also be discussed in this paper. The development of many optimization methods for cancer classification has brought a lot of improvement in the healthcare field. There is demand for further improvements in optimization methods to develop better machine learning models for cancer classification.","PeriodicalId":210770,"journal":{"name":"2021 IEEE International Conference on Automatic Control & Intelligent Systems (I2CACIS)","volume":"489 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115300630","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

SMS based Curfew Monitoring System for Detecting Minors from a Facial Database to Aid the Local Government Unit Using Image Processing 基于短信的宵禁监控系统，从人脸数据库中检测未成年人，辅助地方政府单位使用图像处理

2021 IEEE International Conference on Automatic Control & Intelligent Systems (I2CACIS) Pub Date : 2021-06-26 DOI: 10.1109/I2CACIS52118.2021.9495921

Jessie R. Balbin, John Maverick Ramos, Joseph Nathaniel Reyes, C. Santiago

引用次数: 0

Real-time Design and Implementation of Nonlinear Speed Controller for Permanent Magnet DC Motor Based on PSO Tuner 基于粒子群调谐器的永磁直流电动机非线性速度控制器的实时设计与实现

2021 IEEE International Conference on Automatic Control & Intelligent Systems (I2CACIS) Pub Date : 2021-06-26 DOI: 10.1109/I2CACIS52118.2021.9495918

A. Mohammed, Ayad Al-dujaili, N. Al-Shamaa

引用次数: 0

Foot Deformity Determination and Health Risk Prediction Through Foot Plantar Analysis Using Pressure Sensor Matrix 基于压力传感器矩阵足底分析的足部畸形诊断与健康风险预测

2021 IEEE International Conference on Automatic Control & Intelligent Systems (I2CACIS) Pub Date : 2021-06-26 DOI: 10.1109/I2CACIS52118.2021.9495907

Jessie R. Balbin, J. D. De Guzman, Joaquin Gerard N. Trinidad, Francis Dominic S. Yaya

引用次数: 1

Data Integration Using Data Mining and SMS Reminder for Automation of Blood Donation 基于数据挖掘和短信提醒的献血自动化数据集成

2021 IEEE International Conference on Automatic Control & Intelligent Systems (I2CACIS) Pub Date : 2021-06-26 DOI: 10.1109/I2CACIS52118.2021.9495915

Guhdar Youcif Izadeen, A. Abdulazeez, D. Zeebaree, D. A. Hasan, F. Y. Ahmed

引用次数: 1

Development of Non-Parametric Model and Speed Tracking Control of Tracked Vehicle Electric Motor 履带车辆电机非参数模型及速度跟踪控制的研究

2021 IEEE International Conference on Automatic Control & Intelligent Systems (I2CACIS) Pub Date : 2021-06-26 DOI: 10.1109/I2CACIS52118.2021.9495866

M. A. Subari, K. Hudha, Z. A. Kadir, S. M. F. Syed Mohd Dardin, N. H. Amer

引用次数: 3

Emergency Vehicle Type Classification using Convolutional Neural Network 基于卷积神经网络的应急车辆类型分类

2021 IEEE International Conference on Automatic Control & Intelligent Systems (I2CACIS) Pub Date : 2021-06-26 DOI: 10.1109/I2CACIS52118.2021.9495899

Muhammad Akmal Hakim bin Che Mansor, Nor Ashikin Mohamad Kamal, Mohamad Hafiz bin Baharom, Muhammad Adib bin Zainol

引用次数: 2

Telecontrol of Prosthetic Robot Hand Using Myo Armband 基于Myo臂环的假肢机械手遥控

2021 IEEE International Conference on Automatic Control & Intelligent Systems (I2CACIS) Pub Date : 2021-06-26 DOI: 10.1109/I2CACIS52118.2021.9495919

Muhammad Yunus bin Yakob, M. Z. Baharuddin, A. R. M. Khairudin, M. H. A. Karim

引用次数: 4

Toward a Novel Design for Mechanical Ventilator System to Support Novel Coronavirus (Covid-19) Infected Patients Using IoT Based Technology 基于物联网技术的新型冠状病毒(Covid-19)感染患者机械呼吸机系统设计

2021 IEEE International Conference on Automatic Control & Intelligent Systems (I2CACIS) Pub Date : 2021-06-26 DOI: 10.1109/I2CACIS52118.2021.9495900

M. N. Mohammed, Halim Syamsudin, M. Abdelgnei, Dharshini Subramaniam, Mohamad Amirul Aznil Mohd Taib, N. Hashim., S. Al-Zubaidi, E. Yusuf

{"title":"Toward a Novel Design for Mechanical Ventilator System to Support Novel Coronavirus (Covid-19) Infected Patients Using IoT Based Technology","authors":"M. N. Mohammed, Halim Syamsudin, M. Abdelgnei, Dharshini Subramaniam, Mohamad Amirul Aznil Mohd Taib, N. Hashim., S. Al-Zubaidi, E. Yusuf","doi":"10.1109/I2CACIS52118.2021.9495900","DOIUrl":"https://doi.org/10.1109/I2CACIS52118.2021.9495900","url":null,"abstract":"Recent pandemic of Covid-19 has diffused and become concern to the world. The disease is contagious and infected many people within short time. The Covid-19 has infected more than 100 million of reported cases according to the WHO with more than 2 million deaths. Many symptoms found in infectee of Covid-19 such as fever, dry cough, etc. One of the symptoms, shortness of breath, is found in 18.6% of infectee. Part of people infected by COVID-19 suffered from acute difficulty in breathing which need a help from ventilator for breathing. The ventilator plays important role in saving the Covid-19 patients. Ventilator can aid the patient to breath easily and supporting the lungs by letting in the sufficient air while encountering the hard breathing. In developed area, the ventilator is limited while the demand during pandemic gets increased. This paper proposes a low-cost prototype of ventilator for Covid-19 patient which integrated with IoT. The technology supports the clinicians to monitor the patient condition by letting the ventilator and the phone or tablet to be connected and exchange information.","PeriodicalId":210770,"journal":{"name":"2021 IEEE International Conference on Automatic Control & Intelligent Systems (I2CACIS)","volume":"35 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128909730","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

Variance Component Estimation Dilemma in Cadastral Network Adjustment 地籍网平差中的方差分量估计困境

2021 IEEE International Conference on Automatic Control & Intelligent Systems (I2CACIS) Pub Date : 2021-06-26 DOI: 10.1109/I2CACIS52118.2021.9495848

M. A. Abbas, N. M. Hashim, Akram Zulkifli, S. Sulaiman, M. A. Mustafar, Tengku Afrizal Tengku Ali

{"title":"Variance Component Estimation Dilemma in Cadastral Network Adjustment","authors":"M. A. Abbas, N. M. Hashim, Akram Zulkifli, S. Sulaiman, M. A. Mustafar, Tengku Afrizal Tengku Ali","doi":"10.1109/I2CACIS52118.2021.9495848","DOIUrl":"https://doi.org/10.1109/I2CACIS52118.2021.9495848","url":null,"abstract":"Land record that preserve the positional accuracy is an absolute objective in cadastral implementation. To achieve that, Department of Surveying and Mapping Malaysia (DSMM) has taken drastic decision by transforming the adjustment procedure from traditional approach (i.e. Bowditch) to the most rigorous procedure (i.e. least square adjustment). However, homogenous precisions as stated in DSMM circular are not align with fundamental principle of least square adjustment (LSA). In LSA implementation, there is a knowledge known as stochastic modeling used to derive the realistic variance. With determination to verify the significance of the realistic variance, this study has designed two assessments which focus on positional errors and sensitivity towards outliers. The artificial errors have been introduced in cadastral dataset, both homogenous and realistic variance were exploited in LSA computation. Through positional accuracy examination, minor advantage has been demonstrated by the outcomes of realistic variance. The conclusion can be made when homogenous variances manage to passed the global test but failed to identify the outliers (artificial errors) in the dataset. To preserve the positional accuracy of land record, realistic variance is a crucial requirement in cadastral network adjustment.","PeriodicalId":210770,"journal":{"name":"2021 IEEE International Conference on Automatic Control & Intelligent Systems (I2CACIS)","volume":"32 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115617915","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