Pub Date : 2021-06-26DOI: 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
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.
{"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}
Pub Date : 2021-06-26DOI: 10.1109/I2CACIS52118.2021.9495921
Jessie R. Balbin, John Maverick Ramos, Joseph Nathaniel Reyes, C. Santiago
The Manila City Government just recently implemented a city ordinance of strict implantation of curfew for minors. Upon conducting interviews, the researchers found out that the system of implementation of curfew uses manpower and barangay patrol roaming around the barangay. This study aims to develop a curfew monitoring system using Image Processing with notifying features via SMS. LBPH (or Local Binary Pattern Histogram) algorithm is implemented in the study. The system was successful in recognizing faces that are registered to the system. The challenge that the researchers encountered was the range of facial recognition is limited. People that are far away cannot be recognized by the system. Also, that the face should be facing the camera. Having any angle with the camera will make the % confidence of the recognition lower. The system has great recognition with the face facing directly at the camera with 15 degrees tolerance.
{"title":"SMS based Curfew Monitoring System for Detecting Minors from a Facial Database to Aid the Local Government Unit Using Image Processing","authors":"Jessie R. Balbin, John Maverick Ramos, Joseph Nathaniel Reyes, C. Santiago","doi":"10.1109/I2CACIS52118.2021.9495921","DOIUrl":"https://doi.org/10.1109/I2CACIS52118.2021.9495921","url":null,"abstract":"The Manila City Government just recently implemented a city ordinance of strict implantation of curfew for minors. Upon conducting interviews, the researchers found out that the system of implementation of curfew uses manpower and barangay patrol roaming around the barangay. This study aims to develop a curfew monitoring system using Image Processing with notifying features via SMS. LBPH (or Local Binary Pattern Histogram) algorithm is implemented in the study. The system was successful in recognizing faces that are registered to the system. The challenge that the researchers encountered was the range of facial recognition is limited. People that are far away cannot be recognized by the system. Also, that the face should be facing the camera. Having any angle with the camera will make the % confidence of the recognition lower. The system has great recognition with the face facing directly at the camera with 15 degrees tolerance.","PeriodicalId":210770,"journal":{"name":"2021 IEEE International Conference on Automatic Control & Intelligent Systems (I2CACIS)","volume":"332 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":"115227486","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}
Pub Date : 2021-06-26DOI: 10.1109/I2CACIS52118.2021.9495918
A. Mohammed, Ayad Al-dujaili, N. Al-Shamaa
Speed control of PMDC motors finds applications in various industries. For certain structures, the controller of Proportional, Integral and Derivative (PID) is typically the first choice because of its ease of execution and fast tuning. So, all conventional techniques and optimization stochastic for PID controller tuning provide preliminary feasible parameters for, , and . This paper uses traditional PID and nonlinear PID to control the speed of the PMDC motor, which is tuned by Particle Swarm Optimization (PSO). The methodology is demonstrated by performing simulations using the MATLAB tool. The simulation results exhibit that the role of the nonlinear PID based scheme is more robust than the traditional PID controller, as well as the speed, tracked the desired reference rabidly.
{"title":"Real-time Design and Implementation of Nonlinear Speed Controller for Permanent Magnet DC Motor Based on PSO Tuner","authors":"A. Mohammed, Ayad Al-dujaili, N. Al-Shamaa","doi":"10.1109/I2CACIS52118.2021.9495918","DOIUrl":"https://doi.org/10.1109/I2CACIS52118.2021.9495918","url":null,"abstract":"Speed control of PMDC motors finds applications in various industries. For certain structures, the controller of Proportional, Integral and Derivative (PID) is typically the first choice because of its ease of execution and fast tuning. So, all conventional techniques and optimization stochastic for PID controller tuning provide preliminary feasible parameters for, , and . This paper uses traditional PID and nonlinear PID to control the speed of the PMDC motor, which is tuned by Particle Swarm Optimization (PSO). The methodology is demonstrated by performing simulations using the MATLAB tool. The simulation results exhibit that the role of the nonlinear PID based scheme is more robust than the traditional PID controller, as well as the speed, tracked the desired reference rabidly.","PeriodicalId":210770,"journal":{"name":"2021 IEEE International Conference on Automatic Control & Intelligent Systems (I2CACIS)","volume":"22 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":"126306775","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}
Pub Date : 2021-06-26DOI: 10.1109/I2CACIS52118.2021.9495907
Jessie R. Balbin, J. D. De Guzman, Joaquin Gerard N. Trinidad, Francis Dominic S. Yaya
One of the most overlooked parts of the body is the feet. Foot health can generally affect the overall health of a person if not treated well. This study utilized Support Vector Machines and an artificial neural network to determine the foot deformity of a person by using a foot plantar pressure sensor matrix called Velostat. The researchers used raspberry pi to run the GUI programmed using Python. The developed device will determine if the feet are normal, high arched, or low arched. The testing was done on 40 respondents and resulted in 95% accuracy in determining foot deformity.
{"title":"Foot Deformity Determination and Health Risk Prediction Through Foot Plantar Analysis Using Pressure Sensor Matrix","authors":"Jessie R. Balbin, J. D. De Guzman, Joaquin Gerard N. Trinidad, Francis Dominic S. Yaya","doi":"10.1109/I2CACIS52118.2021.9495907","DOIUrl":"https://doi.org/10.1109/I2CACIS52118.2021.9495907","url":null,"abstract":"One of the most overlooked parts of the body is the feet. Foot health can generally affect the overall health of a person if not treated well. This study utilized Support Vector Machines and an artificial neural network to determine the foot deformity of a person by using a foot plantar pressure sensor matrix called Velostat. The researchers used raspberry pi to run the GUI programmed using Python. The developed device will determine if the feet are normal, high arched, or low arched. The testing was done on 40 respondents and resulted in 95% accuracy in determining foot deformity.","PeriodicalId":210770,"journal":{"name":"2021 IEEE International Conference on Automatic Control & Intelligent Systems (I2CACIS)","volume":"53 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":"125704824","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}
Pub Date : 2021-06-26DOI: 10.1109/I2CACIS52118.2021.9495915
Guhdar Youcif Izadeen, A. Abdulazeez, D. Zeebaree, D. A. Hasan, F. Y. Ahmed
Blood is one of the most vital and essential elements in human existence. When the population increases, so do the request for blood. People who need blood in an emergency are unable to provide it promptly. This paper suggests an effective method of contacting donors, that can be useful in an emergency. When a person requires blood, they request it through a website or mobile device; the request is then routed to the person who meets the matching blood type. the application is then sent an SMS to the donor to approve it, after accepting the request, the application will inform the requestor about it and he/she will get the donor phone number by using an MCU ESP8266 and a SIM800L. The privacy of the person must be protected in the current environment. The donor will be deleted from the reception of notification for the next three months after the blood donation is done. User name, password, and phone number are used to check registered accounts.
{"title":"Data Integration Using Data Mining and SMS Reminder for Automation of Blood Donation","authors":"Guhdar Youcif Izadeen, A. Abdulazeez, D. Zeebaree, D. A. Hasan, F. Y. Ahmed","doi":"10.1109/I2CACIS52118.2021.9495915","DOIUrl":"https://doi.org/10.1109/I2CACIS52118.2021.9495915","url":null,"abstract":"Blood is one of the most vital and essential elements in human existence. When the population increases, so do the request for blood. People who need blood in an emergency are unable to provide it promptly. This paper suggests an effective method of contacting donors, that can be useful in an emergency. When a person requires blood, they request it through a website or mobile device; the request is then routed to the person who meets the matching blood type. the application is then sent an SMS to the donor to approve it, after accepting the request, the application will inform the requestor about it and he/she will get the donor phone number by using an MCU ESP8266 and a SIM800L. The privacy of the person must be protected in the current environment. The donor will be deleted from the reception of notification for the next three months after the blood donation is done. User name, password, and phone number are used to check registered accounts.","PeriodicalId":210770,"journal":{"name":"2021 IEEE International Conference on Automatic Control & Intelligent Systems (I2CACIS)","volume":"20 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":"128998083","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}
Pub Date : 2021-06-26DOI: 10.1109/I2CACIS52118.2021.9495866
M. A. Subari, K. Hudha, Z. A. Kadir, S. M. F. Syed Mohd Dardin, N. H. Amer
In propelling the tracked vehicle, each track is fitted with an electric motor which will regulate torque to the tracks. In this study, the development of electric motor model and motor speed tracking control will be described. To do this, a non-parametric model was chosen by generalizing the experiment data from system input-output properties. However, characterization of tracked vehicle electric motor need to be done before creating the non-parametric model. The final model developed using non-parametric model are then used to study the speed tracking control of tracked vehicle electric motor through simulation and experiment. The tracked vehicle electric motor was tested in two different inputs, which are step input and sine input. The resulted show that the maximum percentage of overshoot recorded for both cases are less than 15%.
{"title":"Development of Non-Parametric Model and Speed Tracking Control of Tracked Vehicle Electric Motor","authors":"M. A. Subari, K. Hudha, Z. A. Kadir, S. M. F. Syed Mohd Dardin, N. H. Amer","doi":"10.1109/I2CACIS52118.2021.9495866","DOIUrl":"https://doi.org/10.1109/I2CACIS52118.2021.9495866","url":null,"abstract":"In propelling the tracked vehicle, each track is fitted with an electric motor which will regulate torque to the tracks. In this study, the development of electric motor model and motor speed tracking control will be described. To do this, a non-parametric model was chosen by generalizing the experiment data from system input-output properties. However, characterization of tracked vehicle electric motor need to be done before creating the non-parametric model. The final model developed using non-parametric model are then used to study the speed tracking control of tracked vehicle electric motor through simulation and experiment. The tracked vehicle electric motor was tested in two different inputs, which are step input and sine input. The resulted show that the maximum percentage of overshoot recorded for both cases are less than 15%.","PeriodicalId":210770,"journal":{"name":"2021 IEEE International Conference on Automatic Control & Intelligent Systems (I2CACIS)","volume":"1 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":"130411975","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}
Pub Date : 2021-06-26DOI: 10.1109/I2CACIS52118.2021.9495899
Muhammad Akmal Hakim bin Che Mansor, Nor Ashikin Mohamad Kamal, Mohamad Hafiz bin Baharom, Muhammad Adib bin Zainol
This paper discusses the Convolutional Neural Network (CNN) applied in emergency vehicle image classification. Emergency vehicles are often found stuck in traffic congestion. It has resulted in the emergency vehicles unable to get to the scene quickly. Detecting emergency vehicles on the road can help provide a route to enable emergency vehicles to arrive more efficiently. Several methods have been used to detect the presence of these emergency vehicles on the road. Convolutional Neural Network is one of the popular classification methods nowadays. This work used VGG-16 as the pre-trained model with reduced convolutional layer and filter size. Based on the experiment, the proposed method gained an accuracy of 95%. Thus, the system has achieved the objective.
{"title":"Emergency Vehicle Type Classification using Convolutional Neural Network","authors":"Muhammad Akmal Hakim bin Che Mansor, Nor Ashikin Mohamad Kamal, Mohamad Hafiz bin Baharom, Muhammad Adib bin Zainol","doi":"10.1109/I2CACIS52118.2021.9495899","DOIUrl":"https://doi.org/10.1109/I2CACIS52118.2021.9495899","url":null,"abstract":"This paper discusses the Convolutional Neural Network (CNN) applied in emergency vehicle image classification. Emergency vehicles are often found stuck in traffic congestion. It has resulted in the emergency vehicles unable to get to the scene quickly. Detecting emergency vehicles on the road can help provide a route to enable emergency vehicles to arrive more efficiently. Several methods have been used to detect the presence of these emergency vehicles on the road. Convolutional Neural Network is one of the popular classification methods nowadays. This work used VGG-16 as the pre-trained model with reduced convolutional layer and filter size. Based on the experiment, the proposed method gained an accuracy of 95%. Thus, the system has achieved the objective.","PeriodicalId":210770,"journal":{"name":"2021 IEEE International Conference on Automatic Control & Intelligent Systems (I2CACIS)","volume":"12 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":"131054921","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}
Pub Date : 2021-06-26DOI: 10.1109/I2CACIS52118.2021.9495919
Muhammad Yunus bin Yakob, M. Z. Baharuddin, A. R. M. Khairudin, M. H. A. Karim
Bionic prosthetic hands are widely utilised to support people who have upper limb amputations and incapability by making it movable and controllable. However, the price of bionic prosthetic arms in the current market is quite expensive, hence limiting people from owning it. Nevertheless, Myo Armband appears to provide fine hand movement and sensitive to input, making it a suitable alternative to gesture-based wireless control. Hence, in this project, it will be used to read and control signals for the 3d printed robotic prosthetic arm. The control of prosthetic robot arm is achieved by sensing the gestures of amputees’ upper limb. Bluetooth is used for the wireless communication between Myo armband and the computer, while communication between computer and the prosthetic robot arm used serial communication. It is observed that fist gestures from Myo armband controlling the prosthetic robot hand have been successfully achieved. The proposed configuration can be used in human-robot interaction and telecontrol studies.
{"title":"Telecontrol of Prosthetic Robot Hand Using Myo Armband","authors":"Muhammad Yunus bin Yakob, M. Z. Baharuddin, A. R. M. Khairudin, M. H. A. Karim","doi":"10.1109/I2CACIS52118.2021.9495919","DOIUrl":"https://doi.org/10.1109/I2CACIS52118.2021.9495919","url":null,"abstract":"Bionic prosthetic hands are widely utilised to support people who have upper limb amputations and incapability by making it movable and controllable. However, the price of bionic prosthetic arms in the current market is quite expensive, hence limiting people from owning it. Nevertheless, Myo Armband appears to provide fine hand movement and sensitive to input, making it a suitable alternative to gesture-based wireless control. Hence, in this project, it will be used to read and control signals for the 3d printed robotic prosthetic arm. The control of prosthetic robot arm is achieved by sensing the gestures of amputees’ upper limb. Bluetooth is used for the wireless communication between Myo armband and the computer, while communication between computer and the prosthetic robot arm used serial communication. It is observed that fist gestures from Myo armband controlling the prosthetic robot hand have been successfully achieved. The proposed configuration can be used in human-robot interaction and telecontrol studies.","PeriodicalId":210770,"journal":{"name":"2021 IEEE International Conference on Automatic Control & Intelligent Systems (I2CACIS)","volume":"5 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":"129104343","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}
Pub Date : 2021-06-26DOI: 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
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.
{"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}
Pub Date : 2021-06-26DOI: 10.1109/I2CACIS52118.2021.9495848
M. A. Abbas, N. M. Hashim, Akram Zulkifli, S. Sulaiman, M. A. Mustafar, Tengku Afrizal Tengku Ali
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.
{"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}
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