IAES International Journal of Artificial Intelligence (IJ-AI)
The oxygen content of the gas-fired boiler flue gas is used to monitor boiler combustion efficien... more The oxygen content of the gas-fired boiler flue gas is used to monitor boiler combustion efficiency. Conventionally, this oxygen content is measured using an oxygen content sensor. However, because it operates in extreme conditions, this oxygen sensor tends to have the disadvantage of high maintenance costs. In addition, the absence of other sensors as an element of redundancy and when there is damage to the sensor causes manual handling by workers. It is dangerous for these workers, considering environmental conditions with high-risk hazards. We propose an artificial neural network (ANN) and random forest-based soft sensor to predict the oxygen content to overcome the problems. The prediction is made by utilizing measured data on the power plant’s boiler, consisting of 19 process variables from a distributed control system. The research has proved that the proposed soft sensor successfully predicts the oxygen content. Research using random forest shows better performance results th...
Controller performance is a crucial aspect of industrial processes; hence, it is critical to main... more Controller performance is a crucial aspect of industrial processes; hence, it is critical to maintaining optimal controller performance conditions. Bad controller performance can be caused by poor proportional integral derivative (PID) controller tuning those results in aggressive and sluggish controllers' behavior. Correct diagnosis of poor controller tuning becomes vital so that it can adequately handle the controller. This study designs several function blocks for online diagnosis of poor PID controller tuning based on the IEC 61499 standard. The design of the function blocks began with design the method used for diagnosing a poor controller tuning. The procedure was based on autocorrelation function (ACF), comparison of signal to noise ratio (SNR) estimation, and idle index. The function blocks were validated with first order plus delay time (FOPDT) processes, which had aggressive, sluggish, or well-tuned behavior. The function blocks were implemented on a Fluid Catalytic Cracking (FCC) plant and industrial data with various process faults to evaluate its capability to diagnose a poor controller tuning. The developed function block can precisely analyze a poor controller tuning on FCC plant and 8 of 10 industrial data. It showed that the function blocks could diagnose a poor controller tuning correctly if the oscillation were regular.
Marine electromagnetic (EM) survey is an engineering endeavor to determine the location and dimen... more Marine electromagnetic (EM) survey is an engineering endeavor to determine the location and dimension of hydrocarbon reservoirs which are particularly situated under the sea floor. Forward modeling is one of the important step in processing the data of a marine EM survey. By this modeling, the distribution of resistivity values along the sea bed could be mapped and the location and dimension of the associated hydrocarbon layer could be predicted. As an alternative to the established methods in conducting forward modeling, in this research two types of artificial neural networks are employed to determine the possibil�ities of them as forward models for marine EM survey. The networks are a multi-layer perceptron (MLP) network and a radial basis function (RBF) network. The motivation of this work is to find out the possibilities of these networks as forward models for marine EM survey. To achieve the research goals, a set of synthetic data must be generated using a simulation software. These data are used to train and test the MLP and RBF networks until they attained a sufficient property of generalization in modeling marine EM survey data. To validate the correctness of the models, a reverse method of forward modeling has been employed, which is the inversion process. Occam's inversion has been specifically used to validate the neural networks' for�ward modeling. It is found that artificial neural networks, specifically MLP and RBF networks, have a possibility to become forward models for marine electromagnetic sur�vey. In addition, this research found that the forward modeling by RBF network is better than the corresponding one by MLP network
The change in the concept of an automation pyramid into an automation cloud in a cyber-physical p... more The change in the concept of an automation pyramid into an automation cloud in a cyber-physical production system makes data communication no longer stratified but can be done directly between devices. Based on IEC 61499, which defines the function blocks for building such communications, communication protocols can be run on various devices. Several communication protocols that can fulfill these requirements are OPC-UA, FBDK / IP, and MQTT. The research was conducted by comparing the three communication protocols for latency parameters and their jitters. The test method used to compare latency parameters is the variance analysis test and the Tukey test. The jitter value of the protocols are compared to the standard deviation parameter. The test results showed that the MQTT communication protocol had a faster latency value, with a 95% confidence level. The standard deviation of the variation value for OPC-UA, FBDK / IP, and MQTT showed the jitter value of 0.72 seconds, 0.35 seconds, and 0.64 seconds. Comparing the three communication protocols' standard deviation values showed that the FBDK / IP communication protocol has significantly less jitter than the OPC-UA and MQTT communication protocols.
Preparation of human resources (HR) is important for the construction and operation of the nuclea... more Preparation of human resources (HR) is important for the construction and operation of the nuclear power plant (NPP) since the project preparation phase. Preparation is carried out through education and training related to nuclear reactors. The use of nuclear reactors as learning laboratories is needed to support these activities. This research aims to design an internet reactor laboratory (IRL) application that can be operated on android devices. The application developed using LabVIEW data dashboard software with data source from the IRL database. The application is evaluated to determine application compatibility with various screen sizes of Android devices, delay time, data accuracy level, and satisfaction assessment of IRL application users. The IRL program design results consist of IRL host computer programs as a data center, and the IRL application. The test results show that the IRL application can be run on all aspect ratios with a minimum screen resolution of 640 x 360 pix...
2016 6th International Annual Engineering Seminar (InAES), 2016
Information about counts and percentages of each type of leukocytes in blood is much needed to di... more Information about counts and percentages of each type of leukocytes in blood is much needed to diagnose patients' illness. To gain that information, some functional enhancements had been applied to the optical microscopes so that they could produce digital images. Output images from these engineered microscopes were then extracted to get feature values from each image. These feature values then became input sets to the method of K-Means Clustering so that the leukocyte images could be classified according to each own cluster. Generally, the leukocyte classification process is conducted through four phases, which are image pre-processing, leukocyte segmentation, feature extraction, and leukocyte classification. Leukocyte types which were classified in this research were neutrophil, lymphocyte, monocyte, and eosinophil. Experiments were conducted using five kinds of features, which are normalized area, circularity, eccentricity, normalized parameter, and solidity, and by varying their types and their significant influences. The purpose of these trials were to determine which feature types would result in the highest value of accuracy and the effects of adding these respective features to the resulted accuracy. Based on the conducted classification results, it was found that the highest accuracy value was reached by circularity feature, which was 67%, meanwhile the lowest accuracy value was produced by the eccentricity feature, which was 43%. In this research, it was concluded that the accuracy value is ultimately determined by selecting the correct feature type rather than adding more features.
TELKOMNIKA (Telecommunication Computing Electronics and Control), 2008
A robot simulator has been developed, that capable in simulating a 6 degree of freedom robot mani... more A robot simulator has been developed, that capable in simulating a 6 degree of freedom robot manipulator. Using this simulator, a user can define the type and angular range of the joints, and length of each link, as well as the colors. User can also select an arbitrary viewing angle and move the robot manually or automatically. The simulator was developed using C++ programming language utilizing OpenGL graphic library. Denavit-Hartenberg notation was used as parameters to specify the shape and size of the manipulator.
2010 International Conference on Intelligent and Advanced Systems, 2010
... Agus Arif Dept. ... I. INTRODUCTION Seabed logging (SBL) is a geophysical endeavor to determi... more ... Agus Arif Dept. ... I. INTRODUCTION Seabed logging (SBL) is a geophysical endeavor to determine the location of a hydrocarbon layer inside the seabed by using various techniques, such as seismic sounding, wellborehole logging, and controlled electromagnetic source. ...
Proceedings of the 2011 International Conference on Electrical Engineering and Informatics, 2011
A marine electromagnetic survey is an engineering endeavour to discover the location and dimensio... more A marine electromagnetic survey is an engineering endeavour to discover the location and dimension of a hydrocarbon layer under an ocean floor. In this kind of survey, an array of electric and magnetic receivers are located on the sea floor and record the scattered, refracted and reflected electromagnetic wave, which has been transmitted by an electric dipole antenna towed by a vessel. The data recorded in receivers must be processed and further analysed to estimate the hydrocarbon location and dimension. To conduct those analyses successfully, a radial basis function (RBF) network could be employed to become a forward model of the input-output relationship of the data from a marine electromagnetic survey. This type of neural networks is working based on distances between its inputs and predetermined centres of some basis functions. A previous research had been conducted to model the same marine electromagnetic survey using another type of neural networks, which is a multi layer perceptron (MLP) network. Based on comparing their validation and training performances (mean-squared errors and correlation coefficients), the MLP network is comparatively better than the RBF network.
Forward modeling is an important step in processing data of seabed logging (SBL) with controlled ... more Forward modeling is an important step in processing data of seabed logging (SBL) with controlled source electromagnetic (CSEM) method to determine the location and dimension of a hydrocarbon layer under the seafloor. In this research, forward modeling was conducted using a radial basis function (RBF) network, which is an important type of artificial neural networks. To train this RBF network,
2009 IEEE Student Conference on Research and Development (SCOReD), 2009
... I. INTRODUCTION Seabed logging (SBL) is a geophysical endeavour to deterY mine the location o... more ... I. INTRODUCTION Seabed logging (SBL) is a geophysical endeavour to deterY mine the location of a hydrocarbon layer inside the seabed by using various techniques, such as seismic sounding, wellY borehole logging, and controlled ... [3] A. Arif, IGeophysical Inversion Using ...
ITB Journal of Information and Communication Technology, 2011
A marine electromagnetic survey is an engineering endeavour to discover the location and dimensio... more A marine electromagnetic survey is an engineering endeavour to discover the location and dimension of a hydrocarbon layer under an ocean floor. In this kind of survey, an array of electric and magnetic receivers are located on the sea floor and record the scattered, refracted and reflected electromagnetic wave, which has been transmitted by an electric dipole antenna towed by a vessel. The data recorded in receivers must be processed and further analysed to estimate the hydrocarbon location and dimension. To conduct those analyses successfuly, a radial basis function (RBF) network could be employed to become a forward model of the input-output relationship of the data from a marine electromagnetic survey. This type of neural networks is working based on distances between its inputs and predetermined centres of some basis functions. A previous research had been conducted to model the same marine electromagnetic survey using another type of neural networks, which is a multi layer perceptron (MLP) network. By comparing their validation and training performances (mean-squared errors and correlation coefficients), it is concluded that, in this case, the MLP network is comparatively better than the RBF network 1 .
2016 1st International Conference on Biomedical Engineering (IBIOMED), 2016
Haar Cascade Classifier is a method for detection of objects within an image, which is widely app... more Haar Cascade Classifier is a method for detection of objects within an image, which is widely applied on face detection. This paper discusses the utilization of Haar Cascade Classifier in locating the positions of white blood cells in an image. The results showed that this method is able to localize white blood cells with precision and recall values of 95% and 74% respectively. This method is also able to distinguish white blood cells from other objects that have color resembling white blood cells.
IOP Conference Series: Earth and Environmental Science
Fuel loading pattern optimization is a complex problem because there are so many possibilities fo... more Fuel loading pattern optimization is a complex problem because there are so many possibilities for combinatorial solutions, and it will take time to try it one by one. Therefore, the Polar Bear Optimization Algorithm was applied to find an optimum PWR loading pattern based on BEAVRS. The desired new fuel loading pattern is the one that has the minimum Power Peaking Factor (PPF) value without compromising the operating time. Operating time is proportional to the multiplication factor (k eff ). These parameters are usually contradictive with each other and will make it hard to find the optimum solution. The reactor was modelled with the Standard Reactor Analysis Code (SRAC) 2006. Fuel pins and fuel assemblies are modelled with the PIJ module for cell calculations. One-fourth symmetry was used with the CITATION X-Y module for core calculations. The optimization was done with 200 populations and 50 iterations. The PPF value for the selected solution should never exceed 2.0 in every burn...
IAES International Journal of Artificial Intelligence (IJ-AI)
The oxygen content of the gas-fired boiler flue gas is used to monitor boiler combustion efficien... more The oxygen content of the gas-fired boiler flue gas is used to monitor boiler combustion efficiency. Conventionally, this oxygen content is measured using an oxygen content sensor. However, because it operates in extreme conditions, this oxygen sensor tends to have the disadvantage of high maintenance costs. In addition, the absence of other sensors as an element of redundancy and when there is damage to the sensor causes manual handling by workers. It is dangerous for these workers, considering environmental conditions with high-risk hazards. We propose an artificial neural network (ANN) and random forest-based soft sensor to predict the oxygen content to overcome the problems. The prediction is made by utilizing measured data on the power plant’s boiler, consisting of 19 process variables from a distributed control system. The research has proved that the proposed soft sensor successfully predicts the oxygen content. Research using random forest shows better performance results th...
Controller performance is a crucial aspect of industrial processes; hence, it is critical to main... more Controller performance is a crucial aspect of industrial processes; hence, it is critical to maintaining optimal controller performance conditions. Bad controller performance can be caused by poor proportional integral derivative (PID) controller tuning those results in aggressive and sluggish controllers' behavior. Correct diagnosis of poor controller tuning becomes vital so that it can adequately handle the controller. This study designs several function blocks for online diagnosis of poor PID controller tuning based on the IEC 61499 standard. The design of the function blocks began with design the method used for diagnosing a poor controller tuning. The procedure was based on autocorrelation function (ACF), comparison of signal to noise ratio (SNR) estimation, and idle index. The function blocks were validated with first order plus delay time (FOPDT) processes, which had aggressive, sluggish, or well-tuned behavior. The function blocks were implemented on a Fluid Catalytic Cracking (FCC) plant and industrial data with various process faults to evaluate its capability to diagnose a poor controller tuning. The developed function block can precisely analyze a poor controller tuning on FCC plant and 8 of 10 industrial data. It showed that the function blocks could diagnose a poor controller tuning correctly if the oscillation were regular.
Marine electromagnetic (EM) survey is an engineering endeavor to determine the location and dimen... more Marine electromagnetic (EM) survey is an engineering endeavor to determine the location and dimension of hydrocarbon reservoirs which are particularly situated under the sea floor. Forward modeling is one of the important step in processing the data of a marine EM survey. By this modeling, the distribution of resistivity values along the sea bed could be mapped and the location and dimension of the associated hydrocarbon layer could be predicted. As an alternative to the established methods in conducting forward modeling, in this research two types of artificial neural networks are employed to determine the possibil�ities of them as forward models for marine EM survey. The networks are a multi-layer perceptron (MLP) network and a radial basis function (RBF) network. The motivation of this work is to find out the possibilities of these networks as forward models for marine EM survey. To achieve the research goals, a set of synthetic data must be generated using a simulation software. These data are used to train and test the MLP and RBF networks until they attained a sufficient property of generalization in modeling marine EM survey data. To validate the correctness of the models, a reverse method of forward modeling has been employed, which is the inversion process. Occam's inversion has been specifically used to validate the neural networks' for�ward modeling. It is found that artificial neural networks, specifically MLP and RBF networks, have a possibility to become forward models for marine electromagnetic sur�vey. In addition, this research found that the forward modeling by RBF network is better than the corresponding one by MLP network
The change in the concept of an automation pyramid into an automation cloud in a cyber-physical p... more The change in the concept of an automation pyramid into an automation cloud in a cyber-physical production system makes data communication no longer stratified but can be done directly between devices. Based on IEC 61499, which defines the function blocks for building such communications, communication protocols can be run on various devices. Several communication protocols that can fulfill these requirements are OPC-UA, FBDK / IP, and MQTT. The research was conducted by comparing the three communication protocols for latency parameters and their jitters. The test method used to compare latency parameters is the variance analysis test and the Tukey test. The jitter value of the protocols are compared to the standard deviation parameter. The test results showed that the MQTT communication protocol had a faster latency value, with a 95% confidence level. The standard deviation of the variation value for OPC-UA, FBDK / IP, and MQTT showed the jitter value of 0.72 seconds, 0.35 seconds, and 0.64 seconds. Comparing the three communication protocols' standard deviation values showed that the FBDK / IP communication protocol has significantly less jitter than the OPC-UA and MQTT communication protocols.
Preparation of human resources (HR) is important for the construction and operation of the nuclea... more Preparation of human resources (HR) is important for the construction and operation of the nuclear power plant (NPP) since the project preparation phase. Preparation is carried out through education and training related to nuclear reactors. The use of nuclear reactors as learning laboratories is needed to support these activities. This research aims to design an internet reactor laboratory (IRL) application that can be operated on android devices. The application developed using LabVIEW data dashboard software with data source from the IRL database. The application is evaluated to determine application compatibility with various screen sizes of Android devices, delay time, data accuracy level, and satisfaction assessment of IRL application users. The IRL program design results consist of IRL host computer programs as a data center, and the IRL application. The test results show that the IRL application can be run on all aspect ratios with a minimum screen resolution of 640 x 360 pix...
2016 6th International Annual Engineering Seminar (InAES), 2016
Information about counts and percentages of each type of leukocytes in blood is much needed to di... more Information about counts and percentages of each type of leukocytes in blood is much needed to diagnose patients' illness. To gain that information, some functional enhancements had been applied to the optical microscopes so that they could produce digital images. Output images from these engineered microscopes were then extracted to get feature values from each image. These feature values then became input sets to the method of K-Means Clustering so that the leukocyte images could be classified according to each own cluster. Generally, the leukocyte classification process is conducted through four phases, which are image pre-processing, leukocyte segmentation, feature extraction, and leukocyte classification. Leukocyte types which were classified in this research were neutrophil, lymphocyte, monocyte, and eosinophil. Experiments were conducted using five kinds of features, which are normalized area, circularity, eccentricity, normalized parameter, and solidity, and by varying their types and their significant influences. The purpose of these trials were to determine which feature types would result in the highest value of accuracy and the effects of adding these respective features to the resulted accuracy. Based on the conducted classification results, it was found that the highest accuracy value was reached by circularity feature, which was 67%, meanwhile the lowest accuracy value was produced by the eccentricity feature, which was 43%. In this research, it was concluded that the accuracy value is ultimately determined by selecting the correct feature type rather than adding more features.
TELKOMNIKA (Telecommunication Computing Electronics and Control), 2008
A robot simulator has been developed, that capable in simulating a 6 degree of freedom robot mani... more A robot simulator has been developed, that capable in simulating a 6 degree of freedom robot manipulator. Using this simulator, a user can define the type and angular range of the joints, and length of each link, as well as the colors. User can also select an arbitrary viewing angle and move the robot manually or automatically. The simulator was developed using C++ programming language utilizing OpenGL graphic library. Denavit-Hartenberg notation was used as parameters to specify the shape and size of the manipulator.
2010 International Conference on Intelligent and Advanced Systems, 2010
... Agus Arif Dept. ... I. INTRODUCTION Seabed logging (SBL) is a geophysical endeavor to determi... more ... Agus Arif Dept. ... I. INTRODUCTION Seabed logging (SBL) is a geophysical endeavor to determine the location of a hydrocarbon layer inside the seabed by using various techniques, such as seismic sounding, wellborehole logging, and controlled electromagnetic source. ...
Proceedings of the 2011 International Conference on Electrical Engineering and Informatics, 2011
A marine electromagnetic survey is an engineering endeavour to discover the location and dimensio... more A marine electromagnetic survey is an engineering endeavour to discover the location and dimension of a hydrocarbon layer under an ocean floor. In this kind of survey, an array of electric and magnetic receivers are located on the sea floor and record the scattered, refracted and reflected electromagnetic wave, which has been transmitted by an electric dipole antenna towed by a vessel. The data recorded in receivers must be processed and further analysed to estimate the hydrocarbon location and dimension. To conduct those analyses successfully, a radial basis function (RBF) network could be employed to become a forward model of the input-output relationship of the data from a marine electromagnetic survey. This type of neural networks is working based on distances between its inputs and predetermined centres of some basis functions. A previous research had been conducted to model the same marine electromagnetic survey using another type of neural networks, which is a multi layer perceptron (MLP) network. Based on comparing their validation and training performances (mean-squared errors and correlation coefficients), the MLP network is comparatively better than the RBF network.
Forward modeling is an important step in processing data of seabed logging (SBL) with controlled ... more Forward modeling is an important step in processing data of seabed logging (SBL) with controlled source electromagnetic (CSEM) method to determine the location and dimension of a hydrocarbon layer under the seafloor. In this research, forward modeling was conducted using a radial basis function (RBF) network, which is an important type of artificial neural networks. To train this RBF network,
2009 IEEE Student Conference on Research and Development (SCOReD), 2009
... I. INTRODUCTION Seabed logging (SBL) is a geophysical endeavour to deterY mine the location o... more ... I. INTRODUCTION Seabed logging (SBL) is a geophysical endeavour to deterY mine the location of a hydrocarbon layer inside the seabed by using various techniques, such as seismic sounding, wellY borehole logging, and controlled ... [3] A. Arif, IGeophysical Inversion Using ...
ITB Journal of Information and Communication Technology, 2011
A marine electromagnetic survey is an engineering endeavour to discover the location and dimensio... more A marine electromagnetic survey is an engineering endeavour to discover the location and dimension of a hydrocarbon layer under an ocean floor. In this kind of survey, an array of electric and magnetic receivers are located on the sea floor and record the scattered, refracted and reflected electromagnetic wave, which has been transmitted by an electric dipole antenna towed by a vessel. The data recorded in receivers must be processed and further analysed to estimate the hydrocarbon location and dimension. To conduct those analyses successfuly, a radial basis function (RBF) network could be employed to become a forward model of the input-output relationship of the data from a marine electromagnetic survey. This type of neural networks is working based on distances between its inputs and predetermined centres of some basis functions. A previous research had been conducted to model the same marine electromagnetic survey using another type of neural networks, which is a multi layer perceptron (MLP) network. By comparing their validation and training performances (mean-squared errors and correlation coefficients), it is concluded that, in this case, the MLP network is comparatively better than the RBF network 1 .
2016 1st International Conference on Biomedical Engineering (IBIOMED), 2016
Haar Cascade Classifier is a method for detection of objects within an image, which is widely app... more Haar Cascade Classifier is a method for detection of objects within an image, which is widely applied on face detection. This paper discusses the utilization of Haar Cascade Classifier in locating the positions of white blood cells in an image. The results showed that this method is able to localize white blood cells with precision and recall values of 95% and 74% respectively. This method is also able to distinguish white blood cells from other objects that have color resembling white blood cells.
IOP Conference Series: Earth and Environmental Science
Fuel loading pattern optimization is a complex problem because there are so many possibilities fo... more Fuel loading pattern optimization is a complex problem because there are so many possibilities for combinatorial solutions, and it will take time to try it one by one. Therefore, the Polar Bear Optimization Algorithm was applied to find an optimum PWR loading pattern based on BEAVRS. The desired new fuel loading pattern is the one that has the minimum Power Peaking Factor (PPF) value without compromising the operating time. Operating time is proportional to the multiplication factor (k eff ). These parameters are usually contradictive with each other and will make it hard to find the optimum solution. The reactor was modelled with the Standard Reactor Analysis Code (SRAC) 2006. Fuel pins and fuel assemblies are modelled with the PIJ module for cell calculations. One-fourth symmetry was used with the CITATION X-Y module for core calculations. The optimization was done with 200 populations and 50 iterations. The PPF value for the selected solution should never exceed 2.0 in every burn...
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