The object detection system is a computer technology related to image processing and computer vis... more The object detection system is a computer technology related to image processing and computer vision that detects instances of semantic objects of a certain class in digital images and videos. The system consists of two main processes, which are classification and detection. Once an object instance has been classified and detected, it is possible to obtain further information, including recognizes the specific instance, track the object over an image sequence and extract further information about the object and the scene. This paper presented an analysis performance of deep learning object detector by combining a deep learning Convolutional Neural Network (CNN) for object classification and applies classic object detection algorithms to devise our own deep learning object detector. MiniVGGNet is an architecture network used to train an object classification, and the data used for this purpose was collected from specific indoor environment building. For object detection, sliding wind...
Herb is one of the plant species that each has unique odors. Each herb species has unique odor wh... more Herb is one of the plant species that each has unique odors. Each herb species has unique odor which differs from each other. This odor parameter is used to differentiate the type of herbs species based on response signals from E-Nose system. The response of electrical signal is generated when the gas sensor array detect the odor of herb species. This paper presents a pattern analysis of electrical signal data by using Principle Component Analysis (PCA) method. The different herb species with same group family were investigated. The result shows the discrimination between herb species is possible using the proposed method.
Smart Indoor Parking System is a parking system that assigns the car to the nearest parking to th... more Smart Indoor Parking System is a parking system that assigns the car to the nearest parking to the entrance by using Dijkstra’s Algorithm and assigns according to the size of the car. There are many types of parking system have been proposed such as smart parking system by using Wireless Sensor Network (WSN) but all these methods have their own advantage and limitation. Besides that, there are also several problems with the current parking system such as lack of parking management system efficiency. Therefore, this Smart Indoor Parking System is proposed to increase the efficiency of current parking management system. The aim of this Smart Indoor Parking System is to provide the customer with the nearest parking to the entrance. The parking is assigned according to the size of the car to utilize the parking space. Then, the parking place is displayed on the monitor besides the boom gate before allowing the driver to enter the parking lot. The parking number will help the driver to b...
Recently, neural networks has generated considerable interest as an alternative non-linear modell... more Recently, neural networks has generated considerable interest as an alternative non-linear modelling tool. The major attraction is the learning capabilities of neural networks, and the fact that multi-layer, feed forward networks can approximate any non-linear function with arbitrary accuracy. This study describes the application of the multi-layer perceptron (MLP) neural network, trained using back-error propagation, to obtain a representative model of a non-linear process over a wide operational region. The purpose of this study is mainly to investigate the use of dynamic neural networks model for fault detection and diagnosis of the process control. The MATLAB with SIMULINK process and Multi-Layer Perceptron Software Package is used as a method to procure the required result.
Indonesian Journal of Electrical Engineering and Computer Science, 2020
There are many challenging issues with research reactor, such as time variation and uncertainty. ... more There are many challenging issues with research reactor, such as time variation and uncertainty. Since its first criticality in 1982, the biggest changes in TRIGA PUSPATI Reactor system is the replacement of instrumentation and control console system from analogue to digital in 2013. Apart from providing methods of controlling the power reactor via the control rod movement, the Instrumentation and Control Console System also provides monitoring and display for all reactor parameters to protect the reactor from undue influences or abnormal circumstances. Meanwhile, the simulation model of the TRIGA PUSPATI Reactor system has been developed in the Simulink-MATLAB. The simulation model development is based on the research reactor mathematical representatives and the real plant parameters of TRIGA PUSPATI Reactor. However, the performance of this simulation model needs to be evaluated. Since there is no report or paper work found on the performance of the simulation model to represent t...
Biomass concentration is an important indicator of production rate in polyhydroxyalkanoates (PHA)... more Biomass concentration is an important indicator of production rate in polyhydroxyalkanoates (PHA) fermentation process. In current practice, measurement of biomass concentration is done off-line by laboratory analysis that is unsuitable for online process monitoring and control. Soft-sensor is often used as an alternative that provides an estimate of hard to measure parameters from easy to measure process data. However, most of these studies use simulated data or data generated from mathematical model that was developed without full consideration of process and measurement uncertainty. In this study, a soft-sensor is developed from real production data for PHA fermentation in pilot-scale bioreactor with the appropriate data pre-processing techniques applied to process data that was obtained from this system. Multilayer perceptron (MLP) neural network is used to estimate biomass concentration using secondary process parameters such as dissolved oxygen (DO), temperature, pH and agitat...
Indonesian Journal of Electrical Engineering and Computer Science, 2020
Falls are dangerous and contribute to over 80% of injury-related hospitalization especially among... more Falls are dangerous and contribute to over 80% of injury-related hospitalization especially amongst the elderly. Hence, fall detection is important for preventing severe injuries and accidental deaths. Meanwhile, recognizing human activity is important for monitoring health status and quality of life as it can be applied in geriatric care and healthcare in general. This research presents the development of a fall detection and human activity recognition system using Threshold Based Method (TBM) and Neural Network (NN). Intentional forward fall and six other activities of daily living (ADLs), which include running, jumping, walking, sitting, lying, and standing are performed by 15 healthy volunteers in a series of experiments. There are four important stages involved in fall detection and ADL recognition, which are signal filtering, segmentation, features extraction and classification. For classification, TBM achieved an accuracy of 98.41% and 95.40% for fall detection and activity r...
Indonesian Journal of Electrical Engineering and Computer Science, 2020
In a fermentation process, dissolved oxygen is the one of the key process variables that needs to... more In a fermentation process, dissolved oxygen is the one of the key process variables that needs to be controlled because of the effect they have on the product quality. In a penicillin production, dissolved oxygen concentration influenced biomass concentration. In this paper, multilayer perceptron neural network (MLP) and Radial Basis Function (RBF) neural network is used in modeling penicillin fermentation process. Process data from an industrial scale fed-batch bioreactor is used in developing the models with dissolved oxygen and penicillin concentration as the outputs. RBF neural network model gives better accuracy than MLP neural network. The model is further used in fuzzy logic controller design to simulate control of dissolved oxygen by manipulation of aeration rate. Simulation result shows that the fuzzy logic controller can control the dissolved oxygen based on the given profile.
In this chapter, an intelligent algorithmic tuning technique suitable for real-time system tuning... more In this chapter, an intelligent algorithmic tuning technique suitable for real-time system tuning based on hill climbing optimization algorithm and model reference adaptive control (MRAC) system technique is proposed. Although many adaptive control tuning methodologies depend partially or completely on online plant system identification, the proposed method uses only the model that is used to design the original controller, leading to simplified calculations that do not require neither high processing power nor long processing time, as opposed to identification technique calculations. Additionally, a modified hill climbing algorithm that is developed in this research is specifically designed, configured and tailored for the automatic tuning of control systems. The modified hill climbing algorithm uses a systematic movement when searching for new solution candidates. The algorithm measures the quality of the solution candidate based on error function. The error function is generated ...
Indonesian Journal of Electrical Engineering and Computer Science
This paper presents the Least Mean Square (LMS) noise canceller using uniform poly-phase digital ... more This paper presents the Least Mean Square (LMS) noise canceller using uniform poly-phase digital filter bank to improve the noise can-cellation process. Analysis filter bank is used to decompose the full-band distorted input signal into sub-band signals. Decomposition the full-band input distorted signal into sub-band signals based on the fact that the signal to noise ratio (S/N) is inversely proportional to the signal bandwidth. Each sub-band signal is fed to individual LMS algorithm to produce the optimal sub-band output. Synthesis filter bank is used to compose the optimal sub-band outputs to produce the final optimal full-band output. In this paper, m-band uniform Discrete Fourier Transform (DFT) digital filter bank has been used because its computational complexity is much smaller than the direct implementation of digital filter bank. The simulation results show that the proposed method provides the efficient performance with less and smooth error signal as compared to conventi...
International journal of electrical and computer engineering systems
Flood is a major disaster that happens around the world. It has caused many casualties and massiv... more Flood is a major disaster that happens around the world. It has caused many casualties and massive destruction of property. Estimating the chance of a flood occurring depends on several factors, such as rainfall, the structure and the flow rate of the river. This research used the neural network autoregressive exogenous input (NNARX) model to predict floods. One of the research challenges was to develop accurate models and improve the forecasting model. This research aimed to improve the performance of the neural network model for flood prediction. A new technique was proposed for modelling nonlinear data of flood forecasting using the wavelet decomposition-NNARX approach. This paper discusses the process of identifying the parameters involved to make a forecast as the rainfall value requires the flow rate of the river and its water level. The original data were processed by wavelet decomposition and filtered to generate a new set of data for the NNARX prediction model where the pro...
2013 IEEE 8th Conference on Industrial Electronics and Applications (ICIEA), 2013
ABSTRACT Robots have been developed by human to do various things to make our life easier. There ... more ABSTRACT Robots have been developed by human to do various things to make our life easier. There are many approaches, systems and technologies can be applied to develop different types of robots depended on the usage. This paper presents the new approach of interfacing a wireless robot using IFC (Interface Free Controller). This controller offers a new concept of microcontroller embedded system developed for robotic application. IFC is an interfacing hardware and it configures the peripherals. This flipper robot is a fighting robot which previously participated in the robot war game. The complete design, interfacing, robot constructions, specification of the robot and testing processes are detailed out.
The object detection system is a computer technology related to image processing and computer vis... more The object detection system is a computer technology related to image processing and computer vision that detects instances of semantic objects of a certain class in digital images and videos. The system consists of two main processes, which are classification and detection. Once an object instance has been classified and detected, it is possible to obtain further information, including recognizes the specific instance, track the object over an image sequence and extract further information about the object and the scene. This paper presented an analysis performance of deep learning object detector by combining a deep learning Convolutional Neural Network (CNN) for object classification and applies classic object detection algorithms to devise our own deep learning object detector. MiniVGGNet is an architecture network used to train an object classification, and the data used for this purpose was collected from specific indoor environment building. For object detection, sliding wind...
Herb is one of the plant species that each has unique odors. Each herb species has unique odor wh... more Herb is one of the plant species that each has unique odors. Each herb species has unique odor which differs from each other. This odor parameter is used to differentiate the type of herbs species based on response signals from E-Nose system. The response of electrical signal is generated when the gas sensor array detect the odor of herb species. This paper presents a pattern analysis of electrical signal data by using Principle Component Analysis (PCA) method. The different herb species with same group family were investigated. The result shows the discrimination between herb species is possible using the proposed method.
Smart Indoor Parking System is a parking system that assigns the car to the nearest parking to th... more Smart Indoor Parking System is a parking system that assigns the car to the nearest parking to the entrance by using Dijkstra’s Algorithm and assigns according to the size of the car. There are many types of parking system have been proposed such as smart parking system by using Wireless Sensor Network (WSN) but all these methods have their own advantage and limitation. Besides that, there are also several problems with the current parking system such as lack of parking management system efficiency. Therefore, this Smart Indoor Parking System is proposed to increase the efficiency of current parking management system. The aim of this Smart Indoor Parking System is to provide the customer with the nearest parking to the entrance. The parking is assigned according to the size of the car to utilize the parking space. Then, the parking place is displayed on the monitor besides the boom gate before allowing the driver to enter the parking lot. The parking number will help the driver to b...
Recently, neural networks has generated considerable interest as an alternative non-linear modell... more Recently, neural networks has generated considerable interest as an alternative non-linear modelling tool. The major attraction is the learning capabilities of neural networks, and the fact that multi-layer, feed forward networks can approximate any non-linear function with arbitrary accuracy. This study describes the application of the multi-layer perceptron (MLP) neural network, trained using back-error propagation, to obtain a representative model of a non-linear process over a wide operational region. The purpose of this study is mainly to investigate the use of dynamic neural networks model for fault detection and diagnosis of the process control. The MATLAB with SIMULINK process and Multi-Layer Perceptron Software Package is used as a method to procure the required result.
Indonesian Journal of Electrical Engineering and Computer Science, 2020
There are many challenging issues with research reactor, such as time variation and uncertainty. ... more There are many challenging issues with research reactor, such as time variation and uncertainty. Since its first criticality in 1982, the biggest changes in TRIGA PUSPATI Reactor system is the replacement of instrumentation and control console system from analogue to digital in 2013. Apart from providing methods of controlling the power reactor via the control rod movement, the Instrumentation and Control Console System also provides monitoring and display for all reactor parameters to protect the reactor from undue influences or abnormal circumstances. Meanwhile, the simulation model of the TRIGA PUSPATI Reactor system has been developed in the Simulink-MATLAB. The simulation model development is based on the research reactor mathematical representatives and the real plant parameters of TRIGA PUSPATI Reactor. However, the performance of this simulation model needs to be evaluated. Since there is no report or paper work found on the performance of the simulation model to represent t...
Biomass concentration is an important indicator of production rate in polyhydroxyalkanoates (PHA)... more Biomass concentration is an important indicator of production rate in polyhydroxyalkanoates (PHA) fermentation process. In current practice, measurement of biomass concentration is done off-line by laboratory analysis that is unsuitable for online process monitoring and control. Soft-sensor is often used as an alternative that provides an estimate of hard to measure parameters from easy to measure process data. However, most of these studies use simulated data or data generated from mathematical model that was developed without full consideration of process and measurement uncertainty. In this study, a soft-sensor is developed from real production data for PHA fermentation in pilot-scale bioreactor with the appropriate data pre-processing techniques applied to process data that was obtained from this system. Multilayer perceptron (MLP) neural network is used to estimate biomass concentration using secondary process parameters such as dissolved oxygen (DO), temperature, pH and agitat...
Indonesian Journal of Electrical Engineering and Computer Science, 2020
Falls are dangerous and contribute to over 80% of injury-related hospitalization especially among... more Falls are dangerous and contribute to over 80% of injury-related hospitalization especially amongst the elderly. Hence, fall detection is important for preventing severe injuries and accidental deaths. Meanwhile, recognizing human activity is important for monitoring health status and quality of life as it can be applied in geriatric care and healthcare in general. This research presents the development of a fall detection and human activity recognition system using Threshold Based Method (TBM) and Neural Network (NN). Intentional forward fall and six other activities of daily living (ADLs), which include running, jumping, walking, sitting, lying, and standing are performed by 15 healthy volunteers in a series of experiments. There are four important stages involved in fall detection and ADL recognition, which are signal filtering, segmentation, features extraction and classification. For classification, TBM achieved an accuracy of 98.41% and 95.40% for fall detection and activity r...
Indonesian Journal of Electrical Engineering and Computer Science, 2020
In a fermentation process, dissolved oxygen is the one of the key process variables that needs to... more In a fermentation process, dissolved oxygen is the one of the key process variables that needs to be controlled because of the effect they have on the product quality. In a penicillin production, dissolved oxygen concentration influenced biomass concentration. In this paper, multilayer perceptron neural network (MLP) and Radial Basis Function (RBF) neural network is used in modeling penicillin fermentation process. Process data from an industrial scale fed-batch bioreactor is used in developing the models with dissolved oxygen and penicillin concentration as the outputs. RBF neural network model gives better accuracy than MLP neural network. The model is further used in fuzzy logic controller design to simulate control of dissolved oxygen by manipulation of aeration rate. Simulation result shows that the fuzzy logic controller can control the dissolved oxygen based on the given profile.
In this chapter, an intelligent algorithmic tuning technique suitable for real-time system tuning... more In this chapter, an intelligent algorithmic tuning technique suitable for real-time system tuning based on hill climbing optimization algorithm and model reference adaptive control (MRAC) system technique is proposed. Although many adaptive control tuning methodologies depend partially or completely on online plant system identification, the proposed method uses only the model that is used to design the original controller, leading to simplified calculations that do not require neither high processing power nor long processing time, as opposed to identification technique calculations. Additionally, a modified hill climbing algorithm that is developed in this research is specifically designed, configured and tailored for the automatic tuning of control systems. The modified hill climbing algorithm uses a systematic movement when searching for new solution candidates. The algorithm measures the quality of the solution candidate based on error function. The error function is generated ...
Indonesian Journal of Electrical Engineering and Computer Science
This paper presents the Least Mean Square (LMS) noise canceller using uniform poly-phase digital ... more This paper presents the Least Mean Square (LMS) noise canceller using uniform poly-phase digital filter bank to improve the noise can-cellation process. Analysis filter bank is used to decompose the full-band distorted input signal into sub-band signals. Decomposition the full-band input distorted signal into sub-band signals based on the fact that the signal to noise ratio (S/N) is inversely proportional to the signal bandwidth. Each sub-band signal is fed to individual LMS algorithm to produce the optimal sub-band output. Synthesis filter bank is used to compose the optimal sub-band outputs to produce the final optimal full-band output. In this paper, m-band uniform Discrete Fourier Transform (DFT) digital filter bank has been used because its computational complexity is much smaller than the direct implementation of digital filter bank. The simulation results show that the proposed method provides the efficient performance with less and smooth error signal as compared to conventi...
International journal of electrical and computer engineering systems
Flood is a major disaster that happens around the world. It has caused many casualties and massiv... more Flood is a major disaster that happens around the world. It has caused many casualties and massive destruction of property. Estimating the chance of a flood occurring depends on several factors, such as rainfall, the structure and the flow rate of the river. This research used the neural network autoregressive exogenous input (NNARX) model to predict floods. One of the research challenges was to develop accurate models and improve the forecasting model. This research aimed to improve the performance of the neural network model for flood prediction. A new technique was proposed for modelling nonlinear data of flood forecasting using the wavelet decomposition-NNARX approach. This paper discusses the process of identifying the parameters involved to make a forecast as the rainfall value requires the flow rate of the river and its water level. The original data were processed by wavelet decomposition and filtered to generate a new set of data for the NNARX prediction model where the pro...
2013 IEEE 8th Conference on Industrial Electronics and Applications (ICIEA), 2013
ABSTRACT Robots have been developed by human to do various things to make our life easier. There ... more ABSTRACT Robots have been developed by human to do various things to make our life easier. There are many approaches, systems and technologies can be applied to develop different types of robots depended on the usage. This paper presents the new approach of interfacing a wireless robot using IFC (Interface Free Controller). This controller offers a new concept of microcontroller embedded system developed for robotic application. IFC is an interfacing hardware and it configures the peripherals. This flipper robot is a fighting robot which previously participated in the robot war game. The complete design, interfacing, robot constructions, specification of the robot and testing processes are detailed out.
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