azura che soh - Academia.edu (original) (raw)

Papers by azura che soh

Research paper thumbnail of Double soft-computing techniques based triple functionalities for Shunt Active Power Filter with voltage source inverter topology

2015 IEEE 15th International Conference on Environment and Electrical Engineering (EEEIC), 2015

Firstly, a unified adaptive linear neurons based fundamental component extraction algorithm for d... more Firstly, a unified adaptive linear neurons based fundamental component extraction algorithm for dual roles is developed; to generate and synchronize a reference current with respect to the phase and the frequency of supply voltage. A modified method of extracting the final amplitude of the reference current is introduced for improving the quality of the reference current. Second, a hybrid Fuzzy-Proportional (P) controller plus Crisp-Integral (I) controller is designed for a self-charging DC-link voltage control algorithm. The proposed controller is utilized in minimizing the error of DC-link voltage and, its control signal is employed in calculating a reference charging current. The Fuzzy-P controller exhibits simple structure for low computational burden and memory requirement. While, the Crisp-I controller is used to eliminate the steady-state error of DC-link voltage. Performances of the SAPF with the proposed techniques are validated by simulation and experimental works.

Research paper thumbnail of Design of a wireless surface EMG acquisition system

2017 24th International Conference on Mechatronics and Machine Vision in Practice (M2VIP), 2017

Research paper thumbnail of Deep Learning Object Detector Using a Combination of Convolutional Neural Network (CNN) Architecture (MiniVGGNet) and Classic Object Detection Algorithm

Pertanika Journal of Science and Technology, 2020

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...

Research paper thumbnail of Pattern analysis using principle component analysis (PCA) method for herbs identification

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.

Research paper thumbnail of Smart Indoor Parking System Based on Dijkstra’s Algorithm

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...

Research paper thumbnail of Process fault detection and diagnosis using a dynamic neural networks model

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.

Research paper thumbnail of ON-OFF Body Ultra-Wideband (UWB) Antenna for Wireless Body Area Networks (WBAN): A Review

IEEE Access, 2020

Ultra-wideband (UWB) technology can offer broad capacity, short-range communications at a relativ... more Ultra-wideband (UWB) technology can offer broad capacity, short-range communications at a relatively low level of energy usage, which is very desirable for wireless body area networks (WBANs). The involvement of the human body in such a device poses immense difficulties for both the architecture of the wearable antenna and the broadcast model. Initially, the bonding between the wearable antenna and the human body should also be acknowledged in the early stages of the design, so that both the potentially degrading output of the antenna as a consequence of the body and the possibility of exposure for the body may be handled. Next, the transmission path in WBAN is affected by the constant activity of the human body, leading to the time-varying dispersion of electromagnetic waves. Few researchers were interested in this field, and some substantial progress has recently been considered. On the other hand, this paper covered both wearable and Non-wearable UWB antenna designs and applications with respect to their substrate characteristics. Finally, this review prospectively exposes the upgraded developments of (ON-OFF) body antennas in the area of wearable and Non-wearable UWB and their implementations in the WBAN device and aims to evaluate the latest design features that inspire the performance of the antennas. INDEX TERMS ON-body antenna, OFF-body antenna, wearable antenna, ultra-wideband (UWB) antenna, wireless body area network (WBAN).

Research paper thumbnail of Recent Advances in Wearable Antenna Technologies: A Review

Progress In Electromagnetics Research B, 2020

Wearable antennas have received a great deal of popularity in recent years owing to their enticin... more Wearable antennas have received a great deal of popularity in recent years owing to their enticing characteristics and opportunities to realize lightweight, compact, low-cost, and versatile wireless communications and environments. These antennas must be conformal, and they must be built using lightweight materials and constructed in a low-profile configuration when mounted on various areas of the human body. These antennas ought to be able to function close to the human body with limited deterioration. These criteria render the layout of wearable antennas demanding, particularly when considering factors such as investigating the usability of textile substrates, high conductive materials during fabrication processes, and the effect of body binding scenarios on the performance of the design. Although there are minor differences in magnitude based on the implementations, several of these problems occur in the body-worn deployment sense. This study addresses the numerous problems and obstacles in the production of wearable antennas, their variety of materials, and the techniques of manufacturing alongside with bending scheme. This is accompanied by a summary of creative features and their respective approaches to address these problems recently raised by work in this area by the science community.

Research paper thumbnail of MYNursingHome: A fully-labelled image dataset for indoor object classification

Research paper thumbnail of TRIGA PUSPATI reactor: model analysis and accuracy

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...

Research paper thumbnail of Soft-Sensing Estimation of Optical Density for PHA Production Using Multilayer Perceptron Neural Network

Journal of Physics: Conference Series, 2020

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...

Research paper thumbnail of Performance evaluation of Modified Widrow-Hoff ADALINE under effect of photovoltaic with shunt active power filter

2016 IEEE Industrial Electronics and Applications Conference (IEACon), Nov 1, 2016

Research paper thumbnail of Development of fall detection and activity recognition using threshold based method and neural network

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...

Research paper thumbnail of Artificial neural network model and fuzzy logic control of dissolved oxygen in a bioreactor

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.

Research paper thumbnail of Improving Convolutional Neural Network (CNN) Architecture (miniVGGNet) with Batch Normalization and Learning Rate Decay Factor for Image Classification

International Journal of Integrated Engineering, 2019

Research paper thumbnail of Simulated Real-Time Controller for Tuning Algorithm Using Modified Hill Climbing Approach Based on Model Reference Adaptive Control System

Deterministic Artificial Intelligence, 2020

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 ...

Research paper thumbnail of Improvement of LMS adaptive noise canceller using uniform Poly-phase digital filter bank

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...

Research paper thumbnail of A Promising Wavelet Decomposition –NNARX Model to Predict Flood

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...

Research paper thumbnail of Adaptive Hybrid Fuzzy-Proportional Plus Crisp-Integral Current Control Algorithm for Shunt Active Power Filter Operation

Energies, 2016

An adaptive hybrid fuzzy-proportional plus crisp-integral current control algorithm (CCA) for reg... more An adaptive hybrid fuzzy-proportional plus crisp-integral current control algorithm (CCA) for regulating supply current and enhancing the operation of a shunt active power filter (SAPF) is presented. It introduces a unique integration of fuzzy-proportional (Fuzzy-P) and crisp-integral (Crisp-I) current controllers. The Fuzzy-P current controller is developed to perform gain tuning procedure and proportional control action. This controller inherits the simplest configuration; it is constructed using a single-input single-output fuzzy rule configuration. Thus, an execution of few fuzzy rules is sufficient for the controller's operation. Furthermore, the fuzzy rule is developed using the relationship of currents only. Hence, it simplifies the controller development. Meanwhile, the Crisp-I current controller is developed to perform integral control action using a controllable gain value; to improve the steady-state control mechanism. The gain value is modified and controlled using the Fuzzy-P current controller's output variable. Therefore, the gain value will continuously be adjusted at every sample period (or throughout the SAPF operation). The effectiveness of the proposed CCA in regulating supply current is validated in both simulation and experimental work. All results have proven that the SAPF using the proposed CCA is capable to regulate supply current during steady-state and dynamic-state operations. At the same time, the SAPF is able to enhance its operation in compensating harmonic currents and reactive power. Furthermore, the implementation of the proposed CCA has resulted more stable dc-link voltage waveform.

Research paper thumbnail of A wireless flipper robot using interface free controller

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.

Research paper thumbnail of Double soft-computing techniques based triple functionalities for Shunt Active Power Filter with voltage source inverter topology

2015 IEEE 15th International Conference on Environment and Electrical Engineering (EEEIC), 2015

Firstly, a unified adaptive linear neurons based fundamental component extraction algorithm for d... more Firstly, a unified adaptive linear neurons based fundamental component extraction algorithm for dual roles is developed; to generate and synchronize a reference current with respect to the phase and the frequency of supply voltage. A modified method of extracting the final amplitude of the reference current is introduced for improving the quality of the reference current. Second, a hybrid Fuzzy-Proportional (P) controller plus Crisp-Integral (I) controller is designed for a self-charging DC-link voltage control algorithm. The proposed controller is utilized in minimizing the error of DC-link voltage and, its control signal is employed in calculating a reference charging current. The Fuzzy-P controller exhibits simple structure for low computational burden and memory requirement. While, the Crisp-I controller is used to eliminate the steady-state error of DC-link voltage. Performances of the SAPF with the proposed techniques are validated by simulation and experimental works.

Research paper thumbnail of Design of a wireless surface EMG acquisition system

2017 24th International Conference on Mechatronics and Machine Vision in Practice (M2VIP), 2017

Research paper thumbnail of Deep Learning Object Detector Using a Combination of Convolutional Neural Network (CNN) Architecture (MiniVGGNet) and Classic Object Detection Algorithm

Pertanika Journal of Science and Technology, 2020

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...

Research paper thumbnail of Pattern analysis using principle component analysis (PCA) method for herbs identification

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.

Research paper thumbnail of Smart Indoor Parking System Based on Dijkstra’s Algorithm

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...

Research paper thumbnail of Process fault detection and diagnosis using a dynamic neural networks model

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.

Research paper thumbnail of ON-OFF Body Ultra-Wideband (UWB) Antenna for Wireless Body Area Networks (WBAN): A Review

IEEE Access, 2020

Ultra-wideband (UWB) technology can offer broad capacity, short-range communications at a relativ... more Ultra-wideband (UWB) technology can offer broad capacity, short-range communications at a relatively low level of energy usage, which is very desirable for wireless body area networks (WBANs). The involvement of the human body in such a device poses immense difficulties for both the architecture of the wearable antenna and the broadcast model. Initially, the bonding between the wearable antenna and the human body should also be acknowledged in the early stages of the design, so that both the potentially degrading output of the antenna as a consequence of the body and the possibility of exposure for the body may be handled. Next, the transmission path in WBAN is affected by the constant activity of the human body, leading to the time-varying dispersion of electromagnetic waves. Few researchers were interested in this field, and some substantial progress has recently been considered. On the other hand, this paper covered both wearable and Non-wearable UWB antenna designs and applications with respect to their substrate characteristics. Finally, this review prospectively exposes the upgraded developments of (ON-OFF) body antennas in the area of wearable and Non-wearable UWB and their implementations in the WBAN device and aims to evaluate the latest design features that inspire the performance of the antennas. INDEX TERMS ON-body antenna, OFF-body antenna, wearable antenna, ultra-wideband (UWB) antenna, wireless body area network (WBAN).

Research paper thumbnail of Recent Advances in Wearable Antenna Technologies: A Review

Progress In Electromagnetics Research B, 2020

Wearable antennas have received a great deal of popularity in recent years owing to their enticin... more Wearable antennas have received a great deal of popularity in recent years owing to their enticing characteristics and opportunities to realize lightweight, compact, low-cost, and versatile wireless communications and environments. These antennas must be conformal, and they must be built using lightweight materials and constructed in a low-profile configuration when mounted on various areas of the human body. These antennas ought to be able to function close to the human body with limited deterioration. These criteria render the layout of wearable antennas demanding, particularly when considering factors such as investigating the usability of textile substrates, high conductive materials during fabrication processes, and the effect of body binding scenarios on the performance of the design. Although there are minor differences in magnitude based on the implementations, several of these problems occur in the body-worn deployment sense. This study addresses the numerous problems and obstacles in the production of wearable antennas, their variety of materials, and the techniques of manufacturing alongside with bending scheme. This is accompanied by a summary of creative features and their respective approaches to address these problems recently raised by work in this area by the science community.

Research paper thumbnail of MYNursingHome: A fully-labelled image dataset for indoor object classification

Research paper thumbnail of TRIGA PUSPATI reactor: model analysis and accuracy

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...

Research paper thumbnail of Soft-Sensing Estimation of Optical Density for PHA Production Using Multilayer Perceptron Neural Network

Journal of Physics: Conference Series, 2020

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...

Research paper thumbnail of Performance evaluation of Modified Widrow-Hoff ADALINE under effect of photovoltaic with shunt active power filter

2016 IEEE Industrial Electronics and Applications Conference (IEACon), Nov 1, 2016

Research paper thumbnail of Development of fall detection and activity recognition using threshold based method and neural network

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...

Research paper thumbnail of Artificial neural network model and fuzzy logic control of dissolved oxygen in a bioreactor

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.

Research paper thumbnail of Improving Convolutional Neural Network (CNN) Architecture (miniVGGNet) with Batch Normalization and Learning Rate Decay Factor for Image Classification

International Journal of Integrated Engineering, 2019

Research paper thumbnail of Simulated Real-Time Controller for Tuning Algorithm Using Modified Hill Climbing Approach Based on Model Reference Adaptive Control System

Deterministic Artificial Intelligence, 2020

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 ...

Research paper thumbnail of Improvement of LMS adaptive noise canceller using uniform Poly-phase digital filter bank

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...

Research paper thumbnail of A Promising Wavelet Decomposition –NNARX Model to Predict Flood

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...

Research paper thumbnail of Adaptive Hybrid Fuzzy-Proportional Plus Crisp-Integral Current Control Algorithm for Shunt Active Power Filter Operation

Energies, 2016

An adaptive hybrid fuzzy-proportional plus crisp-integral current control algorithm (CCA) for reg... more An adaptive hybrid fuzzy-proportional plus crisp-integral current control algorithm (CCA) for regulating supply current and enhancing the operation of a shunt active power filter (SAPF) is presented. It introduces a unique integration of fuzzy-proportional (Fuzzy-P) and crisp-integral (Crisp-I) current controllers. The Fuzzy-P current controller is developed to perform gain tuning procedure and proportional control action. This controller inherits the simplest configuration; it is constructed using a single-input single-output fuzzy rule configuration. Thus, an execution of few fuzzy rules is sufficient for the controller's operation. Furthermore, the fuzzy rule is developed using the relationship of currents only. Hence, it simplifies the controller development. Meanwhile, the Crisp-I current controller is developed to perform integral control action using a controllable gain value; to improve the steady-state control mechanism. The gain value is modified and controlled using the Fuzzy-P current controller's output variable. Therefore, the gain value will continuously be adjusted at every sample period (or throughout the SAPF operation). The effectiveness of the proposed CCA in regulating supply current is validated in both simulation and experimental work. All results have proven that the SAPF using the proposed CCA is capable to regulate supply current during steady-state and dynamic-state operations. At the same time, the SAPF is able to enhance its operation in compensating harmonic currents and reactive power. Furthermore, the implementation of the proposed CCA has resulted more stable dc-link voltage waveform.

Research paper thumbnail of A wireless flipper robot using interface free controller

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.