Pub Date : 2018-08-01DOI: 10.1109/ISITIA.2018.8711311
F. Budiman, M. Rivai, I. G. Bagus Prasta Raditya, Daniel Krisrenanto, Irma Zahroul Amiroh
Air conditioner (AC) is a device that requires high power. To reduce the energy waste by AC, the temperature setting should be adjusted to the room condition. It can be affected by the number of persons and the level of activity in the room. To save electricity consumption, this research is conducted to design an intelligent and automatic AC system based on identification of number of persons and activity level to control working temperature of AC using fuzzy logic refers to thermal comfort standard in Indonesia issued by SNI council. The system used USB camera as an image capture device. In image processing, Histogram of Oriented Gradient (HOG) method is used to identify the number of people, while background subtraction method is used to identify the activity level. This system is implemented into Raspberry Pi 3 as a single board computing. Test results show that the system is capable to detect people from a distance of 3m to 9m and distinguish 2 people within a distance of 30 cm to 150 cm, The system can also differentiate small, medium and high of activity levels. The test results show that the working temperature controlled by the designed fuzzy logic has the lowest value of 21°C and the highest value of 27°C which is in accordance with the thermal comfort standard that has been defined by the SNI council. The differences between working temperature and measured room temperature are within only 0.2°C to 1.2°C.
空调是一种功率要求较高的设备。为减少空调对能源的浪费，空调的温度设置应根据房间的实际情况进行调整。它可能受到人数和房间内活动程度的影响。为了节约电力消耗，本研究参照SNI理事会在印度尼西亚颁布的热舒适标准，设计一种基于人数识别和活动水平识别的智能自动空调系统，利用模糊逻辑控制空调的工作温度。系统采用USB摄像头作为图像采集设备。在图像处理中，采用定向梯度直方图(Histogram of Oriented Gradient, HOG)方法识别人数，采用背景减法识别活动水平。本系统实现在树莓派3上作为单板计算。测试结果表明，该系统能够对3米~ 9米范围内的人进行检测，对30厘米~ 150厘米范围内的2人进行区分，并能区分小、中、高活动水平。测试结果表明，所设计的模糊逻辑控制的工作温度最低为21℃，最高为27℃，符合SNI委员会制定的热舒适标准。工作温度与测量室温之间的差异仅在0.2°C至1.2°C之间。
{"title":"Smart Control of Air Conditioning System Based on Number and Activity Level of Persons","authors":"F. Budiman, M. Rivai, I. G. Bagus Prasta Raditya, Daniel Krisrenanto, Irma Zahroul Amiroh","doi":"10.1109/ISITIA.2018.8711311","DOIUrl":"https://doi.org/10.1109/ISITIA.2018.8711311","url":null,"abstract":"Air conditioner (AC) is a device that requires high power. To reduce the energy waste by AC, the temperature setting should be adjusted to the room condition. It can be affected by the number of persons and the level of activity in the room. To save electricity consumption, this research is conducted to design an intelligent and automatic AC system based on identification of number of persons and activity level to control working temperature of AC using fuzzy logic refers to thermal comfort standard in Indonesia issued by SNI council. The system used USB camera as an image capture device. In image processing, Histogram of Oriented Gradient (HOG) method is used to identify the number of people, while background subtraction method is used to identify the activity level. This system is implemented into Raspberry Pi 3 as a single board computing. Test results show that the system is capable to detect people from a distance of 3m to 9m and distinguish 2 people within a distance of 30 cm to 150 cm, The system can also differentiate small, medium and high of activity levels. The test results show that the working temperature controlled by the designed fuzzy logic has the lowest value of 21°C and the highest value of 27°C which is in accordance with the thermal comfort standard that has been defined by the SNI council. The differences between working temperature and measured room temperature are within only 0.2°C to 1.2°C.","PeriodicalId":388463,"journal":{"name":"2018 International Seminar on Intelligent Technology and Its Applications (ISITIA)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130683677","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-08-01DOI: 10.1109/ISITIA.2018.8711344
Tirta Samuel Mehang, D. Riawan, Vita Lystianingrum B. Putri
Photovoltaic (PV) systems are nowadays one of the most wide-spread renewable energy systems in the network or grid with one purpose to improve the reliability of the grid. However, PV systems in the network also contribute a negative impact as well; when the main grid fails to supply the load and there is a part of the load energized by the PV systems while being isolated. This case is defined as islanding. If this condition cannot be detected, the load bus will experience voltage disturbance and power quality problem. This paper presents an islanding detection using Artificial Neural Network method (ANN). ANN learning data are generated from simulations under three main scenarios: power match, overvoltage, and undervoltage, with varying power factor (cos phi). Voltage signal at PCC node in load bus is classified to identify if system is in islanding condition or not. The simulation results shows that the built ANN is capable to detect both islanding and non-islanding mode.
{"title":"Islanding Detection in Grid-Connected Distributed Photovoltaic Generation Using Artificial Neural Network","authors":"Tirta Samuel Mehang, D. Riawan, Vita Lystianingrum B. Putri","doi":"10.1109/ISITIA.2018.8711344","DOIUrl":"https://doi.org/10.1109/ISITIA.2018.8711344","url":null,"abstract":"Photovoltaic (PV) systems are nowadays one of the most wide-spread renewable energy systems in the network or grid with one purpose to improve the reliability of the grid. However, PV systems in the network also contribute a negative impact as well; when the main grid fails to supply the load and there is a part of the load energized by the PV systems while being isolated. This case is defined as islanding. If this condition cannot be detected, the load bus will experience voltage disturbance and power quality problem. This paper presents an islanding detection using Artificial Neural Network method (ANN). ANN learning data are generated from simulations under three main scenarios: power match, overvoltage, and undervoltage, with varying power factor (cos phi). Voltage signal at PCC node in load bus is classified to identify if system is in islanding condition or not. The simulation results shows that the built ANN is capable to detect both islanding and non-islanding mode.","PeriodicalId":388463,"journal":{"name":"2018 International Seminar on Intelligent Technology and Its Applications (ISITIA)","volume":"110 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129595852","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-08-01DOI: 10.1109/ISITIA.2018.8711296
Anggarjuna Puncak Pujiputra, Hendra Kusuma, T. A. Sardjono
A good accuracy and certainty paper currency recognition has a great signification for banking system as well as for vending machines. In this paper we propose an ultraviolet (UV) Rupiah paper currency image recognition by implementing Gabor wavelet feature extraction. The UV image is used to distinguish between a genuine and a fake paper image currency, since under UV light a different visual in specific areas of the real banknote will glow and show hidden patterns. To have a high accuracy as well as efficiency, we use 3 scales and 8 orientations Gabor bank and subspace-LDA classifier in recognition process. The proposed Gabor method has advantages of easiness and high accuracy. The experimental results demonstrate that this method is quite reasonable in terms of preciseness, with 98.5% overall average recognition rate are obtained for the data of 160 UV Rupiah paper currency images.
{"title":"Ultraviolet Rupiah Currency Image Recognition using Gabor Wavelet","authors":"Anggarjuna Puncak Pujiputra, Hendra Kusuma, T. A. Sardjono","doi":"10.1109/ISITIA.2018.8711296","DOIUrl":"https://doi.org/10.1109/ISITIA.2018.8711296","url":null,"abstract":"A good accuracy and certainty paper currency recognition has a great signification for banking system as well as for vending machines. In this paper we propose an ultraviolet (UV) Rupiah paper currency image recognition by implementing Gabor wavelet feature extraction. The UV image is used to distinguish between a genuine and a fake paper image currency, since under UV light a different visual in specific areas of the real banknote will glow and show hidden patterns. To have a high accuracy as well as efficiency, we use 3 scales and 8 orientations Gabor bank and subspace-LDA classifier in recognition process. The proposed Gabor method has advantages of easiness and high accuracy. The experimental results demonstrate that this method is quite reasonable in terms of preciseness, with 98.5% overall average recognition rate are obtained for the data of 160 UV Rupiah paper currency images.","PeriodicalId":388463,"journal":{"name":"2018 International Seminar on Intelligent Technology and Its Applications (ISITIA)","volume":"45 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129665221","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-08-01DOI: 10.1109/ISITIA.2018.8710975
M. Attamimi, R. Mardiyanto, A. N. Irfansyah
In general, aerial mapping is an image registration problem, i.e., the problem of transforming different sets of images into one coordinate system. Aerial mapping is one of the important capability of an unmanned aerial vehicle (UAV). Here, the images processed by the registration system is strongly influenced by the quality of the image captured by the UAV. To select the image that will be processed efficiently is not easy considering the ground truth in the mapping process is not given before the UAV flies and captures the image. On the other hand, generally, UAV will fly and take the image in sequence regardless of the quality. These will result in several issues, such as: 1) the quality of mapping results becomes bad, and 2) the computational cost of registration process becomes high. To tackle such issues, therefore, we need a recognition system that is able to recognize images that should be excluded from the registration process. In this paper, we define such image as an “inclined image,” i.e., images captured by UAV not perpendicular with the ground. Although we can calculate the inclination angle using a gyroscope attached to the UAV, our interest here is to recognize the images without the use of such sensor like human do. To realize that, we utilize a deep learning method to build an inclined image recognition system. We tested our proposed system with images captured by UAV. The results showed that the proposed system yielded accuracy rate of 86.4%.
{"title":"Inclined Image Recognition for Aerial Mapping by Unmanned Aerial Vehicles","authors":"M. Attamimi, R. Mardiyanto, A. N. Irfansyah","doi":"10.1109/ISITIA.2018.8710975","DOIUrl":"https://doi.org/10.1109/ISITIA.2018.8710975","url":null,"abstract":"In general, aerial mapping is an image registration problem, i.e., the problem of transforming different sets of images into one coordinate system. Aerial mapping is one of the important capability of an unmanned aerial vehicle (UAV). Here, the images processed by the registration system is strongly influenced by the quality of the image captured by the UAV. To select the image that will be processed efficiently is not easy considering the ground truth in the mapping process is not given before the UAV flies and captures the image. On the other hand, generally, UAV will fly and take the image in sequence regardless of the quality. These will result in several issues, such as: 1) the quality of mapping results becomes bad, and 2) the computational cost of registration process becomes high. To tackle such issues, therefore, we need a recognition system that is able to recognize images that should be excluded from the registration process. In this paper, we define such image as an “inclined image,” i.e., images captured by UAV not perpendicular with the ground. Although we can calculate the inclination angle using a gyroscope attached to the UAV, our interest here is to recognize the images without the use of such sensor like human do. To realize that, we utilize a deep learning method to build an inclined image recognition system. We tested our proposed system with images captured by UAV. The results showed that the proposed system yielded accuracy rate of 86.4%.","PeriodicalId":388463,"journal":{"name":"2018 International Seminar on Intelligent Technology and Its Applications (ISITIA)","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122338573","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-08-01DOI: 10.1109/ISITIA.2018.8710876
O. Penangsang, S. B. Panuntun, B.P. Vita Lystianingrum, I. Suryawati
Constant increasing in the Indonesian population causes an increase in the electricity consumption, as well as the complexity in distribution system networks. Such complex networks require a valid and fair online monitoring and analysis system to allow network maintenance. One of the important components in online monitoring is measurement sensors. It demands quite a lot of sensors for all buses to yield a valid and fair monitoring. However, high investment and maintenance cost must be taken into consideration to build a monitoring system. To resolve this matter, state estimation-a calculation process to estimate unknown variables on a bus-can be used. Using state estimation, expenses can be minimized, because the monitoring system requires less sensors to obtain the same load flow results as if sensors are installed at all buses. Therefore, this research applied state estimation method on a Radial Passive Distribution System using Hamiltonian Cycle Theory. The number of sensors required should be first determined based on the selected buses in the network to conduct estimation based on the Hamiltonian Theory-which estimates the loads at the buses without sensors installed. Then, currents, voltages, losses, and voltage drops can be calculated easily in such distribution system. To understand a visualization of the estimation results, Geographic Information System is used. The simulation results show that this method works satisfactorily to estimate the loads at the buses without sensors in a radial distribution system, and the number of sensors reduces up to 39,29% from the total installed PMU's if they are installed at all buses.
{"title":"State Estimation for Radial Passive Distribution System using Hamiltonian Cycle Theory Based on Geographic Information System (GIS)","authors":"O. Penangsang, S. B. Panuntun, B.P. Vita Lystianingrum, I. Suryawati","doi":"10.1109/ISITIA.2018.8710876","DOIUrl":"https://doi.org/10.1109/ISITIA.2018.8710876","url":null,"abstract":"Constant increasing in the Indonesian population causes an increase in the electricity consumption, as well as the complexity in distribution system networks. Such complex networks require a valid and fair online monitoring and analysis system to allow network maintenance. One of the important components in online monitoring is measurement sensors. It demands quite a lot of sensors for all buses to yield a valid and fair monitoring. However, high investment and maintenance cost must be taken into consideration to build a monitoring system. To resolve this matter, state estimation-a calculation process to estimate unknown variables on a bus-can be used. Using state estimation, expenses can be minimized, because the monitoring system requires less sensors to obtain the same load flow results as if sensors are installed at all buses. Therefore, this research applied state estimation method on a Radial Passive Distribution System using Hamiltonian Cycle Theory. The number of sensors required should be first determined based on the selected buses in the network to conduct estimation based on the Hamiltonian Theory-which estimates the loads at the buses without sensors installed. Then, currents, voltages, losses, and voltage drops can be calculated easily in such distribution system. To understand a visualization of the estimation results, Geographic Information System is used. The simulation results show that this method works satisfactorily to estimate the loads at the buses without sensors in a radial distribution system, and the number of sensors reduces up to 39,29% from the total installed PMU's if they are installed at all buses.","PeriodicalId":388463,"journal":{"name":"2018 International Seminar on Intelligent Technology and Its Applications (ISITIA)","volume":"37 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123554030","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-08-01DOI: 10.1109/ISITIA.2018.8710799
Wildan Arif Febrianto, Indrawan Gunartono, O. Penangsang, R. S. Wibowo
Fault in the power distribution system causes protection system tripped and the electrical supply disturbed. The electrical fault occurred by lightning, strong wind, wood cutting, then the aging and an inadequate network component maintenance. It certainly leads to the poor power quality and voltage sag as well. An assessment power quality is an essential thing for utility and the energy supplier to identify and fix a critical area up. The fault location program has an important role in short-term planning operation of electric distribution network to reduce downtime and improve system reliability. A network modelling and faults simulation has been done to obtain voltage sag and current information. Then, the voltage sag at measurement point will be purposed to identify and classify a fault by using K-Means Clustering. Fault location estimation used by technician to repair electrical supply in real system, Kupang substation.
{"title":"Fault Location and Voltage Sag Analysis in Electric Distribution Network","authors":"Wildan Arif Febrianto, Indrawan Gunartono, O. Penangsang, R. S. Wibowo","doi":"10.1109/ISITIA.2018.8710799","DOIUrl":"https://doi.org/10.1109/ISITIA.2018.8710799","url":null,"abstract":"Fault in the power distribution system causes protection system tripped and the electrical supply disturbed. The electrical fault occurred by lightning, strong wind, wood cutting, then the aging and an inadequate network component maintenance. It certainly leads to the poor power quality and voltage sag as well. An assessment power quality is an essential thing for utility and the energy supplier to identify and fix a critical area up. The fault location program has an important role in short-term planning operation of electric distribution network to reduce downtime and improve system reliability. A network modelling and faults simulation has been done to obtain voltage sag and current information. Then, the voltage sag at measurement point will be purposed to identify and classify a fault by using K-Means Clustering. Fault location estimation used by technician to repair electrical supply in real system, Kupang substation.","PeriodicalId":388463,"journal":{"name":"2018 International Seminar on Intelligent Technology and Its Applications (ISITIA)","volume":"218 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121035109","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-08-01DOI: 10.1109/ISITIA.2018.8710786
Fransisca Margaret Pasalbessy, K. Anwar
The Internet-of-Things (IoT) is estimated to be deployed to serve billions of devices constructing super-dense networks, of which the performances are depending on the multiuser detection (MUD) capabilities to support more devices. This paper analyzes the decoding behaviour of Narrowband IoT (NB-IoT) and Single Carrier IoT (SC-IoT) networks using extrinsic information transfer (EXIT) chart to observe their throughput performances in low and high volume traffics. NB-IoT uses slotted ALOHA as its multiple access technique that discards collided packets, while SC-IoT uses coded random access (CRA) scheme, where the collided packets are to be resolved using successive interference cancellation technique, which is equivalent to peeling decoding at packet level. We also analyze network performances in terms of packet-loss-rate (PLR) and throughput using a series of computer simulations. Our results confirmed that SC-IoT using CRA has better performance than NB-IoT in terms of PLR, throughput, and gap of EXIT chart indicating that SC-IoT based on CRA scheme is a promising scheme for future IoT to serve massive number of users or devices.
{"title":"Analysis of Internet of Things (IoT) Networks Using Extrinsic Information Transfer (EXIT) Chart","authors":"Fransisca Margaret Pasalbessy, K. Anwar","doi":"10.1109/ISITIA.2018.8710786","DOIUrl":"https://doi.org/10.1109/ISITIA.2018.8710786","url":null,"abstract":"The Internet-of-Things (IoT) is estimated to be deployed to serve billions of devices constructing super-dense networks, of which the performances are depending on the multiuser detection (MUD) capabilities to support more devices. This paper analyzes the decoding behaviour of Narrowband IoT (NB-IoT) and Single Carrier IoT (SC-IoT) networks using extrinsic information transfer (EXIT) chart to observe their throughput performances in low and high volume traffics. NB-IoT uses slotted ALOHA as its multiple access technique that discards collided packets, while SC-IoT uses coded random access (CRA) scheme, where the collided packets are to be resolved using successive interference cancellation technique, which is equivalent to peeling decoding at packet level. We also analyze network performances in terms of packet-loss-rate (PLR) and throughput using a series of computer simulations. Our results confirmed that SC-IoT using CRA has better performance than NB-IoT in terms of PLR, throughput, and gap of EXIT chart indicating that SC-IoT based on CRA scheme is a promising scheme for future IoT to serve massive number of users or devices.","PeriodicalId":388463,"journal":{"name":"2018 International Seminar on Intelligent Technology and Its Applications (ISITIA)","volume":"50 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121255029","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-08-01DOI: 10.1109/ISITIA.2018.8711302
D. A. Asfani, D. Fahmi, I. M. Yulistya Negara, Agung Brastama, F. Kurniawan, I. Ramadhan
In this paper, a web-based online monitoring system of low voltage series arcing was designed. Furthermore, the line impedance was anayzed. The method of arc detection was done by peak thresholding and peak counting of the current signal that were previously processed by a digital high pass filter in LabViewprogram. The algorithm in detection system was designed to recognize three common cases in a circuit, namely normal condition, load switching condition, and series arcing condition. The LabViewprogram was employed to communicate with a MySQL database that was located on a webhost server in internet network by sending the arcing detection log. The results showed that the proposed system could distinguish the arcing condition from the other cases and send this information to the web. In addition, the line impedance affected the sensitivity of arcing detection system since it attenuated the arcing signal.
{"title":"Web-based Online Monitoring of Low Voltage Series Arcing with Line Impedance Analysis","authors":"D. A. Asfani, D. Fahmi, I. M. Yulistya Negara, Agung Brastama, F. Kurniawan, I. Ramadhan","doi":"10.1109/ISITIA.2018.8711302","DOIUrl":"https://doi.org/10.1109/ISITIA.2018.8711302","url":null,"abstract":"In this paper, a web-based online monitoring system of low voltage series arcing was designed. Furthermore, the line impedance was anayzed. The method of arc detection was done by peak thresholding and peak counting of the current signal that were previously processed by a digital high pass filter in LabViewprogram. The algorithm in detection system was designed to recognize three common cases in a circuit, namely normal condition, load switching condition, and series arcing condition. The LabViewprogram was employed to communicate with a MySQL database that was located on a webhost server in internet network by sending the arcing detection log. The results showed that the proposed system could distinguish the arcing condition from the other cases and send this information to the web. In addition, the line impedance affected the sensitivity of arcing detection system since it attenuated the arcing signal.","PeriodicalId":388463,"journal":{"name":"2018 International Seminar on Intelligent Technology and Its Applications (ISITIA)","volume":"79 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127124722","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-08-01DOI: 10.1109/isitia.2018.8710967
M. Afandi, Hendra Kusuma, T. A. Sardjono
A pair of blood vessels inside of the human neck that serves to deliver blood to the brain is called carotid artery. Cholesterol in human body can form plaque, causes blockage to carotid artery that evoke atherosclerosis, stroke and heart disease which is a dangerous disease that can lead to death. If in certain long time it is not discovered, carotid artery will rupture. In clinical practice, the availability of ultrasound is wide also it is a low cost method to observe plaque in carotid artery. Unfortunately, ultrasound plaque images in carotid artery is diverse, noisy and not easy to be identified. It is also hard to develop computational techniques for recognizing plaque from ultrasound images. Therefore, it is a challenge to develop an optimal method that can be implemented in computer system to recognize plaque from ultrasound images. One method from many techniques available in pattern recognition is a feature extraction which can be obtained from various ways. In this work, A Gabor wavelet which is one of the powerful method in feature extraction is applied to recognize plaque characteristics. However a Gabor wavelet feature extraction will result a huge data, therefore to reduce the data dimension, the Principal Component Analysis (PCA) is applied to reduce such huge data. The result of this method for recognize plaque in carotid artery is satisfied with 100% recognition rate by using 8 orientations and 3 scales bank of Gabor with 100% eigenvectors configuration. In this research we used 24 carotid artery training images.
{"title":"Carotid Artery Plaque Image Recognition Using Gabor Wavelet and Principal Component Analysis","authors":"M. Afandi, Hendra Kusuma, T. A. Sardjono","doi":"10.1109/isitia.2018.8710967","DOIUrl":"https://doi.org/10.1109/isitia.2018.8710967","url":null,"abstract":"A pair of blood vessels inside of the human neck that serves to deliver blood to the brain is called carotid artery. Cholesterol in human body can form plaque, causes blockage to carotid artery that evoke atherosclerosis, stroke and heart disease which is a dangerous disease that can lead to death. If in certain long time it is not discovered, carotid artery will rupture. In clinical practice, the availability of ultrasound is wide also it is a low cost method to observe plaque in carotid artery. Unfortunately, ultrasound plaque images in carotid artery is diverse, noisy and not easy to be identified. It is also hard to develop computational techniques for recognizing plaque from ultrasound images. Therefore, it is a challenge to develop an optimal method that can be implemented in computer system to recognize plaque from ultrasound images. One method from many techniques available in pattern recognition is a feature extraction which can be obtained from various ways. In this work, A Gabor wavelet which is one of the powerful method in feature extraction is applied to recognize plaque characteristics. However a Gabor wavelet feature extraction will result a huge data, therefore to reduce the data dimension, the Principal Component Analysis (PCA) is applied to reduce such huge data. The result of this method for recognize plaque in carotid artery is satisfied with 100% recognition rate by using 8 orientations and 3 scales bank of Gabor with 100% eigenvectors configuration. In this research we used 24 carotid artery training images.","PeriodicalId":388463,"journal":{"name":"2018 International Seminar on Intelligent Technology and Its Applications (ISITIA)","volume":"76 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126109746","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-08-01DOI: 10.1109/ISITIA.2018.8710890
D. Setiawan, H. Suryoatmojo, M. Ashari
This paper is dealing with innovative control strategy of a four-leg voltage source inverter (FLVSI) which is implemented in unbalanced condition. The proposed method is aimed to maintain the balancing of voltage and current distribution system due to unbalance capacity of DG connection and unbalanced load. These unbalance condition can affect the transformer performance which is essentially designed to supply a balanced voltage. For solving the problem, the unbalance voltage and current transformer signals are decomposed to its symmetrical components: positive, negative, and zero sequence. Each results of the decomposition are transformed into a synchronous reference frame (dq coordinate) and controlled by ANFIS controller. Based on the simulation results with Matlab/Simulink, current unbalance of transformer is decreased from 48.44% to 15.15% and voltage unbalance is decreased from 5.09% to 2.46%.
{"title":"Four-leg Voltage Source Inverter for Voltage and Current Balancing of Distribution Transformer with Distributed Generations","authors":"D. Setiawan, H. Suryoatmojo, M. Ashari","doi":"10.1109/ISITIA.2018.8710890","DOIUrl":"https://doi.org/10.1109/ISITIA.2018.8710890","url":null,"abstract":"This paper is dealing with innovative control strategy of a four-leg voltage source inverter (FLVSI) which is implemented in unbalanced condition. The proposed method is aimed to maintain the balancing of voltage and current distribution system due to unbalance capacity of DG connection and unbalanced load. These unbalance condition can affect the transformer performance which is essentially designed to supply a balanced voltage. For solving the problem, the unbalance voltage and current transformer signals are decomposed to its symmetrical components: positive, negative, and zero sequence. Each results of the decomposition are transformed into a synchronous reference frame (dq coordinate) and controlled by ANFIS controller. Based on the simulation results with Matlab/Simulink, current unbalance of transformer is decreased from 48.44% to 15.15% and voltage unbalance is decreased from 5.09% to 2.46%.","PeriodicalId":388463,"journal":{"name":"2018 International Seminar on Intelligent Technology and Its Applications (ISITIA)","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122481505","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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