Pub Date : 2020-09-01DOI: 10.1109/IES50839.2020.9231925
Nilam Ade Pangestu, R. Sigit, T. Harsono, Manik Retno Wahyunitisari, A. Anwar, Dinda Ayu Yunitasari
The diagnosis of tuberculosis (TB) is done by detecting and counting the number of mycobacterium tuberculosis in a sputum examination done manually using a microscope. It is considered ineffective because it requires a long time and different diagnostic results. To overcome this problem, this paper implements digital image processing. There are 5 processes used on the system. Preprocessing with the RGB to HSV method is used to clarify the color of the image. Segmentation to separate objects from background images using thresholding. Feature extraction to get the value of area, perimeter, and level of roundness of the object. Classification uses fuzzy logic to classify mycobacterium tuberculosis based on features. The next is the process of counting mycobacterium tuberculosis. And the last is the process of classify into IUATLD scale based on the number of mycobacterium tuberculosis. From the results of tests conducted on 15 data, the system show that the level of accuracy, precision, sensitivity and specificity of system in calculate mycobacterium tuberculosis is 89%, 90%, 91.66% and 78.88% respectively. And also level of sensitivity, specificity and accuracy of system in classifying the level of infection is 100%, 80 % and 93% respectively. This system was tested on a microscopic sputum image database of RSUD Dr. Soetomo from a different patient.
{"title":"Classification and Counting of Mycobacterium Tuberculosis from Sputum Microscopic Image using Fuzzy Logic","authors":"Nilam Ade Pangestu, R. Sigit, T. Harsono, Manik Retno Wahyunitisari, A. Anwar, Dinda Ayu Yunitasari","doi":"10.1109/IES50839.2020.9231925","DOIUrl":"https://doi.org/10.1109/IES50839.2020.9231925","url":null,"abstract":"The diagnosis of tuberculosis (TB) is done by detecting and counting the number of mycobacterium tuberculosis in a sputum examination done manually using a microscope. It is considered ineffective because it requires a long time and different diagnostic results. To overcome this problem, this paper implements digital image processing. There are 5 processes used on the system. Preprocessing with the RGB to HSV method is used to clarify the color of the image. Segmentation to separate objects from background images using thresholding. Feature extraction to get the value of area, perimeter, and level of roundness of the object. Classification uses fuzzy logic to classify mycobacterium tuberculosis based on features. The next is the process of counting mycobacterium tuberculosis. And the last is the process of classify into IUATLD scale based on the number of mycobacterium tuberculosis. From the results of tests conducted on 15 data, the system show that the level of accuracy, precision, sensitivity and specificity of system in calculate mycobacterium tuberculosis is 89%, 90%, 91.66% and 78.88% respectively. And also level of sensitivity, specificity and accuracy of system in classifying the level of infection is 100%, 80 % and 93% respectively. This system was tested on a microscopic sputum image database of RSUD Dr. Soetomo from a different patient.","PeriodicalId":344685,"journal":{"name":"2020 International Electronics Symposium (IES)","volume":"93 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127060570","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 : 2020-09-01DOI: 10.1109/IES50839.2020.9231855
E. Purwanto, Mentari Putri Jati, B. Sumantri, Muhammad Rizani Rusli
High-efficiency power electronics devices are necessary for induction motor drives. Moreover, induction motors have high usage rates. One efficient type is the AC-AC matrix converter with the advantage of single-stage conversion only. However, this type of converter has a big challenge when applied to the dynamic speed application on the induction motor because of its complexity. Generally, the type of speed controller which is widely used is the proportional-integral (PI) controller. Nevertheless, when applied in induction motor applications which are nonlinear systems with dynamic speed applications accompanied by complex converters, PI has some disadvantages. On the other hand, fuzzy logic offers the ability to handle nonlinear plants capable of covering the limitations of PI. The combination of these two controllers is called Fuzzy Supervisory Control (FSC). It is the best solution when applied to enhance dynamic performance. From the dynamic speed response simulation, the FSC produces 60% lower average total dynamic performance score than the PI. The lower the score the dynamic speed performance will be better. The performance of the FSC is also robust when handling the disturbance from the system. Based on this study, it can be analyzed that the FSC was able to enhance the dynamic performance of matrix converters fed induction motor drives.
{"title":"Performance Enhancement of Matrix Converter Fed Induction Motor Drives Using Fuzzy Supervisory Controller","authors":"E. Purwanto, Mentari Putri Jati, B. Sumantri, Muhammad Rizani Rusli","doi":"10.1109/IES50839.2020.9231855","DOIUrl":"https://doi.org/10.1109/IES50839.2020.9231855","url":null,"abstract":"High-efficiency power electronics devices are necessary for induction motor drives. Moreover, induction motors have high usage rates. One efficient type is the AC-AC matrix converter with the advantage of single-stage conversion only. However, this type of converter has a big challenge when applied to the dynamic speed application on the induction motor because of its complexity. Generally, the type of speed controller which is widely used is the proportional-integral (PI) controller. Nevertheless, when applied in induction motor applications which are nonlinear systems with dynamic speed applications accompanied by complex converters, PI has some disadvantages. On the other hand, fuzzy logic offers the ability to handle nonlinear plants capable of covering the limitations of PI. The combination of these two controllers is called Fuzzy Supervisory Control (FSC). It is the best solution when applied to enhance dynamic performance. From the dynamic speed response simulation, the FSC produces 60% lower average total dynamic performance score than the PI. The lower the score the dynamic speed performance will be better. The performance of the FSC is also robust when handling the disturbance from the system. Based on this study, it can be analyzed that the FSC was able to enhance the dynamic performance of matrix converters fed induction motor drives.","PeriodicalId":344685,"journal":{"name":"2020 International Electronics Symposium (IES)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129587108","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 : 2020-09-01DOI: 10.1109/IES50839.2020.9231676
Rika Rokhana, Wiwiet Herulambang, R. Indraswari
Melanoma is the most aggressive of all skin cancers and its incidence has reached epidemic proportions. It is important to distinguish between benign and malignant melanoma as early as possible to increase the chance of recovery. The development of computational technology, especially machine learning and computer vision, made it possible to classify diseases based on their image. Detection of a disease by using image is beneficial because it can be done more easily, cheaply, quickly, and non-invasively than by using biopsy. The use of conventional machine learning and computer vision method makes their classification performance highly affected by the segmentation result of the skin lesion and the features selected for the classification process. The recent development of deep learning algorithm, such as CNN (Convolutional Neural Network), makes it possible to classify images without going through the process of image segmentation and manual features determination and give high performance with enough training data. Therefore, in this research we propose a deep convolutional neural network (CNN) to classify melanoma images into benign and malignant class. The proposed network architecture consists of several sets of convolutional layers and max-pooling layers, followed by a drop out layer and a fully-connected layer. From the experimental results on 352 test images, the proposed network gives the accuracy, sensitivity, and specificity of 84.76%, 91.97%, and 78.71%. The good performance of the built model hopefully can be developed for real application that can assist the expert to make better diagnosis and treatment.
{"title":"Deep Convolutional Neural Network for Melanoma Image Classification","authors":"Rika Rokhana, Wiwiet Herulambang, R. Indraswari","doi":"10.1109/IES50839.2020.9231676","DOIUrl":"https://doi.org/10.1109/IES50839.2020.9231676","url":null,"abstract":"Melanoma is the most aggressive of all skin cancers and its incidence has reached epidemic proportions. It is important to distinguish between benign and malignant melanoma as early as possible to increase the chance of recovery. The development of computational technology, especially machine learning and computer vision, made it possible to classify diseases based on their image. Detection of a disease by using image is beneficial because it can be done more easily, cheaply, quickly, and non-invasively than by using biopsy. The use of conventional machine learning and computer vision method makes their classification performance highly affected by the segmentation result of the skin lesion and the features selected for the classification process. The recent development of deep learning algorithm, such as CNN (Convolutional Neural Network), makes it possible to classify images without going through the process of image segmentation and manual features determination and give high performance with enough training data. Therefore, in this research we propose a deep convolutional neural network (CNN) to classify melanoma images into benign and malignant class. The proposed network architecture consists of several sets of convolutional layers and max-pooling layers, followed by a drop out layer and a fully-connected layer. From the experimental results on 352 test images, the proposed network gives the accuracy, sensitivity, and specificity of 84.76%, 91.97%, and 78.71%. The good performance of the built model hopefully can be developed for real application that can assist the expert to make better diagnosis and treatment.","PeriodicalId":344685,"journal":{"name":"2020 International Electronics Symposium (IES)","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128131700","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 : 2020-09-01DOI: 10.1109/IES50839.2020.9231838
Bobby Efendy, E. Ekawati, Nazuwatussya'diyah, E. M. Budi
Electrocoagulation is a method of wastewater treatment that applies an electrical current into the liquid to coagulate the suspended particles. This study assessed two control strategies for electrocoagulation systems in wastewater treatment in terms of dynamic performances and energy consumptions. The first control strategy used the electrical current as a manipulated variable, and the second used the waste liquid flowrate instead. For either strategy, the controlled output was the turbidity of the product liquid. The assessment was conducted in an experimental setting, in a laboratory-scale, continuous pilot plant. The experiment began with the identification of the dynamic characteristics of the electrocoagulation process due to the combined changes in the electrical current between 1.8-5.2 Ampere and the changes in waste flowrate between 10.37-14.67 ml/s. First-Order-Process-with-Time-Delay equations approximated these processes. The statistical Analysis of Variance was used to select the best process condition to compare two control strategies. The associated Proportional Integral controllers were designed and applied for either strategy. The experiment showed that manipulating electrical current yield 7.48% longer settling time, but with significantly lower energy consumption throughout the electrocoagulation process. The result highlighted the benefit of using electrical current as of the manipulated variable in the electrocoagulation process in the pilot plant.
{"title":"Assessment of Electrocoagulation Control System Strategy in Textile Wastewater Treatment Plant","authors":"Bobby Efendy, E. Ekawati, Nazuwatussya'diyah, E. M. Budi","doi":"10.1109/IES50839.2020.9231838","DOIUrl":"https://doi.org/10.1109/IES50839.2020.9231838","url":null,"abstract":"Electrocoagulation is a method of wastewater treatment that applies an electrical current into the liquid to coagulate the suspended particles. This study assessed two control strategies for electrocoagulation systems in wastewater treatment in terms of dynamic performances and energy consumptions. The first control strategy used the electrical current as a manipulated variable, and the second used the waste liquid flowrate instead. For either strategy, the controlled output was the turbidity of the product liquid. The assessment was conducted in an experimental setting, in a laboratory-scale, continuous pilot plant. The experiment began with the identification of the dynamic characteristics of the electrocoagulation process due to the combined changes in the electrical current between 1.8-5.2 Ampere and the changes in waste flowrate between 10.37-14.67 ml/s. First-Order-Process-with-Time-Delay equations approximated these processes. The statistical Analysis of Variance was used to select the best process condition to compare two control strategies. The associated Proportional Integral controllers were designed and applied for either strategy. The experiment showed that manipulating electrical current yield 7.48% longer settling time, but with significantly lower energy consumption throughout the electrocoagulation process. The result highlighted the benefit of using electrical current as of the manipulated variable in the electrocoagulation process in the pilot plant.","PeriodicalId":344685,"journal":{"name":"2020 International Electronics Symposium (IES)","volume":"53 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125708838","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 : 2020-09-01DOI: 10.1109/IES50839.2020.9231875
A. Fariza, Mu’arifin, Amailina Puspitasari
Surabaya, one of the major cities in Indonesia, is an endemic area for spreading tuberculosis. Surabaya City Health Office in 2018 has found 7,007 cases of tuberculosis which is the highest case in East Java province. This data shows that TB is still a major health problem. TB risk mapping is needed to guide the Public Health Service in TB control planning, for example, the promotion of clean and healthy living behaviors, immunizations, and home visit programs and optimization of TB screening activities. This paper proposes the spatial risk mapping of tuberculosis based on several criteria that become tuberculosis risk factors using a fuzzy method called spatial fuzzy risk mapping. These criteria consist of the number of people with tuberculosis (BTA Positive), population density, unhealthy houses, and health facilities. Fuzzy multi-criteria decision making determines the weight value of each criterion, followed by the ranking process to select the best alternative from the sub-district areas. After fuzzy membership calculation, the sub-district areas area directly classified into 3 index level that is low, medium, and high according to the rule association. The determination of the TB disease risk index covers 31 sub-districts in Surabaya as densely populated urban areas. The risk map is visualized into spatial GIS mapping. In the last 3 years (2013-2015), there were 4 sub-districts are decreasing (12.9%), 6 sub-districts are increasing (19.4%) and the remaining 68.7% did not change. There are 13.33% sub-districts in 2015 that are defined as low risk by the fuzzy risk, but it must be high risk by the Public Health Service. The fuzzy risk index results appropriate with the real condition and it is suitable with the Public Health Service report.
{"title":"Spatial Fuzzy Risk Mapping for Tuberculosis in Surabaya, Indonesia","authors":"A. Fariza, Mu’arifin, Amailina Puspitasari","doi":"10.1109/IES50839.2020.9231875","DOIUrl":"https://doi.org/10.1109/IES50839.2020.9231875","url":null,"abstract":"Surabaya, one of the major cities in Indonesia, is an endemic area for spreading tuberculosis. Surabaya City Health Office in 2018 has found 7,007 cases of tuberculosis which is the highest case in East Java province. This data shows that TB is still a major health problem. TB risk mapping is needed to guide the Public Health Service in TB control planning, for example, the promotion of clean and healthy living behaviors, immunizations, and home visit programs and optimization of TB screening activities. This paper proposes the spatial risk mapping of tuberculosis based on several criteria that become tuberculosis risk factors using a fuzzy method called spatial fuzzy risk mapping. These criteria consist of the number of people with tuberculosis (BTA Positive), population density, unhealthy houses, and health facilities. Fuzzy multi-criteria decision making determines the weight value of each criterion, followed by the ranking process to select the best alternative from the sub-district areas. After fuzzy membership calculation, the sub-district areas area directly classified into 3 index level that is low, medium, and high according to the rule association. The determination of the TB disease risk index covers 31 sub-districts in Surabaya as densely populated urban areas. The risk map is visualized into spatial GIS mapping. In the last 3 years (2013-2015), there were 4 sub-districts are decreasing (12.9%), 6 sub-districts are increasing (19.4%) and the remaining 68.7% did not change. There are 13.33% sub-districts in 2015 that are defined as low risk by the fuzzy risk, but it must be high risk by the Public Health Service. The fuzzy risk index results appropriate with the real condition and it is suitable with the Public Health Service report.","PeriodicalId":344685,"journal":{"name":"2020 International Electronics Symposium (IES)","volume":"41 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133096800","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 : 2020-09-01DOI: 10.1109/IES50839.2020.9231734
Faris Atoil Haq, B. S. B. Dewantara, Bayu Sandi Marta
ATRACTBOT (Autonomous Trash Can Robot) is a social robot that is equipped with Artificial Intelligence (AI) to carry out its task of collecting waste while still involving humans to raise awareness to dispose of trash in its place. The robot is designed to work indoors, so the ability to map workspaces is needed. In this paper, room mapping is done using eight ultrasonic sensors arranged in such a way that it covers an area of 360 degrees around the robot. The robot moves through the room automatically by using the Braitenberg control method to map the entire room. The experimental results show that the robot succeeded in mapping the room by distinguishing the different color plots for free space and occupied space.
{"title":"Room Mapping using Ultrasonic Range Sensor on the ATRACBOT (Autonomous Trash Can Robot): A Simulation Approach","authors":"Faris Atoil Haq, B. S. B. Dewantara, Bayu Sandi Marta","doi":"10.1109/IES50839.2020.9231734","DOIUrl":"https://doi.org/10.1109/IES50839.2020.9231734","url":null,"abstract":"ATRACTBOT (Autonomous Trash Can Robot) is a social robot that is equipped with Artificial Intelligence (AI) to carry out its task of collecting waste while still involving humans to raise awareness to dispose of trash in its place. The robot is designed to work indoors, so the ability to map workspaces is needed. In this paper, room mapping is done using eight ultrasonic sensors arranged in such a way that it covers an area of 360 degrees around the robot. The robot moves through the room automatically by using the Braitenberg control method to map the entire room. The experimental results show that the robot succeeded in mapping the room by distinguishing the different color plots for free space and occupied space.","PeriodicalId":344685,"journal":{"name":"2020 International Electronics Symposium (IES)","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132197946","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 : 2020-09-01DOI: 10.1109/IES50839.2020.9231780
Mufid Murtadho, Eka Prasetyono, D. O. Anggriawan
Photovoltaic is one of the alternative electric producers that is widely used considering the availability of the main source of photovoltaic. The photovoltaic as an electrical energy source, it also to pay more attention to the risks that can cause the failure with the worst is an event of a fire. The fault causes the failure is parallel DC arc fault. However, Parallel DC Arc Fault cannot be detected by the conventional safety device such as Circuit Breaker. Therefore, the proposed algorithm fast Fourier transform is designed to detect and identify the event of the parallel arc fault. To identify the parallel arc fault and its characteristic, simulation using PSIM is used to get the current waveform of the parallel arc fault. To see the characteristic of the arc fault current, the initial current flow through the arc generator is needed. The order condition in the simulation is Short Circuit, Arc Fault, and then the Normal condition. The sum of the frequency spectrum is used as the method of comparing normal condition and fault condition with the result is the sum of the frequency spectrum during arc fault condition has a bigger value than normal condition. Moreover, the simulation result shows that the proposed algorithm has the accurate result for parallel arc fault detection.
{"title":"Detection of Parallel Arc Fault on Photovoltaic System Based on Fast Fourier Transform","authors":"Mufid Murtadho, Eka Prasetyono, D. O. Anggriawan","doi":"10.1109/IES50839.2020.9231780","DOIUrl":"https://doi.org/10.1109/IES50839.2020.9231780","url":null,"abstract":"Photovoltaic is one of the alternative electric producers that is widely used considering the availability of the main source of photovoltaic. The photovoltaic as an electrical energy source, it also to pay more attention to the risks that can cause the failure with the worst is an event of a fire. The fault causes the failure is parallel DC arc fault. However, Parallel DC Arc Fault cannot be detected by the conventional safety device such as Circuit Breaker. Therefore, the proposed algorithm fast Fourier transform is designed to detect and identify the event of the parallel arc fault. To identify the parallel arc fault and its characteristic, simulation using PSIM is used to get the current waveform of the parallel arc fault. To see the characteristic of the arc fault current, the initial current flow through the arc generator is needed. The order condition in the simulation is Short Circuit, Arc Fault, and then the Normal condition. The sum of the frequency spectrum is used as the method of comparing normal condition and fault condition with the result is the sum of the frequency spectrum during arc fault condition has a bigger value than normal condition. Moreover, the simulation result shows that the proposed algorithm has the accurate result for parallel arc fault detection.","PeriodicalId":344685,"journal":{"name":"2020 International Electronics Symposium (IES)","volume":"34 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125750225","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 : 2020-09-01DOI: 10.1109/IES50839.2020.9231722
Ischia Kurniawati, J. Pratilastiarso, D. Satrio
The condenser is one component that has an important role in the operation of the coal-fired power plant. Changes in the conditions of cooling water have an impact on the thermal performance of the condenser in the condensation process. This study aims to determine changes in the performance of the condenser under changing cooling water conditions which also results in cycle efficiency. In this research, a power plant cycle model which is given a constant load of 350 MW is performed on the Cycle-Tempo. In this study, temperature and flow rate are two parameters that will vary in value. The results of this study indicate that the increase in cooling water temperature causes the heat transfer rate and the pressure inside the condenser to get higher. Conversely, the greater flow rate causes the heat transfer rate and condenser pressure to decrease. The highest heat transfer rate and pressure values of 330723.47 kW and 0.0117 MPa were obtained in the variation of cooling water at the highest temperature of 308 K and the lowest flow rate of 13888.9 kg/s. It affects on decreasing of the cycle efficiency. The solution to maintain efficiency is by adding more cooling water flow rate, about 15% - 21% for each 1 K temperature increasing step.
{"title":"Analysis of the Effect of Cooling Water Condenser to Power Plant Cycle Using Cycle-Tempo Software","authors":"Ischia Kurniawati, J. Pratilastiarso, D. Satrio","doi":"10.1109/IES50839.2020.9231722","DOIUrl":"https://doi.org/10.1109/IES50839.2020.9231722","url":null,"abstract":"The condenser is one component that has an important role in the operation of the coal-fired power plant. Changes in the conditions of cooling water have an impact on the thermal performance of the condenser in the condensation process. This study aims to determine changes in the performance of the condenser under changing cooling water conditions which also results in cycle efficiency. In this research, a power plant cycle model which is given a constant load of 350 MW is performed on the Cycle-Tempo. In this study, temperature and flow rate are two parameters that will vary in value. The results of this study indicate that the increase in cooling water temperature causes the heat transfer rate and the pressure inside the condenser to get higher. Conversely, the greater flow rate causes the heat transfer rate and condenser pressure to decrease. The highest heat transfer rate and pressure values of 330723.47 kW and 0.0117 MPa were obtained in the variation of cooling water at the highest temperature of 308 K and the lowest flow rate of 13888.9 kg/s. It affects on decreasing of the cycle efficiency. The solution to maintain efficiency is by adding more cooling water flow rate, about 15% - 21% for each 1 K temperature increasing step.","PeriodicalId":344685,"journal":{"name":"2020 International Electronics Symposium (IES)","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126147128","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 : 2020-09-01DOI: 10.1109/IES50839.2020.9231928
Fachrul Rozie, I. Syarif, M. A. Al Rasyid
Aquaponics is a merging of agriculture and aquaculture culture systems that may provide a solution to overcome land and water limitations and food security. Water quality in fishponds is a determining factor in aquaculture and is still much needed to be studied extensively. However, evaluating the quality of ponds proves to be a challenging task, mainly due to a lack of data and the constant maintenance involved in handling and controlling water quality. This study aims to develop water quality management systems for catfish ponds by utilizing aquaponics technology and IoT technology, combined with water quality control systems with artificial intelligence fuzzy logic to control temperature and ammonia levels, which are important variables in maintaining water quality. This study additionally makes it easy for farmers to monitor pH parameters, Turbidity, Total Dissolved Solid (TDS), Dissolved Oxygen and Water Level, and receive information related to the pond anytime and anywhere. If the pond water quality is not at an optimal state, farmers can directly intervene and carry out the needed measures as soon as possible. Experiments on monitoring, warning, and control systems were successfully employed.
{"title":"Design and implementation of Intelligent Aquaponics Monitoring System based on IoT","authors":"Fachrul Rozie, I. Syarif, M. A. Al Rasyid","doi":"10.1109/IES50839.2020.9231928","DOIUrl":"https://doi.org/10.1109/IES50839.2020.9231928","url":null,"abstract":"Aquaponics is a merging of agriculture and aquaculture culture systems that may provide a solution to overcome land and water limitations and food security. Water quality in fishponds is a determining factor in aquaculture and is still much needed to be studied extensively. However, evaluating the quality of ponds proves to be a challenging task, mainly due to a lack of data and the constant maintenance involved in handling and controlling water quality. This study aims to develop water quality management systems for catfish ponds by utilizing aquaponics technology and IoT technology, combined with water quality control systems with artificial intelligence fuzzy logic to control temperature and ammonia levels, which are important variables in maintaining water quality. This study additionally makes it easy for farmers to monitor pH parameters, Turbidity, Total Dissolved Solid (TDS), Dissolved Oxygen and Water Level, and receive information related to the pond anytime and anywhere. If the pond water quality is not at an optimal state, farmers can directly intervene and carry out the needed measures as soon as possible. Experiments on monitoring, warning, and control systems were successfully employed.","PeriodicalId":344685,"journal":{"name":"2020 International Electronics Symposium (IES)","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126223985","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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