Pub Date : 2021-04-28DOI: 10.1109/AIMS52415.2021.9466008
Via Indira Kurnia, Natasia Sekarning Tiyas, Brian Pamukti, K. Sujatmoko
This research is analyzing the performance of light interference from another vehicle in Vehicle-to-Vehicle Communication (V2V) using Visible Light Communication (VLC) in order to be known the maximum distance between vehicles can communicate, thereby minimizing the possibility of accidents and density on the highway. This simulation uses On-Off Keying Non Return to Zero (OOK-NRZ) modulation technique with Line of Sight (LoS) channel model and the addition of optical concentrator in photodetector. Simulation is carried out at night conditions with interference from light emitted by another vehicle. The main parameters in this simulation are Bit Error Rate (BER) with reference value of 10−3 and Signal to Interference and Noise Ratio (SINR). From the simulation results, the condition without interference obtained maximum distance between vehicles can communicate well as far as 15.5 meters. When there is interference, the maximum distance the vehicle can communicate is reduced to 14 meters. The presence of interference, the performance of the system becomes worse and the maximum distance of communication between vehicles becomes reduced, with a decrease in communication distance between vehicles of 9,677%. Without interference from another vehicle, SNR value is obtained at a minimum distance $d$ of 18.2 dB. While there is interference, SINR value of 15.3 dB is obtained.
{"title":"Interference Analysis for Vehicle to Vehicle Communication Using Visible Light Communication","authors":"Via Indira Kurnia, Natasia Sekarning Tiyas, Brian Pamukti, K. Sujatmoko","doi":"10.1109/AIMS52415.2021.9466008","DOIUrl":"https://doi.org/10.1109/AIMS52415.2021.9466008","url":null,"abstract":"This research is analyzing the performance of light interference from another vehicle in Vehicle-to-Vehicle Communication (V2V) using Visible Light Communication (VLC) in order to be known the maximum distance between vehicles can communicate, thereby minimizing the possibility of accidents and density on the highway. This simulation uses On-Off Keying Non Return to Zero (OOK-NRZ) modulation technique with Line of Sight (LoS) channel model and the addition of optical concentrator in photodetector. Simulation is carried out at night conditions with interference from light emitted by another vehicle. The main parameters in this simulation are Bit Error Rate (BER) with reference value of 10−3 and Signal to Interference and Noise Ratio (SINR). From the simulation results, the condition without interference obtained maximum distance between vehicles can communicate well as far as 15.5 meters. When there is interference, the maximum distance the vehicle can communicate is reduced to 14 meters. The presence of interference, the performance of the system becomes worse and the maximum distance of communication between vehicles becomes reduced, with a decrease in communication distance between vehicles of 9,677%. Without interference from another vehicle, SNR value is obtained at a minimum distance $d$ of 18.2 dB. While there is interference, SINR value of 15.3 dB is obtained.","PeriodicalId":299121,"journal":{"name":"2021 International Conference on Artificial Intelligence and Mechatronics Systems (AIMS)","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-04-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127648909","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 : 2021-04-28DOI: 10.1109/AIMS52415.2021.9466077
Raufani Aminullah A., Muhammad Nasrun, C. Setianingsih
In the era of globalization, the introduction of emotions into research topics is currently used in specific fields, especially in computer-human interactions. Often, we recognize someone's emotions only through facial expressions. Another way that can be done is that we can recognize someone's emotions through sound signals. In this study, a human emotion detection system using sound signals was used with the feature extraction method, namely the Mel-Frequency Cepstral Coefficient (MFCC). This method was chosen because MFCC approaches the human auditory system's response more closely than other systems. Support Vector Machine (SVM) is the newest data classification method developed by Chervonenkis and Vapnik in the 1990s. SVM is supervised machine learning that is often used to classify human speech recognition in many studies. In several previous studies, the commonly used kernel from SVM Multi-Class was the RBF kernel. This is because SVM uses the Radial Basis Function (RBF) kernel to have better accuracy. The highest accuracy ratio of this study was 72.5%, with a frame size of 0.001 seconds, 80 filter banks, [0.3 - 0.7] gamma, and 1.0 C values.
{"title":"Human Emotion Detection with Speech Recognition Using Mel-frequency Cepstral Coefficient and Support Vector Machine","authors":"Raufani Aminullah A., Muhammad Nasrun, C. Setianingsih","doi":"10.1109/AIMS52415.2021.9466077","DOIUrl":"https://doi.org/10.1109/AIMS52415.2021.9466077","url":null,"abstract":"In the era of globalization, the introduction of emotions into research topics is currently used in specific fields, especially in computer-human interactions. Often, we recognize someone's emotions only through facial expressions. Another way that can be done is that we can recognize someone's emotions through sound signals. In this study, a human emotion detection system using sound signals was used with the feature extraction method, namely the Mel-Frequency Cepstral Coefficient (MFCC). This method was chosen because MFCC approaches the human auditory system's response more closely than other systems. Support Vector Machine (SVM) is the newest data classification method developed by Chervonenkis and Vapnik in the 1990s. SVM is supervised machine learning that is often used to classify human speech recognition in many studies. In several previous studies, the commonly used kernel from SVM Multi-Class was the RBF kernel. This is because SVM uses the Radial Basis Function (RBF) kernel to have better accuracy. The highest accuracy ratio of this study was 72.5%, with a frame size of 0.001 seconds, 80 filter banks, [0.3 - 0.7] gamma, and 1.0 C values.","PeriodicalId":299121,"journal":{"name":"2021 International Conference on Artificial Intelligence and Mechatronics Systems (AIMS)","volume":"88 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-04-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124167095","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 : 2021-04-28DOI: 10.1109/AIMS52415.2021.9466051
A. Turnip, Gilbert F. Y. Sihombing, Giraldo F. J. Sihombing, S. P. Gultom, Darmawan Hidayat
Development of ion selective electrodes of mercury (ISE-Hg) using ionophores has been widely used in previous studies. However, in this study the used ionophores were prepared by synthesizing an active compound of a base material 1,4,10,13-tetraoxa-7,16-diazacyclooctadecane (by adduct via a ratio of 3:10) to yield 7.16-dithenoyl ionophore - 1,4,10,13-tetraoxsa-7,16-diazacyclooctadecane (DTODC). The membrane as an ISE electrode component is made from a mixture of the synthesis of the DTODC, PVC, KTpClPB and the THF. A comparison result of characterization with Ag/AgCl electrode shows that the ISE of azacrown derivative ionophorant compounds with high sensitivity and selectivity in the determination of mercury metal ion levels is obtained.
{"title":"High Sensitivity and Selectivity of Mercury Sensor Based Membrane Ion Selective Electrode with Sputtring Method","authors":"A. Turnip, Gilbert F. Y. Sihombing, Giraldo F. J. Sihombing, S. P. Gultom, Darmawan Hidayat","doi":"10.1109/AIMS52415.2021.9466051","DOIUrl":"https://doi.org/10.1109/AIMS52415.2021.9466051","url":null,"abstract":"Development of ion selective electrodes of mercury (ISE-Hg) using ionophores has been widely used in previous studies. However, in this study the used ionophores were prepared by synthesizing an active compound of a base material 1,4,10,13-tetraoxa-7,16-diazacyclooctadecane (by adduct via a ratio of 3:10) to yield 7.16-dithenoyl ionophore - 1,4,10,13-tetraoxsa-7,16-diazacyclooctadecane (DTODC). The membrane as an ISE electrode component is made from a mixture of the synthesis of the DTODC, PVC, KTpClPB and the THF. A comparison result of characterization with Ag/AgCl electrode shows that the ISE of azacrown derivative ionophorant compounds with high sensitivity and selectivity in the determination of mercury metal ion levels is obtained.","PeriodicalId":299121,"journal":{"name":"2021 International Conference on Artificial Intelligence and Mechatronics Systems (AIMS)","volume":"116 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-04-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116280655","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 : 2021-04-28DOI: 10.1109/AIMS52415.2021.9466072
Mehreen Naeem, Muhammad Jawad Khan, Talha Yousf
Real-time eyeball recognition and tracking using digital image processing techniques can give a way of communication. This paper presents the algorithm for tracking the position of eyes in real-time. The following method consists of two steps: face detection and eye-tracking. In vision-based human-computer interaction, skin color for face detection provides a useful cue. Firstly, face detection is done by combining RGB pixel color, HSI (Hue Saturation Intensity) and YCbCr (Luminance Chrome Blue Chrome Red) color based techniques. Then crop the colored face image from the image and divide cropped image into horizontal sections. As eyes are on the upper part of the face so we have used the speeded up robust features (SURF) key points based method on that section and select the strongest point which is located on the eye region. The eye region is segmented by pixel color techniques. Based on the proposed algorithm possibility of false eye detection is reduced. Experimental results show satisfactory performance in a real-time video stream with average accuracy of 97.2%.
{"title":"Eyeball Identification and Tracking using Digital Image Processing","authors":"Mehreen Naeem, Muhammad Jawad Khan, Talha Yousf","doi":"10.1109/AIMS52415.2021.9466072","DOIUrl":"https://doi.org/10.1109/AIMS52415.2021.9466072","url":null,"abstract":"Real-time eyeball recognition and tracking using digital image processing techniques can give a way of communication. This paper presents the algorithm for tracking the position of eyes in real-time. The following method consists of two steps: face detection and eye-tracking. In vision-based human-computer interaction, skin color for face detection provides a useful cue. Firstly, face detection is done by combining RGB pixel color, HSI (Hue Saturation Intensity) and YCbCr (Luminance Chrome Blue Chrome Red) color based techniques. Then crop the colored face image from the image and divide cropped image into horizontal sections. As eyes are on the upper part of the face so we have used the speeded up robust features (SURF) key points based method on that section and select the strongest point which is located on the eye region. The eye region is segmented by pixel color techniques. Based on the proposed algorithm possibility of false eye detection is reduced. Experimental results show satisfactory performance in a real-time video stream with average accuracy of 97.2%.","PeriodicalId":299121,"journal":{"name":"2021 International Conference on Artificial Intelligence and Mechatronics Systems (AIMS)","volume":"60 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-04-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124646414","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 : 2021-04-28DOI: 10.1109/AIMS52415.2021.9466048
U. Ghafoor, M. N. A. Khan, K. Hong
Motor imagery (MI) is the most favorable brain action exploited in motor deficit rehabilitation. The hemodynamic response (HR) signal is usually weak, which can be enhanced with specific methods. In this research, the improvement in the HR was examined while the participants performed the MI task of right-hand movement. Brain signals, i.e., concentration changes in oxyhemoglobin ($Deltatext{HbO}$) from the left sensorimotor cortex, were attained through functional near-infrared spectroscopy. The experiment was executed in 2 sessions. The first session consisted of the performance of the MI task without visual training. Whereas in the last session, the MI task was performed but with the visual training: A videotape was played on the computer screen that presented a person moving his right hand, repeatedly; the purpose was to help in enhancing the imaginations and, therefore, improving the HR. The t-values between the measured HR and the designed hemodynamics response function were calculated to check certain channels' activeness. Later, the trials of active channels were averaged to obtain mean $Deltatext{HbO}$. MI task with visual training showed elevated activation in $Deltatext{HbO}$. Furthermore, linear discriminant analysis was utilized to classify signals by taking the mean and maximum of HR resulting in mean classification accuracy of 65% and 80% for MI tasks with- and without visual training. These results reflected an enhancement in MI ability through visual training, which will help patients' rehabilitation and BCI applications.
{"title":"Visual Training Improves Motor Imagery Ability for Rehabilitation","authors":"U. Ghafoor, M. N. A. Khan, K. Hong","doi":"10.1109/AIMS52415.2021.9466048","DOIUrl":"https://doi.org/10.1109/AIMS52415.2021.9466048","url":null,"abstract":"Motor imagery (MI) is the most favorable brain action exploited in motor deficit rehabilitation. The hemodynamic response (HR) signal is usually weak, which can be enhanced with specific methods. In this research, the improvement in the HR was examined while the participants performed the MI task of right-hand movement. Brain signals, i.e., concentration changes in oxyhemoglobin ($Deltatext{HbO}$) from the left sensorimotor cortex, were attained through functional near-infrared spectroscopy. The experiment was executed in 2 sessions. The first session consisted of the performance of the MI task without visual training. Whereas in the last session, the MI task was performed but with the visual training: A videotape was played on the computer screen that presented a person moving his right hand, repeatedly; the purpose was to help in enhancing the imaginations and, therefore, improving the HR. The t-values between the measured HR and the designed hemodynamics response function were calculated to check certain channels' activeness. Later, the trials of active channels were averaged to obtain mean $Deltatext{HbO}$. MI task with visual training showed elevated activation in $Deltatext{HbO}$. Furthermore, linear discriminant analysis was utilized to classify signals by taking the mean and maximum of HR resulting in mean classification accuracy of 65% and 80% for MI tasks with- and without visual training. These results reflected an enhancement in MI ability through visual training, which will help patients' rehabilitation and BCI applications.","PeriodicalId":299121,"journal":{"name":"2021 International Conference on Artificial Intelligence and Mechatronics Systems (AIMS)","volume":"25 1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-04-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128643615","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 : 2021-04-28DOI: 10.1109/AIMS52415.2021.9466089
Purwanto, Hermawan, Suherman, D. A. Widodo, N. Iksan
The implementation of smart grid on a micro scale in this study was for household electricity fulfillment needs. The use of renewable energy sources such as solar power will be integrated through a smart grid so that households can become independent in providing electricity and not depend on state electricity. Besides, it can also reduce monthly electricity costs when integrated with the state electricity network. Smart Micro Grid also enables the availability of energy management services such as monitoring, prediction, forecasting, scheduling and decision-making that was supported by some technologies such as artificial intelligent, smart sensors so that consumer use of electricity was more efficient. In this research, the forecasting method developed using the Deep Neural Network (DNN) and the Gate Recurrent Unit (GRU) as the architectural model. The GRU model was chosen because it has better performance compared to other models, namely LSTM, Auto-LSTM, Auto-GRU with MAE and MSE values of 0.0342 and 0.00245.
{"title":"Renewable Energy Generation Forecasting on Smart Home Micro Grid using Deep Neural Network","authors":"Purwanto, Hermawan, Suherman, D. A. Widodo, N. Iksan","doi":"10.1109/AIMS52415.2021.9466089","DOIUrl":"https://doi.org/10.1109/AIMS52415.2021.9466089","url":null,"abstract":"The implementation of smart grid on a micro scale in this study was for household electricity fulfillment needs. The use of renewable energy sources such as solar power will be integrated through a smart grid so that households can become independent in providing electricity and not depend on state electricity. Besides, it can also reduce monthly electricity costs when integrated with the state electricity network. Smart Micro Grid also enables the availability of energy management services such as monitoring, prediction, forecasting, scheduling and decision-making that was supported by some technologies such as artificial intelligent, smart sensors so that consumer use of electricity was more efficient. In this research, the forecasting method developed using the Deep Neural Network (DNN) and the Gate Recurrent Unit (GRU) as the architectural model. The GRU model was chosen because it has better performance compared to other models, namely LSTM, Auto-LSTM, Auto-GRU with MAE and MSE values of 0.0342 and 0.00245.","PeriodicalId":299121,"journal":{"name":"2021 International Conference on Artificial Intelligence and Mechatronics Systems (AIMS)","volume":"71 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-04-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129362368","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 : 2021-04-28DOI: 10.1109/AIMS52415.2021.9466087
Deny Jollyta, S. Efendi, M. Zarlis, H. Mawengkang
Clustering is one of the data analysis activities for grouping data into several categories with the same characteristics based on certain criteria. The problem that often arises in the clustering process is getting optimal clustering results. So far there is no fixed provision to regulate the number of clusters and the type of data that must be placed in each cluster and also there is no optimal size for data grouping. By using a combinatorial optimization approach, a model that is able to group data optimally was developed. The solution was presented as a decision in the form of 0 and 1. The cluster data model was linearized to obtain cluster optimization. To obtain accurate information from a group of data, the results of this study can be used as an alternative solution for cluster optimization problems.
{"title":"A Combinatorial Optimization Approach to Determining Optimal Data in Cluster","authors":"Deny Jollyta, S. Efendi, M. Zarlis, H. Mawengkang","doi":"10.1109/AIMS52415.2021.9466087","DOIUrl":"https://doi.org/10.1109/AIMS52415.2021.9466087","url":null,"abstract":"Clustering is one of the data analysis activities for grouping data into several categories with the same characteristics based on certain criteria. The problem that often arises in the clustering process is getting optimal clustering results. So far there is no fixed provision to regulate the number of clusters and the type of data that must be placed in each cluster and also there is no optimal size for data grouping. By using a combinatorial optimization approach, a model that is able to group data optimally was developed. The solution was presented as a decision in the form of 0 and 1. The cluster data model was linearized to obtain cluster optimization. To obtain accurate information from a group of data, the results of this study can be used as an alternative solution for cluster optimization problems.","PeriodicalId":299121,"journal":{"name":"2021 International Conference on Artificial Intelligence and Mechatronics Systems (AIMS)","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-04-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132007240","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 : 2021-04-28DOI: 10.1109/AIMS52415.2021.9466090
M. Nurohim, M. Asvial
Machine to Machine (M2M) and Internet of Things (IoT) communications were predicted to grow very fast, especially M2M/IoT communications that use cellular networks for Internet connectivity. One of the M2M/IoT challenges over a cellular network was identifying the M2M/IoT device to differentiate it from regular mobile subscriber devices (human to human communication). Hence, this study recommended a numbering model as one of the M2M/IoT device identities. The study in this paper was carried out with a comprehensive survey on previous research, studying standardization, consultation documents, and existing regulatory conditions in Indonesia related to the numbering plan following the recommendation of ITU-T E.164 (The international public telecommunication numbering plan). Finally, this paper recommended two numbering options that can be implemented in Indonesia and several recommendations for further research related to the M2M/IoT numbering plan.
{"title":"A Feasibility Study of M2M/IoT Numbering Model in Indonesia","authors":"M. Nurohim, M. Asvial","doi":"10.1109/AIMS52415.2021.9466090","DOIUrl":"https://doi.org/10.1109/AIMS52415.2021.9466090","url":null,"abstract":"Machine to Machine (M2M) and Internet of Things (IoT) communications were predicted to grow very fast, especially M2M/IoT communications that use cellular networks for Internet connectivity. One of the M2M/IoT challenges over a cellular network was identifying the M2M/IoT device to differentiate it from regular mobile subscriber devices (human to human communication). Hence, this study recommended a numbering model as one of the M2M/IoT device identities. The study in this paper was carried out with a comprehensive survey on previous research, studying standardization, consultation documents, and existing regulatory conditions in Indonesia related to the numbering plan following the recommendation of ITU-T E.164 (The international public telecommunication numbering plan). Finally, this paper recommended two numbering options that can be implemented in Indonesia and several recommendations for further research related to the M2M/IoT numbering plan.","PeriodicalId":299121,"journal":{"name":"2021 International Conference on Artificial Intelligence and Mechatronics Systems (AIMS)","volume":"87 11","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-04-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"113986897","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 : 2021-04-28DOI: 10.1109/AIMS52415.2021.9466078
Kristin Natalia Gulo, Suhartomi, Albert Daniel Saragih, Martinus Ahmad Raif, Refi Ikhtiari
Citrus sinensis have potential resources of natural antioxidant content. This study aimed to identify the antioxidant potential, especially the flavonoid compounds in the extract of sweet orange peel (Citrus sinensis). The method of extraction was maceration in ethanol and ethyl acetate solvents. Willstatter, Bate-Smith, and FeCl3 tests were used to screen flavonoid compounds, and total flavonoid content was measured using an aluminum chloride colorimetric assay. Antioxidant activity was determined using the DPPH and H202 methods by taking the IC50 value. The total content of flavonoids was found higher in ethyl acetate extract ($242.48 pm 13.83 text{mg}$ QE/ gram DW) than in the ethanol extract. The most potent hydrogen peroxide inhibition activity and DPPH inhibition activity were found in the ethyl acetate extract through the value of IC50 511.63 µg/ml in DPPH and IC50 47.78 µg/ml in hydrogen peroxide. Therefore, ethyl acetate extract had the highest antioxidant potential and highest total flavonoid content.
柑桔具有潜在的天然抗氧化剂资源。本研究旨在鉴定甜橙皮提取物的抗氧化潜力，特别是黄酮类化合物。提取方法为乙醇浸渍法和乙酸乙酯浸渍法。使用Willstatter, bat - smith和FeCl3试验筛选类黄酮化合物，并使用氯化铝比色法测定总黄酮含量。采用DPPH法和H202法测定其抗氧化活性，取IC50值。乙酸乙酯提取物总黄酮含量($242.48 pm 13.83 text{mg}$ QE/ g DW)高于乙醇提取物。乙酸乙酯提取物对过氧化氢和DPPH的抑制活性最高，DPPH的IC50为511.63µg/ml，过氧化氢的IC50为47.78µg/ml。因此，乙酸乙酯提取物具有最高的抗氧化潜力和总黄酮含量。
{"title":"Antioxidant Activity of Flavonoid Compounds in Ethanol and Ethyl Acetate Extract from Citrus Sinensis","authors":"Kristin Natalia Gulo, Suhartomi, Albert Daniel Saragih, Martinus Ahmad Raif, Refi Ikhtiari","doi":"10.1109/AIMS52415.2021.9466078","DOIUrl":"https://doi.org/10.1109/AIMS52415.2021.9466078","url":null,"abstract":"Citrus sinensis have potential resources of natural antioxidant content. This study aimed to identify the antioxidant potential, especially the flavonoid compounds in the extract of sweet orange peel (Citrus sinensis). The method of extraction was maceration in ethanol and ethyl acetate solvents. Willstatter, Bate-Smith, and FeCl3 tests were used to screen flavonoid compounds, and total flavonoid content was measured using an aluminum chloride colorimetric assay. Antioxidant activity was determined using the DPPH and H202 methods by taking the IC50 value. The total content of flavonoids was found higher in ethyl acetate extract ($242.48 pm 13.83 text{mg}$ QE/ gram DW) than in the ethanol extract. The most potent hydrogen peroxide inhibition activity and DPPH inhibition activity were found in the ethyl acetate extract through the value of IC50 511.63 µg/ml in DPPH and IC50 47.78 µg/ml in hydrogen peroxide. Therefore, ethyl acetate extract had the highest antioxidant potential and highest total flavonoid content.","PeriodicalId":299121,"journal":{"name":"2021 International Conference on Artificial Intelligence and Mechatronics Systems (AIMS)","volume":"35 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-04-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123195456","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 : 2021-04-28DOI: 10.1109/AIMS52415.2021.9466069
Dzaki Alfarid, Darmawan Hidayat, N. Rohadi
Traffic violations in the campus area continue to increase. This violation against the direction by motorcyclists can endanger other riders and the perpetrator because it can lead to accidents. Therefore, we developed a Vehicle Detection Device Against Traffic Direction with the Maxsonar-EZ3 MB1030 Ultrasonic Sensor Based on Internet Of Things (IoT). This prototype uses two sensor nodes to transmit vehicle violation data against the direction. LoRa Shield with a radio signal frequency of 915 MHz is used to transmit data resulting from violations over a considerable distance. LoRa GPS Shield as a node to determine the coordinates of the location where the breach occurred. The reading and sending patterns of sensors are processed using the Arduino Uno Microcontroller and the results are displayed on the webserver page. This system uses The Things Network as a database of all data resulting from violations against the direction of motorbikes. The scenario in testing this device is to send violation data as well as the location and time of the accident. In this test, an average of 99.6% was reached in the accuracy of a GPS sending location coordinates. Then, testing in varying distances of transmission to test how faraway the data can be sent to the gateway. In this test scenario, it is carried out 100 times with different ranges. The results obtained are data sent excellently to a distance of almost 1 KM, with an average delay of 3 second.
校园内违反交通规则的情况持续增加。摩托车手的这种违反方向的行为可能会危及其他骑手和肇事者，因为它可能导致事故。因此，我们利用Maxsonar-EZ3 MB1030基于物联网的超声波传感器开发了一种针对交通方向的车辆检测装置。该原型使用两个传感器节点沿方向传输车辆违章数据。LoRa Shield的无线电信号频率为915 MHz，用于将违规造成的数据传输到相当远的距离。LoRa GPS Shield作为节点，用于确定泄露发生位置的坐标。传感器的读取和发送模式使用Arduino Uno微控制器进行处理，结果显示在web服务器页面上。该系统使用The Things Network作为数据库，包含所有因摩托车方向违规而产生的数据。测试该设备的场景是发送违规数据以及事故发生的地点和时间。在本次测试中，GPS发送位置坐标的平均精度达到99.6%。然后，在不同的传输距离中进行测试，以测试数据可以发送到网关的距离。在本测试场景中，在不同的范围内进行了100次。所获得的结果是数据被出色地发送到近1公里的距离，平均延迟为3秒。
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