Pub Date : 2021-04-28DOI: 10.1109/AIMS52415.2021.9466036
Makmur A. Zhào, R. Jayadi
Demand fluctuation is a critical factor in the everyday operating choices made by a restaurant. The aim of this study is to investigate menu demand forecasting in restaurants using Multiple Regression and Support Vector Regression Machine (SVR) algorithms to forecast potential visitors and menu demand using point-of-sale (POS) data. A model for predicting store-specific demand is proposed that takes into account variables such as seasonality, public holidays, and order peak times. The model's verification using fundamental restaurant data demonstrates that SVR will produce a percentage error of as low as 14.84 percent when forecasting restaurant guests and 31.2 percent when predicting restaurant menu demand. The results demonstrate that this approach is practical for forecasting revenue and consumer counts, as well as demonstrating that managers will learn about the variables that influence customer behaviors. There are extensive discussions and suggestions for potential studies on predicting and planning management in chain restaurant operations.
{"title":"Forecasting Daily Visitors and Menu Demands in an Indonesian Chain Restaurant using Support Vector Regression Machine","authors":"Makmur A. Zhào, R. Jayadi","doi":"10.1109/AIMS52415.2021.9466036","DOIUrl":"https://doi.org/10.1109/AIMS52415.2021.9466036","url":null,"abstract":"Demand fluctuation is a critical factor in the everyday operating choices made by a restaurant. The aim of this study is to investigate menu demand forecasting in restaurants using Multiple Regression and Support Vector Regression Machine (SVR) algorithms to forecast potential visitors and menu demand using point-of-sale (POS) data. A model for predicting store-specific demand is proposed that takes into account variables such as seasonality, public holidays, and order peak times. The model's verification using fundamental restaurant data demonstrates that SVR will produce a percentage error of as low as 14.84 percent when forecasting restaurant guests and 31.2 percent when predicting restaurant menu demand. The results demonstrate that this approach is practical for forecasting revenue and consumer counts, as well as demonstrating that managers will learn about the variables that influence customer behaviors. There are extensive discussions and suggestions for potential studies on predicting and planning management in chain restaurant operations.","PeriodicalId":299121,"journal":{"name":"2021 International Conference on Artificial Intelligence and Mechatronics Systems (AIMS)","volume":"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":"129896775","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/AIMS52415.2021.9466081
A. Sinaga, E. Astuty
This study aims to help companies to be able to estimate the procurement of raw materials for production, not having stock of raw materials in the warehouse, and determine which suppliers can send goods quickly with affordable prices and good quality. Thus, the company is not optimal in the procurement of raw materials and the selection of appropriate raw material suppliers. In addition, the research aims to optimize the procurement of raw materials that can be used in forecasting in controlling raw materials and decision support systems for the selection of raw material suppliers. The method used to estimate the availability of raw materials is the Simple Moving Average and Analytical Hierarchy Process (AHP) method to determine suppliers. The results of this study indicate that the average percentage of forecast error is 4.17%. Whereas for supplier selection, the AHP method that is used can recommend which suppliers are eligible to be chosen based on predetermined criteria, then the results are sorted by highest ranking. It is expected that the results of this study can be used as a reference for further development, for example by creating information systems that can help companies.
{"title":"Forecasting Raw Material Inventory Using the Single Moving Average and Supplier Selection Using the Analytical Hierarchy Process","authors":"A. Sinaga, E. Astuty","doi":"10.1109/AIMS52415.2021.9466081","DOIUrl":"https://doi.org/10.1109/AIMS52415.2021.9466081","url":null,"abstract":"This study aims to help companies to be able to estimate the procurement of raw materials for production, not having stock of raw materials in the warehouse, and determine which suppliers can send goods quickly with affordable prices and good quality. Thus, the company is not optimal in the procurement of raw materials and the selection of appropriate raw material suppliers. In addition, the research aims to optimize the procurement of raw materials that can be used in forecasting in controlling raw materials and decision support systems for the selection of raw material suppliers. The method used to estimate the availability of raw materials is the Simple Moving Average and Analytical Hierarchy Process (AHP) method to determine suppliers. The results of this study indicate that the average percentage of forecast error is 4.17%. Whereas for supplier selection, the AHP method that is used can recommend which suppliers are eligible to be chosen based on predetermined criteria, then the results are sorted by highest ranking. It is expected that the results of this study can be used as a reference for further development, for example by creating information systems that can help companies.","PeriodicalId":299121,"journal":{"name":"2021 International Conference on Artificial Intelligence and Mechatronics Systems (AIMS)","volume":"21 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":"122282008","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/AIMS52415.2021.9466024
Ivma Salsabila, Darmawan Hidayat, Mohammad Taufik
Honey testing is needed to find out whether the honey is real honey or mixed honey in order to avoid side effects that endanger its users. In this final project using a non-destructive testing method with ultrasonic wave transmission testing. 1MHz frequency ultrasonic waves are emitted by a transmitter and received by a receiver opposite each other with a distance of 9.48mm. The compound used is water and liquid sugar mixed with Perhutani honey with longan flowers with a concentration variation of 0-90 wt%. The parameters used in testing with this ultrasonic wave transmission method are the wave velocity and attenuation coefficient. Speed is calculated from the travel time measured by the phase difference of the sinusoid ultrasonic wave between receiver and transmitter. The attenuation is calculated by comparing the amplitude of the ultrasonic wave receiver with the transmitter. The test results show that the greater the concentration of the mixing substance, the smaller the velocity and attenuation value. Based on the results of the analysis, it can be concluded that the value of the attenuation parameter and the velocity of the ultrasonic waves propagated on honey with the adulterated substance shows a strong correlation.
{"title":"Measurement of Attenuation and Velocity on Ultrasonic Waves in Adulteration of Honey to Find Their Correlation","authors":"Ivma Salsabila, Darmawan Hidayat, Mohammad Taufik","doi":"10.1109/AIMS52415.2021.9466024","DOIUrl":"https://doi.org/10.1109/AIMS52415.2021.9466024","url":null,"abstract":"Honey testing is needed to find out whether the honey is real honey or mixed honey in order to avoid side effects that endanger its users. In this final project using a non-destructive testing method with ultrasonic wave transmission testing. 1MHz frequency ultrasonic waves are emitted by a transmitter and received by a receiver opposite each other with a distance of 9.48mm. The compound used is water and liquid sugar mixed with Perhutani honey with longan flowers with a concentration variation of 0-90 wt%. The parameters used in testing with this ultrasonic wave transmission method are the wave velocity and attenuation coefficient. Speed is calculated from the travel time measured by the phase difference of the sinusoid ultrasonic wave between receiver and transmitter. The attenuation is calculated by comparing the amplitude of the ultrasonic wave receiver with the transmitter. The test results show that the greater the concentration of the mixing substance, the smaller the velocity and attenuation value. Based on the results of the analysis, it can be concluded that the value of the attenuation parameter and the velocity of the ultrasonic waves propagated on honey with the adulterated substance shows a strong correlation.","PeriodicalId":299121,"journal":{"name":"2021 International Conference on Artificial Intelligence and Mechatronics Systems (AIMS)","volume":"32 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":"124036368","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/AIMS52415.2021.9466068
Luqmanul Hakim Iksan, M. I. Awal, Rizky Zull Fhamy, A. Pratama, D. Basuki, S. Sukaridhoto
The Internet of Things (IoT) growth are rapidly in various fields such as industry 4.0, smart cities, and smart homes. Implementation of IoT for electronic assistance had been researched to increase the longevity of human life. However, not all IoT implementation as human life assistance provides action recognition monitoring on multiple elderly people, provide information such as real-time action monitoring, and real-time streaming in a mobile application. Therefore, this research intends to create a system that can receive and provide information on each elderly people who registered. The Action Recognition Backend Platform will be working as cloud computing to receive and manage input data from Edge Computing Action Recognition. This platform integrated Deep Learning, Data Analytics, Big Data Warehouse that implemented Extract, Transform, and Load (ETL) methods, communication services with MQTT, and Kafka Streaming Processor. The test result showed that the edge computing action recognition got better model accuracy performance from our last model [1], which can predict with 50,7% accuracy in 0.5 confidence threshold. Moreover, the backend platform had been successfully implemented a simple IoT paradigm and got an average delivery time of MQTT communication at 204ms, for streaming data process took an average delay of 680ms.
{"title":"Implementation of Cloud Based Action Recognition Backend Platform","authors":"Luqmanul Hakim Iksan, M. I. Awal, Rizky Zull Fhamy, A. Pratama, D. Basuki, S. Sukaridhoto","doi":"10.1109/AIMS52415.2021.9466068","DOIUrl":"https://doi.org/10.1109/AIMS52415.2021.9466068","url":null,"abstract":"The Internet of Things (IoT) growth are rapidly in various fields such as industry 4.0, smart cities, and smart homes. Implementation of IoT for electronic assistance had been researched to increase the longevity of human life. However, not all IoT implementation as human life assistance provides action recognition monitoring on multiple elderly people, provide information such as real-time action monitoring, and real-time streaming in a mobile application. Therefore, this research intends to create a system that can receive and provide information on each elderly people who registered. The Action Recognition Backend Platform will be working as cloud computing to receive and manage input data from Edge Computing Action Recognition. This platform integrated Deep Learning, Data Analytics, Big Data Warehouse that implemented Extract, Transform, and Load (ETL) methods, communication services with MQTT, and Kafka Streaming Processor. The test result showed that the edge computing action recognition got better model accuracy performance from our last model [1], which can predict with 50,7% accuracy in 0.5 confidence threshold. Moreover, the backend platform had been successfully implemented a simple IoT paradigm and got an average delivery time of MQTT communication at 204ms, for streaming data process took an average delay of 680ms.","PeriodicalId":299121,"journal":{"name":"2021 International Conference on Artificial Intelligence and Mechatronics Systems (AIMS)","volume":"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":"128962000","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/AIMS52415.2021.9466005
M. Qadir, Samabia Tehsin, Sumaira Kausar
Since the advancements in technology and IT has revolutionized the world, digital images have come out with crucial importance. With the fruitful advancements and purposes, the authenticity and security breaches in digital images are simultaneously increasing because many editing software and tools give easy access to manipulate and temper the images, resulting in the change of complete information. Copy Move Forgery is the simplest way of tempering images in which an object is copied, removed, and replaced in the same image. As the medical field is too sensitive and even a minor manipulation can produce disastrous results, this study proposes an algorithm specifically designed to detect copy move forgery in medical images, especially when the world has gone towards telemedicine due to the outbreak of COVID-19. The proposed algorithm is based on CNN working on the whole image. The algorithm works in three phases, i.e., pre-processing, feature extraction, and classification. The proposed algorithm has given the accuracy of 89 percent on the dataset that has been created due to the publicly non-availability of forged medical images dataset. The dataset includes the images from abdominal, lungs, transverse view of lungs, chest abdominal, lungs transverse, lungs ap, vertebrae, and transverse heart.
{"title":"Detection of Copy Move Forgery in Medical Images Using Deep Learning","authors":"M. Qadir, Samabia Tehsin, Sumaira Kausar","doi":"10.1109/AIMS52415.2021.9466005","DOIUrl":"https://doi.org/10.1109/AIMS52415.2021.9466005","url":null,"abstract":"Since the advancements in technology and IT has revolutionized the world, digital images have come out with crucial importance. With the fruitful advancements and purposes, the authenticity and security breaches in digital images are simultaneously increasing because many editing software and tools give easy access to manipulate and temper the images, resulting in the change of complete information. Copy Move Forgery is the simplest way of tempering images in which an object is copied, removed, and replaced in the same image. As the medical field is too sensitive and even a minor manipulation can produce disastrous results, this study proposes an algorithm specifically designed to detect copy move forgery in medical images, especially when the world has gone towards telemedicine due to the outbreak of COVID-19. The proposed algorithm is based on CNN working on the whole image. The algorithm works in three phases, i.e., pre-processing, feature extraction, and classification. The proposed algorithm has given the accuracy of 89 percent on the dataset that has been created due to the publicly non-availability of forged medical images dataset. The dataset includes the images from abdominal, lungs, transverse view of lungs, chest abdominal, lungs transverse, lungs ap, vertebrae, and transverse heart.","PeriodicalId":299121,"journal":{"name":"2021 International Conference on Artificial Intelligence and Mechatronics Systems (AIMS)","volume":"20 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":"129176501","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/AIMS52415.2021.9466079
Brian Pamukti, K. Sujatmoko, Natasia Sekarning Tiyas
The Visible Light Communication (VLC) which uses Light Emitting Diode (LED) as a transmitter, not only functions for lighting and communication, but can determine the position of an object. The VLC system has higher accuracy compared to the Global Positioning System (GPS) system which uses satellite signals to obtain the coordinates of objects on earth. The VLC system can detect the position of objects of a smaller size. The Received Signal Strength (RSS) method can be used to determine the location of the object coordinates. This study has compared the results of the positioning error and accuracy values in three scenarios with different transmitter coordinates and using the Line of Sight (LOS) and Non-Line of Sight (NLOS) transmission channels. Using extensive simulation, we obtain that three scenarios through the LOS channel yields an average minimum positioning error value of 7.62E-16 meters with an accuracy of 99%. The three scenarios used in the NLOS channel have an average minimum positioning error value of 0.20 meters in the third scenario with an accuracy value of 99.42%. The simulation results show that the position of the transmitter coordinates affects the positioning error value and the accuracy value. The coordinates of the transmitter that have the highest accuracy value are (2.25,2,3), (-2,2.25,3), (0.25,2.25,3).
{"title":"Enhancement Accuracy for Indoor Positioning System on Non-Line of Sight Channel using Visible Light Communications","authors":"Brian Pamukti, K. Sujatmoko, Natasia Sekarning Tiyas","doi":"10.1109/AIMS52415.2021.9466079","DOIUrl":"https://doi.org/10.1109/AIMS52415.2021.9466079","url":null,"abstract":"The Visible Light Communication (VLC) which uses Light Emitting Diode (LED) as a transmitter, not only functions for lighting and communication, but can determine the position of an object. The VLC system has higher accuracy compared to the Global Positioning System (GPS) system which uses satellite signals to obtain the coordinates of objects on earth. The VLC system can detect the position of objects of a smaller size. The Received Signal Strength (RSS) method can be used to determine the location of the object coordinates. This study has compared the results of the positioning error and accuracy values in three scenarios with different transmitter coordinates and using the Line of Sight (LOS) and Non-Line of Sight (NLOS) transmission channels. Using extensive simulation, we obtain that three scenarios through the LOS channel yields an average minimum positioning error value of 7.62E-16 meters with an accuracy of 99%. The three scenarios used in the NLOS channel have an average minimum positioning error value of 0.20 meters in the third scenario with an accuracy value of 99.42%. The simulation results show that the position of the transmitter coordinates affects the positioning error value and the accuracy value. The coordinates of the transmitter that have the highest accuracy value are (2.25,2,3), (-2,2.25,3), (0.25,2.25,3).","PeriodicalId":299121,"journal":{"name":"2021 International Conference on Artificial Intelligence and Mechatronics Systems (AIMS)","volume":"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":"117249753","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/AIMS52415.2021.9466052
Lathifah Alfat, Ananda Dwi Oktavianto, Barry Samuel Sirait, Muhammad Mulberth Rhenaldo
As coronavirus SARS-CoV-2 emerged around the world, researchers are looking for the best method to decrease the spread. Testing, Tracing, Treatment, or 3T is a rule to control the pandemic COVID-19. However, 3T in Indonesia is still poor, testing capacity is still low as well as the tracing rate. This research aims to model the Indonesian Corona Virus spread from a small cluster in society. As the difficulty rises in acquiring real data, the data are synthetically generated, as well as its relationship. This paper applied Social Network Analysis with Network X, a Python library. The modeling method started with creating the graph and its community graph, then calculate the betweenness centrality to generate Page Rank based graph. This paper shows that the top 3 of the highest Page Rank is LUP with the value of 0.012356, MIH with 0.012035 points, and WAGP with 0.011824. The relationship between people impacts contacts tracing in the graph. The higher rank of a person, the higher chance he or she transmitted the virus or got infected by the virus.
{"title":"Modeling Indonesian COVID-19 Contact Tracing using Social Network Analysis","authors":"Lathifah Alfat, Ananda Dwi Oktavianto, Barry Samuel Sirait, Muhammad Mulberth Rhenaldo","doi":"10.1109/AIMS52415.2021.9466052","DOIUrl":"https://doi.org/10.1109/AIMS52415.2021.9466052","url":null,"abstract":"As coronavirus SARS-CoV-2 emerged around the world, researchers are looking for the best method to decrease the spread. Testing, Tracing, Treatment, or 3T is a rule to control the pandemic COVID-19. However, 3T in Indonesia is still poor, testing capacity is still low as well as the tracing rate. This research aims to model the Indonesian Corona Virus spread from a small cluster in society. As the difficulty rises in acquiring real data, the data are synthetically generated, as well as its relationship. This paper applied Social Network Analysis with Network X, a Python library. The modeling method started with creating the graph and its community graph, then calculate the betweenness centrality to generate Page Rank based graph. This paper shows that the top 3 of the highest Page Rank is LUP with the value of 0.012356, MIH with 0.012035 points, and WAGP with 0.011824. The relationship between people impacts contacts tracing in the graph. The higher rank of a person, the higher chance he or she transmitted the virus or got infected by the virus.","PeriodicalId":299121,"journal":{"name":"2021 International Conference on Artificial Intelligence and Mechatronics Systems (AIMS)","volume":"PP 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":"126355144","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/AIMS52415.2021.9466041
A. Istiqomah, Aries Subiantoro
The high-temperature gas cooled-reactor (HTGR) has been constructed in Japan and produces rated power operation and hydrogen, contributing to the development of future energy strategies. One type of HTGR, the high-temperature engineering test reactor (HTTR), uses long hexagonal fuel assemblies. The HTTR is a graphite-moderated, helium-gas-cooled reactor with thermal power of 30 MW, an inlet coolant temperature of 395° C, and an outlet coolant temperature of 950° C. In this paper, a nonlinear mathematical model of the nuclear reactor core was derived in derivative form using fundamental principles. Unknown parameter data could be estimated with physics equations using the nonlinear least squares curve fitting method. The validation between the mathematical model and experimental data of the plant-obtained simulation response indicates that the model could have been used for further optimization and control. The simulation-response results showed that the mathematical model with estimated parameters has an accuracy above 89%. Consequently, based on the simulation response, the mathematical model could be used as the HTTR continues to function.
{"title":"Core Power Modelling of High-Temperature Engineering Test Reactor (HTTR) Using Nonlinear Least Squares Method for Parameter Estimation","authors":"A. Istiqomah, Aries Subiantoro","doi":"10.1109/AIMS52415.2021.9466041","DOIUrl":"https://doi.org/10.1109/AIMS52415.2021.9466041","url":null,"abstract":"The high-temperature gas cooled-reactor (HTGR) has been constructed in Japan and produces rated power operation and hydrogen, contributing to the development of future energy strategies. One type of HTGR, the high-temperature engineering test reactor (HTTR), uses long hexagonal fuel assemblies. The HTTR is a graphite-moderated, helium-gas-cooled reactor with thermal power of 30 MW, an inlet coolant temperature of 395° C, and an outlet coolant temperature of 950° C. In this paper, a nonlinear mathematical model of the nuclear reactor core was derived in derivative form using fundamental principles. Unknown parameter data could be estimated with physics equations using the nonlinear least squares curve fitting method. The validation between the mathematical model and experimental data of the plant-obtained simulation response indicates that the model could have been used for further optimization and control. The simulation-response results showed that the mathematical model with estimated parameters has an accuracy above 89%. Consequently, based on the simulation response, the mathematical model could be used as the HTTR continues to function.","PeriodicalId":299121,"journal":{"name":"2021 International Conference on Artificial Intelligence and Mechatronics Systems (AIMS)","volume":"82 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":"123438312","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/AIMS52415.2021.9466035
Kenny, N. S. Syafei, D. Novita, A. Turnip
Drug convicts are thought to have decreased performance of the brain to think, concentrate, and carry out logical functions. To monitor how the drug could affect the human brain, mental arithmetic is performed, and the EEG signals are recorded. In this study, addition task performance men show that some subjects have different counting accuracy. Mental arithmetic was monitored by International 10/20 system EEG with 19 scalp electrodes. The raw EEG data was processed and plotted to 2d mapping based on the power spectrum. The spectrum changes seen in Brain mapping, show how the mental arithmetic process takes place. The results of brain mapping can be a parameter that indicates the calculation process so that it can show the quality of the brain's work. Independent component label classifier performed, subject 7 obtain 79,8%, subject12 obtain 94,3%, subject15 obtain 92,3% accuracy as brain label.
{"title":"EEG Brainmapping Analysis of Mental Arithmetic Task Performed by Drug Convicts","authors":"Kenny, N. S. Syafei, D. Novita, A. Turnip","doi":"10.1109/AIMS52415.2021.9466035","DOIUrl":"https://doi.org/10.1109/AIMS52415.2021.9466035","url":null,"abstract":"Drug convicts are thought to have decreased performance of the brain to think, concentrate, and carry out logical functions. To monitor how the drug could affect the human brain, mental arithmetic is performed, and the EEG signals are recorded. In this study, addition task performance men show that some subjects have different counting accuracy. Mental arithmetic was monitored by International 10/20 system EEG with 19 scalp electrodes. The raw EEG data was processed and plotted to 2d mapping based on the power spectrum. The spectrum changes seen in Brain mapping, show how the mental arithmetic process takes place. The results of brain mapping can be a parameter that indicates the calculation process so that it can show the quality of the brain's work. Independent component label classifier performed, subject 7 obtain 79,8%, subject12 obtain 94,3%, subject15 obtain 92,3% accuracy as brain label.","PeriodicalId":299121,"journal":{"name":"2021 International Conference on Artificial Intelligence and Mechatronics Systems (AIMS)","volume":"19 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":"125523229","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/AIMS52415.2021.9466031
Muzzamil Ghaffar, S. Sheikh, Noman Naseer, Fraz Ahmed
Field of Assistive Smart Homes has emerged with the aim of enabling the physically challenged, the elderly or those with constraint motion and to restore their capability of performing necessary daily life tasks by providing required assistance using modern technological tools. Objective of this work is to study possibility of using various available technological tools to enable such people perform independently in main stream life by giving them control of their environment and movement. The said objective is achieved using hybrid physiological gestures, such as, head movement and eye blinks, as even quadriplegic patients can perform these gestures easily. The orientation or movement of head is sensed by a head set embedded with an Inertial Measurement Unit (IMU) and Linear Discriminant Analysis (LDA) is used to recognize the intended command. Eye blinks are detected by sensing Electroencephalography (EEG) signals. After pre-processing, EEG signals are classified on the basis of various signal properties and converted into commands. With the combination of head orientation sensing and eye blink signals, a hierarchy of control commands is generated to control lights, fans, security lock and wheel chair movement. Using the prototype headset, the home environment is simulated and verified in Matlab environment and a GUI is designed for ease of user. The results show the feasibility of the designed system in real time, with average system accuracy of approximately 81.48%, making this design a good and reasonably priced choice for implementation in Assistive Smart Homes, especially in developing countries with low per capita income.
{"title":"Assistive Smart Home Environment using Head Gestures and EEG Eye Blink Control Schemes","authors":"Muzzamil Ghaffar, S. Sheikh, Noman Naseer, Fraz Ahmed","doi":"10.1109/AIMS52415.2021.9466031","DOIUrl":"https://doi.org/10.1109/AIMS52415.2021.9466031","url":null,"abstract":"Field of Assistive Smart Homes has emerged with the aim of enabling the physically challenged, the elderly or those with constraint motion and to restore their capability of performing necessary daily life tasks by providing required assistance using modern technological tools. Objective of this work is to study possibility of using various available technological tools to enable such people perform independently in main stream life by giving them control of their environment and movement. The said objective is achieved using hybrid physiological gestures, such as, head movement and eye blinks, as even quadriplegic patients can perform these gestures easily. The orientation or movement of head is sensed by a head set embedded with an Inertial Measurement Unit (IMU) and Linear Discriminant Analysis (LDA) is used to recognize the intended command. Eye blinks are detected by sensing Electroencephalography (EEG) signals. After pre-processing, EEG signals are classified on the basis of various signal properties and converted into commands. With the combination of head orientation sensing and eye blink signals, a hierarchy of control commands is generated to control lights, fans, security lock and wheel chair movement. Using the prototype headset, the home environment is simulated and verified in Matlab environment and a GUI is designed for ease of user. The results show the feasibility of the designed system in real time, with average system accuracy of approximately 81.48%, making this design a good and reasonably priced choice for implementation in Assistive Smart Homes, especially in developing countries with low per capita income.","PeriodicalId":299121,"journal":{"name":"2021 International Conference on Artificial Intelligence and Mechatronics Systems (AIMS)","volume":"57 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":"128255190","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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