K. Mya, M. Sein, T. Nyunt, Yung-Wey Chong, Rer. Nat. Zainal
Until 2050, global urbanization will increase to 2.4 billion cities and towns. As the population grows, so does the consumption of fruits and vegetables. There will be a need for agricultural land and water resources. Nowadays, hydroponics is gaining popularity due to the plants exceedingly high quality and not required the large space and resources as like traditional planting. In this paper, a system which will be automatically control Electrical Conductivity (EC), Total dissolved solids (TDS), liquid levels, and power of hydrogen (pH) values is proposed to improve the Hydroponics Planting. This system is developed based on Neural Network for auto adjusting the value of hydrogen(pH) and nutrient in lettuce farm. It is designed to enable seamless data collection from various kinds of sensors in urban farm condition. The deployment of proposed system is tested in indoor urban farming environment. Through the experimental results, the proposed system can effectively regulate water and nutrients by assisting plant growth.
{"title":"Automatic Data-Driven Agriculture System for Hydroponic Farming","authors":"K. Mya, M. Sein, T. Nyunt, Yung-Wey Chong, Rer. Nat. Zainal","doi":"10.1145/3449365.3449367","DOIUrl":"https://doi.org/10.1145/3449365.3449367","url":null,"abstract":"Until 2050, global urbanization will increase to 2.4 billion cities and towns. As the population grows, so does the consumption of fruits and vegetables. There will be a need for agricultural land and water resources. Nowadays, hydroponics is gaining popularity due to the plants exceedingly high quality and not required the large space and resources as like traditional planting. In this paper, a system which will be automatically control Electrical Conductivity (EC), Total dissolved solids (TDS), liquid levels, and power of hydrogen (pH) values is proposed to improve the Hydroponics Planting. This system is developed based on Neural Network for auto adjusting the value of hydrogen(pH) and nutrient in lettuce farm. It is designed to enable seamless data collection from various kinds of sensors in urban farm condition. The deployment of proposed system is tested in indoor urban farming environment. Through the experimental results, the proposed system can effectively regulate water and nutrients by assisting plant growth.","PeriodicalId":188200,"journal":{"name":"Proceedings of the 2021 3rd Asia Pacific Information Technology Conference","volume":"34 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-01-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124934606","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}
Video surveillance technology is derived from a branch of artificial intelligence. It can have a computer to automatically analyze the video image source, identify and extract useful key information from it, and automatically control the machine to perform corresponding operations. This article is a video surveillance system based on the SSD target detection algorithm to identify specific data for hard hats. The aim is to be able to patrol and respond to incidents in a more intelligent way without having to use human resources to stay in front of the monitor.
{"title":"Video Surveillance System for Helmet Recognition Based on SSD Target Detection Algorithm","authors":"Shilong Ma, Huan Zhao, Jian Wang, Chao Yang","doi":"10.1145/3449365.3449376","DOIUrl":"https://doi.org/10.1145/3449365.3449376","url":null,"abstract":"Video surveillance technology is derived from a branch of artificial intelligence. It can have a computer to automatically analyze the video image source, identify and extract useful key information from it, and automatically control the machine to perform corresponding operations. This article is a video surveillance system based on the SSD target detection algorithm to identify specific data for hard hats. The aim is to be able to patrol and respond to incidents in a more intelligent way without having to use human resources to stay in front of the monitor.","PeriodicalId":188200,"journal":{"name":"Proceedings of the 2021 3rd Asia Pacific Information Technology Conference","volume":"141 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-01-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131432926","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}
Software configuration management is a technology throughout the whole software life cycle. Its main function is to control software changes in the software life cycle and reduce the impact of various changes. With the increasing complexity of software system, user requirements and frequent software updates, software configuration management has gradually become an important control process of software life cycle. Based on the analysis of the current situation of software configuration management system, this paper puting forward a configuration management model based on process and cooperation, and introduces the key problems in the design and implementation of the software configuration management system based on this model. Based on the analysis of the development process of large-scale software system, this paper summarizes some factors that will affect configuration management, and analyzes how these factors affect configuration management, and then puting forward the method of establishing configuration management system of whole life cycle.
{"title":"Research on Key Technologies of Software Configuration Management in Development of Large-scale Software System","authors":"Wenjun Ji","doi":"10.1145/3449365.3449374","DOIUrl":"https://doi.org/10.1145/3449365.3449374","url":null,"abstract":"Software configuration management is a technology throughout the whole software life cycle. Its main function is to control software changes in the software life cycle and reduce the impact of various changes. With the increasing complexity of software system, user requirements and frequent software updates, software configuration management has gradually become an important control process of software life cycle. Based on the analysis of the current situation of software configuration management system, this paper puting forward a configuration management model based on process and cooperation, and introduces the key problems in the design and implementation of the software configuration management system based on this model. Based on the analysis of the development process of large-scale software system, this paper summarizes some factors that will affect configuration management, and analyzes how these factors affect configuration management, and then puting forward the method of establishing configuration management system of whole life cycle.","PeriodicalId":188200,"journal":{"name":"Proceedings of the 2021 3rd Asia Pacific Information Technology Conference","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-01-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116404452","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}
R. Malhotra, Anmol Budhiraja, Abhinav Singh, Ishani Ghoshal
Software defect prediction is an integral part of the software development process. Defect prediction helps focus on the grey areas beforehand, thus saving the considerable amount of money that is otherwise wasted in finding and fixing the faults once the software is already in production. One of the popular areas of defect prediction in recent years is Heterogeneous Defect Prediction, which predicts defects in a target project using a source project with different metrics. Through our paper, we provide a novel feature selection based approach, En-BPSO, based on binary particle swarm optimization, coupled with majority voting ensemble classifier based fitness function for heterogeneous defect prediction. The datasets we are using are MORPH and SOFTLAB. The results show that the En-BPSO method provides the highest Friedman mean rank amongst all the feature selection methods used for comparison. En-BPSO technique also helps us dynamically determine the optimal number of features to build an accurate heterogeneous defect prediction model.
{"title":"A Novel Feature Selection Approach based on Binary Particle Swarm Optimization and Ensemble Learning for Heterogeneous Defect Prediction","authors":"R. Malhotra, Anmol Budhiraja, Abhinav Singh, Ishani Ghoshal","doi":"10.1145/3449365.3449384","DOIUrl":"https://doi.org/10.1145/3449365.3449384","url":null,"abstract":"Software defect prediction is an integral part of the software development process. Defect prediction helps focus on the grey areas beforehand, thus saving the considerable amount of money that is otherwise wasted in finding and fixing the faults once the software is already in production. One of the popular areas of defect prediction in recent years is Heterogeneous Defect Prediction, which predicts defects in a target project using a source project with different metrics. Through our paper, we provide a novel feature selection based approach, En-BPSO, based on binary particle swarm optimization, coupled with majority voting ensemble classifier based fitness function for heterogeneous defect prediction. The datasets we are using are MORPH and SOFTLAB. The results show that the En-BPSO method provides the highest Friedman mean rank amongst all the feature selection methods used for comparison. En-BPSO technique also helps us dynamically determine the optimal number of features to build an accurate heterogeneous defect prediction model.","PeriodicalId":188200,"journal":{"name":"Proceedings of the 2021 3rd Asia Pacific Information Technology Conference","volume":"148 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-01-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128444389","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}
Shiwei Guo, Mingshan Yang, Huiyan Zhou, Xiaoyan Du
In the radar positioning system, the unevenness of the atmospheric medium causes the deflection of the electromagnetic wave in the propagation process, which reduces the positioning accuracy of the radar, so it is necessary to correct the atmospheric refraction error for the radar's positioning requirement of fast positioning and high precision. Based on the method of correcting atmospheric refraction error by mapping function, the target's distance is regarded as the product of mapping function and altitude, and the application of mapping function in radar target positioning system is studied in order to reduce the complexity of positioning method and the dependence on atmospheric parameters, and an inversion method is used to study the change trends of mapping function's coefficients with altitude. Using the radar positioning environment established by Hopfield model, and taking the calculation result of raying tracing method as the radar observation data, the method's accuracy is studied. The results show that the mapping function method has research and application value in locating high elevation targets, and the accuracy of the positioning method is determined by the altitude and elevation angle of target. At a certain altitude, the closer the target is, the larger the elevation angle is, the smaller the positioning error is and the better the positioning effect is.
{"title":"Application and Research Of Mapping Function Method In Radar Target Positioning System","authors":"Shiwei Guo, Mingshan Yang, Huiyan Zhou, Xiaoyan Du","doi":"10.1145/3449365.3449385","DOIUrl":"https://doi.org/10.1145/3449365.3449385","url":null,"abstract":"In the radar positioning system, the unevenness of the atmospheric medium causes the deflection of the electromagnetic wave in the propagation process, which reduces the positioning accuracy of the radar, so it is necessary to correct the atmospheric refraction error for the radar's positioning requirement of fast positioning and high precision. Based on the method of correcting atmospheric refraction error by mapping function, the target's distance is regarded as the product of mapping function and altitude, and the application of mapping function in radar target positioning system is studied in order to reduce the complexity of positioning method and the dependence on atmospheric parameters, and an inversion method is used to study the change trends of mapping function's coefficients with altitude. Using the radar positioning environment established by Hopfield model, and taking the calculation result of raying tracing method as the radar observation data, the method's accuracy is studied. The results show that the mapping function method has research and application value in locating high elevation targets, and the accuracy of the positioning method is determined by the altitude and elevation angle of target. At a certain altitude, the closer the target is, the larger the elevation angle is, the smaller the positioning error is and the better the positioning effect is.","PeriodicalId":188200,"journal":{"name":"Proceedings of the 2021 3rd Asia Pacific Information Technology Conference","volume":"90 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-01-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131753715","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}
Object detection has solved many problems in different applications like monitoring security, search and rescue operations, semantic segmentation, autonomous driving and so on. Despite this huge success rate in normal ground captured images, it is still a challenging task to detect humans or any other objects from the UAV(Unmanned Aerial Vehicle) captured images due to a few challenges like pose and scale variations, weather conditions, artefacts like people wearing hats, varying attitude and camouflaged environment. In this paper, we propose a novel approach for the detection of humans in aerial images, for search and rescue operations. This method explains how to train the existing high-resolution aerial database of HERIDAL. The EfficientDET deep neural network is trained using a newly generated database to solve the human detection problem. To the best of our knowledge, the proposed method has achieved the best accuracy of 93.29% mAP compared to all existing methods. The proposed method has been compared to the system used by Croatian Mountain search and rescue (SAR) teams (IPSAR) and also with the state-of-art proposed HERIDAL database paper which is based on extracting the salient features, which has slightly worse result compared to the results of this paper.
{"title":"Detection of humans in drone images for search and rescue operations","authors":"Nayee Muddin Khan Dousai, S. Lončarić","doi":"10.1145/3449365.3449377","DOIUrl":"https://doi.org/10.1145/3449365.3449377","url":null,"abstract":"Object detection has solved many problems in different applications like monitoring security, search and rescue operations, semantic segmentation, autonomous driving and so on. Despite this huge success rate in normal ground captured images, it is still a challenging task to detect humans or any other objects from the UAV(Unmanned Aerial Vehicle) captured images due to a few challenges like pose and scale variations, weather conditions, artefacts like people wearing hats, varying attitude and camouflaged environment. In this paper, we propose a novel approach for the detection of humans in aerial images, for search and rescue operations. This method explains how to train the existing high-resolution aerial database of HERIDAL. The EfficientDET deep neural network is trained using a newly generated database to solve the human detection problem. To the best of our knowledge, the proposed method has achieved the best accuracy of 93.29% mAP compared to all existing methods. The proposed method has been compared to the system used by Croatian Mountain search and rescue (SAR) teams (IPSAR) and also with the state-of-art proposed HERIDAL database paper which is based on extracting the salient features, which has slightly worse result compared to the results of this paper.","PeriodicalId":188200,"journal":{"name":"Proceedings of the 2021 3rd Asia Pacific Information Technology Conference","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-01-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133623873","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}
Taweesin Wongpinkaew, Sipat Triukose, Sirin Nitinawarat, K. Piromsopa
In the context of healthcare, volunteers play an important role in improving the patient's experience and lowering the operational cost. However, the process which facilitate their management is reported to be problematic. In this research, we have explored the process and analyzed the problems of the current process. We attempted to solve these problems through a process digitalization and implementing a new IT system by using service design methodology. The system was tested for a duration of 2 month during the COVID-19 outbreak in Thailand. SUS and an in-depth interview was conducted in order to gauge the usability and the effectiveness the system. Results show that the digitization process was a success. Furthermore, the research made an impact in Thailand's fight against COVID-19.
{"title":"Hospital Volunteer Management Process Digitalization Through Service Design: Design Decision and Implementation","authors":"Taweesin Wongpinkaew, Sipat Triukose, Sirin Nitinawarat, K. Piromsopa","doi":"10.1145/3449365.3449373","DOIUrl":"https://doi.org/10.1145/3449365.3449373","url":null,"abstract":"In the context of healthcare, volunteers play an important role in improving the patient's experience and lowering the operational cost. However, the process which facilitate their management is reported to be problematic. In this research, we have explored the process and analyzed the problems of the current process. We attempted to solve these problems through a process digitalization and implementing a new IT system by using service design methodology. The system was tested for a duration of 2 month during the COVID-19 outbreak in Thailand. SUS and an in-depth interview was conducted in order to gauge the usability and the effectiveness the system. Results show that the digitization process was a success. Furthermore, the research made an impact in Thailand's fight against COVID-19.","PeriodicalId":188200,"journal":{"name":"Proceedings of the 2021 3rd Asia Pacific Information Technology Conference","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-01-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124480811","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}
Saurabh Adhikari, C. Plewnia, C. Netramai, H. Lichter
The usage of compute resources by data processing jobs may change over time, requiring careful resource planning when an organization operates these resources itself in an on-premise private cloud. Ideally, the currently available resources always match the need of jobs executed on them. This way the resources would neither be overutilized, which is usually undesirable as the jobs might take longer, nor underutilized, which causes unnecessary costs for unused resources. When an organization decides to extend its private cloud resources, it can still take months until the servers are bought, delivered, and installed. Thus, the resources have to be planned carefully in advance. Estimating the future resource needs is difficult and influenced by many factors. In our experience, creating the estimate is often a manual process supported by self-designed spreadsheets; these spreadsheets are maintained by a single person from time to time and might even be replaced completely if someone else assumes that person's responsibility. However, this approach does not lead to transparent and verifiable forecasts that enable collaboration and learning from past decisions. This paper addresses the problem of generating a transparent and verifiable compute resource usage forecast by proposing a simulation approach. It requires a user to model an estimate of the future workload development of the data processing jobs as well as the current compute resource setup. The simulation can then be run to identify possible future resource bottlenecks. This can be repeated for different scenarios, including situations of failing resources as well as the addition of resources to compensate for bottlenecks and failures. We further provide a first qualitative case study of this approach that demonstrates its potential.
{"title":"A Simulation for Forecasting Compute Resource Usage","authors":"Saurabh Adhikari, C. Plewnia, C. Netramai, H. Lichter","doi":"10.1145/3449365.3449370","DOIUrl":"https://doi.org/10.1145/3449365.3449370","url":null,"abstract":"The usage of compute resources by data processing jobs may change over time, requiring careful resource planning when an organization operates these resources itself in an on-premise private cloud. Ideally, the currently available resources always match the need of jobs executed on them. This way the resources would neither be overutilized, which is usually undesirable as the jobs might take longer, nor underutilized, which causes unnecessary costs for unused resources. When an organization decides to extend its private cloud resources, it can still take months until the servers are bought, delivered, and installed. Thus, the resources have to be planned carefully in advance. Estimating the future resource needs is difficult and influenced by many factors. In our experience, creating the estimate is often a manual process supported by self-designed spreadsheets; these spreadsheets are maintained by a single person from time to time and might even be replaced completely if someone else assumes that person's responsibility. However, this approach does not lead to transparent and verifiable forecasts that enable collaboration and learning from past decisions. This paper addresses the problem of generating a transparent and verifiable compute resource usage forecast by proposing a simulation approach. It requires a user to model an estimate of the future workload development of the data processing jobs as well as the current compute resource setup. The simulation can then be run to identify possible future resource bottlenecks. This can be repeated for different scenarios, including situations of failing resources as well as the addition of resources to compensate for bottlenecks and failures. We further provide a first qualitative case study of this approach that demonstrates its potential.","PeriodicalId":188200,"journal":{"name":"Proceedings of the 2021 3rd Asia Pacific Information Technology Conference","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-01-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121624103","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}
Julius Dimas Trisaktyo Nugroho, Rahmad Mahendra, I. Budi
E-procurement is an electronic procurement system that became a key factor required to manage financial aspect of a country with appropriate controls and protected by legal policies. The Presidential Regulation in Indonesia expect all government institutions to run the e-procurement process following the procurement principles, namely effective, efficient, transparent, open, competitive, fair and accountable. However in the implementation of e-tendering, which is part of e-procurement, found there are practices that not in accordance with the procurement principles. In this study, an in-depth analysis conducted to evaluate the tender activities of the ministry in Indonesia. We apply data mining process towards the national procurement portal to analyze tender data and find the hidden pattern that would be useful to support the decision-making process. This study combines several techniques, e.g. web mining and statistical analysis approach. Our finding includes correlation patterns among a number of values existing in e-procurement portal.
{"title":"Web Mining in e-Procurement: A Case Study in Indonesia","authors":"Julius Dimas Trisaktyo Nugroho, Rahmad Mahendra, I. Budi","doi":"10.1145/3449365.3449382","DOIUrl":"https://doi.org/10.1145/3449365.3449382","url":null,"abstract":"E-procurement is an electronic procurement system that became a key factor required to manage financial aspect of a country with appropriate controls and protected by legal policies. The Presidential Regulation in Indonesia expect all government institutions to run the e-procurement process following the procurement principles, namely effective, efficient, transparent, open, competitive, fair and accountable. However in the implementation of e-tendering, which is part of e-procurement, found there are practices that not in accordance with the procurement principles. In this study, an in-depth analysis conducted to evaluate the tender activities of the ministry in Indonesia. We apply data mining process towards the national procurement portal to analyze tender data and find the hidden pattern that would be useful to support the decision-making process. This study combines several techniques, e.g. web mining and statistical analysis approach. Our finding includes correlation patterns among a number of values existing in e-procurement portal.","PeriodicalId":188200,"journal":{"name":"Proceedings of the 2021 3rd Asia Pacific Information Technology Conference","volume":"40 2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-01-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122923333","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}
The study presents an analysis and generation of pattern sequences acquired from northern Luzon ethnic textiles. The textile sample images were collected, analyzed, and processed into a grayscale raster shapes. The analyzed data for pattern sequences was converted into a deterministic finite automaton which includes the transition tables and diagram. The experiment revealed that some patterns have similar sequences which were grouped together. Based from each grouped sequence, the sequences were analyzed, and an algorithm was developed. Each algorithm was used to generate a new pattern that is closely comparable to the grouped sequences. The study observed the following patterns which are a(bc)nbma, abna, and (ab) nam representing the common sequences appearing in the textile patterns.
{"title":"Sequence Analysis and Generation of Filipino Ethnic Textile Patterns using Finite Automata","authors":"M. Devaraj, I. Recto, Ryan Clarian","doi":"10.1145/3449365.3449386","DOIUrl":"https://doi.org/10.1145/3449365.3449386","url":null,"abstract":"The study presents an analysis and generation of pattern sequences acquired from northern Luzon ethnic textiles. The textile sample images were collected, analyzed, and processed into a grayscale raster shapes. The analyzed data for pattern sequences was converted into a deterministic finite automaton which includes the transition tables and diagram. The experiment revealed that some patterns have similar sequences which were grouped together. Based from each grouped sequence, the sequences were analyzed, and an algorithm was developed. Each algorithm was used to generate a new pattern that is closely comparable to the grouped sequences. The study observed the following patterns which are a(bc)nbma, abna, and (ab) nam representing the common sequences appearing in the textile patterns.","PeriodicalId":188200,"journal":{"name":"Proceedings of the 2021 3rd Asia Pacific Information Technology Conference","volume":"47 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-01-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126193109","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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