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Reconstruction of old well log data using deep learning imputation
Gian Antariksa,Radhi Muammar,Agung Nugraha,Jihwan Lee 대한산업공학회 2022 대한산업공학회 추계학술대회논문집 Vol.2022 No.11
Well logs are important datasets for interpreting subsurface geology because they represent the physical properties of the logged formations. However, at certain intervals, such information may be missing and/or incorrect due to drilling issues (e.g., significantly larger mud weight than formation integrity, resulting in formation damage), an inefficient logging process, or tool operational concerns. In the case of logging tool faults, such flaws are often identified by the existence of abnormal data spikes or erroneously low log readings in the damaged formation. To solve this issue, a new deep learning-based system was tested to imputate such missing values for sonic log (DT) data. The missing well log values were predicted using data-driven machine learning methods, specifically the GRU and LSTM, given time step sequence inputs from a window. To establish the ideal parameters for achieving the best validation score, an empirical research technique was used. Throughout the training phase, the relative value of various input parameters was analyzed in order to eliminate insensitive measurements and prioritize data with a high connection to the target variables. This paper highlights the study’s important findings, problems, and potential improvements for future studies.
XAI(Explainable AI) 기법을 이용한 선박기관 이상탐지 시스템 개발
Habtemariam Duguma Yeshitla,Agung Nugraha,Antariksa Gian,김동현,이상봉,이지환 한국항해항만학회 2022 한국항해항만학회 학술대회논문집 Vol.2022 No.2
본 연구에서는 선박의 중요부품인 메인엔진에서 수집되는 센서 데이터를 사용하여 선박 메인엔진의 이상치를 탐지하는 시스템을소개한다. 본 시스템의 특장점은 이상치 탐지 뿐만 아니라, 이상치의 센서별 기여도를 정량화 함으로써, 이상치 발생을 유형화 하고 추가적인분석을 가능하게 해준다. …
The Impact of Asthma Comorbid in Survival of COVID-19
( Andari Rahmani Putri ),( Ratnawati ),( Sita Andarini ),( Budhi Antariksa ) 대한결핵 및 호흡기학회 2021 대한결핵 및 호흡기학회 추계학술대회 초록집 Vol.129 No.-
Background Gender has been recognized as one of the important factors in epidemiology and the outcome of many diseases. Asthma is one of many comorbid in COVID-19. Adult with asthma appeared to have a reduced risk of severe COVID-19, and female as an independent risk factor for COVID-19 hospitalization. Methods and Results A cross-sectional study was conducted from the COVID-19 registry in Persahabatan Hospital, a national referral hospital for respiratory diseases, in 2020. Out of 2234 patients diagnosed with COVID-19 by both nasopharyngeal and oropharyngeal swab specimens via RT-PCR testing, 30 patients had a history of asthma, 22 (73.3%) were female, and 8 (26.7%) were male. The data shows that the mortality rate of asthma patients with COVID-19 is 16.7% (5 patients). Out of those 5 patients, 4 females (18%) and 1 male (12,5%). Conclusions The prevalence of comorbid asthma in COVID-19 patients during years 2020 is 1.34% in Persahabatan hospital. Female asthma patients with COVID-19 had a higher risk of mortality compared with male. Based on this study, the survival of comorbid asthma in COVID-19 patients is higher in males compared with females.
Development of large scale Agent Based Modeling Simulator with Microservice architecture
Habtemariam Dugum Yeshitla,Nugraha Agung,Lee Jihwan,Antariksa Gian 대한산업공학회 2023 대한산업공학회 춘계학술대회논문집 Vol.2023 No.5
In the effort to simply and facilitate the ABM simulation process and data analysis, this research utilized Microservice architecture to build services that provide web UI, code generation, simulation running and data storage features. The developed system is deoplyable on HPC resources and can be accessed by multiple users, providing a better utilization of the computing resources. The number of simulation nodes can be increased to provide a better capacity. Future works of this reseach can focus on building a distributed ABM simulator to utilizing multiple Simulation nodes for one model. Additionally the data query process can be further simplfied by depending less on SQL syntax. All in all, the development of this system can help to preserve simulation data privecy by allowing Institutions to utilized their existing HPC resources, which removes the cost burden from individual modelers when running their simulations.
Development of large scale Agent Based Modeling Simulator with Microservice architecture
Habtemariam Dugum Yeshitla,Nugraha Agung,Lee Jihwan,Antariksa Gian 한국경영과학회 2023 한국경영과학회 학술대회논문집 Vol.2023 No.5
In the effort to simply and facilitate the ABM simulation process and data analysis, this research utilized Microservice architecture to build services that provide web UI, code generation, simulation running and data storage features. The developed system is deoplyable on HPC resources and can be accessed by multiple users, providing a better utilization of the computing resources. The number of simulation nodes can be increased to provide a better capacity. Future works of this reseach can focus on building a distributed ABM simulator to utilizing multiple Simulation nodes for one model. Additionally the data query process can be further simplfied by depending less on SQL syntax. All in all, the development of this system can help to preserve simulation data privecy by allowing Institutions to utilized their existing HPC resources, which removes the cost burden from individual modelers when running their simulations.