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A LabVIEW Based Optimization and Integration of Supersonic Wind Tunnel Instrumentation System Jefri Abner Hamonangan; Prawito Prajitno; Agus Aribowo
Indonesian Journal of Electrical Engineering and Informatics (IJEEI) Vol 8, No 2: June 2020
Publisher : IAES Indonesian Section

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52549/ijeei.v8i2.591

Abstract

Indonesian National Institute of Aeronautics and Space have a supersonic wind tunnel for research in high speed object . The condition of LAPAN's supersonic wind tunnel can only be used for shockwave observation by using schlieren apparatus. The data acquisition system can not collect data from sting balance, some of the control panels are either not operational or it need calibration. Based from these conditions, this research is done to develop a new integrated control system and data acquisition so that the effectiveness of operation in terms of time and better data quality can be achieved. For angle of attack (AoA) control from manual operation, have been optimized to a digital control using PID control method. With the new system, the AoA control has been automated and a new testing option for moving the AoA while the wind tunnel running can be done. In terms of data acquisition, after the optimization it can collect better data, (noise / interference becomes smaller), and now it can record data from the balance, the pressure data, AoA position and block position can be recorded. The system was created using PXIe from National Instrument and LabVIEW graphical programming as user interface.
Computer-Aided Detection (CAD) Deteksi Nodul Paru-Paru dari Computed Tomography (CT) Osas Lisa Istifarinta; Prawito Prajitno; Djarwani Soeharso Soejoko
Journal of Medical Physics and Biophysics Vol 9, No 1 (2022)
Publisher : Indonesian Association of Physicists in Medicine (AIPM/AFISMI)

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Abstract

Nodul paru merupakan pertumbuhan jaringan abnormal pada paru yang digunakan sebagai diagnosis dini kanker paru. Kanker paru-paru adalah kanker yang paling banyak ditemukan dan mematikan di dunia. Umumnya, deteksi pertama nodul paru diperoleh dari citra CT yang didiagnosis secara visual oleh ahli radiologi. Artinya subjektivitas individu radiologis berpengaruh dalam citra diagnosis tersebut. Untuk membantu ahli radiologi dalam mendeteksi dan mengevaluasi nodul paru pada citra CT secara otomatis, penelitian ini telah mengembangkan sistem Computer-Aided Detection (CAD). Sistem CAD menggunakan metode segmentasi Otsu, dengan ekstraksi fitur Gray Level Co-occurrence Matrix (GLCM) sebagai input untuk klasifikasi nodul. Algoritma Random Forest digunakan untuk membedakan antara normal dan abnormal pada citra CT, khususnya citra dengan kelainan nodul paru. Evaluasi estimasi keberadaan nodul paru pada sistem dilakukan menggunakan Receiver Operating Characteristic (ROC) dengan sensitivitas 95%.Kata Kunci: CAD, CT dada, Deteksi nodul paru, Random Forest