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All Journal Perfecting a Video Game with Game Metrics Physics Student Journal Erudio: Journal of Educational Innovation Natural B
Ahmad Nadhir
Brawijaya University
Computer Science & IT Education Environmental Science Physics

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Journal : Natural B

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The CWT Feature's Uniqueness Analysis of EEG Signal Against 5 BCI Wheelchair Control Indicators Using the Friedman Method Firdaus, Ahmad Kanzu Syauqi; Nadhir, Ahmad; Naba, Agus
Natural B, Journal of Health and Environmental Sciences Vol 4, No 4 (2018)
Publisher : Natural B, Journal of Health and Environmental Sciences

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1095.546 KB)

Abstract

The analysis of the feature’s uniqueness of the electroencephalograph (EEG) signal extracted by continuous wavelet transform (CWT) method against the five BCI wheelchair control indicators has been done. The usage of Friedman method as measuring the uniqueness level of EEG signal features as well as their significance is used in this research. The EEG signals from three subjects that sitting on a regular chair were recorded when they were performing mental commands as seem as controlling a wheelchair with five control indicators. The recorded signals are decomposed by CWT. The absolute mean (|µ|) and the deviation standard (σ) of the CWT decomposition results are used as feature. Then, the uniqueness of |µ| and σ features are analyzed using Friedman Method. Based on the experiment results, it is known that the proposed method is able to map features according to their uniqueness level. The experiment result shows that the highest uniqueness value of |µ| feature from three subjects are 400 (“forward – backward” indicators), 437 (“neutral – turn left” indicators), and 597 (“neutral – turn left” indicators) respectively. While the highest uniqueness value of σ feature from each subjects are 380, 419, and 568 respectively in the same indicator pairs as |µ| feature.
Optimal Control Design of Eco-Friendly Power Generators Using Wind Power Ahmad Nadhir; Agus Naba
Natural B, Journal of Health and Environmental Sciences Vol 1, No 4 (2012)
Publisher : Natural B, Journal of Health and Environmental Sciences

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (59.557 KB) | DOI: 10.21776/ub.natural-b.2012.001.04.3

Abstract

Two optimal control methods based on fuzzy inference system (FIS) for maximizing extraction of energy in wind energy conversion system (WECS) is already presented. An MPPTFIS is a first optimal control method using maximum power point tracking approach and fuzzy system. The objective of MPPTFIS is to make zero value change rate of power and rotor speed. A control system will drive an actuator to increasing or decreasing  the generator speed depend on the measurement rate of power and rotor speed. An optimal of WECS can be achieved by carried through the rate of power and rotor speed that operating near optimal point. The second optimal control method is proposed by using adaptive neuro fuzzy inference system (ANFIS) to finding model of power curve that will be applied for design of linear control feedback (LCANFIS). The advantage of LCANFIS than MPPTFIS is only one parameter measusrement needed: wind speed. MPPTFIS and LCANFIS could maximize extraction of the wind energy that verified by a power coefficient Cp stay at its maximum almost all the time and an actual power line close to a maximum power extraction (MPE) line reference during simulation process using a same of wind profile.  
Preliminary Study on the Determination of Volcanic Tremor Epicenter Using Semblance Method (Case Study of Sakurajima Volcano) Ratri Andinisari; Sukir Maryanto; Ahmad Nadhir
Natural B, Journal of Health and Environmental Sciences Vol 2, No 2 (2013)
Publisher : Natural B, Journal of Health and Environmental Sciences

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1878.07 KB) | DOI: 10.21776/ub.natural-b.2013.002.02.12

Abstract

Volcanic tremor is one of the most important volcanic activities due its strong connection to magma movement and impeding eruption. Therefore, the determination of volcanic tremor epicenter becomes very important. The absence of apparent P and S wave arrival of volcanic tremor is the main constraint of its epicenter determination. The use of semblance method is required because semblance method requires no information about P and S wave arrival in epicenter determination. A preliminary application of semblance method has been done to determine the epicenter of 100 s length volcanic tremor of Sakurajima volcano. In this research we use the recorded seismic signal from 5 different volcano observatories, which are KOM, KAB, HIK, ARI, and HAR. The recorded tremor signal is then analyzed by using semblance method. The analysis is carried out by calculated semblance coefficient in every 30 s moving window along the signal. The resulting semblance coefficient varied from 0,25 to 0,42. The epicenter of observed volcanic tremor is located in the north-east part of Minamidake crater by -18,66o to 54,10o of azimuth counted from the east, while the epicentral distance of the observed volcanic tremor varied from 608,28 to 948,68 m from Minamidake crater.
Co-Authors Agus Naba Amalia Cemara Nuraidha, Amalia Cemara Arif Budianto Didik R. Santoso Didik Rahadi Santoso Firdaus, Ahmad Kanzu Syauqi Gancang Saroja M. Nurhuda Mohammad Hasib Ratri Andinisari Setyawan P. Sakti Sri Dwi Wuryani, Sri Dwi Sukir Maryanto Sukir Maryanto Sukir Maryanto Sukir Maryanto