Rossi Passarella
Universitas Sriwijaya

Published : 25 Documents
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Journal : ICON-CSE

Hand Gesture Recognition as Password to Open The Door With Camera and Convexity Defect Method passarella, rossi; Fadli, Muhammad; Sutarno, Sutarno
ICON-CSE Vol 1, No 1 (2014)
Publisher : ICON-CSE

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Abstract

Computer Vision is one of reasearch that gets a lot of attention with many applications. One of the application is the hand gesture recognition system. By using EmguCV, will be obtained camera images from webcam camera. The Pictures will be disegmented by using  skin detection method for decrease noises in order to obtain the information needed. The final project of this system is to implement the convexity defect method for extracting images and recognize patterns of hand gesture that represent the characters A, B, C, D, and E. The parameters used in pattern recognition of hand gesture is the number and length of the line connecting the hull and defects derived from the pattern of hand gesture.
ELCONAS Electronic Control Using Android System With Bluetooth Communication And Sms Gateway Based Microcontroller Fadhil, Ahmad; Prasetia, Yandi; Adiansyah, Adiansyah; Tunnisa, Titin Wahdania; Ambarwati, Ayu; Passarella, rossi
ICON-CSE Vol 1, No 1 (2014)
Publisher : ICON-CSE

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Abstract

ELCONAS (Electronic Control with Android System) is a tool designed to control electronic devices. This control Android via Bluetooth communication and SMS Gateway that can be controlled by the user. Control using Bluetooth, applied for a certain distance which is connected to android, Bluetooth with limited distance range of services and the use of the remote system is used SMS Gateway is connected via a short message that is sent to the microcontroller through a module that has been installed on the microcontroller, using ArdunioMega 2560. ELCONAS designed to minimize the occurrence of short circuits and even prevent fires because the user can handle it via the application without having to interact directly with electronic devices that are at home or office.
Molecular Docking on Azepine Derivatives as Potential Inhibitors for H1N1-A Computational Approach Frimayanti, Neni; Murdiya, Fri; passarella, rossi
ICON-CSE Vol 1, No 1 (2014)
Publisher : ICON-CSE

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Abstract

Azepine are an important class of organic compounds. They are effective in a wide range of biological activity such as antifeedants, antidepressants, CNS stimulants, calcium channel blocker, antimicrobial and antifungal properties. In our continue efforts to search for a potent inhibitor for H1N1 virus using molecular docking. In this study, 15 azepine (ligands) derivatives were docked to the neuraminidase of A/Breving Mission/1/1918 H1N1 strain in complex with zanamivir (protein). The Cdocker energy was then calculated for these complexes (protein-ligand). Based on the calculation, the lowest Cdocker interaction energy was selected and potential inhibitors can be identified. Compounds MA4, MA7, MA8, MA10, MA11 and MA12 with promising Cdocker energy was expected to be very effective against the neuraminidase H1N1.