Search Results - (( developing intention modified algorithm ) OR ( java application matching algorithm ))

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    A new modified differential evolution algorithm scheme-based linear frequency modulation radar signal de-noising by Al-Dabbagh, Mohanad Dawood, Al-Dabbagh, Rawaa Dawoud, Raja Abdullah, Raja Syamsul Azmir, Hashim, Fazirulhisyam

    Published 2015
    “…The main intention of this study was to investigate the development of a new optimization technique based on the differential evolution (DE) algorithm, for the purpose of linear frequency modulation radar signal de-noising. …”
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    Article
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    The Development Of Planar Curves With High Aesthetic Value by Rudrusamy, Gobithaasan

    Published 2010
    “…The pattern of research in this ¯eld of study has branched to ¯ve major groups; the devel- opment of fairing algorithms; the development of planar curves via curve synthesis, the development of algorithms to modify natural spirals to suit design intent, the modi¯cation of °exible curves (B¶ezier and NURBS) so that the curvature pro¯le is strictly monotonic and ¯nally, the development of algorithms to ¯t natural spirals and approximation via °exible curves.…”
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    Thesis
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    Power system intentional islanding for different contingency scenarios using discrete optimization technique by Nur Zawani Binti Saharuddin

    Published 2023
    “…In addition, the results of the case studies (with critical line outage) showed that the MDEP algorithm was able to obtain the optimal intentional islanding strategy with minimal power flow disruption.…”
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    Securing cloud data system (SCDS) for key exposure using AES algorithm by Thabet Albatol, Mohammed Samer Hasan

    Published 2021
    “…The AES algorithm has its own structure to encrypt and decrypt sensitive data that make the attackers difficult to get the real data when encrypting by AES algorithm. …”
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    A comprehensive analysis of surface electromyography for control of lower limb exoskeleton by Abdelhakim, Deboucha

    Published 2016
    “…The experiments were conducted on five subjects where the sEMG signals were recorded over four major muscles of the lower limb (Biceps Femoris (BF), Rectus Femoris (RF), Gastrocnemius (Gas) and Soleus (Sol) muscles) along with the kinematics recordings. A novel algorithm to determine the overlapped crosstalk recordings was developed along with a modified low pass filter that adaptively removes these recordings. …”
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