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  1. 1

    A New Approach of Optimal Search Solution in Particle Swarm Optimization (PSO) Algorithm for Object Detection Method by Zalili, Musa, Mohd Hafiz, Mohd Hassin, Nurul Izzatie Husna, Fauzi, Rohani, Abu Bakar, Watada, Junzo

    Published 2018
    “…Therefore, to overcome the several problems associated with the object detection method, a new approach in Particle Swarm Optimization (PSO) algorithm for optimal search solution as an alternative method to detect of object tracking quickly, precisely and accurately. …”
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  2. 2

    An Adaptive Switching Cooperative Source Searching And Tracing Algorithms For Underwater Acoustic Source Localization by Majid, Mad Helmi Ab.

    Published 2019
    “…In a source searching task, two possible scenarios can occur: source detected and source not detected. In this study, a complete solution to the two scenarios through an adaptive algorithm switching strategy is explored. …”
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  3. 3

    A Reference Based Surface Defect Segmentation Algorithm For Automatic Optical Inspection System by Wong, Ze-Hao

    Published 2020
    “…Surface defect segmentation algorithms in Automatic Optical Inspection (AOI) system for modern manufacturing industries provide solutions to quality control with speed, volume and traceability. …”
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  4. 4

    Power line corridor vegetation encroachment detection from satellite images using retinanet and support vector machine by Fathi Mahdi Elsiddig Haroun, Mr.

    Published 2023
    “…Several studies have provided solutions for detecting vegetation encroachment based on satellite images. …”
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  5. 5

    Fraud detection in shipping industry based on location using machine learning comparison techniques by Ganesan Subramaniam, Mr.

    Published 2023
    “…However, the challenge in data-driven detection is its effectiveness is often detection accuracy and the speed of detection. …”
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  6. 6

    Optimal distributed generation and load shedding scheme using artificial bee colony- hill climbing algorithm considering voltage stability and losses indices by Ali Abdallah, Ali Emhemed

    Published 2021
    “…To solve this problem, an optimal load shedding approach, integrated with optimal DG sizing is proposed using the ABC-HC algorithm. This technique can find the load location to be shed, as well as the size of DG. …”
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    Using electromechanical impedance and extreme learning machine to detect and locate damage in structures by Djemana, Mohamed, Hrairi, Meftah, Al Jeroudi, Yazan

    Published 2017
    “…In particular, electromechanical impedance (EMI) techniques give simple and low cost solutions for detecting damage in different structures. …”
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  9. 9

    An improved bat algorithm with artificial neural networks for classification problems by Rehman Gillani, Syed Muhammad Zubair

    Published 2016
    “…Then, the proposed BAGD algorithm is frnther hybridized with Simulated Annealing (SA) and Genetic Algorithm (GA) to perform two stage optimization in which the former algorithm finds the optimal solution and the latter algorithm starts from where the first one is converged. …”
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    Passive Client-Centric Rogue Access Point Detection Framework For WiFi Hotspots by Ahmad, Nazrul Muhaimin

    Published 2018
    “…The proliferation of Wi-Fi hotspots in public places provides seamless Internet connectivity anywhere at any time to the wireless clients.Although many hotspots are often unprotected,unmanaged and unencrypted,this does not prevent the clients from actively connecting to the network.The underlying problem is that the network Access Point (AP) is always trusted.The adversary can impersonate a legitimate AP by setting up a rogue AP to commit espionage and to launch evil-twin attack,session hijacking,and eavesdropping.To aggravate the threats, existing detection solutions are ill-equipped to safeguard the client against rogue AP.Infrastructure- centric solutions are heavily relied on the deployment of sensors or centralized server for rogue AP detection, which are limited,expensive and rarely to be implemented in hotspots.Even though client-centric solutions offer threat-aware protection for the client,but the dependency of the existing solutions on the spoofable contextual network information and the necessity to be associated with the network makes those solutions are not viable for the hotspot’s client.Hence,this work proposes a framework of passive client-centric rogue AP detection for hotspots.Unlike existing solutions,the key idea is to piggyback AP-specific and network-specific information in IEEE 802.11 beacon frame that enables the client to perform the detection without authentication and association to any AP.Based on the spatial fingerprints included in the broadcasted information from the APs in the vicinity of the client,this work discloses a novel concept that enables the rogue AP detection via the client’s ability to self-colocalize and self-validate its own position in the hotspot.The legitimacy of the APs in the hotspot,in this view,lies in the fact that the correct matching between the Received Signal Strength Indicator (RSSI) measurements at the client and pre-recorded fingerprints is attainable when the beacons are transmitted only from the legitimate APs.Hence,any anomalousness in AP’s beacon frame or any attempt to replay the legitimate AP’s beacon frame from different location can be detected and classified as rogue AP threats.Through experiments in real environment,the results demonstrate that with proper algorithm selection and parameters tuning,the rogue AP detection framework can achieve over 90% detection accuracy in classifying the absence and presence of rogue AP threats in the hotspot.…”
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  12. 12

    Forward-Backward Time Stepping with Automated Edge-preserving Regularization Technique for Wood Defects Detection by Yong, Guang

    Published 2019
    “…The FBTS integrated with automated edge-preserving regularization technique is first assessed with object detection application. The reconstructed images show that the algorithm was able to determine the dielectric properties within the region of interest (ROI) and estimate the shape, location of the embedded object. …”
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    Automatic detection and indication of pallet-level tagging from rfid readings using machine learning algorithms by Choong, Chun Sern

    Published 2020
    “…Identifying specific locations of items such as containers, warehouse pellets, and returnable packages in a large environment, for instance, in a warehouse, requires an extensive tracking system that could identify the location through data visualization. …”
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  15. 15

    Abnormal event detection in video surveillance / Lim Mei Kuan by Lim, Mei Kuan

    Published 2014
    “…The third contribution aims to provide an integrated solution to detect multiple events in different regions-of-interest of a given scene. …”
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  16. 16

    An enhancement particle-based method for dynamic object tracking by Zalili, Musa

    Published 2016
    “…This method is able to predict the precise location of object movement in the 2-D image. The combination of these two new proposed solutions, consequently, will improve the processing time in detecting the object with precision location. …”
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    Improving performance of automated coronary arterial tree center-line extraction, stent localization and tracking by Boroujeni, Farsad Zamani

    Published 2012
    “…The first contribution is automatic detection of seed points which serve as a prerequisite step for centerline extraction algorithm. …”
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  19. 19

    Modelling Autonomous Evacuation Navigation System (AENS) for optimal route using Dijkstra's algorithm by Abu Samah, Khyrina Airin Fariza

    Published 2016
    “…The ST itself is a conceptual framework that examines, reframes the problem and finds the solution. Through ST adaptation, all subsystems were integrated and using the “Dijkstra’s algorithm” (DA) by modifying its function from shortest path algorithm to safest and shortest algorithm, to the nearest exit. …”
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    Fault Detection and Identification in Quadrotor System (Quadrotor Robot) by Chan, Shi Jing, Pebrianti, Dwi

    Published 2016
    “…Fault Detection and Identification (FDI) monitor, identify, and pinpoint the type and location of system fault in a complex multiple input multiple output (MIMO) non-linear system. …”
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