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    Notch Signaling Inhibition by LY411575 Attenuates Osteoblast Differentiation and Decreased Ectopic Bone Formation Capacity of Human Skeletal (Mesenchymal) Stem Cells by Nihal AlMuraikhi (6002234)

    Published 2019
    “…Among the tested molecules, LY411575, a potent γ-secretase and Notch signaling inhibitor, exhibited significant inhibitory effects on osteoblastic differentiation of hBMSCs manifested by reduced ALP activity, mineralized matrix formation, and decreased osteoblast-specific gene expression as well as in vivo ectopic bone formation. …”
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    Correlation Clustering via s-Club Cluster Edge Deletion by Makarem, Norma

    Published 2023
    “…Cluster Editing, a known model for correlation clustering, has garnered significant consideration in the parameterized complexity area and has been utilized in a range of practical contexts. …”
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    masterThesis
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    Augmented arithmetic optimization algorithm using opposite-based learning and lévy flight distribution for global optimization and data clustering by Abu Zitar, Raed

    Published 2022
    “…This paper proposes a new data clustering method using the advantages of metaheuristic (MH) optimization algorithms. …”
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    An Efficient Brain Tumor Segmentation Method Based on Adaptive Moving Self-Organizing Map and Fuzzy K-Mean Clustering by Surjeet Dalal (4906894)

    Published 2023
    “…With the advent of a new era and research into machine learning, tumor detection and segmentation generated significant interest in the research world. This research presents an efficient tumor detection and segmentation technique using an adaptive moving self-organizing map and Fuzzyk-mean clustering (AMSOM-FKM). …”
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    RL-Based Adaptive UAV Swarm Formation and Clustering for Secure 6G Wireless Communications in Dynamic Dense Environments by Zain Ul Abideen Tariq (17984107)

    Published 2024
    “…Our work introduces an adaptive UAV swarm formation and dynamic device clustering technique designed for efficient anti-jamming in dynamic multi-user clusters threatened by unknown jammers during critical public events. …”
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    A clustering metaheuristic for large orienteering problems by Almiqdad Elzein (13141038)

    Published 2022
    “…Motivated by these limitations, we propose a multi-stage clustering-based metaheuristic for tackling large Orienteering Problems in an effective, strategically controlled amount of computation time. …”
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    Cluster-based anonymity model and algorithm for 1:1 dataset with a single sensitive attribute using machine learning technique by J. Jayapradha (21323774)

    Published 2024
    “…An efficient Cluster Based anonymity model has been proposed to anonymizes the 1:1 dataset with a single sensitive attribute through the introduction of a concept named “Semi-sensitive attribute.” …”
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    A slow but steady nanoLuc: R162A mutation results in a decreased, but stable, nanoLuc activity by Wesam S. Ahmed (10170053)

    Published 2024
    “…In this regard, engineering of brighter bioluminescent proteins, i.e. luciferases, has played a significant role. This is acutely exemplified by the engineering of the NLuc <u>luciferase</u>, which is small in size and displays much enhanced bioluminescence and<u> thermal stability</u> compared to previously available luciferases. …”
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    Simple and effective neural-free soft-cluster embeddings for item cold-start recommendations by Shameem A. Puthiya Parambath (14150997)

    Published 2022
    “…Here we propose a two-stage algorithm based on soft clustering to provide an efficient solution to this problem. …”
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    Supply chain planning of vaccine and pharmaceutical clusters under uncertainty: The case of COVID-19 by Farid Kochakkashani (17876918)

    Published 2023
    “…The clustering technique reduced the size of the problem and the time required to solve the model considerably.…”
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    Unsupervised knowledge representation of panoramic dental X-ray images using SVG image-and-object clustering by Salameh, Khouloud

    Published 2023
    “…We have created a labelled SVG dataset consisting of 22,553 objects from 750 images based on panoramic dental X-ray images. To our knowledge, it is the first significant dataset of labelled SVG objects and images, which we make available online as a benchmark for future research in this area. …”
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