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421
Traffic Offloading with Channel Allocation in Cache-Enabled Ultra-Dense Wireless Networks
Published 2018“…Traffic offloading via device-to-device communications is expected to play a major role to meet the exponential data traffic growth in wireless networks. In this work, we focus on the problem of user capacity maximization in ultra dense heterogeneous networks with device-to-device cooperation, where a large number of users in a given geographical area request common data content, such as video on demand streaming, with strict quality of service guarantees. …”
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422
LDSVM: Leukemia Cancer Classification Using Machine Learning
Published 2022“…The main aim was to predict the initial leukemia disease. Machine learning algorithms such as decision tree (DT), naive bayes (NB), random forest (RF), gradient boosting machine (GBM), linear regression (LinR), support vector machine (SVM), and novel approach based on the combination of Logistic Regression (LR), DT and SVM named as ensemble LDSVM model. …”
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423
Design and Analysis of Lightweight Authentication Protocol for Securing IoD
Published 2021“…An attacker can easily capture data from the available network channel and use it for their own purpose. …”
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424
Dynamic multiple node failure recovery in distributed storage systems
Published 2018“…Our daily lives are getting more and more dependent on data centers and distributed storage systems in general, whether at the business or at the personal level. …”
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425
Decision-level Gait Fusion for Human Identification at a Distance
Published 2014Get full text
doctoralThesis -
426
Efficient XML Structural Similarity Detection using Sub-tree Commonalities
Published 2007“…Developing efficient techniques for comparing XML-based documents becomes essential in the database and information retrieval communities. Various algorithms for comparing hierarchically structured data, e.g. …”
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conferenceObject -
427
SemIndex: Semantic-Aware Inverted Index
Published 2017“…We provide here a new approach, called SemIndex, that extends the standard inverted index by constructing a tight coupling inverted index graph that combines two main resources: a general purpose semantic network, and a standard inverted index on a collection of textual data. We also provide an extended query model and related processing algorithms with the help of SemIndex. …”
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conferenceObject -
428
Combining offline and on-the-fly disambiguation to perform semantic-aware XML querying
Published 2023“…Dedicated weighting functions and various search algorithms have been developed for that purpose and will be presented here. …”
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429
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430
Clustering and Stochastic Simulation Optimization for Outpatient Chemotherapy Appointment Planning and Scheduling
Published 2022“…A Stochastic Discrete Simulation-Based Multi-Objective Optimization (SDSMO) model is developed and linked to clustering algorithms using an iterative sequential approach. …”
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431
From Collatz Conjecture to chaos and hash function
Published 2023“…The effectiveness and dependability of the proposed hash function are evaluated by comparing it with two well-known hash algorithms, namely SHA-3 and SHA-2, as well as several other Chaos-based hash algorithms. …”
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432
Nonlinear Friction Identification of A Linear Voice Coil DC Motor
Published 2015Get full text
doctoralThesis -
433
An Auction-Based Scheduling Approach for Minimizing Latency in Fog Computing Using 5G Infrastructure
Published 2020Get full text
doctoralThesis -
434
Towards secure private and trustworthy human-centric embedded machine learning: An emotion-aware facial recognition case study
Published 2023“…Since the success of AI is to be measured ultimately in terms of how it benefits human beings, and that the data driving the deep learning-based edge AI algorithms are intricately and intimately tied to humans, it is important to look at these AI technologies through a human-centric lens. …”
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435
Machine Learning–Based Approach for Identifying Research Gaps: COVID-19 as a Case Study
Published 2024“…Furthermore, future studies could evaluate more efficient modeling algorithms, especially those combining topic modeling with statistical uncertainty quantification, such as conformal prediction.…”
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437