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1
Replica Creation Algorithm for Data Grids
Published 2012“…This thesis presents a new replication algorithm that improves data access performance in data grids by distributing relevant data copies around the grid. …”
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2
A new Gompertz-three-parameter-lindley distribution for modeling survival time data
Published 2025“…The statistical properties of the proposed distribution including the shape properties, cumulative distribution, quantile functions, moment generating function, failure rate function, mean residual function, and stochastic orders are studied. …”
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Confidence intervals (CI) for concentration parameter in von Mises distribution and analysis of missing values for circular data / Siti Fatimah binti Hassan
Published 2015“…For example, the distribution analogues to the normal distribution in linear data is known as circular normal distribution. …”
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Development of an islanding detection scheme based on combination of slantlet transform and ridgelet probabilistic neural network in distributed generation
Published 2019“…The error measurements of the proposed method such as Mean Absolute Percentage Error, Mean Absolute Error, And Root Mean Square Error for islanding detection are less than 0.02% for ideal and noisy conditions which shows that the algorithm is not sensitive to noise. …”
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Optimal planning of photovoltaic distributed generation considering uncertainties using monte carlo pdf embedded MVMO-SH
Published 2021“…The probabilistic values of PV generation and load models are employed as the input data to the load flow analysis for the radial distribution network. …”
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6
Development an accurate and stable range-free localization scheme for anisotropic wireless sensor networks
Published 2022“…Location information is an integral part of wireless sensor networks, without location information, all received data will lose meaning. However, the current localization scheme is based on equipped GPS on every node, which is not cost-efficient and not suitable for large-scale wireless sensor networks and outdoor environments. …”
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7
Interferometric array planning using division algorithm for radio astronomy applications
Published 2017“…The algorithm is able to distribute the u-v plane more efficiently than GMRT with 49.77% overlapped samples. …”
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Semantic-Based, Scalable, Decentralized and Dynamic Resource Discovery for Internet-Based Distributed System
Published 2010“…In short, our main contributions are outlined new key taxonomy for the semantic-based grid RD studies; an interoperable semantic description RD component model for intergrid services metadata representation; a semantic distributed registry architecture for indexing service metadata; and an agent-based service search and selection algorithm. …”
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Semantic-Based, Scalable, Decentralized and Dynamic Resource Discovery for Internet-Based Distributed System
Published 2010“…In short, our main contributions are outlined new key taxonomy for the semantic-based grid RD studies; an interoperable semantic description RD component model for intergrid services metadata representation; a semantic distributed registry architecture for indexing service metadata; and an agent-qased service search and selection algorithm. …”
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An optimal under frequency load shedding scheme for islanded distribution network / Amalina Izzati Md Isa
Published 2018“…However, the implementation of this technique is feasible for a smart grid distribution system possessing effective communication means, comprehensive monitoring tools and advanced sensors for transferring measurement data and executes load shedding.…”
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A new scheduling technique to improve data management in cloud computing
Published 2013“…Data Management is the key factor of Cloud Computing, which is „the right data in the right place at the right time’. …”
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12
Parallel power load abnormalities detection using fast density peak clustering with a hybrid canopy-K-means algorithm
Published 2025“…Parallel power loads anomalies are processed by a fast-density peak clustering technique that capitalizes on the hybrid strengths of Canopy and K-means algorithms all within Apache Mahout's distributed machine-learning environment. …”
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Dynamic feature selection model for adaptive cross site scripting attack detection using developed multi-agent deep Q learning model
Published 2023“…DQN-MAFS provides a sub-model for reward distribution over agents, which is named as fair agent reward distribution based dynamic feature selection FARD-DFS. …”
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Slice sampler algorithm for generalized pareto distribution
Published 2018“…In this paper, we developed the slice sampler algorithm for the generalized Pareto distribution (GPD) model. …”
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Estimation Of Weibull Parameters Using Simulated Annealing As Applied In Financial Data
Published 2023“…The finding reveals that the Weibull distribution is well-suited to describing the investment behaviour of the MPS based on the estimates via the SA algorithm. …”
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Content-based indexing of low resolution documents
Published 2016“…We present hierarchy indexing techniques, whose foundation are tree and clustering. K-means clustering are used for visual features like colour since their spatial distribution give a good image’s global information. …”
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Channel Modelling and Estimation in Multiple-Input Multiple-Output Orthogonal Frequency Division Multiplexing Wireless Communication Systems
Published 2008“…New time-domain (TD) adaptive estimation methods based on recursive least squares (RLS) and normalized least-mean squares (NLMS) algorithms are proposed. These estimators are then extended to blindly track the time-variations of the channel in the decision-directed (DD) mode. …”
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An observation of different clustering algorithms and clustering evaluation criteria for a feature selection based on linear discriminant analysis
Published 2022“…Overall, the k-means outperforms the Gaussian mixture distribution in selecting smaller feature subsets. …”
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A dynamic replication aware load balanced scheduling for data grids in distributed environments of internet of things
Published 2018“…Grid computing is a powerful distributed and scalable computing infrastructure that deals with massive data-intensive applications. …”
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