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181
Data redundancy management for leaf-edges in connected environments
Published 2022“…Although the sensed data could be useful for various applications (e.g., event detection in cities, energy management in commercial buildings), it first requires pre-processing to clean various inconsistencies (e.g., anomalies, redundancies, missing values). …”
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182
Simulated annealing and genetic algorithms for exam scheduling. (c1997)
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masterThesis -
183
Application of Data Mining to Predict and Diagnose Diabetic Retinopathy
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doctoralThesis -
184
GenDE: A CRF-Based Data Extractor
Published 2020“…If the wrapper failed to work with the new page, a new wrapper/schema would be re-generated by calling an unsupervised wrapper induction system. In this paper, a new data extractor called GenDE is proposed. It verifies the site schema and extracts data from the Web pages using Conditional Random Fields (CRFs). …”
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185
(k, l)-Clustering for Transactional Data Streams Anonymization
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conferenceObject -
186
Exploring Semi-Supervised Learning Algorithms for Camera Trap Images
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doctoralThesis -
187
A fast exact sequential algorithm for the partial digest problem
Published 2016“…Two types of simulated data, random and Zhang, are used to measure the efficiency of the algorithm. …”
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188
Synthesis of MVL Functions - Part I: The Genetic Algorithm Approach
Published 2006“…Multiple-Valued Logic (MVL) has been used in the design of a number of logic systems, including memory, multi-level data communication coding, and a number of special purpose digital processors. …”
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189
Data mining approach to predict student's selection of program majors
Published 2019“…The approach includes a methodology to manage data mining projects, sampling techniques to handle imbalanced data and multiclass data, a set of classification algorithms to predict and measures to evaluate performance of models. …”
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190
Eye-Clustering: An Enhanced Centroids Prediction for K-means Algorithm
Published 2024“…Among these, K-means is widely used for efficiently solving clustering problems. …”
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masterThesis -
191
A Scatter search algorithm for exam scheduling. (c2006)
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masterThesis -
192
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193
Enhanced climate change resilience on wheat anther morphology using optimized deep learning techniques
Published 2024“…The DinoLite Microscope’s high-resolution images are used to measure the length and width of wheat anthers. …”
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194
Second-order conic programming for data envelopment analysis models
Published 2022“…Data envelopment analysis (DEA) is a widely used benchmarking technique. …”
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195
Evolutionary algorithms for state justification in sequential automatic test pattern generation
Published 2005“…A common search operation in sequential Automatic Test Pattern Generation is to justify a desired state assignment on the sequential elements. State justification using deterministic algorithms is a difficult problem and is prone to many backtracks, which can lead to high execution times. …”
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196
Revolutionizing sustainable supply chain management: A review of metaheuristics
Published 2023“…The paper also identifies the key factors that influence the success of using metaheuristics for SSCM, such as the choice of algorithm, problem complexity, and data quality. …”
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197
Novel Peak Detection Algorithms for Pileup Minimization in Gamma Ray Spectroscopy
Published 2006“…This study uses the above facility in developing algorithms for digitally determining the basic pulse parameters and tackling the problem of pulse pile-up in Gamma-ray spectroscopy. …”
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198
The buffered work-pool approach for search-tree based optimization algorithms
Published 2017“…Recent advances in algorithm design have shown a growing interest in seeking exact solutions to many hard problems. …”
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conferenceObject -
199
An image processing and genetic algorithm-based approach for the detection of melanoma in patients
Published 2018“…The second phase classifies lesions using a Genetic Algorithm. Our technique shows a significant improvement over other well-known algorithms and proves to be more stable on both training and testing data.…”
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200
Wild Blueberry Harvesting Losses Predicted with Selective Machine Learning Algorithms
Published 2022“…The outcomes revealed that these ML algorithms can be useful in predicting ground losses during wild blueberry harvesting in the selected fields.…”