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using algorithm » cosine algorithm (Expand Search)
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finding » findings (Expand Search)
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From low-cost sensors to high-quality data: A summary of challenges and best practices for effectively calibrating low-cost particulate matter mass sensors
Published 2021“…Unfortunately, low-cost PM sensors also come with a number of challenges that must be addressed if their data products are to be used for anything more than a qualitative characterization of air quality. …”
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343
Using machine learning for disease detection. (c2013)
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masterThesis -
344
Practical Multiple Node Failure Recovery in Distributed Storage Systems
Published 2016“…The problem is solved using genetic algorithms that search within the feasible solution space. …”
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conferenceObject -
345
Cutting‐edge technologies for detecting and controlling fish diseases: Current status, outlook, and challenges
Published 2024“…Here, we highlighted the potential of machine learning algorithms in early pathogen detection and the possibilities of intelligent aquaculture in controlling disease outbreaks at the farm level. …”
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346
Tracking and repairing damaged healthcare databases using the matrix
Published 2015“…The algorithm is based on data dependency and uses a single matrix. …”
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347
Energy-aware adaptive compression for mobile devices. (c2009)
Published 2009Get full text
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masterThesis -
348
Simple and effective neural-free soft-cluster embeddings for item cold-start recommendations
Published 2022“…The best available recommendation algorithms are based on using the observed preference information among collaborating entities. …”
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349
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350
Assessing Factors Influencing Customers’ Adoption of AI-Based Voice Assistants
Published 2024“…It also provides implications for tech-managers and algorithm designers to build effective voice technology for superior user experience.…”
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351
Diagnosing failed distribution transformers using neural networks
Published 2001“…The ANN was trained utilizing backpropagation algorithm using a real (out of the field) data obtained from utilities distribution networks transformer's failures. …”
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352
Transmission Line Fault Location Using Unsynchronized Measurements
Published 2013Get full text
doctoralThesis -
353
Plant disease detection using drones in precision agriculture
Published 2023“…Color-infrared (CIR) images are the most preferred data used and field images are the main focus. The machine learning algorithm applied most is convolutional neural network (CNN). …”
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354
Optimization of Piezoelectric Sensor-Actuator for Plate Vibration Control Using Evolutionary Computation: Modeling, Simulation and Experimentation
Published 2021“…The analytical model is derived based on the Euler-Bernoulli model. The Optimal location of the collocated sensor-actuator, as well as PID controller gains, are determined using Ant Colony Optimization (ACO) technique, then compared with the Genetic Algorithm (GA) and enumerative method (EM). …”
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355
LDSVM: Leukemia Cancer Classification Using Machine Learning
Published 2022“…This study proposes a novel method using machine learning algorithms based on microarrays of leukemia GSE9476 cells. …”
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356
Building power consumption datasets: Survey, taxonomy and future directions
Published 2020“…Furthermore, data collection platforms and related modules for data transmission, data storage and privacy concerns used in different datasets are also analyzed and compared. …”
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357
Assigning proctors to exams using scatter search. (c2006)
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masterThesis -
358
Cyberbullying Detection in Arabic Text using Deep Learning
Published 2023“…Cyberbullying involves the use of communication technology and data, including messages, photographs, and videos, to undertake aggressive negative actions to harm others. …”
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359
AI-Based Methods for Predicting Required Insulin Doses for Diabetic Patients
Published 2015“…In this paper, we propose and compare three techniques two of which are Artificial Intelligence techniques, namely C4.5 and Case-Based Reasoning, and the third one is a meta-heuristic namely genetic algorithms. …”
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article -
360
Efficient Seismic Volume Compression using the Lifting Scheme
Published 2000“…As the approximation coefficients represent a smooth low-resolution version of the input data they are only quantized using a uniform scalar quantizer (USQ). …”
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article