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A new method for broad‐scale modeling and projection of plant assemblages under climatic, biotic, and environmental cofiltering
Published 2023“…By handling hundreds to thousands of plants and plots simultaneously over large areas, our method can inform broad-scale conservation of plant species under climate change because it allows species that require urgent conservation action (assisted migration, seed conservation, and ex situ conservation) to be detected and prioritized. …”
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Multimodal feature fusion and ensemble learning for non-intrusive occupancy monitoring using smart meters
Published 2025“…In this study, we introduce the multimodal feature fusion for non-intrusive occupancy monitoring (MMF-NIOM) framework, which leverages both classical and deep machine learning algorithms to achieve state-of-the-art occupancy detection performance using smart meter data. …”
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PSYCHOLOGICAL EMOTION RECOGNITION OF STUDENTS USING MACHINE LEARNING BASED CHATBOT
Published 2023“…In this paper, we propose a chatbot for detecting the students feeling by using machine-learning algorithms. …”
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PSYCHOLOGICAL EMOTION RECOGNITION OF STUDENTS USING MACHINE LEARNING BASED CHATBOT
Published 2023“…In this paper, we propose a chatbot for detecting the students feeling by using machine-learning algorithms. …”
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BIT-SLICE MICROPROCESSOR-BASED COMMUNICATIONS DECODER
Published 2020“…The design is versatile: different decoding algorithms can be executed by changing the microprogram. …”
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A GENERAL REAL-TIME DECODER BASED ON AMD2900 DEVICES
Published 2020“…The design is versatile since different decoding algorithms can be executed by changing the microprogram. …”
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Deep Learning-Based Fault Diagnosis of Photovoltaic Systems: A Comprehensive Review and Enhancement Prospects
Published 2021“…Thus, a key factor to be taken into consideration in high-efficiency grid-connected PV systems is the fault detection and diagnosis (FDD). The performance of the FDD method depends mainly on the quality of the extracted features including real-time changes, phase changes, trend changes, and faulty modes. …”
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Empowering IoT Resilience: Hybrid Deep Learning Techniques for Enhanced Security
Published 2024“…The time efficiency of both proposed algorithms renders them well-suited for deployment in IoT ecosystems. …”
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UML-based regression testing for OO software
Published 2010“…In the first phase, we select both unit and system test cases that directly traverse the changed methods and their calling methods. For the second phase, we present algorithms for detecting system level changes in the interaction overview diagram. …”
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Communication-Based Adaptive Overcurrent Protection for Distribution Systems with DistributedGenerators
Published 2012Get full text
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Integration of Textural and Material Information into BIM Using Spectrometry and Infrared Sensing
Published 2015Get full text
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32
Diabetic Sensorimotor Polyneuropathy Severity Classification Using Adaptive Neuro Fuzzy Inference System
Published 2021“…The model accuracy was validated with the results from different machine learning algorithms. The Accuracy, sensitivity, and specificity of the ANFIS model are 91.17±1.18%, 92±2.26%, 96.72±0.93%, respectively. …”
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BioNetApp: An interactive visual data analysis platform for molecular expressions
Published 2019“…Correlation analysis provides several visualization features such as Kamada-Kawai, Fruchterman-Reingold Spring embedding network layouts, in addition to single circle, multiple circle and heatmap layouts, whereas comparative analysis presents expression-data distributions across samples, groups, and time points with boxplot display, outlier detection, and data curve fitting. BioNetApp also provides data clustering based on molecular concentrations using Self Organizing Maps (SOM), K-Means, K-Medoids, and Farthest First algorithms.…”
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Automatic image quality evaluation in digital radiography using for‐processing and for‐presentation images
Published 2024“…<h3>Purpose</h3><p dir="ltr">To investigate the impact of digital image post‐processing algorithms on various image quality (IQ) metrics of radiographic images under different exposure conditions.…”