J. J. McArthur

15 papers Journal 14Unranked 1
YearRankTypeTitle / Venue / Authors
2024 J jnl
Autoencoder-Based fault detection using building automation system data.
Adv. Eng. Informatics
Karim El Mokhtari, J. J. McArthur
2024 J jnl
The benefit of noise-injection for dynamic gray-box model creation.
Adv. Eng. Informatics
Mohamed S. Kandil, J. J. McArthur
2023 J jnl
B-SMART: A reference architecture for artificially intelligent autonomic smart buildings.
Eng. Appl. Artif. Intell.
Mikhail Genkin, J. J. McArthur
2023 J jnl
Exploring Artificial Intelligence Methods for Energy Prediction in Healthcare Facilities: An In-Depth Extended Systematic Review.
CoRR
Marjan FatehiJananloo, Helen Stopps, J. J. McArthur
2023 J jnl
ReLBOT: A Transfer Learning Approach to Minimize Reinforcement Learning Risks in Smart Buildings.
CoRR
Mikhail Genkin, J. J. McArthur
2023 J jnl
The Benefit of Noise-Injection for Dynamic Gray-Box Model Creation.
CoRR
Mohamed S. Kandil, J. J. McArthur
2023 J jnl
Unsupervised Learning for Fault Detection of HVAC Systems: An OPTICS -based Approach for Terminal Air Handling Units.
CoRR
Farivar Rajabi, J. J. McArthur
2022 J jnl
A review of ontologies for smart and continuous commissioning.
CoRR
Sara Gilani, Caroline Quinn, J. J. McArthur
2022 J jnl
B-SMART: A Reference Architecture for Artificially Intelligent Autonomic Smart Buildings.
CoRR
Mikhail Genkin, J. J. McArthur
2022 J jnl
Building Automation System Data Integration with BIM: Data Structure and Supporting Case Study.
CoRR
Caroline Quinn, Ali Zargar Shabestari, Marin Litoiu, J. J. McArthur
2022 J jnl
Comparison of Brick and Project Haystack to Support Smart Building Applications.
CoRR
Caroline Quinn, J. J. McArthur
2022 J jnl
Fault Detection for Non-Condensing Boilers using Simulated Building Automation System Sensor Data.
CoRR
Rony Shohet, Mohamed S. Kandil, J. J. McArthur
2022 — conf
Using Reinforcement Learning with Transfer Learning to Overcome Smart Building Cold Start.
CSCI
Mikhail Genkin, J. J. McArthur
2021 J jnl
A case study comparing the completeness and expressiveness of two industry recognized ontologies.
Adv. Eng. Informatics
Caroline Quinn, J. J. McArthur
2020 J jnl
Fault detection for non-condensing boilers using simulated building automation system sensor data.
Adv. Eng. Informatics
Rony Shohet, Mohamed S. Kandil, Yidan Wang, J. J. McArthur
redb/extractors/macho_extractors/__init__.py
← Index redb/extractors/macho_extractors/__init__.py python 
# MachO extractors package

from .macho_features import MachOFeaturesExtractor
from .macho_segments import MachOSegmentExtractor
from .macho_imports import MachOImportExtractor
from .macho_exports import MachOExportExtractor
from .macho_dylibs import MachODylibExtractor
from .macho_signature import MachOSignatureExtractor
from .macho_similarity_hashes import MachOSimilarityHashExtractor
# MachOUniversalExtractor is deprecated - FAT binary relationships are now
# tracked via parent_sha256 column in redb_basic_properties
# from .macho_universal import MachOUniversalExtractor

__all__ = [
    'MachOFeaturesExtractor',
    'MachOSegmentExtractor',
    'MachOImportExtractor',
    'MachOExportExtractor',
    'MachODylibExtractor',
    'MachOSignatureExtractor',
    'MachOSimilarityHashExtractor',
    # 'MachOUniversalExtractor',  # Deprecated
]