بدائل البحث:
process optimization » model optimization (توسيع البحث)
design optimization » bayesian optimization (توسيع البحث)
phase process » phase proteins (توسيع البحث), whole process (توسيع البحث), phase protein (توسيع البحث)
binary phase » binary image (توسيع البحث), final phase (توسيع البحث)
primary data » primary care (توسيع البحث)
process optimization » model optimization (توسيع البحث)
design optimization » bayesian optimization (توسيع البحث)
phase process » phase proteins (توسيع البحث), whole process (توسيع البحث), phase protein (توسيع البحث)
binary phase » binary image (توسيع البحث), final phase (توسيع البحث)
primary data » primary care (توسيع البحث)
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101
Basic color value distribution map of the street.
منشور في 2023"…We introduced the SegNet deep learning algorithm to semantically segment the street view images, extract the architectural elements and optimize the edges of the architecture. …"
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102
SegNet architecture.
منشور في 2023"…We introduced the SegNet deep learning algorithm to semantically segment the street view images, extract the architectural elements and optimize the edges of the architecture. …"
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103
Overview of workflow.
منشور في 2023"…We introduced the SegNet deep learning algorithm to semantically segment the street view images, extract the architectural elements and optimize the edges of the architecture. …"
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104
Descriptive statistics for the volunteers.
منشور في 2023"…We introduced the SegNet deep learning algorithm to semantically segment the street view images, extract the architectural elements and optimize the edges of the architecture. …"
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105
Jiefang North Road Street.
منشور في 2023"…We introduced the SegNet deep learning algorithm to semantically segment the street view images, extract the architectural elements and optimize the edges of the architecture. …"
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106
Colors with different number of clusters.
منشور في 2023"…We introduced the SegNet deep learning algorithm to semantically segment the street view images, extract the architectural elements and optimize the edges of the architecture. …"
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107
Fortran & C++: design fractal-type optical diffractive element
منشور في 2022"…</p> <p>(2) calculate diffraction fields for fractal and/or grid-matrix (binary) phase-holograms.</p> <p>(3) optimize the fractal and/or grid-matrix holograms for given target diffraction images, using annealing algorithms. …"
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108
Active Learning Accelerated Discovery of Stable Iridium Oxide Polymorphs for the Oxygen Evolution Reaction
منشور في 2020"…We emphasize that the proposed AL algorithm can be easily generalized to search for any binary metal oxide structure with a defined stoichiometry.…"
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109
Image 1_Noninvasive estimation of oxygenation index in pediatric critical care: an independent retrospective observational validation.pdf
منشور في 2025"…Objective<p>To independently validate an empirically optimized algorithm for calculating estimated Oxygenation Index (eOI) using noninvasive parameters from pediatric intensive care populations.…"
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110
CSPP instance
منشور في 2025"…</b></p><p dir="ltr">Its primary function is to create structured datasets that simulate container terminal operations, which can then be used for developing, testing, and benchmarking optimization algorithms (e.g., for yard stacking strategies, vessel stowage planning).…"
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111
Supplementary Material for: A new tool to assess patient-ventilator synchrony in preterm infants receiving non-invasive ventilation: a randomized crossover pilot study
منشور في 2025"…Methods: This study involved designing a custom algorithm for signal analysis. Data were collected through a polygraph that could simultaneously gather respiratory data from the patients and ventilator. …"
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112
An Ecological Benchmark of Photo Editing Software: A Comparative Analysis of Local vs. Cloud Workflows
منشور في 2025"…Experimental Methodology Framework Local Processing Pipeline Architecture Data Flow: Storage I/O → Memory Buffer → CPU/GPU Processing → Cache Coherency → Storage I/O ├── Input Vector: mmap() system call for zero-copy file access ├── Processing Engine: OpenMP parallelization with NUMA-aware thread affinity ├── Memory Management: Custom allocator with hugepage backing └── Output Vector: Direct I/O bypassing kernel page cache Cloud Processing Pipeline Architecture Data Flow: Local Storage → Network Stack → TLS Tunnel → CDN Edge → Origin Server → Processing Grid → Response Pipeline ├── Upload Phase: TCP window scaling with congestion control algorithms ├── Network Layer: Application-layer protocol with adaptive bitrate streaming ├── Server-side Processing: Containerized microservices on Kubernetes orchestration ├── Load Balancing: Consistent hashing with geographic affinity routing └── Download Phase: HTTP/2 multiplexing with server push optimization Dataset Schema and Semantic Structure Primary Data Vectors Field Data Type Semantic Meaning Measurement Unit test_type Categorical Processing paradigm identifier {local_processing, cloud_processing} photo_count Integer Cardinality of input asset vector Count avg_file_size_mb Float64 Mean per-asset storage footprint Mebibytes (2^20 bytes) total_volume_gb Float64 Aggregate data corpus size Gigabytes (10^9 bytes) processing_time_sec Integer Wall-clock execution duration Seconds (SI base unit) cpu_usage_watts Float64 Thermal design power consumption Watts (Joules/second) ram_usage_mb Integer Peak resident set size Mebibytes network_upload_mb Float64 Egress bandwidth utilization Mebibytes energy_consumption_kwh Float64 Cumulative energy expenditure Kilowatt-hours co2_equivalent_g Float64 Carbon footprint estimation Grams CO₂e test_date ISO8601 Temporal execution marker RFC 3339 format hardware_config String Node topology identifier Alphanumeric encoding Statistical Distribution Characteristics The dataset exhibits non-parametric distribution patterns with significant heteroscedasticity across computational load vectors. …"
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113
Table 1_Identification of routine blood derived hematological and lipid indices in ILD through machine learning; a retrospective case-control study.docx
منشور في 2025"…</p>Methods<p>We retrospectively analyzed 603 patients who had visited the Hubin Campus between January 2022 and April 2025, employing a 1:2 case-control design with age- and gender-matched groups. We collected clinical information, complete blood count data, lipid metabolism indicators, and various derived indices.…"
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114
Image 1_Identification of routine blood derived hematological and lipid indices in ILD through machine learning; a retrospective case-control study.tif
منشور في 2025"…</p>Methods<p>We retrospectively analyzed 603 patients who had visited the Hubin Campus between January 2022 and April 2025, employing a 1:2 case-control design with age- and gender-matched groups. We collected clinical information, complete blood count data, lipid metabolism indicators, and various derived indices.…"
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115
Dataset: Spatial Variability and Uncertainty of Soil Nitrogen across the Conterminous United States at Different Depths
منشور في 2022"…Finally, we used uncertainty information to propose optimized locations for designing future soil surveys and found that the Atlantic Neotropical, Pacific Northwest, Pacific Southwest, and Appalachian/Cumberland Plateau NEON domains may require larger survey efforts. …"