RMSE on the test data when fitting (logistic) quadratic models to binary data across increasing measurement error values . حسب Jakub Stoklosa (3315042)

Generalized Low-Rank Plus Sparse Tensor Estimation by Fast Riemannian Optimization حسب Jian-Feng Cai (498405)

Reverse engineering information flow using stimulus-encoding and stimulus-transfer estimation algorithms. حسب Gabriel Matías Lorenz (21094672)

Individual Transition Label Noise Logistic Regression in Binary Classification for Incorrectly Labeled Data حسب Seokho Lee (10088)

"…We propose an efficient algorithm under the thresholding rule for individual parameter estimation. …"

Overview of the segmentation algorithm. حسب Michael C. Robitaille (11949174)

Determination of the Solute Content and Volumetric Properties of Binary Ionic Liquid Mixtures Using a Global Regularity of Molar Volume Expansion حسب Javad Hekayati (1383249)

"…For instance, the water content, which is of great significance in IL studies, can easily be estimated using the proposed algorithm. By doing so, an overall AARD of 3.47% was obtained for the estimation of the water content of 68 binary systems. …"

Fig 1 - حسب Jakub Stoklosa (3315042)

Big Data Model Building Using Dimension Reduction and Sample Selection حسب Lih-Yuan Deng (17081779)

"…Recently, several procedures have been proposed to select “optimal design points” as training subdata under pre-specified models, such as linear regression and logistic regression. …"

DataSheet_1_Preoperatively Estimating the Malignant Potential of Mediastinal Lymph Nodes: A Pilot Study Toward Establishing a Robust Radiomics Model Based on Contrast-Enhanced CT I... حسب Mengshi Dong (5181833)

Data_Sheet_1_Performance of TB-LAMP in the Diagnosis of Tuberculous Empyema Using Samples Obtained From Pleural Decortication.docx حسب Chang Liu (35901)

QSAR model for predicting neuraminidase inhibitors of influenza A viruses (H1N1) based on adaptive grasshopper optimization algorithm حسب Z.Y. Algamal (5547620)

"…Obtaining a reliable QSAR model with few descriptors is an essential procedure in chemometrics. The binary grasshopper optimization algorithm (BGOA) is a new meta-heuristic optimization algorithm, which has been used successfully to perform feature selection. …"

Data_Sheet_1_A real-time driver fatigue identification method based on GA-GRNN.ZIP حسب Xiaoyuan Wang (492534)

Multicategory Angle-Based Learning for Estimating Optimal Dynamic Treatment Regimes With Censored Data حسب Fei Xue (24567)

"…Specifically, the proposed method obtains the optimal DTR via integrating estimations of decision rules at multiple stages into a single multicategory classification algorithm without imposing additional constraints, which is also more computationally efficient and robust. …"

Table 1_Provider fidelity in tuberculosis screening practices among adolescents and adults living with HIV in public health facilities in Tanzania: a cross-sectional evaluation.doc... حسب Lucas L. Shilugu (22644302)

"…Modified Poisson regression with robust variance was used to estimate prevalence ratios (PRs) to determine factors associated with two binary outcomes: (1) consistent TB screening over 12-month period, and (2) correct utilization of the screening tool. …"

Table 2_Provider fidelity in tuberculosis screening practices among adolescents and adults living with HIV in public health facilities in Tanzania: a cross-sectional evaluation.doc... حسب Lucas L. Shilugu (22644302)

"…Modified Poisson regression with robust variance was used to estimate prevalence ratios (PRs) to determine factors associated with two binary outcomes: (1) consistent TB screening over 12-month period, and (2) correct utilization of the screening tool. …"

Comparisons of prediction of phenotypes by the microbiome. حسب Daphna Rothschild (561439)

Data Sheet 1_Artificial intelligence-assisted capsule endoscopy for detecting lesions in Crohn’s disease: a systematic review and meta-analysis.docx حسب Yuling Bin (20970842)

"…Meta-regression analysis further revealed that AI algorithm type, study population size, and study design might be key sources of heterogeneity.…"

An AI-based Ecosystem for Real-time Gravitational Wave Analyses حسب Erik Katsavounidis (19369348)

"…These searches include A-frame, a low-latency machine learning pipeline for compact binary sources of gravitational waves, DeepClean, a deep learning-based denoising scheme for astrophysical gravitational waves, GWAK, a semi-supervised AI strategy to identify unmodeled gravitational wave transients, and AMPLFI, a pipeline for deep learning-based parameter estimation, leading to latency improvements for multi-messenger targets. …"

An Ecological Benchmark of Photo Editing Software: A Comparative Analysis of Local vs. Cloud Workflows حسب Pierre-Alexis DELAROCHE (22092572)

"…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. …"

PGAE-ICA_A simplified digital system for intellectual measurement-assessment in children and adolescents using cognitive testing and machine learning techniques حسب Runzhou Wang (5894849)

"…A genetic algorithm-optimized extreme learning machine model was then constructed and trained to predict intellectual status of children and adolescents. …"