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Block-Sphere Vector Quantization GroupAffect-4: A Multimodal Dataset of Four-Person Collaborative Interaction CogScale: Scalable Benchmark for Sequence Processing TextAlign: Preference Alignment for Text Rendering with Hierarchical Rewards LogRouter: Adaptive Two-Level LLM Routing for Log Question Answering in Big Data Systems Agentic Cost-Aware Query Planning with Knowledge Distillation for Big Data Analytics Covariance Structure and Coordinate Heterogeneity Govern Binary Quantization of Contrastive Embeddings IVF-TQ: Calibration-Free Streaming Vector Search via a Codebook-Free Residual Layer Automatic Unsupervised Ensemble Outlier Model Selection--Extended Version A Generative AI Framework for Intelligent Utility Billing CO 2 Analytics and Sustainable Resource Optimisation Towards Foundation Models for Relational Databases with Language Models and Graph Neural Networks Gaussian Relational Graph Transformer Croissant Baker: Metadata Generation for Discoverable, Governable, and Reusable ML Datasets Reducing Hallucination in Vision-Language Models via Stage-wise Preference Optimization under Distribution Shift A Horn extension of DL-Lite with NL data complexity 3D Primitives are a Spatial Language for VLMs Enabling AI-Native Mobility in 6G: A Real-World Dataset for Handover, Beam Management, and Timing Advance A CAP-like Trilemma for Large Language Models: Correctness, Non-bias, and Utility under Semantic Underdetermination EpiCastBench: Datasets and Benchmarks for Multivariate Epidemic Forecasting FERMI: Exploiting Relations for Membership Inference Against Tabular Diffusion Models Toward Multi-Database Query Reasoning for Text2Cypher Autonomous FAIR Digital Objects: From Passive Assertions to Active Knowledge HOME-KGQA: A Benchmark Dataset for Multimodal Knowledge Graph Question Answering on Household Daily Activities Detect, Localize, and Explain: Interactive Hierarchical Log Anomaly Analytics with LLM Augmentation Open Ontologies: Tool-Augmented Ontology Engineering with Stable Matching Alignment Machine Learning-Based Pre-Test Risk Stratification for PCR-Confirmed Chlamydia Using Patient-Reported Data and Urine Biomarkers Reconciling Consistency-Based Diagnosis with Actual-Causality-Based Explanations PrepBench: How Far Are We from Natural-Language-Driven Data Preparation? Anatomy of a Query: W5H Dimensions and FAR Patterns for Text-to-SQL Evaluation Building informative materials datasets beyond targeted objectives
Designing an Adaptive Bandwidth Management for Higher Edu...
Rolysent K Paredes, Alexander A. Hernandez · 2020-11-19 · via cs.DB updates on arXiv.org

Purpose: This study proposes an adaptive bandwidth management system which can be explicitly used by educational institutions. The primary goal of the system is to increase the bandwidth of the users who access more on educational websites. Through this proposed bandwidth management, the users of the campus networks is encouraged to utilize the internet for educational purposes. Method: The weblog from a university's pfSense proxy server was utilized and undergo Web Usage Mining (WUM) to determine the number of educational and non-educational websites accessed by the users. Certain formulas were used in the computation of the bandwidth which was dynamically assigned to the users. A prototyping technique was applied in developing adaptive bandwidth management system. The prototype was simulated and evaluated by experts in compliance with ISO/IEC 14598-6 and ISO/IEC 9126-1 standards. Results: This study found that the prototype is capable of adjusting the bandwidth of the network users dynamically. The users who browsed more on educational websites or contents were assigned with higher bandwidth compared to those who are not. Further, the evaluated prototype met the software standards of ISO. Conclusion: The proposed adaptive bandwidth management can contribute to the continuous development in the area of computer networking, especially in designing and managing campus networks. It also helps the network administrators or IT managers in allocating bandwidth with minimal effort.