College of Engineering
Parent: UC Davis
eScholarship stats: History by Item for September through December, 2024
Item | Title | Total requests | 2024-12 | 2024-11 | 2024-10 | 2024-09 |
---|---|---|---|---|---|---|
8r5848vp | RXMesh: A GPU Mesh Data Structure | 143 | 26 | 33 | 43 | 41 |
0x86w4w1 | Optimized GPU Implementation of Grid Refinement in Lattice Boltzmann Method | 136 | 40 | 30 | 32 | 34 |
1sm051d2 | Dynamic Mesh Processing on the GPU | 123 | 41 | 23 | 32 | 27 |
0227z2t1 | SANISAND-MSf: a sand plasticity model with memory surface and semifluidised state | 81 | 13 | 17 | 32 | 19 |
0p96v327 | DYNAMIC BEHAVIOR OF FOUNDATIONS: AN EXPERIMENTAL STUDY IN A CENTRIFUGE | 81 | 16 | 19 | 26 | 20 |
0hc042kf | CENTRIFUGE PREDICTION OF EGRESS SYSTEM PERFORMANCE | 74 | 24 | 15 | 21 | 14 |
830502mm | Use of Photron Cameras and TEMA Software to Measure 3D Displacements in Centrifuge Tests | 74 | 23 | 8 | 21 | 22 |
6j27m45d | Extracting and visualizing topological information from large high-dimensional data sets | 73 | 24 | 12 | 20 | 17 |
2jf918dh | CSE-92-18 - An Evaluation of Feature Selection Methodsand Their Application to Computer Security | 68 | 17 | 21 | 20 | 10 |
9534w5x1 | Multi-Stage Delivery of Malware | 68 | 19 | 9 | 18 | 22 |
5rv3d8np | Effect of Anisotropic Consolidation on Cyclic Liquefaction Resistance of Granular Materials via 3D-DEM Modeling | 63 | 27 | 6 | 19 | 11 |
6rt535s6 | Building a Performance Model for Deep Learning Recommendation Model Training on GPUs | 59 | 18 | 17 | 14 | 10 |
7j96s061 | Maximum Clique Enumeration on the GPU | 57 | 18 | 12 | 20 | 7 |
9fz7k633 | Neon: A Multi-GPU Programming Model for Grid-based Computations | 55 | 18 | 15 | 14 | 8 |
9wd8g79f | Effects of pressure and flow rate on the efficiency and performance of autothermal reforming systems for hydrogen production | 50 | 18 | 16 | 9 | 7 |
48j4k7np | Dynamic Graphs on the GPU | 46 | 21 | 6 | 10 | 9 |
3v12f7dn | Quotient Filters: Approximate Membership Queries on the GPU | 43 | 12 | 5 | 18 | 8 |
0bg5p8ch | Generalizing Tanglegrams | 40 | 6 | 6 | 20 | 8 |
3sf156w6 | Computational study of transport phenomena in microchannel reactors for hydrogen production by steam reforming | 39 | 18 | 7 | 11 | 3 |
5qd0r4ws | Parallel Algorithms and Dynamic Data Structures on the Graphics Processing Unit: a warp-centric approach | 38 | 13 | 8 | 9 | 8 |
7xs630v9 | Distributed Helios - Mitigating Denial of Service Attacks in Online Voting | 38 | 2 | 25 | 11 | |
4xb8p2jn | Resolving the Unexpected in Elections: Election Officials' Options | 36 | 11 | 1 | 20 | 4 |
7dc8d5vb | Benchmarking Deep Learning Frameworks with FPGA-suitable Models on a Traffic Sign Dataset | 34 | 15 | 7 | 10 | 2 |
5rj639x8 | Effects of inlet velocity and steam-to-methanol ratio on the phenomena of process intensification in protruded millisecond microchannel reactors | 33 | 12 | 6 | 10 | 5 |
74986309 | Numerical modeling of soil liquefaction and lateral spreading using the SANISAND-Sf model in the LEAP experiments | 33 | 10 | 13 | 8 | 2 |
0b41q7v8 | Leveraging Security Metrics to Enhance System and Network Resilience | 32 | 10 | 4 | 13 | 5 |
3z8926ks | Evolution vs. Intelligent Design in Program Patching | 32 | 16 | 3 | 7 | 6 |
5rz6t3q4 | NetSage: Open Privacy-Aware Network Measurement, Analysis, And Visualization Service | 32 | 5 | 4 | 20 | 3 |
65t741zg | GPU LSM: A Dynamic Dictionary Data Structure for the GPU | 32 | 3 | 10 | 9 | 10 |
9n3966b9 | Computational fluid dynamics and thermodynamic analysis of transport and reaction phenomena in autothermal reforming reactors for hydrogen production | 32 | 18 | 4 | 5 | 5 |
9zf8102c | Security Analysis of Scantegrity, an Electronic Voting System | 32 | 4 | 2 | 21 | 5 |
042876p3 | Effect of coefficient of uniformity on cyclic liquefaction resistance of granular materials | 31 | 7 | 5 | 11 | 8 |
0pn70122 | Molecular dynamics study of the thermal properties and phenomena of graphane and fluorographene | 31 | 18 | 3 | 8 | 2 |
1xb249zt | Modeling Systems Using Side Channel Information | 30 | 3 | 4 | 17 | 6 |
6bs3k9rt | Your Security Policy is What?? | 30 | 5 | 1 | 21 | 3 |
9r06p21c | What Do Firewalls Protect?An Empirical Study of Firewalls, Vulnerabilities, and Attacks | 30 | 8 | 1 | 17 | 4 |
4sk284kw | Benchmarking Deep Learning Frameworks and Investigating FPGA Deployment for Traffic Sign Classification and Detection | 28 | 10 | 4 | 11 | 3 |
6kp4p18t | Graph Coloring on the GPU | 28 | 11 | 6 | 7 | 4 |
6ww1c3bw | Parametrization and Effectiveness of Moving Target Defense Security Protections for Industrial Control Systems | 28 | 6 | 6 | 13 | 3 |
1vh8z8hp | Characteristic limitations of advanced plasticity and hypoplasticity models for cyclic loading of sands | 27 | 7 | 6 | 11 | 3 |
33k7b297 | SKS02: Centrifuge Test of Liquefaction-Induced Downdrag in Uniform Liquefiable Deposit | 26 | 3 | 8 | 11 | 4 |
37j8j27d | High-Performance Linear Algebra-based Graph Framework on the GPU | 26 | 10 | 7 | 8 | 1 |
7w08k57j | A Hybrid Constrained Coral Reefs Optimization Algorithm with Machine Learning for Optimizing Multi-reservoir Systems Operation | 26 | 7 | 8 | 7 | 4 |
4bw6m317 | The Hive Mind: Applying a Distributed Security Sensor Network to GENI- GENI Spiral 2 Final Project Report | 24 | 3 | 1 | 18 | 2 |
74f3q3wf | Applying Machine Learning to Identify NUMA End-System Bottlenecks for Network I/O | 24 | 5 | 6 | 12 | 1 |
0xj8f0s6 | Effect of particle shape on cyclic liquefaction resistance of granular materials | 23 | 12 | 2 | 7 | 2 |
8t42g1c5 | Improvements of efficiency and performance for steam reforming reactors with optimum conditions of wall thermal conductivities and channel dimensions | 23 | 6 | 4 | 11 | 2 |
9v75738g | Towards Flexible and Compiler-Friendly Layer Fusion for CNNs on Multicore CPUs | 23 | 3 | 6 | 12 | 2 |
6ks778pm | Thermal fluctuations and bending rigidities of graphane and fluorographene at different temperatures | 22 | 5 | 4 | 8 | 5 |
9459p69n | Continuous and efficient production of hydrogen from methanol in protruded millisecond microchannel reactors for fuel cell applications | 22 | 10 | 4 | 7 | 1 |
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