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Filtering by: Creator Palma, Elbio D. Academic Affiliation Electrical Engineering and Computer Science Resource Type Masters Thesis

Relational Learning over Dirty Data Using Data Constraints

Creator:

Lee, Ga Young

Abstract:

Real-world datasets are dirty and contain many errors. Examples of these issues are violations of integrity constraints, duplicates, and inconsistencies in representing data values and entities. Applying machine learning on dirty databases may lead to inaccurate results. Users have to spend a lot of time and effort repairing data errors...

Resource Type:

Masters Thesis

Full Text:

Dj , respectively, 1 ≤ i ≤ n, and 1 ≤ j ≤ m. Operation ≈d is a similarity operator defined over
Dynamic Composite Load Signature Detection and Classification using Supervised Learning over Disturbance Data

Creator:

Tray, Kelly

Abstract:

Load modeling that can accurately represent the dynamic behavior of generators and loads is important in the operation and planning of transmission and distribution systems. Yet, it is a complex subject in power system research communities and electric utilities. The composition of the end-use loads is changing continually based on...

Resource Type:

Masters Thesis

Full Text:

of {x1,i, x2,i, ..., xd,i, yi}. d is denoted as dimension number of features (d-dimensional data
Fabrication and characterization of p-type CuO / n-type ZnO heterostructure gas sensors prepared by sol-gel processing techniques

Creator:

Ravichandran, Ram

Abstract:

Increased interest in the field of sensor technology stems from the availability of an inexpensive and robust sensor to detect and quantify the presence of a specific gas. Bulk p-CuO/n-ZnO heterocontact based gas sensors have been shown to exhibit the necessary sensitivity and selectivity characteristics, however, low interfacial CuO/ZnO contact...

Resource Type:

Masters Thesis

Full Text:

sizes corresponding to ZnO and CuO are visible . . . . . . . . . . . . . . 62 32 3-d AFM image of the

ScholarsArchive@OSU

Relational Learning over Dirty Data Using Data Constraints

Dynamic Composite Load Signature Detection and Classification using Supervised Learning over Disturbance Data

Fabrication and characterization of p-type CuO / n-type ZnO heterostructure gas sensors prepared by sol-gel processing techniques

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