Active Learning SVM Classification Algorithm for Complaints Management Process Automatization

2019 ◽  
Author(s):  
Pavels Goncarovs
Keyword(s):  
Active Learning ◽  
Classification Algorithm ◽  
Management Process ◽  
Svm Classification

scholarly journals Obscure Image Classification and Restoration using Support Vector Machines

2019 ◽  
Vol 8 (4) ◽  
pp. 8231-8236
Keyword(s):  
Kernel Estimation ◽  
Classification Algorithm ◽  
Support Vector ◽  
Svm Classification ◽  
Vector Machines ◽  
Blurred Image ◽  
Simulation Results ◽  
Blurred Images ◽  
Identification And Characterization ◽  
Restoration Model

A restoration and classification computation for blurred image which depends on obscure identification and characterization is proposed in this paper. Initially, new obscure location calculation is proposed to recognize the Gaussian, Motion and Defocus based blurred locales in the image. The degradation-restoration model referred with pre-processing followed by binarization and features extraction/classification algorithm applied on obscure images. At this point, support vector machine (SVM) classification algorithm is proposed to cluster the blurred images. Once the obscure class of the locales is affirmed, the structure of the obscure kernels of the blurred images are affirmed. At that point, the obscure kernel estimation techniques are embraced to appraise the obscure kernels. At last, the blurred locales are re-established utilizing nonblind image deblurring calculation and supplant the blurred images with the restored images. The simulation results demonstrate that the proposed calculation performs well

Discovering Ways That Don’t Work on the Road to Success

2013 ◽  
pp. 94-113
Author(s):  
Tawnya Means ◽  
Eric Olson ◽  
Joey Spooner
Keyword(s):  
Project Management ◽  
Active Learning ◽  
Lessons Learned ◽  
Management Process ◽  
The Road ◽  
Management Techniques ◽  
On The Road ◽  
Studio Classroom ◽  
Complex Project ◽  
Edison Project

Educational technology projects undertaken by higher education institutions range in complexity, scope, and impact. The Edison project created a sophisticated studio classroom that supports active learning teaching methods for both local and distant students. The team undertaking this complex project was composed of information technology and instructional design professionals with no real background in formal project management techniques. The team soon discovered that intuition and organic processes for implementing a complex project with increasing scope resulted in risks and challenges that threatened the success and potential impact of the project. The project team learned valuable lessons about the need for a systematic project management process. This case shares the project details, major accomplishments, and lessons learned by the team through the Active Learning Studio classroom (Edison) project.

Based on SVM Classification of Connection Pools Algorithm

2014 ◽  
Vol 945-949 ◽  
pp. 2435-2438
Author(s):  
Juan Zhao ◽  
Hui Yun Xiong
Keyword(s):  
Classification Algorithm ◽  
Experimental Results ◽  
Svm Classifier ◽  
Database Access ◽  
Service Platform ◽  
Buffer Pool ◽  
Svm Classification ◽  
Connection Pool

The connection pool technology has become a deal with large amount of data requested a solution that is widely used now. This paper used the SVM classification algorithm for classified all database requests quickly, so the corresponding database request could be assigned to different connection pool distribution. We applied the connection pool to measurement service platform and tested on the accuracy of the SVM classifier and buffer pool hit ratios of the connection pool module. The experimental results show that the connection pools can improve the efficiency of database access obviously.

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