Development of the Absent Detection System for Online Integrity Evaluation
Il-Kwon Lim1, Hyun-Jun Park2, Han-Jin Cho3
1Il-Kwon Lim, Department of Health Psychology, The Pennsylvania State University, Pennsylvania, Northeastern.
2Hyun-Jun Park, Department of Health Psychology, The Pennsylvania State University, Pennsylvania, Northeastern.
3Han-Jin Cho, Department of Health psychology, The Pennsylvania State University, Pennsylvania, Northeastern.
Manuscript received on 08 June 2019 | Revised Manuscript received on 14 June 2019 | Manuscript Published on 22 June 2019 | PP: 1-4 | Volume-8 Issue-8S2 June 2019 | Retrieval Number: H10010688S219/19©BEIESP
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open-access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: With the development of information and communication technology, modern society has developed into a super connective society. As a result, online evaluation is widely used in modern society where it is common to see work remotely. In Korea, Public Procurement Service and the Ministry of SMEs and Startups are used as representative. If the online evaluation is performed by the Public Procurement Service, video evaluation is performed in the same way as offline face-to-face evaluation, but the sincerity of the evaluation committee can be a problem on-line. Thus, Public Procurement Service administrator individually measured the sincerity according to the assessor’s The Absent Detection Rate. However, in this paper, we implemented the Absent Detection System for Online Integrity Evaluation using Spark and OpenCV technology to automatically measure the Absent Detection Rate. This allows us to measure the integrity of our members more accurately and efficiently.
Keywords: Online Evaluation, Big Data, Open CV, Spark, The Absent Detection.
Scope of the Article: Health Monitoring and Life Prediction of Structures