• Journal of the Korea Society of Computer and Information
• /
• v.24 no.1
• /
• pp.57-65
• /
• 2019

In this paper, we propose a Rights Management Information(RMI) expression systems for individual sites are integrated and the performance evaluation is performed to find out an efficient comparing and updating method of RMI through various image feature point search techniques. In addition, we proposed a weighted scoring model for both public domain sites and posts in order to use the most latest RMI based on reliable data. To solve problem that most public domain sites are exposed to copyright infringement by providing inconsistent RMI(Rights Management Information) expression system and non-up-to-date RMI information. The weighted scoring model proposed in this paper makes it possible to use the latest RMI for duplicated images that have been verified through the performance evaluation experiments of SIFT and CNN techniques and to improve the accuracy when applied to search engines. In addition, there is an advantage in providing users with accurate original public domain images and their RMI from the search engine even when some modified public domain images are searched by users.

• Asia pacific journal of information systems
• /
• v.30 no.4
• /
• pp.847-878
• /
• 2020

In the era of disruptive change, a data-driven approach is vital to Human Resource Management (HRM) of any leading organization, for it is used to gain a competitive advantage. HR analytics (HRA) has emerged as innovative technologies since advanced analytics, i.e., predictive or prescriptive analytics, were widely used in the High Performing Organizations (HPOs). Therefore, many organizations elevate themselves to become HPOs through Data Science on the "people side." This paper proposes a systematic literature review using the Literature Weighted Scoring (LWS) to develop a conceptual framework based on three adoption theories, which are the Technology-Organization-Environment (TOE), Diffusion of Innovation (DOI), and Unified Theory of Acceptance and Use of Technology (UTAUT). The results show that a total of 13 theory-derived factors are determined as influential factors affecting HRA adoption, and the top three factors are "Quantitative Self-Efficacy," "Top Management Support," and "Data Availability." The conceptual framework with hypotheses is proposed to provide a foundation for further studies on organizational HRA adoption.

• Journal of Korean Society for Quality Management
• /
• v.26 no.3
• /
• pp.100-107
• /
• 1998

To evaluate the total quality activities is the most fundamental and critical process as one of the PDCA cycle. The quality award criteria such as Malcolm Baldrige National Quality Award and Deming Award can be a, pp.ied to the guideline for evaluating quality activities. We can identify several important factors for TQM by referring quality award criteria, but they don't suggest how efficiently implement TQM. In this paper, two methodologies are a, pp.ied to evaluate the TQM activities comparatively. One of them is the traditional scoring system (TSS) by analytic hierarchy process (AHP). TSS is the system which evaluates the performance of TQM by the weighted sum of critical success factors. Several quality award system are typical examples of TSS. The other is the efficiency measuring system (EMS) by data envelop analysis (DEA). DEA outperformed other alternative methods to measure the efficiency and it can be a, pp.ied to evaluate the TQM activities. The evaluation system by DEA can be named as EMS. The objective of this paper is to suggest a model called TAE (Total quality management Activities Evaluation), for evaluating TQM activities. In this model TQM organizations are classified into four types by considering TSS and EMS. Those types are high weighted sum and high efficiency type, high weighted sum and low efficiency type, low weighted sum and high efficiency type, and low weighted sum and low efficiency type. Therefore TQM organizations must not only make efforts to get the higher scores in terms of TSS, but also take necessary steps to enhance their efficiencies.

• Knowledge Management Research
• /
• v.6 no.2
• /
• pp.105-118
• /
• 2005

The future will see all industries become technology-driven in the competitive global market place. Firms with deep technological roots and innovation strategies have some advantages. Business valuation of technology is critical to the future of firm's business. In this situation widely used scoring valuation is not enough to evaluate relative business competitiveness associated with technology and to assign its relative ranking category. Therefore, a more useful and comprehensive new valuation approach, which is called business composite index, is needed to complement and to enhance the existing scoring valuation approach. In this research, statistical factor analysis is applied to determine the common factors and to estimate associated weights. And business composite index, which is a kind of weighted scoring method, is derived based on the results of factor analysis. This research shows that business composite index is considered very useful to measure the business relative strength of individual technology and also to assign its relative ranking category instead of absolute ranking based on scoring valuation approach.

• Journal of The Korean Association For Science Education
• /
• v.43 no.3
• /
• pp.237-251
• /
• 2023

This study explores the possibility of automated scoring for scientific graph answers by designing an automated scoring model using convolutional neural networks and applying it to students' kinematics graph answers. The researchers prepared 2,200 answers, which were divided into 2,000 training data and 200 validation data. Additionally, 202 student answers were divided into 100 training data and 102 test data. First, in the process of designing an automated scoring model and validating its performance, the automated scoring model was optimized for graph image classification using the answer dataset prepared by the researchers. Next, the automated scoring model was trained using various types of training datasets, and it was used to score the student test dataset. The performance of the automated scoring model has been improved as the amount of training data increased in amount and diversity. Finally, compared to human scoring, the accuracy was 97.06%, the kappa coefficient was 0.957, and the weighted kappa coefficient was 0.968. On the other hand, in the case of answer types that were not included in the training data, the s coring was almos t identical among human s corers however, the automated scoring model performed inaccurately.

• Journal of Audiology & Otology
• /
• v.23 no.1
• /
• pp.53-58
• /
• 2019

Background and Objectives: The aim of the present study was to assess the feasibility of a PC-based facial asymmetry assessment program (PC-FAAP) and to compare the results of PC-FAAP with subjective regional scoring by raters in acute unilateral peripheral facial nerve paralysis (FNP). Subjects and Methods: Participants were divided into 3 groups with 8 participants per group: group I, normal; group II, mild to moderate FNP; and group III, severe FNP. Using the PC-FAAP, the mouth asymmetry ratio (MAR), eyebrow asymmetry ratio (EAR), and complete eye closure asymmetry ratio (CAR) were calculated by comparing the movement of tracking points on both sides. The FNP grading scale (FGS) integrated each score, and the scores were weighted with a ratio of 5:3:2 (MAR:CAR:EAR). Subjective regional scoring was measured on a 0-100 scale score by three otologists. PC-FAAP and subjective scoring were compared in each group regarding the consistency of the results. Results: The mean scores of the MAR, EAR, CAR, and FGS of each group were significantly different. PC-FAAP showed significant differences between the three groups in terms of MAR, EAC, CAR, and FGS. PC-FAAP showed more consistent results than subjective assessment (p<0.001). The PC-FAAP was significantly more consistent in group I and group III (p<0.001 and p=0.002, respectively). FGS in group III was the only parameter that showed a more consistent result in PC-FAAP than the subjective scoring (p=0.008). Conclusions: An FNP grading system using a PC-based program may provide more consistent results, especially for severe forms.

• Korean Journal of Audiology
• /
• v.23 no.1
• /
• pp.53-58
• /
• 2019

Background and Objectives: The aim of the present study was to assess the feasibility of a PC-based facial asymmetry assessment program (PC-FAAP) and to compare the results of PC-FAAP with subjective regional scoring by raters in acute unilateral peripheral facial nerve paralysis (FNP). Subjects and Methods: Participants were divided into 3 groups with 8 participants per group: group I, normal; group II, mild to moderate FNP; and group III, severe FNP. Using the PC-FAAP, the mouth asymmetry ratio (MAR), eyebrow asymmetry ratio (EAR), and complete eye closure asymmetry ratio (CAR) were calculated by comparing the movement of tracking points on both sides. The FNP grading scale (FGS) integrated each score, and the scores were weighted with a ratio of 5:3:2 (MAR:CAR:EAR). Subjective regional scoring was measured on a 0-100 scale score by three otologists. PC-FAAP and subjective scoring were compared in each group regarding the consistency of the results. Results: The mean scores of the MAR, EAR, CAR, and FGS of each group were significantly different. PC-FAAP showed significant differences between the three groups in terms of MAR, EAC, CAR, and FGS. PC-FAAP showed more consistent results than subjective assessment (p<0.001). The PC-FAAP was significantly more consistent in group I and group III (p<0.001 and p=0.002, respectively). FGS in group III was the only parameter that showed a more consistent result in PC-FAAP than the subjective scoring (p=0.008). Conclusions: An FNP grading system using a PC-based program may provide more consistent results, especially for severe forms.

• Journal of KIISE:Software and Applications
• /
• v.29 no.11
• /
• pp.795-802
• /
• 2002

We propose a fast and powerful Question-answering (QA) system in Korean, which uses a predictive answer indexer based on 2-pass scoring method. The indexing process is as follows. The predictive answer indexer first extracts all answer candidates in a document. Then, using 2-pass scoring method, it gives scores to the adjacent content words that are closely related with each answer candidate. Next, it stores the weighted content words with each candidate into a database. Using this technique, along with a complementary analysis of questions which is based on lexico-syntactic pattern matching method, the proposed QA system saves response time and enhances the precision.

• MALSORI
• /
• no.52
• /
• pp.101-110
• /
• 2004

This paper proposes a new confidence measure for utterance verification with posterior probability approximation. The proposed method approximates probabilistic likelihoods by using Viterbi search characteristics and a clustered phoneme confusion matrix. Our measure consists of the weighted linear combination of acoustic and phonetic confidence scores. The proposed algorithm shows better performance even with the reduced computational complexity than those utilizing conventional confidence measures.

• IE interfaces
• /
• v.1 no.2
• /
• pp.1-12
• /
• 1988

A justification methodology which evaluates the tactical aspects of an FMS project is proposed. For evaluation of quantifiable tactical costs/savings a method of internal rate of return on incremental investment is developed while for the tactical ones which are difficult to quantify a weighted factor scoring model is proposed.