• IE interfaces
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• v.25 no.2
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• pp.187-195
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• 2012

The driver model based on the ACT-R cognitive architecture was developed in order to predict the performance and cognitive workload of a driver operating HVI devices. In the 10 HVI tasks, the predicted performance time and cognitive workload by the ACT-R driver model was well matched and highly correlated with the mean of performance times and subjective workload ratings from 15 participants, respectively. It is strongly proposed that the ACT-R driver model in this study can be applied to evaluate the usability of a new HVI design with less cost in the early stage of system development.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.25 no.4
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• pp.442-450
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• 2014

This paper is a study of the propagation characteristic of matching liquids in the skin-covered breast model. In order to evaluate the matching liquids, we investigated six kinds of matching liquids applied to proposed 1-D breast model from frequency range of 3~6 GHz. A uniform plane wave is projected / transmitted inside the multi-layered breast model. Then the propagation characteristics inside the model and the transmission loss of each matching liquids were analyzed. The studying method presented in the paper can be used in the breast cancer detection system, the field of cancer detection using human tissue and the field of other medical devices. This paper was applied to the breast cancer detection system. Consequently, these studies could be used to determine the suitable type of matching liquids for breast cancer detection system and to apply useful for performance analysis.

• Journal of the Korean Society of Food Culture
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• v.22 no.2
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• pp.191-200
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• 2007

This study was designed to investigate the correlation between perceived TQM performance and organizational culture of dietitians. The objective of the study is to help the management of foodservice by providing a direction which will elevate perceived TQM performance of dietitians and presenting plans which will ensure effective dietitians. Questionnaires handed out to 308 dietitians worked in institutional foodservice operation including elementary, middle and high schools, hospitals, business and industries. In terms of TQM importance and performance, the more important dietitians perceived, the higher their performance level rose. Data form the IPA, external and internal customer satisfaction, executive ability, communication system and technology, information technology and application ability, food process, strategy, and leadership were required further improvement by dietitians. Of present organizational culture model, human relations model and open systems model were more likely to be adopted by dietitians in middle and high schools. According to the type of foodservice management, the open systems model was more preferred by dietitians from self-operated operations rather than respondents from contracted operations. Canonical correlation analysis between TQM performance and organizational culture showed canonical correlation to be higher (canonical correlations coefficient: .66). In conclusion, TQM performance-organizational culture showed higher canonical correlation. In the organizational culture, foodservice operation is capable of improving the aims for the rational goal model and the open systems model. The results showed that TQM performance and organizational culture had significant relationship, especially positive organizational culture emphasizing on internal process and rational goal model would have influence on TQM performance of dietitians. Foodservice operation, however, should recognize importance of open and development culture to improve dietitians' TQM performance. To apply open system foodservice organization should encourage dietitian and foodservice employees to challenge and compete for the works, Moreover, organizational effort such as information exchange program and support system should be established.

• Journal of the Korean Society for Precision Engineering
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• v.30 no.6
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• pp.650-657
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• 2013

This study uses a muscle activation sensor and elbow joint model to develop an estimation algorithm for human elbow joint torque for use in a human-robot interface. A modular-type MVS (Muscle Volume Sensor) and calibration algorithm are developed to measure the muscle activation signal, which is represented through the normalization of the calibrated signal of the MVS. A Hill-type model is applied to the muscle activation signal and the kinematic model of the muscle can be used to estimate the joint torques. Experiments were performed to evaluate the performance of the proposed algorithm by isotonic contraction motion using the KIN-COM$^{(R)}$ equipment at 5, 10, and 15Nm. The algorithm and its feasibility for use as a human-robot interface are verified by comparing the joint load condition and the torque estimated by the algorithm.

• Journal of Korea Society of Industrial Information Systems
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• v.16 no.4
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• pp.9-18
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• 2011

In this paper, we propose a method which recognizes human activity using model-based gaze direction estimation in an indoor environment. The method consists of two steps. First, we detect a head region and estimate its gaze direction as prior information in the human activity recognition. We use color and shape information for the detection of head region and use Bayesian Network model representing relationships between a head and a face for the estimation of gaze direction. Second, we recognize event and scenario describing the human activity. We use change of human state for the event recognition and use a rule-based method with combination of events and some constraints. We define 4 types of scenarios related to the gaze direction. We show performance of the gaze direction estimation and human activity recognition with results of experiments.

• Journal of Korea Ship Safrty Technology Authority
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• s.27
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• pp.25-36
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• 2009

Despite the development of the various navigational equipment, such as GPS, ARPA, ECDIS, AIS, VDR, and hull monitoring system, marine accidents are still a leading concern in shipping industry. For all accidents over the reporting period, approximately 60 to 80% of the accidents was involved in human error. It means that in each case, some events which were associated with human error initiated an accident, and those failures of human performance led to the failure to avoid an accident or mitigate it's consequences. However, the improvement and the effort on the maritime human error are still limited in an elementary step. The objective of this paper is to propose a modified Human Factors Analysis and Classification System (HFACS) model in order to analyse the collision accidents of tug-barge ship.

• Fashion & Textile Research Journal
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• v.14 no.1
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• pp.37-47
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• 2012

The purpose of this study was to explore an intrinsic concept of 'company innovativeness' based on qualitative data obtained from 54 practitioners with at least 5 year-experience in the industry. Data were analyzed based on the grounded theory and Nvivo 2.0 program. Based on results, seven theme were generated. Seven intrinsic theme include 5 intrinsic concepts such as learning orientation, excellence of human resource, treatment for employees, market orientation and work efficiency, and 2 performance concepts such as business performance and innovation performance. These diverse concepts were considered as an important guideline in judging whether a company is innovative or not. In addition, diverse programs were provided by companies for a purpose of enhancing company innovativeness. Based on results, a research model was suggested to be elaborated in future studies. Implications and suggestions were generated based on results.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.9
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• pp.2334-2347
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• 2023

Metaverse services generate text data, data of ubiquitous computing, in real-time to analyze user emotions. Analysis of user emotions is an important task in metaverse services. This study aims to classify user sentiments using deep learning and pre-trained language models based on the transformer structure. Previous studies collected data from a single platform, whereas the current study incorporated the review data as "Metaverse" keyword from the YouTube and Google Play Store platforms for general utilization. As a result, the Bidirectional Encoder Representations from Transformers (BERT) and Robustly optimized BERT approach (RoBERTa) models using the soft voting mechanism achieved a highest accuracy of 88.57%. In addition, the area under the curve (AUC) score of the ensemble model comprising RoBERTa, BERT, and A Lite BERT (ALBERT) was 0.9458. The results demonstrate that the ensemble combined with the RoBERTa model exhibits good performance. Therefore, the RoBERTa model can be applied on platforms that provide metaverse services. The findings contribute to the advancement of natural language processing techniques in metaverse services, which are increasingly important in digital platforms and virtual environments. Overall, this study provides empirical evidence that sentiment analysis using deep learning and pre-trained language models is a promising approach to improving user experiences in metaverse services.

• Industrial Engineering and Management Systems
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• v.11 no.1
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• pp.54-69
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• 2012

Chan and Qi (SCM 8/3 (2003) 209) developed an innovative measurement method that aggregates performance measures in a supply chain into an overall performance index. The method is useful and makes a significant contribution to supply chain management. Nevertheless, it can be cumbersome in computation due to its highly complex algorithmic fuzzy model. In aggregating the performance information, weights used by Chan and Qi-which aim to address the imprecision of human judgments-are incompatible with weights in additive models. Furthermore, the default assumption of linearity of its scoring procedure could lead to an inaccurate assessment of the overall performance. This paper addresses these limitations by developing an alternative measurement that takes care of the above. This research integrates three different approaches to multiple criteria decision analysis (MCDA)-the multiattribute value theory (MAVT), the swing weighting method and the eigenvector procedure-to develop a comprehensive assessment of supply chain performance. One case study is presented to demonstrate the measurement of the proposed method. The performance model used in the case study relies on the Supply Chain Operations Reference (SCOR) model level 1. With this measurement method, supply chain managers can easily benchmark the performance of the whole system, and then analyze the effectiveness and efficiency of the supply chain.

• The Journal of Korean Institute for Practical Engineering Education
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• v.2 no.1
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• pp.106-114
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• 2010

HRDI(Human Resources Development Institute) has not performed the efficient costing model because of it's variety types of institutes, courses and vocational education and training techniques. This study proposed the integrated costing model using job costing, activity based costing and standard costing methods to meet needs of HRDI. And the model will be used in two-phased approach including adoptable model and ideal model. The integrated model includes costing techniques, cost elements, indirect cost allocation bases and cost analysis methods using a contribution margin model to calculate and analyse cost information in HRDI. The proposed integrated costing model of HRDI has some limitation of no relationship with the performance management. But this model will prepare valuable information by using detailed data and costing techniques. And then this model will be developed as a advanced costing model using standard costing to relate with the performance model.