• Journal of the Ergonomics Society of Korea
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• v.32 no.1
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• pp.59-68
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• 2013

Objective: The purpose of this paper is to introduce a task complexity model combining task design aspects and complexity dimensions and to explain an approach to identifying and organizing task complexity factors based on the model. Background: Task complexity is a critical concept in describing and predicting human performance in complex systems such as nuclear power plants(NPPs). In order to understand the nature of task complexity, task complexity factors need to be identified and organized in a systematic manner. Although several methods have been suggested for identifying and organizing task complexity factors, it is rare to find an analytical approach based on a theoretically sound model. Method: This study regarded a task as a system to be designed. Three levels of design ion, which are functional, behavioral, and structural level of a task, characterize the design aspects of a task. The behavioral aspect is further classified into five cognitive processing activity types(information collection, information analysis, decision and action selection, action implementation, and action feedback). The complexity dimensions describe a task complexity from different perspectives that are size, variety, and order/organization. Combining the design aspects and complexity dimensions of a task, we developed a model from which meaningful task complexity factors can be identified and organized in an analytic way. Results: A model consisting of two facets, each of which is respectively concerned with design aspects and complexity dimensions, were proposed. Additionally, twenty-one task complexity factors were identified and organized based on the model. Conclusion: The model and approach introduced in this paper can be effectively used for examining human performance and human-system interface design issues in NPPs. Application: The model and approach introduced in this paper could be used for several human factors problems, including task allocation and design of information aiding, in NPPs and extended to other types of complex systems such as air traffic control systems as well.

• Nuclear Engineering and Technology
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• v.54 no.11
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• pp.4170-4180
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• 2022

The task complexity (TACOM) measure was previously developed to quantify the complexity of proceduralized tasks conducted by nuclear power plant operators. Following the development of the TACOM measure, its appropriateness has been validated by investigating the relationship between TACOM scores and three kinds of human performance data, namely response times, human error probabilities, and subjective workload scores. However, the information reflected in quantified TACOM scores is still insufficient to determine the levels of complexity of proceduralized tasks for human reliability analysis (HRA) applications. In this regard, the objective of this study is to suggest criteria for determining the levels of task complexity based on logistic regression between human error occurrences in digitalized main control rooms and TACOM scores. Analysis results confirmed that the likelihood of human error occurrence according to the TACOM score is secured. This result strongly implies that the TACOM measure can be used to identify the levels of task complexity, which could be applicable to various research domains including HRA.

• Journal of the Korea Convergence Society
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• v.11 no.5
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• pp.165-173
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• 2020

The emergence of unmanned agricultural machinery has brought new research content to the development of precision agriculture. In order to speed up the research on key technologies of unmanned agricultural machinery, classification of intelligence level of unmanned agricultural machinery has become a primary task. In this study, the researchers take the complex interactive system consisting of unmanned grain harvester, task and driving environment as the research object, and carry out a research on the grading and classification of intelligent level of unmanned grain harvester. The researchers of this study also establish an evaluation model of unmanned grain harvester vehicle, which consists of human intervention degree, environmental complexity, and task complexity. Besides, the grading and classification of intelligence level of the unmanned grain harvester is carried out according to the human intervention degree, environmental complexity and the task complexity of the unmanned grain harvester. It provides a direction for the future development of unmanned agricultural machinery.

• English Language & Literature Teaching
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• v.17 no.4
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• pp.207-227
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• 2011

This paper investigates how two different modes of feedback (selective vs. comprehensive) affect selected students' writing development in terms of three different types of measurement (accuracy, fluency, and complexity). 139 university students participated in the study, and 278 writing samples were analyzed. The results of the study indicate that participants who received selective feedback wrote more accurately and fluently than their counterparts. However, in terms of complexity, both selective and comprehensive groups showed no sign of improvement in semester-based investigations. The results of this study support Skehan's (2009) theory of trade-off effects, suggesting that 'natural' tension exists between accuracy and complexity when resources are limited. Moreover, this finding contrasts with the theory of Cognition Hypothesis, which proposes that task complexity will be associated with increases in complexity and accuracy. In the study, selected participants (N=21) strongly nominated their error sources as unfamiliarity toward using key words, usage, transition, and sentence types. This study not only contributes to the accumulation of our current knowledge in the related area of theory, but offers educational implications for those who are dealing with intermediate-level students when deciding what particular teaching content should constitute a priority within a limited instructional period.

• Educational Technology International
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• v.25 no.1
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• pp.27-65
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• 2024

The purpose of this study was to identify differences in learning patterns according to content complexity in video-based learning environments and to derive variables that have an important effect on learning achievement within particular learning contexts. To achieve our aims, we observed and collected data on learners' cognitive processes through perceived affordances, using behavioral logs and eye movements as specific indicators. These two types of reaction data were collected from 67 male and female university students who watched two learning videos classified according to their task complexity through the video learning player. The results showed that when the content complexity level was low, learners tended to navigate using other learners' digital logs, but when it was high, students tended to control the learning process and directly generate their own logs. In addition, using derived prediction models according to the degree of content complexity level, we identified the important variables influencing learning achievement in the low content complexity group as those related to video playback and annotation. In comparison, in the high content complexity group, the important variables were related to active navigation of the learning video. This study tried not only to apply the novel variables in the field of educational technology, but also attempt to provide qualitative observations on the learning process based on a quantitative approach.

• Journal of the Institute of Electronics and Information Engineers
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• v.50 no.10
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• pp.199-203
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• 2013

In this paper, a fast algorithm of discrete cosine transform-based interpolation filter (DCT-IF) for HEVC (high efficiency video coding) encoder is proposed. DCT-IF filter accounts for around 30% of encoder complexity, according to the computational complexity analysis with the HEVC reference software. In this work, the proposed DCT-IF is optimized by applying frame-level interpolation, SIMD optimization, and task-level parallelization via OpenMP on a developed C-based HEVC encoder. Performance analysis is conducted by measuring speed-up factor of the proposed optimization technique on the developed encoder. The results show that speed-up factors by frame-level interpolation, SIMD, and OpenMP are approximately 38-46, 3.6-4.4, and 3.0-3.7, respectively. In the end, we achieved the speed-up factor of 498.4 with the proposed fast algorithm.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.20 no.42
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• pp.39-47
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• 1997

There are four parameters (i.e. overall density, local density, grouping, layout complexity) to consider in designing screen of a visual display terminal. Among these, only the optimum level of overall density is known to be about 25~30% by some studies. Therefore, the present experiment is conducted to define the optimum levels of the other parameters to achieve the user's best performance in visual search task. The results are as follows; (1) The function related to the levels of local density and user's search times is shown to be U -shaped. When the level of local density is about 40%, the search time is shorter than those of any other levels. (2) In the experiment of grouping, user's performance is best when the number of group is 5, and the size of group does not exceed visual angle $5^{\circ}$ (0,088rad). (3) The user performance is improved as the layout becomes less complex.

• The Mathematical Education
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• v.62 no.3
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• pp.363-380
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• 2023

This study analyzed the difficulties and mathematical modeling knowledge improvement that an elementary school teacher experienced in modifying a mathematics textbook task to a mathematical modeling task. To this end, an elementary school teacher with 10 years of experience participated in teacher-researcher community's repeated discussions and modified the average task in the data and pattern domain of the 5th grade. The results are as followings. First, in the process of task modification, the teacher had difficulties in reflecting reality, setting the appropriate cognitive level of mathematical modeling tasks, and presenting detailed tasks according to the mathematical modeling process. Second, through repeated task modifications, the teacher was able to develop realistic tasks considering the mathematical content knowledge and students' cognitive level, set the cognitive level of the task by adjusting the complexity and openness of the task, and present detailed tasks through thought experiments on students' task-solving process, which shows that teachers' mathematical modeling knowledge, including the concept of mathematical modeling and the characteristics of the mathematical modeling task, has improved. The findings of this study suggest that, in terms of the mathematical modeling teacher education, it is necessary to provide teachers with opportunities to improve their mathematical modeling task development competency through textbook task modification rather than direct provision of mathematical modeling tasks, experience mathematical modeling theory and practice together, and participate in teacher-researcher communities.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.4
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• pp.1693-1713
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• 2018

An important technique used by database administrators (DBAs) is to improve performance in decision-support workloads associated with a Star schema is multi-level partitioning. Queries will then benefit from performance improvements via partition elimination, due to constraints on queries expressed on the dimension tables. As the task of multi-level partitioning can be overwhelming for a DBA we are proposing a wizard that facilitates the task by calculating a partitioning scheme for a particular workload. The system resides completely on a client and interacts with the costing estimation subsystem of the query optimizer via an API over the network, thereby eliminating any need to make changes to the optimizer. In addition, since only cost estimates are needed the wizard overhead is very low. By using a greedy algorithm for search space enumeration over the query predicates in the workload the wizard is efficient with worst-case polynomial complexity. The technology proposed can be applied to any clustering or partitioning scheme in any database management system that provides an interface to the query optimizer. Applied to the Teradata database the technology provides recommendations that outperform a human expert's solution as measured by the total execution time of the workload. We also demonstrate the scalability of our approach when the fact table (and workload) size increases.

• Journal of the Korean Society of Clothing and Textiles
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• v.25 no.4
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• pp.754-763
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• 2001

The purpose of this study was to examine: 1) the differences in the automation level by company characteristics(i.e., product category, product type, firm size); 2) the effects of company context(i.e., environmental uncertainty, task uncertainty) on the automation level; and 3) the effect of the automation level on manufacturing performance(i.e., quality, flexibility, time, cost). Data were collected from a mail survey. Four hundred eighty two questionaries were mailed to apparel manufacturers nationwide, and 60 responses were analyzed. The results revealed that: 1) mens and womens wear manufacturers and large manufacturers(i.e., the number of employees, sales volume) showed higher automation level; 2) environmental complexity positively affected the automation level; and 3) the automation level had a positive effect only on quality performance.