• Journal of Korea Multimedia Society
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• v.22 no.9
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• pp.1000-1010
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• 2019

Image semantic segmentation and dehazing are key tasks in the computer vision. In recent years, researches in both tasks have achieved substantial improvements in performance with the development of Convolutional Neural Network (CNN). However, most of the previous works for semantic segmentation assume the images are captured in clear weather and show degraded performance under hazy images with low contrast and faded color. Meanwhile, dehazing aims to recover clear image given observed hazy image, which is an ill-posed problem and can be alleviated with additional information about the image. In this work, we propose a deep multi-task network for simultaneous semantic segmentation and dehazing. The proposed network takes single haze image as input and predicts dense semantic segmentation map and clear image. The visual information getting refined during the dehazing process can help the recognition task of semantic segmentation. On the other hand, semantic features obtained during the semantic segmentation process can provide cues for color priors for objects, which can help dehazing process. Experimental results demonstrate the effectiveness of the proposed multi-task approach, showing improved performance compared to the separate networks.

• Journal of Gifted/Talented Education
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• v.25 no.4
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• pp.469-491
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• 2015

The present study investigated the inhibition mechanisms of gifted children, which is one of the main executive functions in human cognitive system. The inhibition process was subdivided into cognitive and emotion aspects in order to examine the interplay between these two aspects with respect to inhibition processing. In Experiment 1, word-color Stroop task was used to study the cognitive inhibition process of 100 gifted children(Gender: 62 males, 38 females; Academic grade: 46 Elementary school students, 54 Secondary school students). In addition, emotional Stroop task was utilized in Experiment 2 to examine the effect of emotional component during cognitive inhibition process. Results revealed a significant cognitive cost (i.e., word-color Stroop effect) when participants had to withhold automatic response during cognitive inhibition task in Experiment 1. Such cognitive cost was reduced as the chronological age of the participants increased, with no difference in gender. The results in Experiment 2 showed no significant emotional inhibition cost (i.e., emotional Stroop effect) during cognitive inhibition task, and there was no effect of gender nor age. This suggests that the emotional component conveyed in words did not lead to cognitive bias effects. This study proposes that the cognitive and emotional inhibition processes are seemingly independent mechanisms that engage in complex interactions during inhibition processing of behavioral response.

• Journal of Digital Convergence
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• v.4 no.1
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• pp.83-92
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• 2006

The purpose of this study is to confirm whether the task and system development process makes a significant influence on the system performance. The task is defined as a interdependency and system development process is defined as analysis, user participation and executive support. Field research was employed to empirically investigate the relationship among the variables. The finding of the study can be summarized as follows. The strict analysis under the task of high interdependency has a significant effect on the system performance. And high executive support is needed for the system performance under any level of interdependency.

• Proceedings of the KSR Conference
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• 2006.11b
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• pp.1082-1087
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• 2006

Human factors still plays a significant role in railway accidents. The accidents often resulted from multiple causes of hardware failures and human errors. So to ensure the safety of railway operations, human error should be effectively prevented and managed. Among several factors influencing human performance, task load (or task complexity) is well known as a major contributor to human error. In order to reduce the potential of human error, a systematic analysis should be undertaken to evaluate task load and to reduce it by modifying task process and/or education&training. In this paper, we proposed a systematic framework for railway industry to perform task analysis and to evaluate task load, and applied it to KTX operational tasks. According to the application study, we identified 14 generic task types of KTX operation. And also this paper shows the quantitative task load of those generic tasks which were analyzed by NASA-TLX method.

• The Journal of Korean Society for Radiation Therapy
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• v.17 no.1
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• pp.41-43
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• 2005

Purpose : Wish to present degree management process that is efficient confirm radiation treatment exclusive use CT simulator's Q.A item that become Q.A and Differentiation of diagnosis area that present Report of the AAPM Task Group No.66 using Q.A tool that produce itself and secure safe and correct CT-simulation process and equip convenience. Method and material : Manufacture CT simulator's Q.A tool on source and confirm virtue between isocenter of wall laser system, patient table, CT scanner's imaging plane that present in Report of the AAPM Task Group No.66 by daily publication unit. Result : Confirmed measured value from Report of the AAPM Task Group No.66 to confirmation of presenting degree management item in wall laser's ${\pm}2mm$, table's ${\pm}2mm$, imaging plane's ${\pm}2mm$ tolerance extent. Conclusion : There is unconfirmed item from CT-simulation process for therapy to CT Q.A protocol of existent diagnosis area, premising suitable degree management of radiation treatment exclusive use CT-simulator equipment confirming presenting Q.A item in Report of the AAPM Task Group No.66 safe and correct CT-simulation process guarantee can

• The Journal of Information Systems
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• v.29 no.4
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• pp.77-99
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• 2020

Purpose The purpose of this study is to investigate the effect of two-way communication and knowledge sharing on the task performance of employees in the interdependent task structure in organizations. Based on the theories of social interdependence and organizational commitment, this study hypothesized the effects of task interdependency and emotional commitment on two-way communication and knowledge sharing, followed by the effects of these variables on the task performance of employees. Design/methodology/approach Survey results show that task interdependence and emotional commitment have positive effects on the degree of two-way communication and knowledge sharing. Two-way communication also has a positive impact on knowledge sharing, and knowledge sharing also improved the task performance of members. However, the relationship between two-way communication and task performance shows no significant impact. Findings Theoretically, this study is meaningful in that the process of task interdependence in relation to emotional commitment leading to task performance is theorized. In practice, this research suggests it is important to improve employees' two-way communication and knowledge sharing in order to lead to increase task performance in the interdependent task environment.

• ETRI Journal
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• v.42 no.5
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• pp.748-760
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• 2020

MapReduce is a framework that can process huge datasets in parallel and distributed computing environments. However, a single machine failure during the runtime of MapReduce tasks can increase completion time by 50%. MapReduce handles task failures by restarting the failed task and re-computing all input data from scratch, regardless of how much data had already been processed. To solve this issue, we need the computed key-value pairs to persist in a storage system to avoid re-computing them during the restarting process. In this paper, the task failure resilience (TFR) technique is proposed, which allows the execution of a failed task to continue from the point it was interrupted without having to redo all the work. Amazon ElastiCache for Redis is used as a non-volatile cache for the key-value pairs. We measured the performance of TFR by running different Hadoop benchmarking suites. TFR was implemented using the Hadoop software framework, and the experimental results showed significant performance improvements when compared with the performance of the default Hadoop implementation.

• The Journal of Korea Robotics Society
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• v.16 no.1
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• pp.56-63
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• 2021

As the use of robots in service area increases, research has been conducted to replace human tasks in daily life with robots. Among them, this study focuses on the tidy-up task on a desk using a robot arm. The order in which tidy-up motions are carried out has a great impact on the success rate of the task. Therefore, in this study, a neural network-based method for determining the priority of the tidy-up motions from the input image is proposed. Reinforcement learning, which shows good performance in the sequential decision-making process, is used to train such a task planner. The training process is conducted in a virtual tidy-up environment that is configured the same as the actual tidy-up environment. To transfer the learning results in the virtual environment to the actual environment, the input image is preprocessed into a segmented image. In addition, the use of a neural network that excludes unnecessary tidy-up motions from the priority during the tidy-up operation increases the success rate of the task planner. Experiments were conducted in the real world to verify the proposed task planning method.

• Research in Mathematical Education
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• v.25 no.4
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• pp.285-309
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• 2022

A large body of previous studies investigated mathematical tasks by analyzing the design process prior to lessons or textbooks. While researchers have revealed the significant roles of mathematical tasks within written curricular, there has been a call for studies about how mathematical tasks are implemented or what is experienced and learned by students as enacted curriculum. This article proposes a mathematical task analytic framework based on a holistic definition of tasks encompassing both written tasks and the process of task enactment. We synthesized the features of the mathematical tasks and developed a task analytic framework with multiple dimensions: breadth, depth, bridging, openness, and interaction. We also applied the scoring rubric to analyze three multiplication tasks to illustrate the framework by its five dimensions. We illustrate how a series of tasks are analyzed through the framework when students are engaged in multiplicative thinking. The framework can provide important information about the qualities of planned tasks for mathematics instruction (proactive) and the qualities of implemented tasks during instruction (reactive). This framework will be beneficial for curriculum designers to design rich tasks with more careful consideration of how each feature of the tasks would be attained and for teachers to transform mathematical tasks with the provision of meaningful learning activities into implementation.

• Journal of the Korea Convergence Society
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• v.9 no.6
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• pp.69-75
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• 2018

Efficiency of Process in manufacturing industry is a critical factor to connect directly to competitiveness of product. In particular, due to FTAs with various worlds around the world, the domestic and overseas manufacturing industries are facing intense competitions, and it requires elaborate task management system for shortening production time. This study aims at seeking how to raise efficiency of manufacturing process, using motion analysis solution. When improving the process of manufacturing after verifying optimization using motion analysis solution, it can save costs for additional process, modification, or supplement. It can also deduce practical effect to improve productivity of companies. It is expected that the study will contribute to improve wastes in the work field and task assignment efficiency, to shorten time replacing equipment, to measure standard time, and to standardize task system.