• KSII Transactions on Internet and Information Systems (TIIS)
• /
• 제15권9호
• /
• pp.3204-3220
• /
• 2021

We perform the task of video object segmentation by incorporating a conditional random field (CRF) and convolutional neural networks (CNNs). Most methods employ a CRF to refine a coarse output from fully convolutional networks. Others treat the inference process of the CRF as a recurrent neural network and then combine CNNs and the CRF into an end-to-end model for video object segmentation. In contrast to these methods, we propose a novel higher-order CRF model to solve the problem of video object segmentation. Specifically, we use CNNs to establish a higher-order dependence among pixels, and this dependence can provide critical global information for a segmentation model to enhance the global consistency of segmentation. In general, the optimization of the higher-order energy is extremely difficult. To make the problem tractable, we decompose the higher-order energy into two parts by utilizing auxiliary variables and then solve it by using an iterative process. We conduct quantitative and qualitative analyses on multiple datasets, and the proposed method achieves competitive results.

• Nuclear Engineering and Technology
• /
• 제53권11호
• /
• pp.3505-3516
• /
• 2021

During nuclear facility decommissioning, workers are continuously exposed to high-level radiation. Hence, adequate path planning is critical to protect workers from unnecessary radiation exposure. This work discusses recent development in radioactive path planning and the algorithms recommended for the task. Specifically, we review the conventional methods for nuclear decommissioning path planning, analyze the techniques utilized in developing algorithms, and enumerate the decision factors that should be considered to optimize path planning algorithms. As a major contribution, we present the quantitative performance comparison of different algorithms utilized in solving path planning problems in nuclear decommissioning and highlight their merits and drawbacks. Also, we discuss techniques and critical consideration necessary for efficient application of robots and robotic path planning algorithms in nuclear facility decommissioning. Moreover, we analyze the influence of obstacles and the environmental/radioactive source dynamics on algorithms' efficiency. Finally, we recommend future research focus and highlight critical improvements required for the existing approaches towards a safer and cost-effective nuclear-decommissioning project.

• 아태비즈니스연구
• /
• 제11권3호
• /
• pp.261-271
• /
• 2020

Purpose - This study was to establish a unified tourism management class for university students based on Gangwon-do. Community based learning(CBL) was applied to provide a tangible and intangible resource of tourism resources the theoretical approaches and the actual experiences of the community. Design/methodology/approach - In order to design a unified tourism management module, this study applied qualitative research and quantitative research methods to collect information on the direction of the module. the study conducted in-depth interviews and then an online survey. Findings - According to the results of the study, the main parts should include necessity of unification, inter-Korean tourism, inter-Korean cooperation, inter-Korean economy, and international relations. Research implications or Originality - The overall composition of the unification tourism management class should be designed as the unification tourism management theory to acquire the subject knowledge, the field trip to the border area for experiential learning, and the assignment of the field study task to understand the community.

• 식품보건융합연구
• /
• 제6권6호
• /
• pp.17-23
• /
• 2020

The main task of agro-industrial production is to provide the population with food products for the production of which energy is expended in the form of electricity, technical means, fuels and lubricants, mineral fertilizers, etc. Accordingly, we have developed a concept and general methodological principles for the analysis of ecological and biotechnical systems in animal husbandry, it makes it possible to simulate the influence of various factors on the energy and ecological efficiency of systems, to compare and search for energy-saving modes and technologies. General methodological principles have been developed for the analysis of energy efficiency and environmental safety of agricultural ecological and biotechnical systems, which are based on the definition of the bioenergy efficiency coefficient, the quantitative expression of which is the ratio of energy accumulated in products to the total energy consumption for its production. This makes it possible to model with sufficient accuracy the influence of various factors on the energy and environmental efficiency of the system, to compare and search for energy-saving modes and technologies in order to find and select the most energy efficient ones to increase the energy efficiency of the complex.

• 유통과학연구
• /
• 제19권7호
• /
• pp.19-27
• /
• 2021

Purpose: Former research has argued that organizations in distribution channels face several issues to make a better team-based system. The purpose of the present research is to measure between employee's job performance and three major issues which disturb a solid team system. Research design, data and methodology: Scant past studies are available to guide for team practitioners which elements should be eliminated to improve team performance. To achieve this goal, the present authors obtained 267 US workers in distribution channels and conducted ANOVA test to measure the relationship between three team issues (Free-rider, Trust, and Communication) and job performance. Results: Our statistical findings clearly suggests that there was a statistically recognizable difference at the significance level of probability between the mean value of employees' job performance and three major issues, showing the high degree of job performance can be occurred by eliminating three major team issues. Conclusions: Therefore, the present research concludes that it is necessary that team-based management in the supply chain should focus on removing free-rider issues and also adopt open communication lines to overcome team-building challenges due to communication. Above all else, the ability to increase trust can be enhanced via task delegation and more team members' engagement.

• 국제학술발표논문집
• /
• The 3th International Conference on Construction Engineering and Project Management
• /
• pp.230-236
• /
• 2009

Double-front construction machinery, which was designed for complicated tasks, requires intelligent systems that can provide the quantitative work analysis needed to determine effective work procedures and that can provide operational and cognitive support for operators. Construction work environments are extremely complicated, however, and this makes state identification difficult. We therefore defined primitive static states (PSS) that are determined using on-off data for the lever inputs and manipulator loads for each part of the grapple and front and that are completely independent of the various environmental conditions and operator skill levels. To confirm the usefulness of PSS, we performed experiments with a demolition task by using our virtual reality simulator. We confirmed that PSS could robustly and accurately identify the work states and that untrained skills could be easily inferred from the PSS-based work analysis. We also confirmed in skill-training experiments that advice information using PSS-based skill analysis greatly improved work performance. We thus confirmed that PSS can adequately identify work states and are useful for work analysis and skill improvement.

• International Journal of Korean Welding Society
• /
• 제1권1호
• /
• pp.17-22
• /
• 2001

Because the quantitative relationships between welding parameters and welding result are not yet blown, optimal values of welding parameters for $CO_2$ robotic arc welding is a difficult task. Using the various artificial data processing methods may solve this difficulty. This research aims to develop an expert system for $CO_2$ robotic arc welding to recommend the optimal values of welding parameters. This system has three main functions. First is the recommendation of reasonable values of welding parameters. For such work, the relationships in between the welding parameters are investigated by the use of regression analysis and fuzzy system. The second is the estimation of bead shape by a neural network system. In this study the welding current voltage, speed, weaving width, and root gap are considered as the main parameters influencing a bead shape. The neural network system uses the 3-layer back-propagation model and a generalized delta rule as teaming algorithm. The last is the optimization of the parameters for the correction of undesirable weld bead. The causalities of undesirable weld bead are represented in the form of rules. The inference engine derives conclusions from these rules. The conclusions give the corrected values of the welding parameters. This expert system was developed as a PC-based system of which can be used for the automatic or semi-automatic $CO_2$ fillet welding with 1.2, 1.4, and 1.6mm diameter the solid wires or flux-cored wires.

• 한국응급구조학회지
• /
• 제27권3호
• /
• pp.33-46
• /
• 2023

Purpose: This study aims to evaluate the risk of work-related musculoskeletal disorders (WMSDs) in 119 EMT during patient-carrying tasks using a long backboard (LBB) and a variable stretcher. Methods: Manikins were used as patients, and 45 new 119 EMT from K Fire Academy were filmed performing patient-carrying tasks on stairs. The tasks were analyzed using Ovako working posture analysis system (OWAS) and Rapid entire body assessment (REBA). Results: In using LBB, the OWAS score was Mode 3(Mean 2.37, Maximum 3), requiring as soon as possible corrective action, the REBA score was Mode 11(Mean 9.16, Maximum 11), requiring immediate improvement. In using variable stretcher, the OWAS score was Mode 1(Mean 2.33, Maximum 3), non-necessity for corrective action, the REBA score was Mode 9(Mean 8.0, Maximum 11), requiring as soon as possible. Conclusion: In conclusion, improvement was needed in one task (carrying a patient using a LBB) in the OWAS and in two tasks (carrying a patient using a LBB, carrying a patient using a variable stretcher) in the REBA. Thereby, required attention and management of WMSDs during training. In addition, it is essential to carry out objective and quantitative assessments through ergonomic analysis by occupational health professionals when designing future training programs to prevent WMSDs.

• 로봇학회논문지
• /
• 제19권1호
• /
• pp.117-129
• /
• 2024

This paper introduces collective navigation through a narrow gap using a curriculum-based deep reinforcement learning algorithm for a swarm of unmanned aerial vehicles (UAVs). Collective navigation in complex environments is essential for various applications such as search and rescue, environment monitoring and military tasks operations. Conventional methods, which are easily interpretable from an engineering perspective, divide the navigation tasks into mapping, planning, and control; however, they struggle with increased latency and unmodeled environmental factors. Recently, learning-based methods have addressed these problems by employing the end-to-end framework with neural networks. Nonetheless, most existing learning-based approaches face challenges in complex scenarios particularly for navigating through a narrow gap or when a leader or informed UAV is unavailable. Our approach uses the information of a certain number of nearest neighboring UAVs and incorporates a task-specific curriculum to reduce learning time and train a robust model. The effectiveness of the proposed algorithm is verified through an ablation study and quantitative metrics. Simulation results demonstrate that our approach outperforms existing methods.

• Educational Technology International
• /
• 제25권1호
• /
• pp.27-65
• /
• 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.