• Journal of Digital Convergence
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• v.16 no.10
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• pp.465-477
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• 2018

The purpose of this study is how it affect them what the effect of skin recognition on the purchasing behavior and propensity to buy facial cleanser in 311 women in their 20s and 50s. This study analyzed by importance, interest, and satisfaction of skin recognition, and type of impulse buying, type of depending on brand, type of planning buying. The group with high interest in skin recognition had a long time to clean. As they got a purchasing information the group with low knowledge had the information from nearby, and the group with high knowledge got information from internet. At the view of purchasing propensity the women who are highly interested in the skin have a tendency of type of impulse buying and type of planning buying, and the women with high skin importance are less inclined to type of impulse buying. In conclusion, Skin recognition uses purchasing behavior and propensity to buy facial cleanser.

• Journal of Korean Society of Rural Planning
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• v.26 no.3
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• pp.39-47
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• 2020

While agricultural water has been declared free in Korea to ensure access to these limited resource since the year 2000, farmers have however developed lackadaisical behavior towards water saving leading to its scarcity. To overcome this problem, a variety of experience-oriented education model was developed for farmers to promote the adoption of water conservation, and preventive measure against the drought impacts. In this study, farmers' awareness and their attitudinal behavior of agricultural water savings were investigated. The monitoring of water supply structure and the repair facilities in Pohang and Yeongdeok areas were conducted. The field visits and behavioral surveys showed a high degree of over-use and illegal water withdrawals by the farmers due to poor water-saving and management practices. We found that most of the KRC employees strongly admitted the necessity of water-saving education. On the other hand, the farmers showed good interest in the implementation of water-saving awareness through education. Besides this, most farmers agreed to adopt water-saving practices in the fields. Farmers also acknowledged the recklessness of water use was due to the aging of waterways, poor water management, and illegal water consumption. The majority of the farmers responded against imposing the water-use tariffs. However, there was a low response to paying the water-use charge. Aging agricultural facilities and the lack of institutional penalties or incentives were the major obstacles in achieving efficient water-saving. Considering the current drought frequency, urgent water-saving education of farmers was deemed necessary to prepare the farming community against the water shortages. Based on the results of this study, we have to identify the irrigation practices of farmers and provide water-saving education to enforce more efficient use and management of agricultural water.

• Journal of the Korea Society of Computer and Information
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• v.28 no.3
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• pp.75-82
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• 2023

The main purpose of this study is to analyze the metacognition of digital library search behavior of college students and to provide a fundamental data for the designing a user-centered online information retrieval system to find more optimal search results. In order to achieve the purpose of this study, metacognition was classified into the five main categories, including schema-training, planning, monitoring, evaluation, and transfer, and a total of twenty subcategories were included. A total of 112 students participated in the online questionnaire. The collected data were analyzed using SPSS version 26, and it was found that there was a significant correlation between metacognition of college students and their digital library searching behavior. In particular, the digital library search experience was found to be the strongest factor to be considered as the most important variable in digital library design based on the aspect of user metacognition.

• International Journal of Control, Automation, and Systems
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• v.5 no.6
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• pp.674-680
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• 2007

The probabilistic roadmap (PRM) method, which is a popular path planning scheme, for a manipulator, can find a collision-free path by connecting the start and goal poses through a roadmap constructed by drawing random nodes in the free configuration space. PRM exhibits robust performance for static environments, but its performance is poor for dynamic environments. On the other hand, reinforcement learning, a behavior-based control technique, can deal with uncertainties in the environment. The reinforcement learning agent can establish a policy that maximizes the sum of rewards by selecting the optimal actions in any state through iterative interactions with the environment. In this paper, we propose efficient real-time path planning by combining PRM and reinforcement learning to deal with uncertain dynamic environments and similar environments. A series of experiments demonstrate that the proposed hybrid path planner can generate a collision-free path even for dynamic environments in which objects block the pre-planned global path. It is also shown that the hybrid path planner can adapt to the similar, previously learned environments without significant additional learning.

• Journal of Institute of Control, Robotics and Systems
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• v.15 no.12
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• pp.1232-1239
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• 2009

This paper proposes an exploration strategy to efficiently find a specific place in large unknown environments with wall-following based path planning. Many exploration methods proposed so far showed good performance but they focused only on efficient planning for modeling unknown environments. Therefore, to successfully accomplish the room finding task, two additional requirements should be considered. First, suitable path-planning is needed to recognize the room number. Most conventional exploration schemes used the gradient method to extract the optimal path. In these schemes, the paths are extracted in the middle of the free space which is usually far from the wall. If the robot follows such a path, it is not likely to recognize the room number written on the wall because room numbers are usually too small to be recognized by camera image from a distance. Second, the behavior which re-explores the explored area is needed. Even though the robot completes exploration, it is possible that some rooms are not registered in the constructed map for some reasons such as poor recognition performance, occlusion by a human and so on. With this scheme, the robot does not have to visit and model the whole environment. This proposed method is very simple but it guarantees that the robot can find a specific room in most cases. The proposed exploration strategy was verified by various experiments.

• Journal of Sensor Science and Technology
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• v.27 no.4
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• pp.209-215
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• 2018

Recent research in animal behavior has shown that gradient information plays an important role in finding food and home. It is also important in optimization of performance because it indicates how the inputs should be adjusted for maximization/minimization of a performance index. We introduce perturbation as an additional input to obtain gradient information. Unlike the typical approach of calculating the gradient from the derivative, the proposed processing is very robust to noise since it is performed as a summation. Experimental results prove the validity of the process of spatial gradient acquisition. Quantitative indices for measuring the effect of the amplitude and the frequency are developed based on linear regression analysis. Drones are very useful for environmental monitoring and an autonomous path planning is required for unstructured environment. Guiding the drone for finding the origin of the interested physical property is done by estimating the gradient of the sensed value and generating the drone trajectories in the direction which maximizes the sensed value. Simulation results show that the proposed method can be successfully applied to identify the source of the physical quantity of interest by utilizing it for path planning of an autonomous drone in 3D environment.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2015.05a
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• pp.202-203
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• 2015

To promote the remodeling project it is important to get apartment residents' consent. It is significant variable to determine project to progress smoothly from planning stage which committee of association establishment sets up to establishment stage of association. On average, it takes about 1~1.6 year in planning phase which means before construction phase of remodeling. Therefore, it is very important issue to get apartment residents' consent in planning phase. In this research, we focused on residents' opinion and proposed solution of conflict with gathering residents' opinion to proceed remodeling project. By setting particular remodeling situation, related residents represented as agents made effort to efficient coordination to reduce total duration of decision making. Therefore, we proposed multi-agent based on fuzzy inference to simulate behavior of decision making on remodeling project effectively. From this method, optimal alternative is selected by considering each agents' attributes which represented by fuzzy set. This research will develope to further research for realizing concrete multi-agent based on fuzzy inference considering all stakeholders in remodeling project.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.5
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• pp.179-188
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• 2021

The purpose of this study is to examine the level of aggressive tax planning (ATP) among companies listed in the Access, Certainty, Efficiency (ACE) Market of Bursa Malaysia. On top of that, this study also investigates the relationship between company characteristics, ethnicity, and ATP. This study uses a balanced pooled sample of 105 firm years-observations for the period from 2014 to 2018. These samples were selected to provide new insight into this market and to explore the attitude of small firms toward ATP in Malaysia. The data was retrieved from DataStream and the downloaded annual reports. The finding shows that profitability and financial distress have a significant relationship with ATP. Other variables including size, capital intensity, inventory intensity, leverage, and ethnicity, were not determinants of ATP. The result in this study may assist the reader in understanding the nature of companies in the ACE market, particularly on its behavior toward tax planning. A strict requirement is needed to be adopted in the sample selection process, thus limiting the sample size. Further, since the previous study focused on large companies, the discussion of this paper will provide new insight into the nature of tax planning within the small- and medium-sized companies in Malaysia.

• Advances in concrete construction
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• v.12 no.6
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• pp.451-459
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• 2021

The mechanical behaviors and chloride resistance performance of fiber reinforced cementitious composites (FRCC) with hybrid polyethylene (PE) and steel fiber (in total 2% by volume) were investigated. Based on micro-mechanics and fracture mechanics, the reason why the tensile strain capacity of FRCC changed obviously was obtained. Besides, the effects of the total surface area of fiber in FRCC on compressive strength and chloride content were clarified. It is found that the improvement of the tensile strain capacity of FRCC with hybrid fiber is attributed to the growth of strain-hardening performance index (the ratio of complementary energy to crack tip toughness). As the total surface area of fiber related with the interfacial transition zone (ITZ) between fiber and matrix increases, compressive strength decreases obviously. Since the total surface area of fiber is small, the chloride resistance performance of FRCC with hybrid PE and steel fiber is better than that of FRCC containing only PE fiber.

• Journal of Auto-vehicle Safety Association
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• v.16 no.1
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• pp.6-11
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• 2024

This paper presents a motion planning algorithm of autonomous racing vehicles for mimicking the characteristics of a human driver. Time optimal maneuver of a race car has been actively studied as a major research area over the past decades. Although the time optimization problem yields a single time series solution of minimum time maneuver inputs for the vehicle, human drivers achieve similar lap times while taking various racing lines and velocity profiles. In order to model the characteristics of a specific driver and reproduce the motion, a stochastic motion planning framework based on kernelized motion primitive is introduced. The proposed framework imitates the behavior of the generated reference motion, which is based on a small number of human demonstration laps along the racetrack using Gaussian mixture model and Gaussian mixture regression. The mean and covariance of the racing line and velocity profile mimicking the driver are obtained by accumulating the outputs tested at equidistantly sampled input points. The results confirmed that the obtained lateral and longitudinal motion simulates the driver's driving characteristics, which are feasible for actual vehicle test environments.