• Membrane Journal
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• v.31 no.6
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• pp.393-403
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• 2021

Enzymes are important class of catalyst for biotransformation. Stability and reusability of enzymes during the catalysis process is a key issue. Activity of enzyme can be enhanced by its immobilization on a suitable substrate by creation of specific microenvironment. A variety of membranes has been used as substrate due to the biocompatibility and simpler method to tune hydrophilicity/hydrophobicity property of the membrane surface. In this review, polymer membranes including cellulose, polyacrylonitrile (PAN), polydimethylsiloxane (PDMS), polyvinylidene fluoride (PVDF), polyethersulfone (PES) are introduced and discussed in detail. Biodegradation of organic contaminants by immobilized enzyme is an environmental friendly process to reduce the contamination of environment in pharmaceutical company and textile industries. The controlled hydrolysis of oil can be performed in enzyme immobilized membrane bioreactor (EMBR), resulting in reducing carbon emission and reduced environmental pollution. Bioethanol and biodiesel are considered alternative fossil fuels that can be prepared in EMBR.

• PNF and Movement
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• v.20 no.2
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• pp.167-177
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• 2022

Purpose: Pes planus is a common foot deformity that involves the loss of the medial longitudinal arch. The medial longitudinal arch deformity is usually asymptomatic; however, it can lead to an increased risk of pain and injury. Low-Dye taping is designed to treat plantar heel pain and pes planus. However, low-Dye taping is relatively complex, and a considerable amount of time is required to apply the tape correctly. The purpose of this study was to compare the acute effect of two different types of taping (low-Dye taping and modified Mulligan taping) on arch reformation, plantar pressure, and gait characteristics in participants with asymptomatic flexible pes planus. Methods: Twenty subjects (9 males and 11 females; mean age = 21.95 years) with asymptomatic flexible pes planus voluntarily participated in this study. Arch reformation was evaluated using navicular height measurements. Changes in plantar pressure distribution were measured using BioRecue equipment. Gait parameters were measured using spatiotemporal data collected during consecutive gait cycles using a G-WALK device. One-way analysis of variance was used to compare the three different conditions (i.e., bare foot, low-Dye taping, and modified Mulligan taping) for each variable. Results: Navicular height was significantly increased in subjects who underwent the two types of taping compared to those who experienced the bare foot condition. The plantar pressure was significantly shifted to the posterolateral area after modified Mulligan taping compared with the bare foot condition. There were no significant differences in the gait parameters. Conclusion: The findings of this study indicate that modified Mulligan taping has a similar effect to low-Dye taping, and modified Mulligan taping is a simpler method than low-Dye taping.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.05a
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• pp.94-96
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• 2021

Software-Defined Networking (SDN), which has emerged to overcome the limitations of existing network architectures, makes routing management simpler and more efficient through a central controller. SR (Segment Routing) is a flexible and scalable way of doing source routing, and defines the information path of the network through a list of segments arranged in the packet header. In an SDN environment, the performance of each router is almost the same, but packets tend to be concentrated on routes that are frequently used depending on routing algorithms. Routers in that path have a relatively high frequency of failure and are more likely to become bottlenecks. In this paper, we propose a routing algorithm that allows the router, which is a resource in the network, to evenly process packets in the SDN with SR, so that the administrator can utilize the resources in the network without idle routers, and at the same time facilitate the management of the router.

• The KIPS Transactions:PartA
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• v.11A no.7 s.91
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• pp.483-488
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• 2004

For real-time applications, the underlying operating system (0S) should support timeliness guarantees of real-time tasks. However, most of current operating systems do not provide timely management facilities in an efficient way. There could be two approaches to support timely management facilities for real-time applications: (1) by modifying 0S kernel and (2) by Providing a middleware without modifying 0S. In our approach, we adopted the middleware approach based on the TMO (Time-triggerred Message-triggered Object) model which is a well-known real-tine object model. The middleware, named TMSOM (TMO Support Middleware) has been implemented on various OSes such as Linux and Windows XP/NT/98. In this paper, we mainly consider TMOSM implemented on Linux(TMOS/Linux). Although the real-time schedul-ing aIgorithm used in current TMOSM/Linux can produce an efficient real-time schedule, it can be improved for periodic real-time tasks by considering several factors. In this paper, we discuss those factors and propose an improved real-time scheduling algorithm for periodic real-time tasks, In order to simulate the performance of our algorithm, we measure timeliness guarantee rate for periodic real-time tasks. The result shows that the performance of our algorithm is superior to that of existing algorithm. Additionally, the proposed algorithm can improve system performance by making the structure of real-time middleware simpler.

• Journal of Korean Society of Forest Science
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• v.84 no.2
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• pp.121-130
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• 1995

Forecasting accuracy is examined in the context of Michigan travel demand. Eight different annual models are used to forecast up to two years ahead, and nine different quarterly models up to four quarters. In the evaluation of annual models' performance, multiple regression performed better than the other methods in both the one year and two year forecasts. For quarterly models, Winters exponential smoothing and the Box-Jenkins method performed better than naive 1 s in the first quarter ahead, but these methods in the second, third, and fourth quarters ahead performed worse than naive 1 s. The sophisticated models did not outperform simpler models in producing quarterly forecasts. The best model, multiple regression, performed slightly better when fitted to quarterly rather than annual data: however, it is not possible to strongly recommend quarterly over annual models since the improvement in performance was slight in the case of multiple regression and inconsistent across the other models. As one would expect, accuracy declines as the forecasting time horizon is lengthened in the case of annual models, but the accuracy of quarterly models did not confirm this result.

• Journal of the Korean Institute of Intelligent Systems
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• v.3 no.2
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• pp.18-35
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• 1993

The water level control system of the steam generator in a pressurized water reactor and its control problems are analysed. In this work the stable control strategy during the low power operation and transient states is studied. To solve the problem, a fuzzy logic control method is applied as a basic algorithm of the controller. The control algorithm is based on the operator's knowledges and the experiences of manual operation for water level control at the compact nuclear simulator set up in Korea Atomic Energy Research Institute. From a viewpoint of the system realization, the control variables and rules are established considering simpler tuning and the input-output relation. The control strategy includes the dynamic tuning method and employs a substitutional information using the bypass valve opening instead of incorrectly measured signal at the low flow rate as the fuzzy variable of the flow rate during the pressure control mode of the steam generator. It also involves the switching algorithm between the control valves to suppress the perturbation of water level. The simulation results show that both of the fine control action at the small level error and the quick response at the large level error can be obtained and that the performance of the controller is improved.

• Journal of Ocean Engineering and Technology
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• v.32 no.6
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• pp.447-457
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• 2018

In this study, a two-dimensional fully nonlinear transient wave numerical tank was developed using a desingularized indirect boundary integral equation method. The desingularized indirect boundary integral equation method is simpler and faster than the conventional boundary element method because special treatment is not required to compute the boundary integral. Numerical simulations were carried out in the time domain using the fourth order Runge-Kutta method. A mixed Eulerian-Lagrangian approach was adapted to reconstruct the free surface at each time step. A numerical damping zone was used to minimize the reflective wave in the downstream region. The interpolating method of a Gaussian radial basis function-type artificial neural network was used to calculate the gradient of the free surface elevation without element connectivity. The desingularized indirect boundary integral equation using an isolated point source and radial basis function has no need for information about the element connectivity and is a meshless method that is numerically more flexible. In order to validate the accuracy of the numerical wave tank based on the desingularized indirect boundary integral equation method and meshless technique, several numerical simulations were carried out. First, a comparison with numerical results according to the type of desingularized source was carried out and confirmed that continuous line sources can be replaced by simply isolated sources. In addition, a propagation simulation of a $2^{nd}$-order Stokes wave was carried out and compared with an analytical solution. Finally, simulations of propagating waves in shallow water and propagating waves over a submerged bar were also carried and compared with published data.

• The Journal of Society for e-Business Studies
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• v.24 no.2
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• pp.71-89
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• 2019

In order to come up with satisfying product and improvement, firms use traditional marketing research methods to obtain consumers' opinions and further try to reflect them. Recently, gathering data from consumer communication platforms like internet and SNS has become popular methods. Meanwhile, with the development of information technology, mobile companies are launching new digital products for children to protect them from harmful content and provide them with necessary functions and information. Among these digital products, Kids Phone, which is a wearable device with safe functions that enable parents to learn childern's location. Kids phone is relatively cheaper and simpler than smartphone but it is noted that there are several problems such as some useless functions and frequent breakdowns. This study analyzes the reviews of Kids phones from domestic mobile companies, identifies the characteristics, strengths and weaknesses of the products, proposes improvement methods strategies for devices and services through SNS consumer analysis. In order to do that customer review data from online shopping malls was gathered and was further analyzed through text mining methods such as TF/IDF, Sentiment Analysis, and network analysis. Customer review data was gathered through crawling Online shopping Mall and Naver Blog/$Caf\acute{e}$. Data analysis and visualization was done using 'R', 'Textom', and 'Python'. Such analysis allowed us to figure out main issues and recent trends regarding kids phones and to suggest possible service improvement strategies based on sentiment analysis.

• Journal of Internet Computing and Services
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• v.16 no.3
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• pp.21-32
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• 2015

Since spatio-temporal local features for video representation have become an important issue of modeless bottom-up approaches in action recognition, various methods for feature extraction and description have been proposed in many papers. In particular, BoF(bag of features) has been promised coherent recognition results. The most important part for BoF is how to represent dynamic information of actions in videos. Most of existing BoF methods consider the video as a spatio-temporal volume and describe neighboring 3D interest points as complex volumetric patches. To simplify these complex 3D methods, this paper proposes a novel method that builds BoF representation as a way to learn 2D interest points directly from video data. The basic idea of proposed method is to gather feature points not only from 2D xy spatial planes of traditional frames, but from the 2D time axis called spatio-temporal frame as well. Such spatial-temporal features are able to capture dynamic information from the action videos and are well-suited to recognize human actions without need of 3D extensions for the feature descriptors. The spatio-temporal BoF approach using SIFT and SURF feature descriptors obtains good recognition rates on a well-known actions recognition dataset. Compared with more sophisticated scheme of 3D based HoG/HoF descriptors, proposed method is easier to compute and simpler to understand.

• Journal of KIISE:Software and Applications
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• v.35 no.3
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• pp.179-188
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• 2008

An important issue in multiagent reinforcement learning is how an agent should team its optimal policy through trial-and-error interactions in a dynamic environment where there exist other agents able to influence its own performance. Most previous works for multiagent reinforcement teaming tend to apply single-agent reinforcement learning techniques without any extensions or are based upon some unrealistic assumptions even though they build and use explicit models of other agents. In this paper, basic concepts that constitute the common foundation of multiagent reinforcement learning techniques are first formulated, and then, based on these concepts, previous works are compared in terms of characteristics and limitations. After that, a policy model of the opponent agent and a new multiagent reinforcement learning method using this model are introduced. Unlike previous works, the proposed multiagent reinforcement learning method utilize a policy model instead of the Q function model of the opponent agent. Moreover, this learning method can improve learning efficiency by using a simpler one than other richer but time-consuming policy models such as Finite State Machines(FSM) and Markov chains. In this paper. the Cat and Mouse game is introduced as an adversarial multiagent environment. And effectiveness of the proposed multiagent reinforcement learning method is analyzed through experiments using this game as testbed.