• Korean Journal of Social Welfare
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• v.64 no.2
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• pp.31-54
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• 2012

Along with increasing mothers' employment, work-family reconciliation has been recognised as a key policy agenda in contemporary welfare states. Although various policy instruments have been introduced and expanded in recent years, the problem of time allocation within couples still remains as a fundamental issue, which has been largely underresearched at a micro perspective. In this context, this study aims to identify dominant types of work-family time allocation within married couple, and to apply these types to the Korean case using the fuzzy-set ideal type analysis. Further, a series of multiple regression analyses will be implemented to find factors affecting each ideal type of work-family time allocation. The 1999 and 2009 Korea Time Use Survey datasets will be adopted for the analyses. Married couples are selected as samples only when men work 40 hours or more per week and they have at least one pre-school child. Empirical analyses cover three parts. First of all, four ideal types on work-family time allocation are classified by intersecting two core variables - the ratio of men's (paid) working and family (caring time plus domestic work) time to total working and family time. In this research, the four types will be labelled the traditional male breadwinner model (TM, high working and low family time), the dual burden model (DB, shared working but low family time), the family-friendly male breadwinner model (FM, high working but shared family time), and the adaptive partnership model (AP, shared working and shared family time). By comparing the composition of the four ideal types in 1999 and 2009, it will examine the trend of work-family time allocation in Korea. In addition, multiple regressions will be useful for investigating which characteristics contribute to the different degree of each fuzzy ideal score in the four models. Finally, policy implications and further research agenda will be discussed.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.67 no.11
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• pp.1423-1433
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• 2018

Recently, a permanent magnet synchronous motor of middle and small-capacity has high torque, high precision control and acceleration / deceleration characteristics. But existing control has several problems that include unpredictable disturbances and parameter changes in the high accuracy and rigidity control industry or nonlinear dynamic characteristics not considered in the driving part. In addition, in the drive method for the control of low-vibration and high-precision, the process of connecting the permanent magnet synchronous motor and the load may cause the response characteristic of the system to become very unstable, to cause vibration, and to overload the system. In order to solve these problems, various studies such as adaptive control, optimal control, robust control and artificial neural network have been actively conducted. In this paper, an incremental encoder of the permanent magnet synchronous motor is used to detect the position of the rotor. And the position of the detected rotor is used for low vibration and high precision position control. As the controller, we propose augmented state feedback control with a speed observer and first order deadbeat disturbance observer. The augmented state feedback controller performs control that the position of the rotor reaches the reference position quickly and precisely. The addition of the speed observer to this augmented state feedback controller compensates for the drop in speed response characteristics by using the previously calculated speed value for the control. The first order deadbeat disturbance observer performs control to reduce the vibration of the motor by compensating for the vibrating component or disturbance that the mechanism has. Since the deadbeat disturbance observer has a characteristic of being vulnerable to noise, it is supplemented by moving average filter method to reduce the influence of the noise. Thus, the new controller with the first order deadbeat disturbance observer can perform more robustness and precise the position control for the influence of large inertial load and natural frequency. The simulation stability and efficiency has been obtained through C language and Matlab Simulink. In addition, the experiment of actual 2.5[kW] permanent magnet synchronous motor was verified.

• Proceedings of the Korean Society for Agricultural Machinery Conference
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• 1993.10a
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• pp.109-118
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• 1993

Development process of agricultural technology has been studied with a case study of Korean agriculture. Technological is considered as a transformer of inputs into outputs and hence technological appropriateness, an important aspect of agricultural development strategies, is considered as a dynamic concepts. Considering the concept of agricultural system as a delivery system for providing essential materials and services to producers and consumers, it has been divided into two major groups of dimensions vis. external challenge dimensions and internal response dimensions. Market, investment and agro-ecosystem constitute the external challenge dimensions : whereas trade , technology as well as production and resources allocation constitute internal response dimensions. The system manager is responsible for maintaining equilibrium in the mentioned six sub-systems. Two kinds of alternatives paths of technological development viz. land saving technology and labour saving technolog have been studied. Technology is considered as a combination of four basic components viz. facilities, abilities, facts and frameworks. Adoption of innovation in agriculture depends on profitability, awareness, risk aversion, financial capacity, institutional infrastructure, availability of physical inputs and adaptability to the local conditions. For a cast study of Korea, changes in the agricultural system through external challenge dimensions are investigated. The impacts of industrialization on agro-ecosystem reported are shift of labour from the agricultural sector to non-agricultural sectors and continuously increasing demand of farm the agricultural sector to non-agricultural sectors accompanied by increase in land prices. The impacts on the commodity market discussed are shift in demand from rice, barley and other cereals to meat , dairy products and vegetables : and increasing in supply capacity of agricultural inputs. The process of agricultural development from 1962 to 19 1 9 (i.e. from start of the first to the end of the sixth five year plan) are also discussed in details with several policy measures taken. The trend of agricultural income and productivity are also analyzed. The main cause of increase in the agricultural income is considered as increase in labour productivity. The study revealed that during the span of 1965-88, holding size has not changed significantly, but both the land and labour productivity increased and so did the agricultural income. R&D activities in Korea have changed over time in three stages vix. import of improved technology, localization by adaptive research and technological mastery. For the new technology to be made affordable to farmers, policy measures like fertilizer and food grain exchange system, dual price system in rice and barely and loan for machinery were strengthened.

• The KIPS Transactions:PartB
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• v.9B no.2
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• pp.139-146
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• 2002

The robot soccer simulation game is a dynamic multi-agent environment. In this paper we suggest a new reinforcement learning approach to each agent's dynamic positioning in such dynamic environment. Reinforcement learning is the machine learning in which an agent learns from indirect, delayed reward an optimal policy to choose sequences of actions that produce the greatest cumulative reward. Therefore the reinforcement learning is different from supervised learning in the sense that there is no presentation of input-output pairs as training examples. Furthermore, model-free reinforcement learning algorithms like Q-learning do not require defining or learning any models of the surrounding environment. Nevertheless these algorithms can learn the optimal policy if the agent can visit every state-action pair infinitely. However, the biggest problem of monolithic reinforcement learning is that its straightforward applications do not successfully scale up to more complex environments due to the intractable large space of states. In order to address this problem, we suggest Adaptive Mediation-based Modular Q-Learning (AMMQL) as an improvement of the existing Modular Q-Learning (MQL). While simple modular Q-learning combines the results from each learning module in a fixed way, AMMQL combines them in a more flexible way by assigning different weight to each module according to its contribution to rewards. Therefore in addition to resolving the problem of large state space effectively, AMMQL can show higher adaptability to environmental changes than pure MQL. In this paper we use the AMMQL algorithn as a learning method for dynamic positioning of the robot soccer agent, and implement a robot soccer agent system called Cogitoniks.

• KIPS Transactions on Software and Data Engineering
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• v.8 no.12
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• pp.499-506
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• 2019

An intelligent robot should decide its behavior accordingly to the dynamic changes in the environment and user's requirements by evaluating options to choose the best one for the current situation. Many intelligent robot systems that use the Procedural Reasoning System (PRS) accomplishes such task management functions by defining the priority functions in the task model and evaluating the priority functions of the applicable tasks in the current situation. The priority functions, however, are defined locally inside of the plan, which exhibits limitation for the tasks for multi-domain services because global contexts for overall prioritization are hard to be expressed in the local priority functions. Furthermore, since the prioritization functions are not defined as an explicit module, reuse or extension of the them for general context is limited. In order to remove such limitations, we propose a policy-based meta-planning for general task management for multi-domain services, which provides the ability to explicitly define the utility of a task in the meta-planning process and thus the ability to evaluate task priorities for general context combining the modular priority functions. The ontological specification of the model also enhances the scalability of the policy model. In the experiments, adaptive behavior of a robot according to the policy model are confirmed by observing the appropriate tasks are selected in dynamic service environments.

• Journal of Broadcast Engineering
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• v.14 no.1
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• pp.59-69
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• 2009

A bi-directional symmetric prediction technique has been developed to improve coding efficiency of B-slice and to reduce the computational complexity required to estimate two motion vectors. On the contrary to the conventional bi-directional mode which encodes both forward and backward motion vectors, it only encodes a single forward motion vector, and the missing backward motion vector is derived in a symmetric way from the forward motion vector using temporal distance between forward/backward reference frames to and from the current B picture. Since the backward motion vector is derived from the forward motion vector, it can halve the computational complexity for motion estimation, and also reduces motion vector data to encode. This technique always derives the backward motion vector from the forward motion vector, however, there are cases when the forward motion vector is better to be derived from the backward motion vector especially in scene changes. In this paper, we generalize the idea of the symmetric coding with forward motion vector coding, and propose a new symmetric coding with backward motion vector coding and adaptive selection between the conventional symmetric mode and the proposed symmetric mode based on rate-distortion optimization.

• Journal of the Korean Association of Oral and Maxillofacial Surgeons
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• v.26 no.5
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• pp.497-506
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• 2000

This study is comprised of data obtained from the files of 346 patients with temporomandibular disorders. All patients were diagnosed, treated and followed in the Department of Dentistry at the Inha university hospital, Incheon, Korea. The patients had treated with medications, physical therapy, occlusal splint and arthrocentesis. The study data were obtained from the medical records and telephone interviews that were conducted by research assistants. The results were as follows 1. The patient's main complaint was pain(77%), and mouth opening limitation was 17%. 2. An analysis of the medical records of the 346 patients disclosed that 82% were improved and 17% had no improvement when they were dismissed. 1% of the patients had become worse during therapy. 3. A success rate of 82% was achieved when medication assisted physical therapy was included. In the current status at the telephone interview, 270 patients(89%) reported that they were doing well with 56% describing themselves as asymtomatic and 32% experiencing only minor residual or recurrent symptoms. 11% regarded themselves as unimproved and worse. 4. In the current status of the unsuccessfully treated patients by medications and physical therapy, 64% of patients were doing well(3% as asymptomatic and 56% as only minor residual or recurrent symptom). But 36% of patients was reported as unimproved and worse. 5. TMJ has a remarkable adaptive potential and TMJ disorder has a natural history of spontaneous fluctuations and favorable prognosis during the subsequent natural course. 6. In the treatment of the temporomandibular disorders, there is a treatment ladder, starting with the simplest and least expensive treatment, that is ascended until resolution of the patient's symptoms occur. These findings suggest that conservative reversible therapies are both sufficient and appropriate for management of temporomandibular disorder in most patients. Major alterations of mandibular position or dentoalveolar relationships do not appear to be necessary for obtaining either short term or long term success and therefore they can be generally regards as inappropriate treatment for this disorder. The fact that physical therapy is non-invasive and does not appear to be fraught with irreversible changes, makes it a very applicable vehicle in the area of clinical TMJ disorder management.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.43 no.10 s.352
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• pp.79-89
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• 2006

TCP is the most widely used transport protocol in Internet applications that guarantees a reliable data transfer. But, in the wireless multi-hop networks, TCP performance is degraded because it is designed for wired networks. The main reasons of TCP performance degradation are contention for wireless medium at the MAC layer, hidden terminal problem, exposed terminal problem, packet losses in the link layer, unfairness problem, reordering problem caused by path disconnection, bandwidth waste caused by exponential backoff of retransmission timer due to node's mobility and so on. Specially, in the mobile ad-hoc networks, discrepancy between a station's transmission range and interference range produces hidden terminal problem that decreases TCP performance greatly by limiting simultaneous transmission at a time. In this paper, we propose a new MAC algorithm for mobile ad-hoc networks to solve the problem that a node can not transmit and just increase CW by hidden terminal. In the IEEE 802.11 MAC DCF, a node increases CW exponentially when it fails to transmit, but the proposed algorithm, changes CW adaptively according to the reason of failure so we get a TCP performance enhancement. We show by ns-2 simulation that the proposed algorithm enhances the TCP performance by fairly distributing the transmission opportunity to the failed nodes by hidden terminal problems.

• Structural Monitoring and Maintenance
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• v.2 no.1
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• pp.77-93
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• 2015

The idea of using measured dynamic characteristics for damage detection is attractive because it allows for a global evaluation of the structural health and condition. However, vibration-based damage detection for complex structures such as long-span cable-supported bridges still remains a challenge. As a suspension or cable-stayed bridge involves in general thousands of structural components, the conventional damage detection methods based on model updating and/or parameter identification might result in ill-conditioning and non-uniqueness in the solution of inverse problems. Alternatively, methods that utilize, to the utmost extent, information from forward problems and avoid direct solution to inverse problems would be more suitable for vibration-based damage detection of long-span cable-supported bridges. The auto-associative neural network (ANN) technique and the probabilistic neural network (PNN) technique, that both eschew inverse problems, have been proposed for identifying and locating damage in suspension and cable-stayed bridges. Without the help of a structural model, ANNs with appropriate configuration can be trained using only the measured modal frequencies from healthy structure under varying environmental conditions, and a new set of modal frequency data acquired from an unknown state of the structure is then fed into the trained ANNs for damage presence identification. With the help of a structural model, PNNs can be configured using the relative changes of modal frequencies before and after damage by assuming damage at different locations, and then the measured modal frequencies from the structure can be presented to locate the damage. However, such formulated ANNs and PNNs may still be incompetent to identify damage occurring at the deck members of a cable-supported bridge because of very low modal sensitivity to the damage. The present study endeavors to enhance the damage identification capability of ANNs and PNNs when being applied for identification of damage incurred at deck members. Effort is first made to construct combined modal parameters which are synthesized from measured modal frequencies and modal shape components to train ANNs for damage alarming. With the purpose of improving identification accuracy, effort is then made to configure PNNs for damage localization by adapting the smoothing parameter in the Bayesian classifier to different values for different pattern classes. The performance of the ANNs with their input being modal frequencies and the combined modal parameters respectively and the PNNs with constant and adaptive smoothing parameters respectively is evaluated through simulation studies of identifying damage inflicted on different deck members of the double-deck suspension Tsing Ma Bridge.

• Journal of the Korean Geographical Society
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• v.45 no.1
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• pp.49-74
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• 2010

Cities are major sources of greenhouse gas emissions but also suitable places for implementing proactive climate mitigation and adaptation strategies. Based on the interdisciplinary review of literature, we categorize the current discussion about urban climate mitigation and adaptation planning, policy and practices into four perspectives - sustainability science, global change science, multilevel governance, and structural engineering. While these four schools of thought have distinct perspectives rooted in different disciplinary lenses, our synthesis of the literature identifies several universal themes that are common to all of the perspectives in the context of combating threats posed by climate change. The Portland case study illustrates that a city can make changes to reduce greenhouse gas emissions and increase adaptive capacity to climate change impacts by implementing smart growth, devising local climate action plans that target emission reductions in various sectors, recognizing the interactions and influences of multiple scales of governance, and supporting the installation of various green infrastructures that contribute to green economy. Furthermore, a university can serve as a hub in this climate mitigation and adaptation arena by connecting various levels of community organizations in both public and private sectors, creating innovative research centers and spatially explicit green infrastructure, designing impact assessments and campus carbon inventories, and engaging students and the larger community through service learning.