• International Journal of High-Rise Buildings
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• v.6 no.2
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• pp.197-205
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• 2017

The conflict between indoor environmental quality and energy consumption has become an unneglectable problem for highrise office buildings, where occupants' productivity is highly affected by their working environment. An effective Façade, therefore, should play the role of an active building skin by adapting to the ever-changing external environment and internal requirements. This paper explores the energy-saving and indoor environment-improving potential of a phase-change material (PCM) integrated Façade. Building performance simulations, combined with parametric study and sensitivity analysis, are adopted in this research. The result quantifies the potential of a PCM-integrated Façade with different configurations and PCM properties, taking as an example a south-oriented typical office room in Shanghai. It is found that a melting temperature of around $22^{\circ}C$ for the PCM layer is optimal. Compared to a conventional Façade, a PCM-integrated Façade effectively reduces total energy use, peak heating/cooling load, and operative temperature fluctuation during the periods of May-July and November-December.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.49 no.1
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• pp.112-118
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• 2012

In daily life, there are many information broadcasting by using voice information systems. If surrounding noises are mixed with the information signals, the clarity of the signal become down graded too much to understand. Surrounding noises are not uniformed, but very irregular signals always changing. Therefore, it is very hard to control the output signals along with the irregular signals. This paper suggests a method to change the level of the voice information adapting to the surround noise in the white noise environment. The surround noise level is measured by subtracting the stored output voice signal from the voice signal degraded by the noise. The noise is used to estimation of SNR. And, the method to change the output level of voice signal adapting to the noise level. The suggested adaptive voice information system has the advantage to improve listeners' speech perception and to use amplifier's energy effectively.

• Journal of Korean Society of Disaster and Security
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• v.16 no.1
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• pp.37-48
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• 2023

The possibility of a super-large disaster is increasing due to changes in national territory, urban space and social environment, extreme weather conditions due to climate change, and paralysis of national infrastructure due to natural disasters. In this study, in order to support the systematic establishment of national territorial disaster prevention strategies for future disasters, alternatives to intelligent national territorial disaster prevention policies for future disasters were considered. Changes in the national environment related to future disasters, domestic and foreign prior studies and policy trends related to national disaster prevention, and studies related to the national disaster management system were investigated, and institutional and technical policy alternatives were derived. As a policy alternative, it was suggested that the creation of a self-adapting national territory for future disasters should be systematized and continuously supported through a technically intelligent decision-making support system.

• International Journal of Advanced Culture Technology
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• v.5 no.4
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• pp.38-43
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• 2017

Many students prefer to study abroad to increase their chances of having a better future. While studying abroad they may encounter difficulties such as adapting to the culture of the country they are studying in. Chinese students coming to Korea are no exception to this, and when they are studying abroad, the new environment they are in may cause them hardships which may impact on their social life and even their academic performance. In order to develop their careers, they face many difficulties and challenges. Cultural differences they experience may change their attitudes, thoughts, and values. This research focuses on international students who are not yet certain about their future plans. In order to grasp levels of daily life satisfaction, ease of communication, and future planning orientation, this study conducted a survey of Chinese students who study in Korea. The empirical analysis showed that students with high level of life satisfaction have a tendency to enter graduate school. However, communication has no relation to future planning orientation.

• Proceedings of the IEEK Conference
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• 2005.11a
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• pp.1043-1048
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• 2005

As sensor network is drawing more attention than ever before due to the development of sensors and the technology of communications, various routing-algorithms, to realize a sensor node with low-power and a miniature size, is being introduced in the field. This paper is to discuss a way to find an optimal path by changing a routing- algorithm adequately according to environmental changes. This is also to suggest an appropriate sensor network model in the ubiquitous aera. The result from the experiment that we conducted showed us that as we suggested, an algorithm, changing and adapting itself to each different environment, operated more stably and transmitted data more effectively than the current fixed one. And it was also confirmed that this type of algorithm can provide low-power management, which is very important in sensor network.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.1072-1075
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• 2005

This paper presents that TD method is applied to the human adaptive devices for smart home with context awareness (or recognition) technique. For smart home, the very important problem is how the appliances (or devices) can adapt to user. Since there are many humans to manage home appliances (or devices), managing the appliances automatically is difficult. Moreover, making the users be satisfied by the automatically managed devices is much more difficult. In order to do so, we can use several methods, fuzzy controller, neural network, reinforcement learning, etc. Though the some methods could be used, in this case (in dynamic environment), reinforcement learning is appropriate. Among some reinforcement learning methods, we select the Temporal Difference learning method as a core algorithm for adapting the devices to user. Since this paper assumes the environment is a smart home, we simply explained about the context awareness. Also, we treated with the TD method briefly and implement an example by VC++. Thereafter, we dealt with how the devices can be applied to this problem.

• Journal of Korea Multimedia Society
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• v.11 no.12
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• pp.1758-1764
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• 2008

In this paper, we propose query restructure method which realizes not only to present the result from database in Web page but also to adapt user's browsing environments. Recently, wireless PDA (Personal Digital Assistant) and portable phone and terminals equipped with Web browser become very popular. Various browsers would be required to create the HTML which adapt to the user's browsing environment. We propose an adaptive data presentation system which is an extension of SQL which creates HTML pages dynamically adapting to the size of screen. In our proposed method, the three basic rules for the layout conversion are provided and applying these rules, an efficient layout conversion technique optimized to user environment is proposed. Moreover, we propose a standard for converting layouts and a layout optimization for adaptive conversion of layouts.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1995.10a
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• pp.880-884
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• 1995

Manufacturing environment is getting characterized by unstable market demand,short product life cycle and timebased competition. For adapting this environment,machine tools have to be further versatile functionally in order to reduce part's set-up time. Unlike existing manufacturing systems mainly to focus on part flow, it is important to control tool flow using fast tool change device and tool delivery device in parallel machines consisting of versatile machine tools, because complete operations on a part can be performed on one machine tool in a single machine set-up. In this paper, under dynamic tool allocation strategy to share tools among machine tools, we propose a real-time tool allocation and operation esequence model with an objective of minimizing flow time using autonomy and negotiation of agents in parallel machines

• Journal of The Korean Society of Agricultural Engineers
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• v.61 no.2
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• pp.51-61
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• 2019

In this study, interest in rural life of good natural environment rather than busy life is increasing as human life is extended by scientific and medical technology and society has improved. The reckless development of rural villages has caused social problems as the natural environment has been damaged, failing to function as a pleasant home. To address these problems, the government has implemented a rural village development project, but if the site is selected incorrectly, the residents may not be recruited, or applicants may lose their status, or the portion of the infrastructure building fee may increase. In order to prepare objective and clear assessment methods for the target site not to cause such problems, a layering analysis method (AHP: Analytic Method) was used to identify the current status of the rural village formation project, draw assessment items, and determine the importance of each item.

• The Journal of Korea Robotics Society
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• v.15 no.4
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• pp.398-403
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• 2020

Robot's throwing control is difficult to accurately calculate because of air resistance and rotational inertia, etc. This complexity can be solved by using machine learning. Reinforcement learning using reward function puts limit on adapting to new environment for robots. Therefore, this paper applied deep reinforcement learning using neural network without reward function. Throwing is evaluated as a success or failure. AI network learns by taking the target position and control policy as input and yielding the evaluation as output. Then, the task is carried out by predicting the success probability according to the target location and control policy and searching the policy with the highest probability. Repeating this task can result in performance improvements as data accumulates. And this model can even predict tasks that were not previously attempted which means it is an universally applicable learning model for any new environment. According to the data results from 520 experiments, this learning model guarantees 75% success rate.