• Journal of Korea Multimedia Society
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• v.23 no.2
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• pp.155-165
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• 2020

In this paper, we propose a smart thermostat temperature set-point control method based on machine learning and rule engine, which controls thermostat's temperature set-point so that it can achieve energy savings as much as possible without sacrifice of occupants' comfort while users' preference usage pattern is respected. First, the proposed method periodically mines data about how user likes for heating (winter)/cooling (summer) his or her home by learning his or her usage pattern of setting temperature set-point of the thermostat during the past several weeks. Then, from this learning, the proposed method establishes a weekly schedule about temperature setting. Next, by referring to thermal comfort chart by ASHRAE, it makes rules about how to adjust temperature set-points as much as low (winter) or high (summer) while the newly adjusted temperature set-point satisfies thermal comfort zone for predicted humidity. In order to make rules work on time or events, we adopt rule engine so that it can achieve energy savings properly without sacrifice of occupants' comfort. Through experiments, it is shown that the proposed smart thermostat temperature set-point control method can achieve better energy savings while keeping human comfort compared to other conventional thermostat.

• Proceedings of the Korea Contents Association Conference
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• 2007.11a
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• pp.226-230
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• 2007

This paper proposes a local scheduling method based on user pattern for Volunteer computing project, Korea@Home. It enables Korea@Home participants to run the agent without disturbance. It is devised to prevent user's application from delay while running the agent and decreases the frequency of switching resource between the user and the agent. We analyze the user's patterns of donating computing resource with Korea@Home which is a representative volunteer computing project in Korea. It has contributed the computing power to several applications including climate prediction and virtual screening. It promotes the volunteers to participate continuously without disturbance and increases the potential computing power with non-disturbance scheduling based on user usage pattern for Volunteer Computing.

• Journal of information and communication convergence engineering
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• v.9 no.6
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• pp.637-640
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• 2011

The hybrid neural networks have characteristics such as fast learning times, generality, and simplicity, and are mainly used to classify learning data and to model non-linear systems. The middle layer of a hybrid neural network clusters the learning vectors by grouping homogenous vectors in the same cluster. In the clustering procedure, the homogeneity between learning vectors is represented as the distance between the vectors. Therefore, if the distances between a learning vector and all vectors in a cluster are smaller than a given constant radius, the learning vector is added to the cluster. However, the usage of a constant radius in clustering is the primary source of errors and therefore decreases the recognition success rate. To improve the recognition success rate, we proposed the enhanced hybrid network that organizes the middle layer effectively by using the enhanced ART1 network adjusting the vigilance parameter dynamically according to the similarity between patterns. The results of experiments on a large number of calling card images showed that the proposed algorithm greatly improves the character extraction and recognition compared with conventional recognition algorithms.

• Journal of the Institute of Electronics and Information Engineers
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• v.51 no.6
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• pp.110-116
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• 2014

Pattern matching algorithms are widely used in computer security systems such as computer networks, ubiquitous networks, sensor networks, and so on. However, the advances in information technology causes grow on the amount of data and increase on the computation complexity of pattern matching processes. Therefore, there is a strong demand for a novel high performance pattern matching algorithms. In light of this fact, this paper newly proposes a suffix tree based pattern matching algorithm. The suffix tree is constructed based on the suffix values of all patterns. Then, the shift nodes which informs how many characters can be skipped without matching operations are added to the suffix tree in order to boost matching performance. The proposed algorithm reduces memory usage on the suffix tree and the amount of matching operations by the shift nodes. From the performance evaluation, our algorithm achieved 24% performance gain compared with the traditional algorithm named as Wu-Manber.

• KIPS Transactions on Computer and Communication Systems
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• v.5 no.11
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• pp.411-418
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• 2016

Context-aware application has a lot of power consumption because it creates context by using a number of smartphone's sensors. Furthermore, only few kinds of researches have been conducted that provide information for the evaluation result of power consumption in the aspect of applications. In addition, evaluation of power consumption do not consider user's usage pattern or provide only total amount of power consumption, and inform developers power consumption of sensors undistinguishable. It makes developers hard to develop a power consumption-considered application. If developers could get information for power consumption of context-aware application in detail, a development of power-considered context-aware applications would be possible. Consequently, this paper proposes a BMT(Bench Mark Test) model which is able to inform developers useful evaluation criteria and result about power consumption of smartphone's components and sensors with usage pattern considered.

• Journal of The Korean Association of Information Education
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• v.5 no.3
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• pp.389-400
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• 2001

The Internet Game is widespreaded quickly on web, and there are many kinds of funny games for users to use easily, so that can be applied to ICT(Information Communication Technology)education. In this paper, we provide the analysis on the usage of Internet games for children and teachers that is conducted by the decision tree algorithm, which is one of the popular data mining techniques. The results show the pattern of children's and teachers' usages of Internet games.

• Spatial Information Research
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• v.19 no.1
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• pp.61-72
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• 2011

Greenhouses gas emission due to usage of fossil fuel has been known as one of the main causes of global warming. Fundamentally, greenhouse gas is a by-product of economic activity. Since majority of economic activity happens in an urban setting, a countermeasure in an urban setting is needed. Therefore, an analysis of relationship between carbon dioxide emission and urban form will be investigated for urban planning and management in the future. The purpose of this study is to analyze the relationship between carbon dioxide emission and urban spatial patterns, and suggesting an urban form with low carbon dioxide emission. In order to achieve this, first theoretical analysis was carried out on urban spatial patterns related to physical size, usage rate, and activity level. Secondly, Seoul's dam on electricity, natural gas, local heating, petroleum, and water usage and mapping a carbon dioxide emission map. Thirdly, relationship between carbon dioxide emission and urban spatial patterns are analyzed and urban spatial patterns that affects energy usage in urban setting was elucidated, and elicited implications on future directions on urban planning based on our analyses above.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 1997.10a
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• pp.121-124
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• 1997

This paper is concerned with the generation and use of modular BOM, which is typically utilized in representing product configurations for two-level master production schedule. A method called VCM (Value Clustering Method) is proposed to build modular BOMS. We adopted a where-used matrix to represent part-product relationships. VCM is a method that can identify modules of components based on the where-used matrix. The method uses product family group value, product value, and component value. This can facilitate retrieving information about modules, finding out alternative usage pattern of components, and recognizing modules used in a particular product.

• Proceedings of the KIEE Conference
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• 2007.11c
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• pp.97-100
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• 2007

There are regulations on each building for its classification and It is corresponding determined contract demand. For transformer's capability calculation algorithm, cumulated power information of each customer is used to analysis the correlation between power usage and Demand Rate. By modeling this using Least Square Method, it can be targeted to recognize the pattern of transformer use in the past and make a prediction on it in the future.

• Proceedings of the IEEK Conference
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• 2008.06a
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• pp.257-258
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• 2008

본 글에서는 국내 와이브로와 HSDPA 가입자를 대상으로 시장조사를 수행하고 가입자를 대상 시장조사를 수행하고 가입자 특성과 이용특성, 가입이유와 유보이유, 만족도와 세부 서비스별 이용경험, 이용의향을 심층적으로 분석하고자 하였다. 이에 본 조사를 바탕으로 국내 모바일 브로드밴드 사업을 위한 시장 확산의 전략적 방향을 제언하고자 한다.