• Journal of the Korean housing association
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• v.22 no.4
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• pp.33-41
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• 2011

The purpose of this study was to identify characteristics of space usage patterns by types of elderly households(single or couple). For the study, 74 elders who were older than 65 were selected and their living behaviors at their home during a day (24 hours) were analyzed. Respondents were classified into 6 types based on a combination of their household type, income level and health status. The results showed that the elderly residents tended to live a well-regulated life, however, each type had unique time and space use pattern. For example, the more the elder residents were healthy, the more they used many rooms. Frail elderly residents spent most of the day in their bedroom. Also, if they had a spouse, each one tended to use a separate private room for his or her daily life whether they shared a bedroom or not.

• Journal of Korea Multimedia Society
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• v.20 no.2
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• pp.404-419
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• 2017

This study is to examine how middle and high school students vary in terms of good and bad usage of online games and how these factors have varying effects on their use of the internet as a whole. My focus is to study their behavioral patterns individually while playing internet-based online games. The results are as follows: First, 260 out of 390 subjects used the internet. Male students who are high school students with siblings, or preschool time game users were revealed to play online games more often rather than female students who are middle school students with no siblings, or non-preschool time game users. Secondly, the analysis of differences of good and bad usage of online games revealed that there is a significant correlation between gender and beginning age. Lastly, a thorough analysis of the average difference in terms of following the online game shutdown found that there is no significant correlation among the sub-groups. However, an analysis of the difference of the problematic game usage has shown that there is a significant difference in the heavy user group. This findings means that the students who don't follow the online game shutdown spend more time than those who do.

• Journal of Information Processing Systems
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• v.12 no.3
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• pp.436-454
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• 2016

This research presents the battery discharge rate models for the energy consumption of mobile phone batteries based on machine learning by taking into account three usage patterns of the phone: the standby state, video playing, and web browsing. We present the experimental design methodology for collecting data, preprocessing, model construction, and parameter selections. The data is collected based on the HTC One X hardware platform. We considered various setting factors, such as Bluetooth, brightness, 3G, GPS, Wi-Fi, and Sync. The battery levels for each possible state vector were measured, and then we constructed the battery prediction model using different regression functions based on the collected data. The accuracy of the constructed models using the multi-layer perceptron (MLP) and the support vector machine (SVM) were compared using varying kernel functions. Various parameters for MLP and SVM were considered. The measurement of prediction efficiency was done by the mean absolute error (MAE) and the root mean squared error (RMSE). The experiments showed that the MLP with linear regression performs well overall, while the SVM with the polynomial kernel function based on the linear regression gives a low MAE and RMSE. As a result, we were able to demonstrate how to apply the derived model to predict the remaining battery charge.

• Journal of the Korean School Mathematics Society
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• v.16 no.4
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• pp.797-820
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• 2013

This study intended on analyzing the error patterns of mathematic problem posing sentences by the 100 elementary pre-teachers and discussing about the solutions. The results showed that the problem posing sentences have five error patterns: phonological error patterns, word error patterns, sentence error patterns, meaning error patterns, and notation error patterns. Divided into fourteen specific error patterns, they are as in the following. 1) Phonological error patterns are consisted of the 'ㄹ' addition error pattern and the abbreviated word error pattern. 2) Words error patterns are divided with the inappropriate usage of word error pattern and the inadequate abbreviation error pattern, which are formulized four subgroups such as the case maker, ending of the word, inappropriate usage of word, and inadequate abbreviation of article or word error pattern in detail. 3) Sentence error patterns are assumed four kinds of forms: the reference, ellipsis of sentence component, word order, and incomplete sentence error pattern. 4) Meaning error patterns are composed the logical contradiction and the ambiguous meaning. 5) Notation error patterns are formed four patterns as the spacing, punctuation, orthography of Hangul, and spelling rules of foreign words in Korean. Furthermore, the solutions for these error patterns were discussed: First, it has to be perceived the differences between spoken and written language. Second, it has to be rejected the spoken expressions in written contexts. Third, it should be focused on the learning of the basic sentence patterns during the class. Forth, it is suggested that the word meaning should have the logical development perception based on what it means. Finally, it is proposed that the system of spelling of Korean has to be learned. In addition to these suggestions, a new understanding is necessary regarding writing education for college students.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.67 no.11
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• pp.1536-1541
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• 2018

For effective electricity consumption in urban railway station such as peak load shaving, it is important to know each electrical load pattern by various usage. The total electricity consumption in the urban railway substation is already measured in Korea, but the electricity consumption for each usage is not measured. The author proposed the deep learning method to estimate the electrical load pattern for each usage in the urban railway substation with public data such as weather data. GRU (gated recurrent unit), a variation on the LSTM (long short-term memory), was used, which aims to solve the vanishing gradient problem of standard a RNN (recursive neural networks). The optimal model was found and the estimation results with that were assessed.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.28 no.10
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• pp.69-74
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• 2014

With the increasing interest of energy efficiency, several buildings and factories begin to monitor energy usages with a built-in energy management system. However, the built-in energy monitoring system does not reflect the dynamics of buildings and factories energy usage. To overcome the latter, we deploy several sensors to monitor the dynamics of buildings energy usage patterns. In this paper, we are proposing a framework of a sensor based energy monitoring system. Based on our limited experiments, we can monitor power usages by a person, device and time period. As a result, we can plan a better energy usage and improve energy efficiency by the monitored energy usage profile data.

• Journal of Information Technology Applications and Management
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• v.9 no.1
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• pp.27-44
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• 2002

Performance evaluations of database algorithms are usually conducted on a set of queries for a given test database. For more detailed evaluation results, it is often necessary to use different query workloads several times. Each query workload should reflect the querying patterns of the application domain in real world, which are non-uniform in the usage frequencies of attributes in queries of the workload for a given database. It is not trivial to generate many different query workloads manually, while considering non-uniform distributions of attributes'usage frequencies. In this paper we propose a technique to generate non-uniform distributions, which will help construct query workloads more efficiently. The proposed algorithm generates a query-attribute usage distribution based on given constraints on usage frequencies of attributes and qreries. The algorithm first allocates as many attributes to queries as Possible. Then it corrects the distribution by considering attributes and queries which are not within the given frequency constraints. We have implemented and tested the performance of the proposed algorithm, and found that the algorithm works well for various input constraints. The result of this work could be extended to help automatically generate SQL queries for various database performance benchmarking.

• 한국벤처창업학회:학술대회논문집
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• 2017.04a
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• pp.51-51
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• 2017

In the domain of IS, game was used as a tool to enhance the results of decision making, education and more. In another stream of research, researchers focused on revealing the motive of people playing games. This study focuses on the effect of the tool; increased accessibility via mobile, to online game using patterns and behaviors. Due human reaction towards competition, technology acceptance and the online game's gambling traits, it is expected that the increased mobile accessibility (tool) will increase and intensify the game playing behavior. Also, it is expected that the in-game purchase will increase as well. In depth interview with both game service providers and players is planned to confirm that the mobile version acted as a tool to increase accessibility, rather than a additional game. Survey along with an interview is to be conducted to find relevant play and spending patterns if they are to exist.

• Journal of information and communication convergence engineering
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• v.14 no.1
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• pp.9-13
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• 2016

With the introduction of the data-oriented plan for LTE service, one may concerned with the background of the ISP's policy in charging for LTE services. In this work we investigate the latest usage patterns of voice and data applications for customers over the current mobile network, via which we investigate why mobile operators introduced data-oriented plans. To be specific, we collected the real-field data for the volume of voice and data traffic from the LTE network before the data-oriented plans were introduced. From the collected data we compute the absolute volume as well as the proportion of voice and data applications. From these observations we infer mobile operators' reasoning behind the decision to introduce data-oriented plans with unlimited voice calls over the mobile network.

• Journal of the Korean Society of Clothing and Textiles
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• v.21 no.1
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• pp.67-81
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• 1997

The main purpose of this study was to compare the characteristics of male innovators and of male opinion leaders across product categories in terms of personality, attitudes, social participation, media usage patterns and demographic aspects. Six product categories such as clothing, cosmetics, small electronic appliances, medium-large electronic appliances, interior supplies and sports-leisure goods was used. A valid and reliable self-report scale was used to measure innovativeness and opinion leadership for 423 male adults living in social area Analyses showed that venturesomeness is the most common characteristics between innovators and opinion leaders across product categories. Innovators showed higher tendency of narcissism while opinion leadership showed higher cosmopolitainsm. Common charateristics of innovators and of opininion leaders of both clothing and cosmetics are cosmopolitanism, narcissism, exhibitionism, venturesomeness. The degrees of social participation and media usage patterns were different according to product categories for both innovators and opinion leaders. The implications of these findings for diffusion theory and merchandising were discussed.