• Journal of Internet Computing and Services
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• v.24 no.2
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• pp.57-66
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• 2023

Currently, a new energy system is emerging that implements consumption reduction by improving energy efficiency. Accordingly, as smart grids spread, the rate system by timing is expanding. The rate system by timing is a rate system that applies different rates by season/hour to pay according to usage. In this study, external factors such as temperature/day/time/season are considered and the time series prediction model, LSTM, is used to predict energy power usage data. Based on this energy usage prediction model, energy usage charges are reduced by analyzing usage patterns for each device and transferring power energy from the maximum load time to the light load time. In order to analyze the usage pattern for each device, a clustering technique is used to learn and classify the usage pattern of the device by time. In summary, this study predicts usage and usage fees based on the user's power data usage, analyzes usage patterns by device, and provides customized demand transfer services based on analysis, resulting in cost reduction for users.

• Journal of Computing Science and Engineering
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• v.5 no.4
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• pp.338-345
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• 2011

Nowadays mobile devices are used for various applications such as making voice/video calls, browsing the Internet, listening to music etc. The average battery consumption of each of these activities and the length of time a user spends on each one determines the battery lifetime of a mobile device. Previous methods have provided predictions of battery lifetime using a static battery consumption rate that does not consider user characteristics. This paper proposes an approach to predict a mobile device's available battery lifetime based on usage patterns. Because every user has a different pattern of voice calls, data communication, and video call usage, we can use such usage patterns for personalized prediction of battery lifetime. Firstly, we define one or more states that affect battery consumption. Then, we record time-series log data related to battery consumption and the use time of each state. We calculate the average battery consumption rate for each state and determine the usage pattern based on the time-series data. Finally, we predict the available battery time based on the average battery consumption rate for each state and the usage pattern. We also present the experimental trials used to validate our approach in the real world.

• The Research Journal of the Costume Culture
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• v.28 no.6
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• pp.875-889
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• 2020

This study examined the effect of Instagram usage time (short, long) and spending on fashion products (light, heavy) on product attitude and purchase intention of products promoted by an influencer. The moderating effect of influencer type (mega, macro, micro) was also investigated. A total of 515 males and females in their 20s participated in an online survey. Descriptive statistics were analyzed and exploratory factor analysis and two-way ANOVA were conducted. Research findings were as follows. First, the usage time, both short and long, had a positive effect on product attitude. Also, the interactive effects of usage time and influencer type on product attitude were found. Consumers with short Instagram usage time displayed the highest attitude toward products promoted by a macro-influencer whereas consumers with long Instagram usage time displayed the highest attitude toward products promoted by a micro-influencer. Second, usage time and influencer type did not show interactive effects on purchase intention. Third, both categoriacl variables of users' spending on fashion products had a positive effect on product attitude. Fourth, the interaction effects of spending on fashion products and influencer types on purchase intention were found. The group of light buyers showed the highest purchase intention on products promoted by the macro-influencer while the group of heavy buyers showed the highest purchase intention of products promoted by the micro-influencer. Based on the results, implications were suggested.

• Journal of the Korea Safety Management & Science
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• v.15 no.2
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• pp.113-120
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• 2013

This study was conducted to investigate the characteristics of smartphone usage and posture of users during using smartphone. A survey was conducted for 983 smartphone users to understand the association between smartphone usage and including subjective symptoms associated with musculoskeletal disorders. Main results from the survey were as follows; 1) 18.8% of the subjects experienced musculoskeletal symptoms at least at one of body parts. Specifically, 8.1%, 5.6%, 4.1%, and 11.3% of the subjects experienced musculoskeletal symptoms at neck, shoulder, elbow, and hand respectively, 2) The symptoms of musculoskeletal disorders were also associated with amount of text message and time for daily usage of smartphone. Specifically, relative risks of musculoskeletal disorders at hand/wrist/fingers in terms of "amount of text message" and "time for daily usage" for experienced user were 1.425 and 1.368 respectively to inexperienced user. This study identified 'amount of text message' and 'time for daily usage' as the major risk factors of smartphone usage in terms of musculoskeletal symptoms. The results of the study provided a good basis in order to remove or reduce the risks associated with musculoskeletal symptoms due to smartphone usage.

• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• v.16 no.5
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• pp.385-389
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• 2003

There are four main components of the CMP process: polishing pad, slurry, elastic supporter, and pad conditioner. The polishing pad is an essential component to the reproducibility of polishing uniformity in CMP process. However, the polishing pad in recently using metal CMP raised the several points of high cost caused by the increase of cycle time and the many usage of slurry. It is necessary to develop the novel polishing pad which would lead the cost reduction by the higher pad life-cycle, minimized cycle time and lower slurry usage. The characteristics of polishing pad were studied on the effects of different sets of the Polishing pad, which can be applied to metal chemical mechanical polishing process for global planarization of multilevel interconnection structure. The main purpose of this experiment is cost reduction by the increase of pad life-time, the decrease of cycle time and the lower usage of slurry through the specific hard porous structured pad design. It is confirmed that the novel polishing pad made the slurry usage decrease to 60% as well as the pad life-time increase twice with the 25% improvement of removal rate. The polishing time could be decreased and it also helped the cycle time to diminish. It can be expected that this results will help both the process throughput and the device yield to be improved.

• Journal of the Korean Society of School Health
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• v.31 no.3
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• pp.135-145
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• 2018

Purpose: The study aimed to investigate the factors associated with long hours of smartphone usage and to identify the characteristics of the high-risk group among female middle school students in South Korea. Methods: The study analyzed the data of 13,648 female middle school students using their own smartphone extracted from the 13th Youth Health Behavior Online Survey (2017). The factors related to using smartphones for a long time was analyzed by binomial logistic regression. The characteristics of the high-risk group was defined by a decision tree analysis. Results: The average hours spent on smartphone usage was 269.54 minutes per day. The significant factors associated with the long hours of smartphone usage were grade, living with parents, perceived household economic status, perceived academic achievement, stress, sadness and hopelessness, the main purpose of smartphone usage, drinking, body mass index, breakfast, and satisfaction with sleep quality. The subjects showing low academic performance and having breakfast four times a week or less were more likely to use their smartphone for a long time. Conclusion: Based on the results of the research, we need to establish intervention strategies focusing on the factors influencing long-time usage of smartphone. Particularly, the subjects who show poor academic performance and skip breakfast frequently should be considered as the high-risk group for spending long hours on smartphone usage.

• The Journal of Korean society of community based occupational therapy
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• v.4 no.1
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• pp.11-21
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• 2014

Objective : This study was aimed to survey the correlation between time usage and hope in 20s and 30s the disabled. Methods : From November to December 2012, 52 the disabled who have therapy in rehabilitation hospital in Busan and Gyeongnam, being diagnosed with spinal cord injury and stroke, were chosen. Semi-structured interview was carried out using a questionnaire involved time usage and hope. Results : The followings are the results of this study. First, the participants spent most time sleeping (10:47) and using media (3:41) on weekends. In additions, they spent most time sleeping (9:43) and health management (5:12) on weekdays. Second, doing household chores were positive correlation (.688) between time usage and hope (p<.05). However, no significant differences in time usage and hope. Conclusion : The results of this study would contribute to propose various activities for 20s and 30s the disabled.

• The Journal of the Convergence on Culture Technology
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• v.8 no.6
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• pp.23-30
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• 2022

This study is an exploratory study to examine the relation between parents and children's smartphone usage time. The data from the 11th Korea Media Panel Survey conducted by the Korea Information Society Development Institute was used for empirical analysis. The findings revealed that parents' smartphone usage time and children's smartphone usage time are positively correlated, indicating that their smartphone use patterns share similarities as members of a family system. This study lays the foundation for future work to explain individual media use through family and media use environment.

• Journal of the military operations research society of Korea
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• v.17 no.2
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• pp.100-112
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• 1991

Software system is a hierarchical structure with collection of program units. Software system can import external packages globally or locally depending on the usage within a system. If the imported package is used globally, the soft-ware system can be influenced globally by any change of package and programmer's debugging time for the program maintenance will be greater. To solve these problems, it is desirable to use the imported package locally right on the usage point within the system. The model presented in this paper analyzed entity usage of package in structure of program, identified the usage level to obtain localization and provided information for restructure of the program to localize package usage. To obtain localization, it identified declared entities inside the imported package and analyzed the specification and body part of program unit to identify entities referenced from the imported package. The proposed model can be used to improve the maintainability of software system and contributed to reduction of programmer's debugging time in program maintenance.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.26 no.6D
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• pp.909-916
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• 2006

This study investigates tourists' sightseeing excursion behaviors and their information usage patterns at Fuji five lakes Area. This paper aims to empirically analyze the relationship between a sightseeing excursion behavior and use of tourist information applying a cluster analysis and a quantitative regression model. The main results are summarized as follows: (1) Tourists' information need is high about 90% of all tourists get information, 80% get the information before travel, 70% on the journey, 60% at the same time. (2) The patterns of information usage are categorized into 3 groups by the timing when tourists try to get the information.(3) There exists a difference among the time-spatial characteristics of excursion's behaviors such as the time after arriving time at sightseeing area, the time till go to home, duration time, and the total travel time between spots, the number of spots, and the size of excursion scale. (4) The quantitative regression model shows that information usage which constrained by time and space significantly determines both the number of the sightseeing spots and the duration time.