• Journal of Advanced Technology Convergence
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• v.2 no.4
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• pp.43-48
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• 2023

Globally, there is a collaborative effort to achieve global carbon neutrality in response to climate change. In the case of South Korea, greenhouse gas emissions are rapidly increasing, presenting an urgent situation that requires resolution. In this context, this study developed a thermal energy collection device named a 'steam trap' and created an AI model capable of predicting future electricity usage by collecting energy usage data through steam traps. The average accuracy of electricity usage prediction with this AI model was 96.7%, demonstrating high precision. Consequently, the AI model enables the prediction and management of days with high electricity consumption and identifies which facilities contribute to elevated power usage. Future research aims to optimize energy consumption efficiency through efficient equipment operation using anomaly detection in steam traps and standardizing energy management systems, with the ultimate goal of reducing greenhouse gas emissions.

• Journal of Korea Society of Digital Industry and Information Management
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• v.11 no.3
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• pp.159-177
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• 2015

As smart phones become more common nowadays, mobile instant messengers such as kakao talk and line are used as essential communication tools exchanging information between individuals. Also, the mobile instant messengers extend their use to business area beyond communication between individuals. This study is on how factors of mobile instant messenger such as perceived security, perceived privacy, perceived enjoyment and perceived interactivity affect business continual usage intention through perceived usefulness. The proposed model is based on Expectation-Confirmation Theory of Oliver and Technology Acceptance Mode of Bhattacherjee. For an analysis, 159 survey responses were collected from the office workers in Seoul and nearby cities, having experiences of mobile instant messengers. To validate the proposed research model, PLS analysis is performed with the valid 154 questionnaires. The path analysis results are as follows. First, perceived security has a positive effect on expectation-confirmation. Second, perceived enjoyment has a positive effect on perceived usefulness. Third, perceived interactivity has a positive effect on both perceived usefulness and expectation-confirmation. Fourth, perceived usefulness has a positive usefulness on satisfaction and continual usage intention of mobile instant messenger. Last, expectation-confirmation has a positive effect on perceived usefulness, and satisfaction has a positive effect on continual usage intention of mobile instant messenger. Since the mobile instant messenger may bring a pressure of work and a violation of privacy, it is necessary that the company provide a guideline for use of the mobile instant messenger and establish the in-house mobile instant messenger system.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.20 no.1
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• pp.40-53
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• 2021

Recently, shared dockless e-scooter usage has rapidly increased, rather than the station-based shared mobility service, because of convenience. This transition leads to new social problems in urban areas such as increased traffic accidents and hindrance of pedestrian environments. In this study, we analyze the usage characteristics of shared e-scooters in Seoul, and identify factors influencing demand for shared e-scooters by developing a negative binomial regression model. As a result, the usage characteristics show that the average trip distance, the average trip duration, and the average trip speed were 1.5km, 9.4min, and 10.3km/h, respectively. Demographic factor, transport facility factors, land use factors, and weather factors have statistically significant impacts on demand for shared e-scooters. The results of this study will be used as basic data for suggesting effective operation strategies for areas with higher shared e-scooter demand and for establishing transport policies for facilitating shared e-scooter usage.

• Journal of Biomedical Engineering Research
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• v.44 no.2
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• pp.147-156
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• 2023

Efforts to employ smart home sensors to monitor the indoor activities of elderly single residents have been made to assess the feasibility of a safe and healthy lifestyle. However, the bathroom remains an area of blind spot. In this study, we have developed and evaluated a new edge computer device that can automatically detect water usage activities in the bathroom and record the activity log on a cloud server. Three kinds of sound as flushing, showering, and washing using wash basin generated during water usage were recorded and cut into 1-second scenes. These sound clips were then converted into a 2-dimensional image using MEL-spectrogram. Sound data augmentation techniques were adopted to obtain better learning effect from smaller number of data sets. These techniques, some of which are applied in time domain and others in frequency domain, increased the number of training data set by 30 times. A deep learning model, called CRNN, combining Convolutional Neural Network and Recurrent Neural Network was employed. The edge device was implemented using Raspberry Pi 4 and was equipped with a condenser microphone and amplifier to run the pre-trained model in real-time. The detected activities were recorded as text-based activity logs on a Firebase server. Performance was evaluated in two bathrooms for the three water usage activities, resulting in an accuracy of 96.1% and 88.2%, and F1 Score of 96.1% and 87.8%, respectively. Most of the classification errors were observed in the water sound from washing. In conclusion, this system demonstrates the potential for use in recording the activities as a lifelog of elderly single residents to a cloud server over the long-term.

• 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.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.158-163
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• 2005

Competitive electricity markets necessitate equitable methods for allocating transmission usage in order to set transmission usage charges and congestion charges in an unbiased and an open-accessed basis. So in competitive markets it is usually necessary to trace the contribution of each participant to line usage, congestion charges and transmission losses, and then to calculate charges based on these contributions. A UPFC offers flexible power system control, and has the powerful advantage of providing, simultaneously and independently, real-time control of voltage, impedance and phase angle, which are the basic power system parameters on which sys-tem performance depends. Therefore, UPFC can be used efficiently and flexibly to optimize line utilization and increase system capability and to enhance transmission stability and dampen system oscillations. In this paper, a mathematical approach to allocate the contributions of system users and UPFCs to transmission system usage is presented. The paper uses a dc-based load flow modeling of UPFC-inserted transmission lines in which the injection model of the UPFC is used. The relationships presented in the paper showed modified distribution factors that modeled impact of utilizing UPFCs on line flows and system usage. The derived relationships show how bus voltage angles are attributed to each of changes in generation, injections of UPFC, and changes in admittance matrix caused by inserting UPFCs in lines. The relationships derived are applied to two test systems. The results illustrate how transmission usage would be affected when UPFC is utilized. The relationships derived can be adopted for the purpose of allocating usage and payments to users of transmission network and owners of UPFCs used in the network. The relationships can be modified or extended for other control devices.

• International Journal of Reliability and Applications
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• v.5 no.4
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• pp.147-154
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• 2004

This work developed and algorithm for a set covering model when the reliability of covers is a concern. This model extended the usage of the set covering model.

• Journal of Korean Institute of Industrial Engineers
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• v.17 no.1
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• pp.83-94
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• 1991

This study is concerned with the scheduling problem for mixed-model assembly lines in Just-In-Time(JIT) production systems. The most important goal of the scheduling for the mixed-model assembly line in JIT production systems is to keep a constant rate of usage for every part used by the systems. In this study, we develop two heuristic algorithms able to keep a constant rate of usage for every part used by the systems in the single-level and the multi-level. In the single-level, the new algorithm generates sequence schedule by backward tracking and prevents the destruction of sequence schedule which is the weakest point of Miltenburg's algorithms. The new algorithm gives better results in total variations than the Miltenburg's algorithms. In the multi-level, the new algorithm extends the concept of the single-level algorithm and shows more efficient results in total variations than Miltenburg and Sinnamon's algorithms.

• Asia pacific journal of information systems
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• v.15 no.1
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• pp.1-24
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• 2005

The purpose of this study is to identify the factors affecting the performance of knowledge management systems. To extend DeLone & MeLean's model, we included the user specialization in the information systems success model. The questionnaires are collected from 109 knowledge management system users. The major findings are summarized as followed. First, system characteristics such as ease of use, response time, and knowledge management process support affect the knowledge management systems usage. Second, knowledge characteristics such as relevancy, completeness, reliability, importance, and currency also affect the knowledge management systems usage. Third, the end-users are satisfied with the knowledge management systems because it is easy to use and relevant.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.35 no.3
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• pp.70-76
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• 2012

This research tested how the perceived risk and the trust affect the usage intention of the cloud computing. To this end, this research setups a research model and tests it with the statistic tools. In order to build the model, TAM (Technology Acceptance Model) and UTAUT (Unified Theory of Acceptance and Use of Technology) were employed and, the factors such as the perceived risk, the trust and the intention of the cloud computing use were derived. This research finds that the perceived risk does not affect the intention of usage. Also the perceived risk has the negative effect for the trust. Thus this research has the following suggestions.