• Journal of IKEEE
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• v.25 no.2
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• pp.388-398
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• 2021

This paper proposes a particle swarm optimization (PSO)-based peak shaving scheme using energy storage system (ESS) for electricity tariff reduction. The proposed scheme compares the actual load with the estimated load consumption, calculates the additional output power that the ESS needs to discharge additionally to reduce peak load, and adds the input. In addition, in order to compensate for the additional power, the process of allocating power to the determined point is performed, and an optimization that minimizes the average of the load expected at the active power allocations using PSO so that the allocated value does not affect the peak load. To investigated the performance of the proposed scheme, case study of small and large load prediction errors was conducted by reflecting actual load data and load prediction algorithm. As a result, when the proposed scheme is performed with the ESS charge and discharge control to reduce electricity tariff, even when the load prediction error is large, the peak load is successfully reduced, and the peak load reduction effect of 17.8% and electricity tariff reduction effect of 6.02% is shown.

• Journal of Korea Port Economic Association
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• v.38 no.1
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• pp.113-127
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• 2022

The purpose of this study is to analyze the efficiency of 90 domestic passenger shipping routes using the DEA Window model as a Decision Making Unit (DMU). Data from 2015 to 2019 are divided into three windows, and efficiency was analyzed by using the number of passenger ships of sails, gross tonnage and distance traveled as input variables and transportation performance of the general public and islanders as output variables. As a result of the analysis, improvements are derived and presented for routes with low relative efficiency. In particular, the efficiency is evaluated for general routes operated by private operators as profit routes and auxiliary routes supported by the government as non-profit routes. In addition, scale efficiency (SE) is derived by using the technical efficiency (TE) of the CCR model and the pure technical efficiency (PTE) values of the BCC model. It is found that the inefficiency of the route was due to pure technical efficiency (PTE) rather than scale efficiency (SE). It will be necessary to consider the improvements for each route shown in the analysis results of this study when establishing the policy for the domestic passenger shipping route.

• Journal of Korea Water Resources Association
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• v.55 no.2
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• pp.121-133
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• 2022

The drought resulting from insufficient rainfall compared to the amount in an ordinary year can significantly impact a broad area at the same time. Another feature of this disaster is hard to recognize its onset and disappearance. Therefore, a reliable and fast way of predicting both the suffering area and the amount of water shortage from the upcoming drought is a key issue to develop a countermeasure of the disaster. However, the available drought scenarios are about 50 events that have been observed in the past. Due to the limited number of events, it is difficult to predict the water shortage in a case where the pattern of a natural disaster is different from the one in the past. To overcome the limitation, in this study, we applied the four RCP climate change scenarios to the water balance model and the annual amount of water shortage from 360 drought events was estimated. In the following chapter, the deep neural network model was trained with the SPEI values from the RCP scenarios and the amount of water shortage as the input and output, respectively. The trained model in each sub-basin enables us to easily and reliably predict the water shortage with the SPEI values in the past and the predicted meteorological conditions in the upcoming season. It can be helpful for decision-makers to respond to future droughts before their onset.

• The Journal of the Acoustical Society of Korea
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• v.41 no.6
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• pp.610-620
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• 2022

An acoustic vector sensor can simultaneously receive vector quantities, such as particle velocity and acceleration, as well as acoustic pressure at one location, and thus it can be used as a single input multiple output receiver in underwater acoustic communication systems. On the other hand, vector signals received by a single vector sensor have different channel characteristics due to the azimuth angle between the source and receiver and the difference in propagation angle of multipath in each component, producing different communication performances. In this paper, we propose a channel parameter-based weighting method to improve the performance of an acoustic communication system using a single vector sensor. To verify the proposed method, we used communication data collected from the experiment conducted during the KOREX-17 (Korea Reverberation Experiment). For communication demodulation, block-based time reversal technique which is robust against time-varying channels were utilized. Finally, the communication results showed that the effectiveness of the channel parameter-based weighting method for the underwater communication system using a single vector sensor was verified.

• Korea Trade Review
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• v.43 no.5
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• pp.25-45
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• 2018

This paper estimates the export losses of the Korean domestic automobile industry due to US trade pressure and its economic ripple effects. Using the HS 6 digit tariff and export data from 2010 to 2017, this paper estimates the tariff elasticity of Korea's US automobile exports against a US tariff increase by applying the Poisson Pseudo maximum likelihood estimation method. After estimating Korea's export losses to the US in three trade pressure scenarios, we estimate its impact on Korean domestic production, value-added and job creation by applying the tariff impact accumulation model based on the industry input-output analysis. Empirical results show that the impact of 25% global tariff by the US on the Korean domestic economy is estimated to result in $30.8 billion in export losses for the five years from 2019 to 2023, about 300 thousand job losses, 88.0 trillion in production inducement losses, and 24.0 trillion in value-added inducement losses. The impacts of withdrawal of the automobile tariff concession are estimated at $4.27 billion export losses and 41.7 thousand job losses. A 15% tariff rate on automobile parts for 3 years is estimated to result in $1.93 billion export losses and 18.7 thousand job losses.

• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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• v.6 no.5
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• pp.367-377
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• 2016

The purpose of the projects for strengthening the Service Business Competitiveness, which had been sponsored by the Ministry of Trade, Industry and Energy, and managed by the NIPA, is to support for combining the whole business process of the SMEs with the business model considering the scientific aspects of the services, to enhance the productivity of them and to add the values of their activities. 5 organizations are selected in 2014, and 4 in 2015 as leading organizations for these projects. This study analyzed the efficiency of these projects using DEA. Throughout the analysis of the prior researches, this study used the amount of government-sponsored money as the input variable, and the number of new customer business, the sales revenue, and the number of new employment as the output variables. And the result of this analysis showed that the decision making unit 12, 15, and 21 was efficient. And from this study, we found out two more performance indicators such as, the number of new employment and the amount of sales revenue, besides the number of new customer businesses.

• The Journal of the Convergence on Culture Technology
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• v.9 no.4
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• pp.487-494
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• 2023

In this study, performance comparison was performed on R and TensorFlow, which are free deep learning tools. In the experiment, six types of deep neural networks were built using each tool, and the neural networks were trained using the 10-year Korean temperature dataset. The number of nodes in the input layer of the constructed neural network was set to 10, the number of output layers was set to 5, and the hidden layer was set to 5, 10, and 20 to conduct experiments. The dataset includes 3600 temperature data collected from Gangnam-gu, Seoul from March 1, 2013 to March 29, 2023. For performance comparison, the future temperature was predicted for 5 days using the trained neural network, and the root mean square error (RMSE) value was measured using the predicted value and the actual value. Experiment results shows that when there was one hidden layer, the learning error of R was 0.04731176, and TensorFlow was measured at 0.06677193, and when there were two hidden layers, R was measured at 0.04782134 and TensorFlow was measured at 0.05799060. Overall, R was measured to have better performance. We tried to solve the difficulties in tool selection by providing quantitative performance information on the two tools to users who are new to machine learning.

• Journal of the Korea Society of Computer and Information
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• v.28 no.10
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• pp.247-256
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• 2023

This study was conducted with the purpose of suggesting alternatives for the efficient operation of senior day care facilities in 22 cities and counties in the Jeonnam region by analyzing the efficiency of senior day care facilities. The analysis data for the study used the National Health Insurance Corporation's long-term care insurance for the elderly (2022), the Input variables were the number of facilities, the number of workers, the number of affordable, and the number of senior long-term care insurance recipients and the Output variables were the the number of users. As a result of the analysis, CCR was most efficient in Goheung-gun, Gokseong-gun, Gwangyang-si, Boseong-gun, Yeongam-gun, and Jindo-gun, BCC was most efficient in Goheung-gun, Gokseong-gun, Gwangyang-si, Gurye-gun, Damyang-gun, Boseong-gun, and Jindo-gun, and SE was most efficient in that order: Jindo-gun, Gokseong-gun, and Gwangyang-si. It turned out to be a super efficient area. In the contribution analysis, the number of affordable and workers variables were found to be variables that had a large impact on efficiency contribution. In the improvement potential analysis, the number of facilities variable was found to be a variable that had a significant impact on efficiency. Therefore, for the efficient operation of senior day care facilities, we suggest adjusting supply and demand, such as the number of facilities and affordable, and suggest that training programs to strengthen the expertise of workers who contribute greatly are required.

• Journal of Internet of Things and Convergence
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• v.9 no.6
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• pp.23-28
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• 2023

Windows operating system generates various logs with timestamps. Timestamp tampering is an act of anti-forensics in which a suspect manipulates the timestamps of data related to a crime to conceal traces, making it difficult for analysts to reconstruct the situation of the incident. This can delay investigations or lead to the failure of obtaining crucial digital evidence. Therefore, various techniques have been developed to detect timestamp tampering. However, there is a limitation in detection if a suspect is aware of timestamp patterns and manipulates timestamps skillfully or alters system artifacts used in timestamp tampering detection. In this paper, a method is designed to detect changes in timestamps, even if a suspect alters the timestamp of a file on a storage device, it is challenging to do so with precision beyond millisecond order. In the proposed detection method, the first step involves verifying the timestamp of a file suspected of tampering to determine its write time. Subsequently, the confirmed time is compared with the file size recorded within that time, taking into consideration the performance of the storage device. Finally, the total capacity of files written at a specific time is calculated, and this is compared with the maximum input and output performance of the storage device to detect any potential file tampering.

• Industry Promotion Research
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• v.8 no.4
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• pp.267-276
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• 2023

Based on the tourism input-output data of five provinces and cities in China's Bohai Rim region from 2015~2021, this study analyzes the efficiency of regional tourism using DEA-BCC and DEA-Malmquist index, as well as its contribution to regional economic efficiency, and identifies factors influencing the comprehensive efficiency. The research results indicate that the comprehensive efficiency of the tourism industry in the China Bohai Sea region has reached an optimal level of 88.9%, but there is still room for improvement, with overall fluctuations. The overall productivity of the tourism industry exhibits a "U"-shaped fluctuating pattern, with growth mainly driven by technological advancements. Due to the impact of the COVID-19 pandemic, the region experienced a nearly 50% decrease in total factor productivity in 2019~2020. However, in 2021, with the implementation of various government stimulus policies, the tourism efficiency rapidly recovered to 80% of pre-pandemic levels. In terms of the impact of the tourism industry on the regional economy in the China Bohai Sea region, Hebei Province stands out as a significant contributor. Based on the aforementioned research findings, the following recommendations are proposed in three aspects: optimizing the supply structure, increasing innovation investment, and strengthening internal collaboration. These recommendations provide valuable insights for enhancing regional tourism efficiency and promoting regional synergy.