• Asia-Pacific Journal of Business
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• v.11 no.2
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• pp.61-79
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• 2020

Purpose - This article empirically investigated the effects of the socio-political factor of censorship preconditioning, and organizational support, mediating performance expectancy of public sector officials' behavioural intention to utilise social media in a post-communist country, Mongolia. Design/methodology/approach - This study collected 212 survey data from public sector organisations in Mongolia. Using the Partial Least Squire (PLS) method, this study analyzed the proposal model grounded on the UTAUT model. Findings - There are still communist footprints in the form of censorship, which remained as a negative precondition factor, and this has an indirect negative influence, and organisational support mediates to enhance performance expectancy. Effort expectancy and social influence factors have direct positive influence on the use of social media systems in the government domain of Mongolia Research implications or Originality - This study empirically investigated the model of public employees' intention to examine the post-communist countries' cultural, social, economic, and political systems, government organisational environment of the former communist sphere. The cultural factors, censorship and organisational support, to the existing IT adoption UTAUT model were also identified to test the situation of a post-communist country, Mongolia. This study contributes to the new theoretical involvement with social media by testing a new social media-based third-party intercommunication channel, including intent to use in the public service for post-communist countries. This study practically provides the guidelines to promote social media usage for public sector in the post-communist situation.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.8
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• pp.1088-1094
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• 2021

This paper proposes a partial BMA (Broadcasting Multiple Access) network structure and D-ARP (Distributed Address Resolution Protocol) method in order to support full mesh routing function in the DAMA (Demand Assigned Multiple Access)-based MF-TDMA (Multi Frequency-Time Division Multiple Access) satellite system. The partial BMA network enables legacy router devices and routing protocols to be adopted in the satellite communication system, and decreases the amount of routing protocol overhead. In addition, we introduce the D-ARP method that help a spoke satellite node acquiring the MAC (Media Access Control) address from remote satellite nodes in none BMA satellite network. The D-ARP method provides the MAC address of remote nodes to each other nodes through the broadcasting-enabled satellite channel. And we lastly evaluate and analysis the network performance of the proposed approach.

• The Journal of Information Systems
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• v.31 no.1
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• pp.147-173
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• 2022

Purpose As the use of social network services has become common, it has become possible to freely communicate and establish relationships with other people anytime, anywhere for communication and information sharing. Influencers who have a strong influence on consumers' perceptions and attitudes through their own opinions and stories have appeared on various social media channels such as YouTube. Recently, companies utilize influencers with a large number of followers to check interactions with customers to understand customer attitudes and opinions about products in real time. Start-ups with insufficient resources need to quickly examine customer responses to reduce the probability of failure after product planning. The Lean process of creating an MVP and quickly confirming and learning the market response should be repeated over and over again. Findings In this paper, we try to suggest that the YouTube platform can play a sufficient role as a customer experiment space through examples. The case company is a company that has successfully commercialized products by continuously interacting with customers through the YouTube platform for the first four months of its founding. This paper is expected to be helpful in the experimental process for prospective founders and early founders to examine customer responses to reduce the probability of market failure before commercialization. Design/methodology/approach This paper analyzed the YouTube channel data of case companies based on the netnography methodology and presented the contents of the lean process management carried out in the experimental stage and the post-production stage through interview research.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.9
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• pp.3172-3193
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• 2022

Cognitive radio-simultaneous wireless information and power transfer (CR-SWIPT) has attracted much interest since it can improve both the spectrum and energy efficiency of wireless networks. This paper focuses on the resource sharing between a point-to-point primary system (PRS) and a multiuser multi-antenna cellular cognitive radio system (CRS) containing a large number of cognitive users (CUs). The resource sharing optimization problem is formulated by jointly scheduling CUs and adjusting the transmit power at the cognitive base station (CBS). The effect of accessing CUs' spatial channel correlation on the possible transmit power of the CBS is investigated. Accordingly, we provide a low-complexity suboptimal approach termed the semi-correlated semi-orthogonal user selection (SC-SOUS) algorithm to enhance the spectrum efficiency. In the proposed algorithm, CUs that are highly correlated to the information decoding primary receiver (IPR) and mutually near orthogonal are selected for simultaneous transmission to reduce the interference to the IPR and increase the sum rate of the CRS. We further develop a spatial correlation-based resource sharing (SC-RS) strategy to improve energy sharing performance. CUs nearly orthogonal to the energy harvesting primary receiver (EPR) are chosen as candidates for user selection. Therefore, the EPR can harvest more energy from the CBS so that the energy utilization of the network can improve. Besides, zero-forcing precoding and power control are adopted to eliminate interference within the CRS and meet the transmit power constraints. Simulation results and analysis show that, compared with the existing CU selection methods, the proposed low-complex strategy can enhance both the achievable sum rate of the CRS and the energy sharing capability of the network.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.11
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• pp.3950-3969
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• 2021

Radio Frequency (RF)-based indoor localization technologies play significant roles in various Internet of Things (IoT) services (e.g., location-based service). Most such technologies require that all the devices comply with a specified technology (e.g., WiFi, ZigBee, and Bluetooth). However, this requirement limits its application scenarios in today's IoT context where multiple devices complied with different standards coexist in a shared environment. To bridge the gap, in this paper, we propose a cross-technology localization approach, which is able to localize target nodes using a different type of devices. Specifically, the proposed framework reuses the existing WiFi infrastructure without introducing additional cost to localize Non-WiFi device (i.e., ZigBee). The key idea is to leverage the interference between devices that share the same operating frequency (e.g., 2.4GHz). Such interference exhibits unique patterns that depend on the target device's location, thus it can be leveraged for cross-technology localization. The proposed framework uses Principal Components Analysis (PCA) to extract salient features of the received WiFi signals, and leverages Dynamic Time Warping (DTW), Gradient Boosting Regression Tree (GBRT) to improve the robustness of our system. We conduct experiments in real scenario and investigate the impact of different factors. Experimental results show that the average localization accuracy of our prototype can reach 1.54m, which demonstrates a promising direction of building cross-technology technologies to fulfill the needs of modern IoT context.

• Journal of The Korean Society of Agricultural Engineers
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• v.64 no.3
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• pp.63-73
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• 2022

A more accurate understanding of the irrigation water supply is necessary for efficient agricultural water management. Although we measure water levels in an irrigation canal using ultrasonic water level gauges, some errors occur due to malfunctions or the surrounding environment. This study aims to apply CNN (Convolutional Neural Network) Deep-learning-based image classification and segmentation models to the irrigation canal's CCTV (Closed-Circuit Television) images. The CCTV images were acquired from the irrigation canal of the agricultural reservoir in Cheorwon-gun, Gangwon-do. We used the ResNet-50 model for the image classification model and the U-Net model for the image segmentation model. Using the Natural Breaks algorithm, we divided water level data into 2, 4, and 8 groups for image classification models. The classification models of 2, 4, and 8 groups showed the accuracy of 1.000, 0.987, and 0.634, respectively. The image segmentation model showed a Dice score of 0.998 and predicted water levels showed R² of 0.97 and MAE (Mean Absolute Error) of 0.02 m. The image classification models can be applied to the automatic gate-controller at four divisions of water levels. Also, the image segmentation model results can be applied to the alternative measurement for ultrasonic water gauges. We expect that the results of this study can provide a more scientific and efficient approach for agricultural water management.

• Journal of Korean Port Research
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• v.10 no.1
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• pp.1-14
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• 1996

Rapid change in the technological environment of marine transportation and the development of the ocean shipping industry have fostered a revolution in the port system. This in turn has caused major changes in the function and use of port in Korea. Aside from this, Mokpo Port, however continues to decline, because the existing port facilities and related subsystem are already obsolete with no chance of regaining operational effectiveness and treatment for proper implementation. Although a few studies have been done on the Mokpo Port, has not been found, any reseach for the analytical approach to the transportation system of it. This paper aims to make an extensive analysis of the physical distribution system in Mokpo Port focusing on the coordination of subsystems such as navigational aids system. The base of introduced simulation tool here is the queueing theory. The overall findings are as follows: 1. Among those vessels called at Mokpo Port in 1994, 556 ships(2,736,669 G/T) are oceangoing while 8155 ships(2,587,217 G/T) are domestic. The average size of oceangoing vessels is 4,922,1 G/T, and the domestic is 317,8 G/T. The average arrival interval and service time of the domestic vessels are 6.0 hours and 24.1 hours respectively marking the berth occupation rate over 100%. Those for oceangoing vessels are 34.5 hours, 120.0 hours and 37.2%. In order to maintainin the berth occupation rate to 70% the capacity considering the 1994 of domestic piers must be extended to 145% and oceangoing vessels must be increased to 165%. 2. The capacity of approaching channel is enough to handle the total traffic volume of 3. Tugs are sufficiently being provided to handle all ships requiring their services 4. The capacity of storage and inland transportation systems are sufficient to handle the throughput and the yard stroage utilization rate of No.1 - No.5 is 4.5% and No.6 is 30% of 1993's. 5. The utilization rate of LLC(Level Looping Crane) and PNT(PNeumaTic) are 2.7% and 18.8%, respectively.

• Journal of the Korean Geotechnical Society
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• v.24 no.5
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• pp.15-25
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• 2008

Contamination level assessment of harbor dredged materials is carried out for beneficial use, which generated annually due to port construction and maintenance of harbor channel. The basic purpose of environmental risk assessment was a scientific approach to susceptibility of hazard risk to human's health from different dredged materials. And this paper proposes a guideline of safely beneficial use of dredged materials at both industrial area and residental area, generated from major port execution throughout a sound investigation of their contamination levels. Newly proposed guidelines were in general higher levels compared to both current guidelines of treatment and use of dredged materials and soil environment protection levels. Finally, environmental assessment results of dredged material contamination generated in major ports of Korea for beneficial use based on pre-assessment environmental levels show that some port's dredged materials contain heavy metals such as Cd, As, Cr and Zn, more than base levels which requires more precise contamination investigation. Others were found to be very appropriate for beneficial use.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.29 no.6B
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• pp.537-542
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• 2009

To improve stage-discharge curve equation considering water level's function, this study suggested the method that can efficiently compute rivers discharge based on hydraulic characteristics such as river width, area, channel bed slope and entropy concept adopting probabilistic approach. This scheme is proposed to estimate discharge from the velocity formulation based on the entropy function in the equilibrium state derived from the relation between mean and maximum flow velocity. It has been tested using field and laboratory hydraulic data collected from the Alberta university in Canada. As a result it was found that the method proposed in this study was more efficient and accurate comparing with the traditional stage-discharge curve equation.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2022.06a
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• pp.205-208
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• 2022

Multi-exposure high dynamic range (HDR) image reconstruction, the task of reconstructing an HDR image from multiple low dynamic range (LDR) images in a dynamic scene, often produces ghosting artifacts caused by camera motion and moving objects and also cannot deal with washed-out regions due to over or under-exposures. While there has been many deep-learning-based methods with motion estimation to alleviate these problems, they still have limitations for severely moving scenes. They also require large parameter counts, especially in the case of state-of-the-art methods that employ attention modules. To address these issues, we propose a frequency domain approach based on the idea that the transform domain coefficients inherently involve the global information from whole image pixels to cope with large motions. Specifically we adopt Residual Fast Fourier Transform (RFFT) blocks, which allows for global interactions of pixels. Moreover, we also employ Depthwise Overparametrized convolution (DO-conv) blocks, a convolution in which each input channel is convolved with its own 2D kernel, for faster convergence and performance gains. We call this LFFNet (Lightweight Frequency Fusion Network), and experiments on the benchmarks show reduced ghosting artifacts and improved performance up to 0.6dB tonemapped PSNR compared to recent state-of-the-art methods. Our architecture also requires fewer parameters and converges faster in training.