• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.22 no.3
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• pp.83-91
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• 2022

This paper proposes a scalable hybrid P2P(peer-to-peer) cloud architecture for MMOGs(massively multiplayer online games) which includes load management schemes for each region. A game world is divided into several game regions and each game region is serviced by at least one peer(player) in this MMOG cloud environment. The load must be managed regionally to support smooth interactions among them even in the presence of a high concentration of players in a specific region. In the proposed architecture where an efficient and effective provisioning of resources is realized, it is suitable for players to interact with cloud servers effectively and it avoids bottlenecks of the current client-server MMOG architecture. This architecture also relieves a lot of computational power and network traffic, the load on the servers in the cloud by exploiting the capacity of the players. Simulation results show that the proposed hybrid P2P cloud architecture can reduce the considerable bandwidth at the server compared to the client server architecture as the available resources grow with the number of players in crowding or hotspots.

• Journal of Korean Academy of Nursing
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• v.53 no.2
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• pp.236-248
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• 2023

Purpose: Nursing informatics competency is used to manage and improve the delivery of safe, high-quality, and efficient healthcare services in accordance with best practices and professional and regulatory standards. This study examined the relationship between nursing informatics competency (NIC), nursing care left undone, and nurse reported quality of care (NQoC) and nursing productivity. A path model for their effects on nursing productivity among clinical nurses was also established. Methods: Data were collected using structured questionnaires answered by 192 nurses working in a tertiary hospital located in J city, Korea, and analyzed using SPSS/WIN 23.0 and AMOS 21.0 program. Results: The fit indices of the alternative path model satisfied recommended levels χ² = .11 (p = .741), normed χ² (χ² /df) = .11, SRMR = .01, RMSEA = .00, GFI = 1.00, NFI = 1.00, AIC = 18.11. Among the variables, NIC (β = .44, p < .001), NQoC (β = .35, p < .001) had a direct effect on nursing productivity. Due to the mediating effect of NQoC on the relationship between NIC and nursing productivity, the effect size was .14 (95% CI .08~.24). Meanwhile, nursing care left undone through NQoC in the relationship between NIC and nursing productivity, has a significant mediation effect (estimate .01, 95% CI .00~.03). The explanatory power of variables was 44.0%. Conclusion: Education and training for enhancing NIC should be provided to improve nursing productivity, quality of care and to reduce missed nursing care. Furthermore, monitoring the quality of nursing care and using it as a productivity index is essential.

• Journal of the Korea Society for Simulation
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• v.18 no.4
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• pp.219-225
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• 2009

The primary purpose of this study is to build computer models referring overall flow of complex and various semiconductor wafer manufacturing process and to implement a educational model which operates with a presentation tool showing device design. It is important that Korean semiconductor industries secure high competitive power on efficient manufacturing management and to develop technology continuously. Models representing the FAB processes and the functions of each process are developed for Seoul National University Semiconductor Research Center. However, it is expected that the models are effective as visually educational tools in Korean semiconductor industries. In addition, it is anticipated that these models are useful for semiconductor process courses in academia. Scalability and flexibility allow semiconductor manufacturers to customize the models and perform simulation education. Subsequently, manufacturers save budget.

• Journal of Sensor Science and Technology
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• v.32 no.3
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• pp.140-146
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• 2023

Water quality is crucial for human health and the environment. Accurate measurement of the quantity of organic carbon in water is essential for water quality evaluation, identification of water pollution sources, and appropriate implementation of water treatment measures. Total organic carbon (TOC) analysis is an important tool for this purpose. Although other methods, such as chemical oxygen demand (COD) and biochemical oxygen demand (BOD) are also used to measure organic carbon in water, they have limitations that make TOC analysis a more favorable option in certain situations. For example, COD requires the use of toxic chemicals, and BOD is time-consuming and can produce inconsistent and unreliable results. In contrast, TOC analysis is rapid and reliable, providing accurate measurements of organic carbon content in water. However, common methods for TOC analysis can be complex and energy-intensive because of the use of high-temperature heaters for liquid-to-gas phase transitions and the use of acid, which present safety risks. This study focuses on a TOC analysis method using TiO₂ photocatalysis, which has several advantages over conventional TOC analysis methods, including its low cost and easy maintenance. For TiO₂, rutile and anatase powders are mixed with an inorganic binder and spray-coated onto a glass fiber substrate. The TiO₂ powder and inorganic binder solutions are adjusted to optimize the photocatalytic reaction performance. The TiO₂ photocatalysis method is a simple and low-power approach to TOC analysis, making it a promising alternative to commonly used TOC analysis methods. This study aims to contribute to the development of more efficient and cost-effective approaches for water quality analysis and management by exploring the effectiveness and reliability of the developed equipment.

• Journal of IKEEE
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• v.26 no.1
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• pp.62-66
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• 2022

Recently, there have been many research efforts based on data-based deep learning technologies to deal with the interference problem between heterogeneous wireless communication devices in unlicensed frequency bands. However, existing approaches are commonly based on the use of complex neural network models, which require high computational power, limiting their efficiency in resource-constrained network interfaces and Internet of Things (IoT) devices. In this study, we address the problem of classifying heterogeneous wireless technologies including Wi-Fi and ZigBee in unlicensed spectrum bands. We focus on a data-driven approach that employs a supervised-learning method that uses received signal strength indicator (RSSI) data to train Deep Convolutional Neural Networks (CNNs). We propose a simple measurement methodology for collecting RSSI training data which preserves temporal and spectral properties of the target signal. Real experimental results using an open-source 2.4 GHz wireless development platform Ubertooth show that the proposed sampling method maintains the same accuracy with only a 10% level of sampling data for the same neural network architecture.

• Journal of Advanced Technology Convergence
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• v.3 no.2
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• pp.9-15
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• 2024

Due to the high inflation rate of dining out, along with changes in group meals or cafeteria services, office workers are increasingly using workplace cafeterias to reduce their meal expenses even slightly. With the recent development of ICT technology, various fields are realizing that not only are smartphones becoming more popular, but they are also becoming an integration of the latest technologies. In this paper, we analyze the current status of cafeterias with a large number of customers and propose ways to improve problems or difficulties. Since most people always carry their smartphones for urgent communication or work tasks, we aim to develop a cafeteria management system that utilizes the NFC function of smartphones. By presenting the process from customer entry to menu selection, it will enable more efficient use of the cafeteria.

• The Journal of the Acoustical Society of Korea
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• v.25 no.4
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• pp.151-158
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• 2006

In this paper, we proposed a new audio fingerprint extraction method, based on Philips' music retrieval algorithm, which uses the energy difference of neighboring filter-bank and probabilistic characteristics of music. Since Philips method uses too many filter-banks in limited frequency band, it may cause audio fingerprints to be highly sensitive to additive noises and to have too high correlation between neighboring bands. The proposed method improves robustness to noises by reducing the number of filter-banks while it maintains the discriminative power by representing the energy difference of bands with 2 bits where the quantization levels are determined by probabilistic characteristics. The correlation which exists among 4 different levels in 2 bits is not only utilized in similarity measurement. but also in efficient reduction of searching area. Experiments show that the proposed method is not only more robust to various environmental noises (street, department, car, office, and restaurant), but also takes less time for database search than Philips in the case where music is highly degraded.

• Journal of Radiation Industry
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• v.18 no.1
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• pp.89-93
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• 2024

Accidents at nuclear facilities and nuclear power plants led to leaks of large amounts of radioactive substances. Of the various radioactive nuclides released, ¹³⁷Cs are radioactive substances generated during the fission of uranium. Therefore, due to the high fission yield (6.09%), strong gamma rays, and a relatively long half-life (30 years), a rapid and efficient removal method and a study of adsorbents are needed. Accordingly, an adsorbent was prepared using Prussian blue (PB), a material that selectively adsorbs radioactive cesium. As a result of evaluating the adsorption performance with the prepared adsorbent, it was confirmed that 82% of the removal efficiency was obtained, and most of the cesium was rapidly adsorbed within 10 to 15 minutes. The purpose of this study was to adsorb cesium using the Prussian blue alginate bead and to compare the change in detection efficiency according to the amount of adsorbent added for quantitative evaluation. However, in this case, it is difficult to determine the detection efficiency using a standard source with the same conditions as the measurement sample, so the efficiency change of the HPGe detector according to the different heights of Prussian blue was calculated through MCNP simulation using certified standard materials (1 L, Marinelli beaker) for radioactivity measurement. It is expected to derive a relational equation that can calculate detection efficiency through an efficiency curve according to the volume of Prussian blue, quantitatively evaluate the activity at the same time as the adsorption of radioactive nuclides in actual contaminated water and use it in the field of nuclear facility operation and dismantling in the future.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.38 no.5
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• pp.486-497
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• 2001

In this paper, we propose a new addressing mode, which can be used for programmable image processor to perform image-processing algorithms effectively. Conventional addressing modes are suitable for one-dimensional data processing such as voice, but the proposed addressing mode consider two-dimensional characteristics of image data. The proposed instruction for two-dimensional addressing requires two operands to specify a pixel and doesn't require any change of memory architecture. The proposed two-dimensional addressing mode for image processor has the following advantages. The proposed instruction combines several instructions to load a pixel data from an external memory to a register. Hence, the proposed instruction reduces required code size so that it satisfies high performance and low power requirements of image processor. In addition, it uses inherent two-dimensional characteristics of image data and offers user-friendly instruction to assembler programmer The proposed two-dimensional addressing mode is applicable to DSP, media processor, graphic device, and so on. In this paper, we propose a new concept of two-dimensional addressing mode and an efficient hardware implementation method of it.

• Journal of KIISE:Information Networking
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• v.31 no.1
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• pp.37-52
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• 2004

Broadcast has been often used to disseminate the frequently requested data efficiently to a large volume of mobile units over a single or multiple channels. Since the mobile units have limited battery power, the minimization of the access time for the broadcast data is an important problem. There have been many research efforts that focus on the improvement if the broadcast techniques by providing indexes on the broadcast data. In this paper, we studied an efficient index allocation method for the broadcast data over multiple physical channels, which cannot be coalesced into a single high bandwidth channel. Previously proposed index allocation techniques either require the equal size of index and data or have a performance degradation problem when the number of given physical channels is not enough. These two problems will result in the increased average access time for the broadcast data. To cope with these problems, we propose an efficient tree- structured index allocation method for the broadcast data with different access frequencies over multiple physical channels. Our method minimizes the average access time for the broadcast data by broadcasting the hot data and their indexes more often than the less hot data and their indexes. We present an in-0e0th experimental and theoretical analysis of our method by comparing it with other similar techniques. Our performance analysis shows that it significantly decrease the average access time for the broadcast data over existing methods.