• Proceedings of the Korea Water Resources Association Conference
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• 2017.05a
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• pp.251-251
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• 2017

전 세계적으로 기후변화 및 다양한 삶의 패턴이 변화되면서 예상되는 자원의 부족을 해결하기 위한 많은 노력이 진행되고 있다. 특히 범 국가적으로 지속가능한 자원안보 실현을 위한 적정 솔루션을 제공하고 자원의 연계에 따른 효율성과 효과성을 극대화하기 위해 물, 에너지, 식량의 연계를 통한 기술을 개발하고 적용하고 있으나, 아직까지 국가단위의 대규모 사례는 부족하며, Community Scale의 형태로 진행되고 있는 실정이다. 본 논문에서는 국내에서의 물, 에너지, 식량의 연계 기술을 도출하기 위해 국외에서 진행되고 있는 기술에 대한 현황과 효과를 분석하여 국내의 적용방안에 대해 분석하고자 한다. 국외의 사례로는 프랑스 전력공사(EDF)에서는 2000년 초반 기존의 규정대로 물공급을 지속하면 발전에 어려움이 발생하는 것을 인식하여, 주요 농업 관개시설과 물절약협약을 체결하고 물절약에 따른 금전적 보상대책을 마련하였다. 이를 통해 물 절약의 30%는 기존의 관행과 관리방식의 변화에 의해 이루어졌고, 약 70%는 효율적 물 사용기술을 통해 절감효과를 도출하였다. 또한 관개용수와 발전량의 효율적 물사용을 통해 3억2,500만$m^3$에서 2억3,500만$m^3$ 으로의 절감효과를 달성할 수 있었다. 오스틴 수도회사, 텍사스 가수 서비스, 오스틴 에너지 회사 등 텍사스의 3개회사가 상호 협약을 통해 다가구 에너지 및 물효율 프로그램을 개발하고 자원을 효율적으로 관리할 수 있는 주택을 개조하여, 연간 470만 kWh의 전기와 3,785만 리터의 물을 절약하고 있다. 베트남 Red강의 경우 베트남의 근대화 및 산업화를 위해 많은 물과 전기가 필요함에 따라 물사용량을 규제하였고 이로 인해 농작물 재배를 고려하여 장기적이고 다방면적인 전략을 도출하였다. 정유회사 CHEVRON에서는 미국 캘리포니아에서 오일 1배럴을 생산할 때마다 10배럴의 물을 생산하여 오일생산 과정에 이용하며 $182km^2$ 면적의 농장에 농업용수를 공급할 수 있었다. 특히, California 오일 추출과정에서 물과 오일을 분리하고 그 과정에서 발생한 물을 재이용하기 위하여 수처리과정을 통하여 매일 $2,650m^3$의 물 생산하게 되었다. 이러한 외국의 사례들을 바탕으로 하여 국내에서도 다양한 형태의 넥서스 기술을 접목하여 미래에 예측되는 자원 부족을 선제적으로 대응하는 방안을 수립할 때이다.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.19 no.5
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• pp.143-150
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• 2019

Cloud computing has recently become an attractive solution for massively multiplayer online games(MMOGs), as it lifts operators from the burden of buying and maintaining hardware. Peer-to-peer(P2P) -based solutions present several advantages, including the inherent scalability, self-repairing, and natural load distribution capabilities. We propose a hybrid architecture for MMOGs that combines technological advantages of two different paradigms, P2P and cloud computing. An efficient and effective provisioning of resources and mapping of load are mandatory to realize an architecture that scales in economical cost and quality of service to large communities of users. As the number of simultaneous players keeps growing, the hybrid architecture relieves a lot of computational power and network traffic, the load on the servers in the cloud by exploiting the capacity of the peers. For MMOGs, besides server time, bandwidth costs represent a major expense when renting on-demand resources. Simulation results show that by controlling the amount of cloud and user-provided resource, the proposed hybrid architecture can reduce the bandwidth at the server while utilizing enough bandwidth of players.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.19 no.3
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• pp.25-32
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• 2019

The core of the block chain technology is solving the problem of agreement on double payment, and the PoW, PoS and DPoS algorithms used for this have been studied. PoW in-process proofs are consensus systems that require feasible efforts to prevent minor or malicious use of computing capabilities, such as sending spam e-mail or initiating denial of service (DoS) attacks. The proof of the PoS is made to solve the Nothing at stake problem as well as the energy waste of the proof of work (PoW) algorithm, and the decision of the sum of each node is decided according to the amount of money, not the calculation ability. DPoS is that a small number of authorized users maintain a trade consensus through a distributed network, whereas DPS provides consent authority to a small number of representatives, whereas PoS has consent authority to all users. If PoS is direct democracy, DPoS is indirect democracy. This study aims to contribute to the continuous development of the related field through the study of the algorithm of the block chain agreement.

• The Journal of the Korea Contents Association
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• v.19 no.1
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• pp.132-140
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• 2019

Recently, many cities around the world introduced and operated shared bicycle system to reduce the traffic and air pollution. Seoul also provides shared bicycle service called as "Ddareungi" since 2015. As the use of shared bicycle increases, the demand for bicycle in each station is also increasing. In addition to the restriction on budget, however, there are managerial issues due to the different demands of each station. Currently, while bicycle rebalancing is used to resolve the huge imbalance of demands among many stations, forecasting uncertain demand at the future is more important problem in practice. In this paper, we develop forecasting model for demand for Seoul shared bicycle using statistical time series analysis and apply our model to the real data. In particular, we apply Holt-Winters method which was used to forecast electricity demand, and perform sensitivity analysis on the parameters that affect on real demand forecasting.

• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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• v.9 no.1
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• pp.179-187
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• 2019

With the recent development of small computing devices, IoT sensor network can be widely deployed and is now readily available with sensing, calculation and communi-cation functions at low cost. Sensor data management is a major component of the Internet of Things environment. The huge volume of data produced and transmitted from sensing devices can provide a lot of useful information but is often considered the next big data for businesses. New column-wise compression technology is mounted to the large data server because of its superior space efficiency. Since sensor nodes have narrow bandwidth and fault-prone wireless channels, sensor-based storage systems are subject to incomplete data services. In this study, we will bring forth a short overview through providing an analysis on IoT sensor networks, and will propose a new storage management scheme for IoT data. Our management scheme is based on RAID storage model using column-wise segmentation and compression to improve space efficiency without sacrificing I/O performance. We conclude that proposed storage control scheme outperforms the previous RAID control by computer performance simulation.

• KIPS Transactions on Computer and Communication Systems
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• v.11 no.5
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• pp.139-146
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• 2022

With the recent development of the Internet of Things (IoT) and the convergence of vehicles and IT technologies, high-performance applications such as autonomous driving are emerging, and multi-access edge computing (MEC) has attracted lots of attentions as next-generation technologies. In order to provide service to these computation-intensive tasks in low latency, many methods have been proposed to partition tasks so that they can be performed through cooperation of multiple MEC servers(MECSs). Conventional methods related to task partitioning have proposed methods for partitioning tasks on vehicles as mobile devices and offloading them to multiple MECSs, and methods for offloading them from vehicles to MECSs and then partitioning and migrating them to other MECSs. In this paper, the performance of task partitioning methods using offloading and migration is compared and analyzed in terms of service delay, blocking rate and energy consumption according to the method of selecting partitioning targets and the number of partitioning. As the number of partitioning increases, the performance of the service delay improves, but the performance of the blocking rate and energy consumption decreases.

• Journal of IKEEE
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• v.26 no.4
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• pp.568-576
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• 2022

Automatic modulation classification(AMC) is a core technique in Software Defined Radio(SDR) platform that enables smart and flexible spectrum sensing and access in a wide frequency band. In this study, we propose a simple yet accurate deep learning-based method that allows AMC for variable-size radio signals. To this end, we design a classification architecture consisting of two Convolutional Neural Network(CNN)-based models, namely main and small models, which were trained on radio signal datasets with two different signal sizes, respectively. Then, for a received signal input with an arbitrary length, modulation classification is performed by augmenting the input samples using a self-replicating padding technique to fit the input layer size of our model. Experiments using the RadioML 2018.01A dataset demonstrated that the proposed method provides higher accuracy than the existing methods in all signal-to-noise ratio(SNR) domains with less computation overhead.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.22 no.4
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• pp.17-22
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• 2022

With the spread of web services, data types are becoming more diversified. In addition to the form of storing data such as images, videos, and texts, the number and form of properties and metadata expressing the data are different for each data. In order to efficiently process such unstructured data, a key-value store is widely used for state-of-the-art applications. LSM-Tree (Log Structured Merge Tree) is the core data structure of various commercial key-value stores. LSM-Tree is optimized to provide high performance for small writes by recording all write and delete operations in a log manner. However, there is a problem in that the delay time and processing speed of user requests are lowered as batches of deletion operations for expired data are inserted into the LSM-Tree as special key-value data. This paper presents a Filtered LSM-Tree (FLSM-Tree) that solves the above problem by separating the deleted key from the main tree structure while maintaining all the advantages of the existing LSM-Tree. The proposed method is implemented in LevelDB, a commercial key-value store and it shows that the read performance is improved by up to 47% in performance evaluation.

• The Journal of the Korea Contents Association
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• v.22 no.5
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• pp.247-260
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• 2022

This paper investigates plans to expand distribution channels for books by installing a book vending machine at convenience stories for the vitalization of the publishing culture and industry. After establishing the meaning of convenience stories and the concept of a book vending machine, the researcher identified a need for the installation and management of a book vending machine at convenience stories. This plan will promote fairness and transparency in book sales through the convenience store system and push forward outsourcing between the publishing industry and the convenience store industry, the expansion of omnichannel service for consumers, and experiential values for clients to increase their customer satisfaction. The composition of the book vending machine will take the smart library form for its management with a universal design applied to a kiosk program. In the study, the researcher schematized this process and conducted a survey with 310 adults to search for practical management plans for a book vending machine. In the future, more research on the diversification of sales and distribution channels for publications such as the installation of a book vending machine at convenience stores will hopefully contribute to the growing amount of reading per capita and promotion of a reading environment for people according to the vitalization of the publishing culture and industry.

• Journal of Advanced Navigation Technology
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• v.28 no.5
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• pp.738-744
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• 2024

The goal of this system is to effectively summarize and visualize important DICOM image data in the medical field. Using React and Node.js, the system collects and parses DICOM images, extracting critical medical information in the process. It then employs a large language model (LLM) to generate automatic summary reports, providing users with personalized medical information. This approach enhances accessibility to medical data and leverages web technologies to process large-scale data quickly and reliably. The system also aims to improve communication between patients and doctors, enhancing the quality of care and enabling medical staff to make faster, more accurate decisions. Additionally, it seeks to improve patients' medical experiences and overall satisfaction. Ultimately, the system aims to improve the quality of healthcare services.