• Proceedings of the Korean Information Science Society Conference
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• 2010.06c
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• pp.185-190
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• 2010

최근 위치 인식 기술과 휴대 장치의 발달로 인해 이동하는 객체를 기반으로 하는 위치 기반 서비스(Location Based Service, LBS)의 관심이 점점 증가하고 있고 그에 관련된 연구들이 활발하게 진행되고 있다. 이동 객체의 응용은 빈번하게 변경되는 이동객체의 위치정보를 효과적으로 처리할 수 있는 색인구조를 필요로 한다. 위치정보를 색인하기 위해 R-tree 기반의 색인들이 제안되었다. 하지만 R-tree는 변경보다는 검색 연산에 초점이 맞추어진 색인구조이기 때문에 잦은 변경을 다루어야 하는 이동객체 환경에 적합하지 못하다. 최근 이러한 객체의 빠른 위치 변경을 지원하는 그리드 기반의 색인 구조가 제안되었다. 하지만 셀의 객체 점유율에 따라 검색 속도가 저하되는 단점은 여전히 해결되지 못하고 있다. 이러한 단점은 객체들이 특정 영역에 몰리는 경우 또는 그리드의 해상도를 잘못 지정한 경우 더욱 부각된다. 본 논문에서는 이러한 단점을 해결하기 위해 가상 셀 기반의 색인 구조를 제안한다. 데이터 페이지에 객체의 점유율을 보장하기 위해 여러 개의 인접한 셀들의 데이터를 한 데이터 페이지에 함께 저장한다. 공간 채움 곡선을 기반으로 순서화된 셀들로 셀의 인접성을 결정한다. 또한 공간 채움 곡선의 차수를 동적으로 지정하여 객체가 집중된 셀에 대해서는 셀의 단위 크기를 작게 지정한다. 뿐만 아니라 셀을 표현하기 위한 식별자를 위해 비트를 이용한 표현식을 제안하였다. 이로 인해 노드의 팬아웃을 증가시켰고, 저장공간을 절약하였다. 실험을 통해서 제안하는 색인 기법의 우수성을 증명하였다.

• Journal of Software Assessment and Valuation
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• v.16 no.2
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• pp.127-133
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• 2020

As the usages of artificial intelligence is increased, the demand to algorithms for small portable devices increases. Also as the embedded system becomes high-performance, it is possible to implement algorithms for high-speed computation and machine learning as well as operating systems. As the machine learning algorithms process repetitive calculations, it depend on the cloud environment by network connection. For an stand alone system, low power consumption and fast execution by optimized algorithm are required. In this study, for the purpose of smart control, an energy measurement sensor is connected to an embedded system, and a real-time monitoring system is implemented to store measurement information as a database. Continuously measured and stored data is applied to a learning algorithm, which can be utilized for optimal power control, and a system interfacing various sensors required for energy measurement was constructed.

• Proceedings of the Korea Water Resources Association Conference
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• 2022.05a
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• pp.336-336
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• 2022

빗물자원의 대부분은 바다로 유입되어 소모되거나, 하수로 유입되어 불필요한 고도처리 공정이 진행되고, 하수처리장 용량에 과부하를 발생시키는 등 막대한 예산이 투입되고 있는 실정이다. 갈수기시 농가에서 용수를 확보하기 위한 용수 운반장치 등 기반구축이 쉽지 않으며, 인력 부족으로 정상적인 용수공급에 어려움을 겪고 있다. 이에 빗물자원을 용수로서 효율적으로 활용하기 위한 시스템의 구축이 필요하다. 본 연구는 빗물저류조에 스마트 관수제어 시스템을 적용한 것으로 지중에 설치된 토양수분 센서와 저류조 내부의 수위 센서에서 관측된 데이터를 토대로 자동으로 지중에 수분을 공급하는 시설이다. 지중에 수분이 부족할 경우 밸브를 열어 자동으로 펌프를 가동시켜 저류조 내부의 물을 지중으로 공급시키며 지중의 수분이 충분하거나 저류조 내부의 물이 부족해질 경우 밸브를 닫아 공급을 중단하도록 한다. 또한 저류조의 수위와 토양의 수분량, 펌프의 작동여부 등은 앱을 이용하여 실시간으로 확인이 가능하며, 스마트폰 앱을 이용한 수동조작 또한 가능하다. 본 기술은 집수, 저류, 공급, 통신, 제어, 센서 총 6종의 모듈로 구성되어 있으며, 사용자의 환경 및 예산의 따라 집수, 저류, 공급 모듈 등 맞춤형 제품 구성이 가능하도록 개발하였다. 저류조의 물공급을 관리, 제어하는 시스템으로 센서로부터 전송받은 데이터를 기준으로 펌프를 작동시켜 수분공급을 제어할 수 있으며 해당 기록을 서버에 저장하여 데이터의 통계를 구할 수 있도록 하였다. 사용자가 앱을 통하여 직접적인 제어 및 가동환경에 대한 설정을 할 수 있어 사용자가 직접 현장에 오지 않아도 토지의 현황과 저류조의 수위, 수분 공급상황 등을 직접 제어할 수 있도록 개발하였다.

• Smart Media Journal
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• v.12 no.4
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• pp.19-26
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• 2023

IoT edge services utilizing neuromorphic hardware architectures are suitable for autonomous IoT applications as they perform intelligent processing on the device itself. However, spiking neural networks applied to neuromorphic hardware are difficult for IoT developers to comprehend due to their complex structures and various hyper-parameters. In this paper, we propose a method for generating spiking neural network (SNN) models that satisfy user performance requirements while considering the constraints of neuromorphic hardware. Our proposed method utilizes previously trained models from pre-processed data to find optimal SNN model parameters from profiling data. Comparing our method to a naive search method, both methods satisfy user requirements, but our proposed method shows better performance in terms of runtime. Additionally, even if the constraints of new hardware are not clearly known, the proposed method can provide high scalability by utilizing the profiled data of the hardware.

• Journal of Internet of Things and Convergence
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• v.10 no.2
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• pp.77-84
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• 2024

Over the past few years, IoT edges have begun to emerge based on new low-latency communication protocols such as 5G. However, IoT edges, despite their enormous advantages, pose new complementary threats, requiring new security solutions to address them. In this paper, we propose a cloud environment-based IoT edge architecture model that complements IoT systems. The proposed model acts on machine learning to prevent security threats in advance with network traffic data extracted from IoT edge devices. In addition, the proposed model ensures load and security in the access network (edge) by allocating some of the security data at the local node. The proposed model further reduces the load on the access network (edge) and secures the vulnerable part by allocating some functions of data processing and management to the local node among IoT edge environments. The proposed model virtualizes various IoT functions as a name service, and deploys hardware functions and sufficient computational resources to local nodes as needed.

• Smart Media Journal
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• v.12 no.11
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• pp.145-153
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• 2023

In a P2P-based distributed storage system where peers frequently join and leave, it is essential to guarantee not only data availability but also playback quality comparable to that provided by local storage devices when playing back video files with real-time constraints. In addition, cloud storage services based on distributed storage systems provide each user with the functionality to share their files with other users, so when multiple users request playback of the same video file at the same time, all playback should be supported seamlessly in real time. Therefore, in this paper, we propose a scheme that process multiple simultaneous playback requests for each video file in real time as well as data availability in a P2P-based distributed storage system that supports file sharing. This scheme can support real-time simultaneous playback and efficiently use storage space by adjusting the amount of redundant data encoded through erasure coding according to the number of concurrent playback requests for each video file.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2019.05a
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• pp.278-280
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• 2019

Flow cytometer is one of the instrument that can measure various optical properties of a single cell or microparticle. These parameters including size, granularity, and fluorescence intensity are determined by the physical and optical interaction of the cells with excitation light source. However, users have some difficulties such as high cost, size of instrument, and limited fluorescence selectivity. In addition, abundant data is also unintentionally acquired even though user wants to have a single optical parameter. For these reasons, the use of flow cytometer is more challenging for researchers to apply their study. Therefore, the proposed study aims to develop a low-cost portable fluorescence acquisition system using a commercially available light-emitting diode and photodiode. It is designed by a 3D printer, and fluorescence selectivities are increased by changing of the light source / optical filter / detection sensor. Various number sets of fluorescently labeled cells were measured, and its feasibility was evaluated through the proposed system. As a result, acquried fluorescence intensities were proportional to the concentration of the cells and showed high linearity.

• Journal of The Korean Association of Information Education
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• v.9 no.3
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• pp.453-462
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• 2005

Recently, due to technical improvements of storage devices and networks, the amount of data increase rapidly. In addition, it is required to find the knowledge embedded in a data stream as fast as possible. Huge data in a data stream are created continuously and changed fast. Various algorithms for finding frequent itemsets in a data stream are actively proposed. Current researches do not offer appropriate method to find frequent itemsets in which flow of time is reflected but provide only frequent items using total aggregation values. In this paper we proposes a novel algorithm for finding the relative frequent itemsets according to the time in a data stream. We also propose the method to save frequent items and sub-frequent items in order to take limited memory into account and the method to update time variant frequent items. The performance of the proposed method is analyzed through a series of experiments. The proposed method can search both frequent itemsets and relative frequent itemsets only using the action patterns of the students at each time slot. Thus, our method can enhance the effectiveness of learning and make the best plan for individual learning.

• Smart Media Journal
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• v.10 no.1
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• pp.88-98
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• 2021

As blockchain technology has emerged as a security issue for IoT, technology which integrates block chain into IoT is being studied. In this paper is a research concerning token-based IoT service access control technology for data sharing, which propose a possessor focused data sharing technic by using the permissioned blockchain. To share IoT health data, a Hyperledger Fabric Network consisting of three organizations was designed to provide a way to share data by applying different access control policies centered on device owners for different services. In the proposed system, the device owner issues access control tokens with different security levels applied to the participants in the organization, and the token issue information is shared through the distributed ledger of the HFN. In IoT, it is possible to lightweight the access control processing of IoT devices by granting tokens to service requesters who request access to data. Furthmore, by sharing token issuance information among network participants using HFN, the integrity of the token is guaranteed and all network participants can trust the token. The device owners can trust that their data is being used within their authorized rights, and control the collection and use of data.

• Journal of the Institute of Convergence Signal Processing
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• v.20 no.4
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• pp.245-251
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• 2019

Sonar bearing accuracy is the correspondence between the target orientation predicted by sonar and actual target orientation, and is obtained from measurements. However, when measuring sonar bearing accuracy, many errors are included in the results because they are made at sea, where complex and diverse environmental factors are applied. In particular, parallax error caused by the difference between the position of the GPS receiver and the sonar sensor, and the time delay error generated between the speed of underwater sound waves and the speed of electromagnetic waves in the air have a great influence on the accuracy. Correcting these parallax errors and time delay errors without an automated tool is a laborious task. Therefore, in this study, we propose a sonar bearing accuracy measurement equipment with parallax error and time delay error correction. The tests were carried out through simulation data and real data. As a result of the test it was confirmed that the parallax error and time delay error were systematically corrected so that 51.7% for simulation data and more than 18.5% for real data. The proposed method is expected to improve the efficiency and accuracy of sonar system detection performance verification in the future.